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Inclusion of a crew safety node into the preliminary design of fishing vessels Akintürk, Ayhan 1997

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INCLUSION OF A CREW SAFETY NODE INTO THE PRELIMINARY DESIGN OF FISHING VESSELS By Ayhan Akinturk BSc. , Istanbul Technical University, Istanbul, Turkey 1986; MSc. , University of Newcastle Upon Tyne, U.K. 1990  A THESIS SUBMITTED I N PARTIAL F U L F I L L M E N T O F THE REQUIREMENTS FOR T H E DEGREE OF DOCTOR  OF PHILOSOPHY  in T H E FACULTY OF G R A D U A T E STUDIES DEPARTMENT OF MECHANICAL  ENGINEERING  We accept this thesis as conforming to the required standard  T H E UNIVERSITY'OF BRITISH COLUMBIA  May 1997 © Ayhan Akinturk, 1997  In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives.  It is understood that copying or publication of this thesis for  financial gain shall not be allowed without my written permission.  Department of Mechanical Engineering The University of British Columbia 2324 Main Mall Vancouver, B.C., Canada V6T 1Z4  Abstract  The working and living conditions on-board of fishing vessels affect the crew's performance and well being. They contribute to occupational accidents on-board, which cost to the health and lives of crew members. There is also a cost of lost opportunity, when crew members can not perform their duties on-board and have to halt fishing due to deteriorated conditions at sea. In this thesis, a methodology that will allow the inclusion of crew comfort and safety considerations into the preliminary design of fishing vessels has been developed. This new methodology and the traditional preliminary design spired for monohull and SWATH (Small Waterplane Area Twin Hull) vessels have been implemented in Echidna, which is a logic programming environment that supports constraint based reasoning. In the literature, ship motions have been reported to be the most prominent contributory factor to the occupational accidents and crew's performance on-board. Hence, two sets of rules suitable to a knowledge-based environment and based on different engineering concepts have been developed and implemented for the preliminary design of fishing vessels to improve their seakeeping characteristics. Unlike some ship motions' calculation programs, for example SHIPMO, these rules do not require detailed hull form definition. Hence, they are used as guidelines (or heuristic rules) during the initial stages of ship design. Considering the nonlinear nature of ship design, the procedure developed was able to find a solution for a given design sea state and owner requirements. The effects of the rules on ship size, cost and improved seakeeping qualities are presented in this thesis. Additionally, monohull and SWATH vessels for the same owner requirements are ii  compared in terms of vessel size and cost. Finally, the knowledge-based system described in this thesis provides a tool to map crew comfort levels and a design sea state to the vessel parameters. Hence the cost difference due to the crew comfort and safety considerations can be quantified. The methodology described here can easily be applied for small craft with small changes to the knowledge base. Keywords : ship design, crew safety, crew comfort, knowledge-based design, seakeeping.  iii  Table of Contents  Abstract  ii  List of Tables  viii  List of Figures  xii  Acknowledgements  xix  Chapter 1 INTRODUCTION  1  1.1  Objective of This Study  6  1.2  Proposed Method  7  Chapter 2 OCCUPATIONAL S A F E T Y ON-BOARD FISHING VESSELS 2.1  Statistics of Accidents On-board  9 : -. .  9  2.1.1  Canada  12  2.1.2  France  16  2.1.3  United Kingdom  2.1.4  Norway  21  2.1.5  Spain  27  2.1.6  Japan  32  .  20  2.2  Some notes on accident statistics  32  2.3  Impact of Ship Motions on Fishing  33  iv  2.4  Design considerations for improved working conditions on-board based on warships  39  2.5  Methods for reduced motions  43  2.6  Design margins  45  Chapter 3 A N OVERVIEW OF SHIP DESIGN  47  3.1  Overview of Literature for Ship Design  49  3.2  Overview of the Ship Design Process (Design Spiral)  55  3.3  Summary  56  Chapter 4 DESIGN, K N O W L E D G E - B A S E D SYSTEMS A N D ECHIDNA  59  4.1  Design in a Knowledge-Based Environment  61  4.2  Echidna Expert System Shell  63  Chapter 5 M O N O H U L L VESSEL DESIGN K N O W L E D G E BASE (UBC-MONO) 68 5.1  Remarks  70  5.2  Summary  76  Chapter 6 SWATH PRELIMINARY DESIGN A N D UBC-SWATH  84  6.1  Multi-hull vessel for fishing role  84  6.2  General Features of Multi-hull Design  6.3  SWATH Design Algorithms and Discussion  86  6.4  Remarks  90  .  85  Chapter 7 S E A K E E P I N G CONSIDERATIONS  97  7.1  Rule Set I  99  7.2  Evaluation of the Example Designs by Rule Set I  114  7.2.1  120  Remarks about the ship dimensions and displacement  7.3  Rule Set II  134  7.4  Comparison of the outcomes of Rule Sets I and II  149  7.5  The Criterion Suggested by Kimura et al. [40]  156  7.5.1  160  Summary  Chapter 8 SWATH M O N O H U L L COMPARISON Chapter 9 CONCLUSIONS 9.1  174  179  Suggestions for Future Work  181  Nomenclature  184  Bibliography  186  Appendix A Echidna - Knowledge Base Environment  193  A.l Run-time user commands  196  A.2 Knowledge base for the barge example  197  A. 3 A sample output for the barge example  202  Appendix B Monohull Design Algorithms B. l  Linear Dimensions  206 206  vi  B.2 Weight Estimation  208  B.3 Resistance and Powering  209  B.4 Stability  211  B. 5 Cost Estimation  212  Appendix C SWATH design algorithms C. l  Linear Dimensions  214 214  C.2 Strut(S) Linear Dimensions  217  C.3 Weight Estimation  217  C.4 Resistance and Powering  221  C.5 Cost Estimation  224  Appendix D Prediction of a vessel's heave and pitch motions  226  Appendix E Frequencies of Peak Heave and Pitch Responses  228  Appendix F RMS Heave and Pitch Responses  229  vii  List of Tables  1.1  Deaths and accident rates for 1985 per 1000 employees in some industries [26]  3  1.2  Types of Casualties in Fishing  3  2.1  Accidents Aboard Canadian Registered Ships by Vessel Type (Source : [66, pp. 36])  2.2  13  Fatalities Aboard Canadian Registered Ships by Vessel Type (Source : [66, pp. 36])  2.3  Injuries Aboard Canadian Registered Ships by Vessel Type (Source : [66, PP.36])  2.4  13  . . .  15  Based on Tables 2.1, 2.2, and 2.3, the percentages of aboard casualties occurred on Canadian Registered fishing vessels  2.5  10 year averages of percentage values of primary contributing factors in casualties aboard all vessel types  2.6  15  16  Number of Accidents Aboard Canadian Registered Ships by Primary Contributing Factor. All vessel types mentioned in Tables 2.1, 2.2, and 2.3 are included. (Source : [66, pp. 38])  2.7  17  Fatalities Aboard Canadian Registered Ships by Primary Contributing Factor. All vessel types mentioned in Tables 2.1, 2.2, and 2.3 are included. (Source : [66, pp. 38])  17  viii  2.8  Injuries Aboard Canadian Registered Ships by Primary Contributing Factor. All vessel types mentioned in Tables 2.1, 2.2, and 2.3 are included. (Source : [66, pp. 38])  2.9  18  Deaths in United Kingdom Fishing Vessels during 1980 - 1988 (Source : [26])  22  2.10 Ratio of number of fishers with respect to the length of the vessels in the Norwegian fishing fleet [41]  22  2.11 Contributing factors to on-board casualties in the Norwegian fishing fleet ([34] in [41])  23  2.12 The most important causes of injury in the Norwegian fishing fleet [36]. Values are % of the total disabilities or less serious injuries 2.13 Survey on noise levels on 17 Norwegian fishing vessels ([1] from [41]) . . .  24 26  2.14 Number of casualties for different fishing types in the Norwegian fishing vessels ([12] in [41])  27  2.15 % number of accidents on deck by type of crew member in Spanish fishing vessels [22]  29  2.16 % number of accidents by type of crew member in Spanish fishing vessels (Source [22])  29  2.17 Places of accidents in Spanish fishing vessels [22]  30  2.18 Work agents causing the most serious injuries in Spanishfishingvessels [22] 31 2.19 Motion Correlations given by Walden and Grundmann [68]  44  5.1  Input to Echidna for Kynoc. "[ ]" indicates an input as an interval. . . .  71  5.2  Comparison of Echidna produced design with real Kynoc  72  5.3  Example for the intervals after Echidna reaches a solution  73  ix  5.4  Example for the parameters' intervals after Echidna completes design and further arbitrarily refines them  5.5  73  Input to Echidna for the second phase of validation for a fleet of varying hold capacities  74  6.1  Input parameters for SWATH vessel design expert system  87  6.2  Statistical analysis of % variations for A after excluding the pathological cases (4 cases out of 41 total number of cases). The 4 existing designs are as follows: a 305 ton fishing vessel, a 225 ton ferry, a 225 ton crew boat and a car ferry with a 1250 ton displacement  88  7.1  Input values to Echidna knowledge base for monohull fishing vessel. . . .  7.2  The averages and standard deviations (over hold capacities) of the %  102  Changes obtained in rms heave and pitch motion amplitudes. The vessel is assumed to be operating in Sea State 5 7.3  117  The averages and standard deviations (over hold capacities) of the % Changes obtained in rms heave and pitch accelerations.  The vessel is  assumed to be operating in Sea State 5  118  9.1  Principal particulars of the SWATH M.V. Frederick G. Creed (from [28]). 175  9.2  Principal particulars of the monohull F.P.V. Louisbourg (from [28]). . . 175  9.3  Comparison of some of the significant motion characteristics between M.V. Frederick G. Creed and F.P.V. Louisbourg (from [28])  176  A. l  Refinement of intervals during the example barge design in Echidna . . .  195  B. l  Coefficients for UBC Series Resistance Algorithm for  210  C. l  Residual drag coefficient as a function of volumetric Froude number. . . . 223  = 0.615  F.l  Sea state information. [Sabuncu, 1983]  229  F.2 Scaling factors for the raw regression data obtained from the software SHIPMO  229  xi  List of Figures  1.1  Deaths per 10,000 man-years in some occupations. (Source [36])  2  2.1  Crew members trying to transfer an empty net from the factory ship. . .  2.2  A crew member working at the stern to secure one of the doors used to keep the mouth of the trawl net open while trawling  10  11  2.3  Tasks performed on-board after taking the catch is in (from [8, p 88]).  2.4  Position of the fishing gear at the bow (from [32])  20  2.5  Position of thefishinggear in the middle (from [32])  21  3.1  Design Spiral  49  3.2  Representation of design process by Mistree et al. [50]  50  3.3  The process of basic design of ships in Akagi and Fujita's expert system (from [3])  4.1  14  58  Generative and interpretive knowledge in defining spaces of designs (from [27])  5.1  .  64  Comparison of Echidna generated aluminum and steel designs' lengths (vessel type : seiner). The jump could be because of alternative estimation rules embedded for some variables in the knowledge base  5.2  77  Comparison of Echidna generated aluminum and steel designs' beams (vessel type : seiner). The jump could be because of alternative estimation rules embedded for some variables in the knowledge base  xii  78  5.3  Comparison of Echidna generated aluminum and steel designs' drafts (vessel type : seiner). T h e j u m p could be because of alternative estimation rules embedded for some variables in the knowledge base  5.4  79  Comparison of Echidna generated aluminum and steel designs' hull weights (vessel type : seiner)  5.5  80  Comparison of Echidna generated aluminum and steel designs' required powers (vessel type : seiner)  5.6  81  Comparison of Echidna generated aluminum and steel designs' displacements (vessel type : seiner)  5.7  82  Comparison of Echidna generated aluminum and steel designs' costs (vessel type : seiner)  6.1  83  Comparison of U B C - S W A T H and existing design A ' s . T h e horizontal axis represents existing designs' displacement values  92  6.2  Comparison of U B C - S W A T H and existing design L AS  93  6.3  Comparison of U B C - S W A T H and existing design S e a m ' s  94  6.4  Comparison of U B C - S W A T H and existing design Draffs  95  6.5  Comparison of U B C - S W A T H and existing design Installed  7.1  Frequencies that maximize sea spectrum and ship response spectrum.  7.2  T h e variation of the ratios (Equation 7.1). Control case shows the ratios  0  Powers.  . .  96  .  107  without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5 7.3  108  T h e effects of Rule Set I on the lengths. Control case shows the lengths without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5  109  xiii  7.4 The effects of Rule Set I on the beams. Control case shows the beams without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5  110  7.5 The effects of Rule Set I on the drafts. Control case shows the drafts without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5 7.6  Ill  The effects of Rule Set I on the displacements. Control case shows the displacements without any seakeeping rules included in the design. Designsea-state is 5; operational-sea-state is 5  112  7.7 The effects of Rule Set I on the costs. Control case shows the costs without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5  113  7.8 Values of rms for heave  122  7.9  122  % change in rms heave values  7.10 Values of rms heave  123  7.11 % change in rms heave values  123  7.12 Values of rms for heave  124  7.13 % change in rms heave values  124  7.14 Values of rms for pitch  125  7.15 % change in rms pitch values  125  7.16 Values of rms for pitch  126  7.17 % change in rms pitch values  126  7.18 Values of rms for pitch  127  7.19 % change in rms pitch values  127  8.20 Values of rms for heave accelerations (Rule Set I)  128  xiv  8.21 % change in rms heave accelerations (Rule Set I)  128  8.22 Values of rms for heave accelerations (Rule Set I)  129  8.23 % change in rms heave accelerations (Rule Set I)  129  8.24 Values of rms for heave accelerations (Rule Set I)  130  8.25 % change in rms heave accelerations (Rule Set I)  130  8.26 Values of rms for pitch accelerations (Rule Set I)  131  8.27 % change in rms pitch accelerations (Rule Set I)  131  8.28 Values of rms for pitch accelerations (Rule Set I)  132  8.29 % change in rms pitch accelerations (Rule Set I)  132  8.30 Values of rms for pitch accelerations (Rule Set I)  133  8.31 % change in rms pitch accelerations (Rule Set I)  133  8.32 The effects of Rule Set II on rms heave amplitudes. Design and operational sea states are 5  140  8.33 The effects of Rule Set II on rms pitch amplitudes. Design and operational sea states are 5  140  8.34 The effects of Rule Set II on lengths. Design-sea-state is 5  141  8.35 The effects of Rule Set II on beams. Design and operational sea states are 5.141 8.36 % Change in the lengths of the example designs. Design-sea-state is 5.  . 142  8.37 % Change in the beams of the example designs. Design-sea-state is 5. . . 143 8.38 The effects of Rule Set II on drafts. Design and operational sea states are 5.144 8.39 The effects of Rule Set II on displacements. Design-sea-state is 5  144  8.40 % Change in the drafts of the example designs. Design-sea-state is 5. . . 145 8.41 % Change in the displacements of the example designs. Design-sea-state is 5  146  8.42 The effects of Rule Set II on costs. Design-sea-state is 5  147  8.43 % Change in the costs of the example designs. Design-sea-state is 5. . . . 148 xv  8.44 % Changes of the lengths of example designs obtained using Rule Sets I and II. Design-sea-state is 5  151  8.45 % Changes of the beams of example designs obtained using Rule Sets I and II. Design-sea-state is 5  152  8.46 % Changes of the drafts of example designs obtained using Rule Sets I and II. Design-sea-state is 5  153  8.47 % Changes of the displacements of example designs obtained using Rule Sets I and II. Design-sea-state is 5. .  154  8.48 % Changes of the costs of example designs obtained using Rule Sets I and II. Design-sea-state is 5  155  8.49 A crew member working at the stern  157  8.50 Values of T (Equation 8.15), where T measures conditions to assess the m  m  ability of a crew member to maintain his balance (see page 38). Design-seastate is 5 and operational-sea-state is 2; ship speed = 0.01 [fen]; midpoints of Echidna intervals were used  162  8.51 % Change in the values of T with respect to "Control case", in which m  there was no seakeeping considerations, (for the data in Figure 8.50). . . 163 8.52 Values of T (Equation 8.15), where T measures conditions to assess the m  m  ability of a crew member to maintain his balance (see page 38). Design-seastate is 5 and operational-sea-state is 5; ship speed = 0.01[fenj; midpoints of Echidna intervals were used  164  8.53 % Change in the values of T with respect to "Control case", in which m  there was no seakeeping considerations, (for the data in Figure 8.52). . . 165  xvi  8.54 Values of T  m  (Equation 8.15), where T  m  measures conditions to assess the  •ability of a crew member to maintain his balance (see page 38). Designsea-state is 5 and operational-sea-state is 2; ship speed = 5[fcn]; midpoints of Echidna intervals were used 8.55 % Change in the values of T  166 with respect to "Control case", in which  m  there was no seakeeping considerations, (for the data in Figure 8.54). . . 8.56 Values of T  m  (Equation 8.15), where T  167  measures conditions to assess the  m  ability of a crew member to maintain his balance (see page 38). Designsea-state is 5 and operational-sea-state is 5; ship speed = 5[An]; midpoints of Echidna intervals were used 8.57 % Change in the values of T  m  168 with respect to "Control case", in which  there was no seakeeping considerations, (for the data in Figure 8.56). . . 8.58 Values of T  m  (Equation 8.15), where T  m  169  measures conditions to assess the  ability of a crew member to maintain his balance (see page 38). Designsea-state is 5 and operational-sea-state is 2; ship speed = 10[A;TI]; midpoints of Echidna intervals were used 8.59 % Change in the values of T  m  170 with respect to "Control case", in which  there was no seakeeping considerations, (for the data in Figure 8.58). . . 8.60 Values of T  m  (Equation 8.15), where T  m  171  measures conditions to assess the  ability of a crew member to maintain his balance (see page 38). Designsea-state is 5 and operational-sea-state is 5; ship speed = 10[fcra]; midpoints of E c h i d n a intervals were used 8.61 % Change in the values of T  m  172 with respect to "Control case", in which  there was no seakeeping considerations, (for the data in Figure 8.60). . .  xvii  173  9.1  Comparison of the displacements of SWATH and monohull type of fishing vessels obtained using Echidna. For monohulls, Control case corresponds to the case in which there was no seakeeping considerations in the design. For SWATH designs, no seakeeping considerations were used during the design  9.2  177  For the mid points of Echidna intervals, the values of the ratios (SWATH displacements over monohull displacements, for data given in Figure 9.1). Control case is the one, in which there was no seakeeping considerations in the design  178  A.l  An example class definition for rectangles (the object in this example). . 195  C.l  Schematic of a SWATH vessel  225  xviii  Acknowledgements  I would like to express my sincere gratitude to Dr. S. M. Cah§al for his patience steadfast encouragement, guidance and support throughout my research. I would also like to thank the members of my supervisory committee, Dr. A. B. Dunwoody, Dr. F. Sassani, Dr. W. Havens and Ms. Judy Village for their invaluable comments and suggestions. Furthermore, I would especially thank Dr. Havens for allowing us to use Echidna, the expert system shell developed at the Expert Systems Laboratory, in Simon Fraser University. Without Echidna, the research would not have reached where it is today. Ms. Susan Sidebottom had been very patient with my questions while learning how to use Echidna. She and the other members of the laboratory deserve special thanks from me for their valuable answers and suggestions. I would also like to thank Ms. Judy Village, for her extremely helpful suggestions and commentary on the ergonomic aspects of this research. Dr. Mehmet Atlar has contributed a lot to this work. He has been ever helpful in any kind of difficulty during this research. I would like to express my indebtedness to him. Dr. Erol Varoglu showed me many interesting points related to research. Our stimulating talks have contributed greatly to my understanding of knowledge-based systems and problem solving strategies and have been times of enjoyment for me. I thank him sincerely for all of these. I would also like to thank the Ministry of Education of Turkey, without their sponsorship I would not be able to undertake such an academic journey. Special thanks to Mr. Andrew Duthie from the Department of Fisheries and Oceans for his support in the earlier parts of this project. xix  During my researh, my friends and colleagues had contributed to this work and my life through social events, technical discussions and immeasurable technical support at times. I am greatly indebted to them. Last but not least, my gratitude also goes to my family for their perpetual support and encouragement.  xx  Chapter 1 INTRODUCTION  Ship design is one of the oldest endeavors of mankind. Historically, it has been a reproduction of successful ships mostly. There have been a number of novel ideas introduced into different aspects of ship design, such as the introduction of steam engines as an alternative power source to sailing, using different hull materials e.g. steel, aluminum, fiber glass, etc., or different hull forms e.g. hydrofoils, catamarans, SWATH (Small Waterplane Area Twin Hull), etc. to name a few. However, life at sea for humans still continue to be hazardous. Statistics related to the risk levels in different occupations (see Figure 1.1) are in agreement with this fact and reveal that particularly fishing is among the most dangerous occupations. According to Hansen in [36] fishing with 13.7 deaths per 10000 man-years due to accidents is the most hazardous occupation among the others in Figure 1.1. A similar study done in England [26] reveals similar findings. Chaplin and Burney [26] reported the following comparison between the fishing industry and the some other industries (see Table 1.1). For the period of 1981 to 1988 for all vessels in the fishing industry, death and non-fatal accident rates per 1000 employees were 1.05 and 6.42 respectively. These rates are much higher than the rates for other industries reported in Table 1.1. It should be noted that the numbers given in Figure 1.1 and Table 1.1 are total numbers related to casualties in fishing. The numbers related to each type of categories of casualties in fishing given in Table 1.2 are not given separately. However, Dorval [32] mentions a statistical report done in France that had disturbing facts for life at sea. According to the statistics, the probability of a fisherman dying at sea is 3%,  1  Chapter  1.  INTRODUCTION  2  while the probability of dying due to an occupational accident during his/her career is 50%. H e reports that the situation is not much different for other European countries as well.  1  4  Figure 1.1: Deaths per 10,000 man-years i n some occupations. (Source [36])  A s described by K u o , "Safety is a perceived quality that determines to what extent the management, engineering and operation of a system is free of danger to life, property and the environment" [43]. According to this definition, these three categories make a different contribution to the overall safety i n different circumstances. It is also implied that there is no absolute level of safety i n performing a task. Perhaps, the best that can be expected is to assess priorities for problem areas, which will produce the greatest return for an  Chapter  1.  INTRODUCTION  3  Table 1.1: Deaths and accident rates for 1985 per 1000 employees in some industries [26] Industry Ore and mineral extraction Coke ovens Oil and gas extraction Coal mining Construction Meted manufacturing Fishing industry  Deaths 0.54 0.29 0.26 0.17 0.11 0.06 1.05  Major accidents 2.97 5.71 3.39 4.17 2.26 2.42 6.42  improved safety. It is important to ensure an acceptable level of safety. The general safety problem in fishing can be studied in two categories in terms of casualties related : 1. to vessel 2. to occupational accidents on-board. Each category might involve different types of casualties as given in Table 1.2.  Table 1.2: Types of Casualties in Fishing Related to vessels Related to occupational accidents Grounding Falls Capsizing Crushing Collision Blows Fire and explosion Cuts, pricks, wounds Leaks Falling objects Foundering Caught by gear etc. etc.  A safer vessel from the vessel casualties point of view may mean increased stability  Chapter  1.  INTRODUCTION  4  while the other group requires introduction of ergonomic design concepts, i.e. design of a fishing vessel as a work place. For example, in the first category, improvements in a vessel's safety could mean improved design features, e.g. increased initial stability, watertight deckhouses or a better understanding of the factors that degrade safety in the vessel's lifetime. For the second category, occupational accidents, improved safety may mean improved working conditions on-board of vessels. This could involve reduction in levels of noise, as well as vibration and motions i.e motion amplitudes and acceleration levels, better deck and bridge design, training and education of fishermen, etc. It is also interesting to note that requirements for each category towards a safer vessel may dictate conflicting goals. For example, increased GM, which is a parameter related to initial stability, could be desirable from a vessel's safety point of view, though it may prove otherwise for the crew on-board as the frequency of roll motion may fall in the uncomfortable region for humans. With regard to occupational casualties in fishing, Chaplin and Burney [26] believe that this is partly because a fishing vessel is a moving platform to work on and expose fishermen to the elements which are not generally experienced in other industries. Additionally, they suspect that unrestricted working hours in fishing, unlike other workers ashore, may impose higher levels of fatigue on the crew. There are two relevant factors for greater safety: • Identification of the main problem areas • Knowledge of remedial actions which will be effective. Then prevention from accidents may be considered in three stages: • Design Stage • Construction Stage • Operation Stage  Chapter  1.  INTRODUCTION  5  The identification of problem areas and the understanding of how casualties occur will help to improve the measures necessary to be taken. In the design stage, it is important to check whether any safety regulation is violated or not, and determine what kind of recommendations are provided by the rules of classification societies and regulatory bodies. It is also necessary to design an adequate protective system to withstand the effects of the accidents. Thus, every possible means of eliminating hazards can be taken into proper consideration. In the construction stage, safety is mostly related to the supervision of whether those safety features specified in the design stage were properly constructed and provided, such as hand-rails, non-skid floors, etc. In the operation stage, the training of crews and a good maintenance policy will influence safety problems, in particular the avoidance of hazards, listed in Table 1.2. More discussion can be found on the casualties related to occupational accidents onboard fishing vessels in Chapter 2. However, the following numbers taken from [66] with regard to accidents on-board of fishing vessel in Canada illustrate the severity of the safety problem: Year  Injured  Died  1988  109  12  1989  111  16  1990  80  11  The consequences of occupational accidents or danger of having casualties can be considered in two categories: • Cost of injured and dead crew to society and the economy.  This cost can be  expressed in monetary terms as well as the impact on those left behind.  Chapter 1.  INTRODUCTION  • Cost of lost opportunity to fish. A s reported by Tupper  6  [67], the New England  fishing fleet in the U S A operates at 60% of its annual natural production capacity because they are forced to halt fishing due to deteriorated sea conditions.  1.1  Objective of This Study  B o t h human health and life and monetary aspects of the losses due to occupational accidents on-board fishing vessels continue to be a matter of concern. W i t h this in mind, in this study the main interest area is the identification of the most important factors affecting occupational safety, crew comfort and performance aboard fishing vessels. After the definition of the factors, the objective is then to develop a design tool for the preliminary design of fishing vessels, which will include some ergonomic rules in order to improve living and working conditions hence crew safety on-board fishing vessels. A design modification including a step to minimize crew risk related to occupational accidents is also one of the objectives of this study. In order to develop such a design tool, one needs to establish some kind of mapping between the parameters that define a vessel and the factors related to a human being's performance or well-being on-board of a vessel: for example, above 0.2g R M S vertical acceleration, the performance of personnel on-board degrades for certain tasks. In order to be able to use such information in ship design we need to establish a relationship that maps a given sea conditions and a vessel to the acceleration levels on-board of the vessel under consideration.  1  According to the terminology used in Chapter 4, this is a mapping between the design characteristics and the performances. 1  Chapter 1.  1.2  INTRODUCTION  7  Proposed Method  In earlier studies within the Mechanical Engineering Department in the University of British Columbia , a general formulation technique following a classical design spiral and using a nonlinear optimization technique was implemented for the preliminary design of fishing vessels. The procedure based on an objective function and a series of equalities and inequalities was solved with existing computer codes such as Coupler Optimization Technique [14]. As a follow-up an Expert System shell (PC Consultant) was used to simulate a classical ship design spiral [24]. This study is based on the use of a knowledge-based system developed at Simon Fraser University called Echidna [60], [37] which has features that make it more suitable for design. While in principle any nonlinear problem solver that handles inequalities and equalities could be used to design a ship, Echidna with its built-in logic to handle constraints, and the ability to reduce the design space using constraint propagation, offered a superior programming environment. The main difference between an approach based on a design spiral or a sequential solution and a knowledge-based solution is that in the latter there was no assigned solution path. The solution path is internally selected by the program based on the available information and constraints supplied to the knowledge base. The Echidna system enables the user to define constraints, ranges, tolerances and relationships for vessel design parameters such as length, beam, draft, displacement, etc. The built-in constraint processing facilitates the informationflowbetween the parameters during each iterative cycle of the design, thus narrowing the feasible domains of the parameters. For the purpose of this study, the preliminary design of two ship concepts - namely monohull and SWATH, have been implemented in an Echidna environment. The SWATH concept was selected as an alternative to a monohull because of its superior seakeeping  Chapter 1.  INTRODUCTION  8  qualities. The implementation and validation of these concepts in Echidna are further discussed in Chapters 5 and 6. The results of these'two implementations, which had no ergonomic design considerations during the design, are reported in [25] and [4] for monohull and SWATH concepts respectively. From the existing information in the literature, vessel motions are reported to be the most important contributing factors to occupational accidents on-board of fishing vessels [67], [56], [31]. Two different rule sets, referred to as Rule Set I and Rule Set II in this thesis, are used during the design for improving the conditions on-board in terms of vessel motions. The effects of these two set of rules on the size of the designs as well as building costs are given in Chapter 7.  Chapter 2 OCCUPATIONAL S A F E T Y ON-BOARD FISHING VESSELS  Crew members perform different tasks on-board fishing vessels. As shown in Figures 2.1 and  2.2, the tasks could be related to handling of net and doors. Depending on the  fishing method, e.g. gilnetting, trawling, etc., and whether or not a factory ship is used, crew members may also perform such tasks as gutting, transferring the fish along the deck, cleaning the catch after the catch is taken aboard as illustrated in Figure 2.3. During the course of this study, afishingtrip was made on-board Eastward-Ho; this is one of the fishing vessels operating in the West Coast of Canada. Two of the photos taken during that trip is given in Figures 2.1 and 2.2. These photos show two example work postures for this particularfishingmethod. In thisfishingtrip, the catch (handled-in net) was immediately transferred to a factory ship nearby. After this, the net was returned to the fishing vessel. Figure 2.1 shows some of the crew members trying to snag and hand the empty net on-board. Figure 2.2 shows a crew member securing one of the doors, also called as otter boards, after the fishing had been completed. These metal doors, act as lifting surfaces, which keep the front of the net open during trawling are quite heavy. In rough sea conditions, securing the doors may endanger the crew member.  2.1  Statistics of Accidents On-board  In an attempt to understand the working conditions aboardfishingvessels, some of the accident statistics in the literature are reviewed in the present section. Statistics on  9  Figure 2.1: Crew members trying to transfer an empty net from the factory ship.  Figure 2.2: A crew member working at the stern to secure one of the doors used to keep the m o u t h of the trawl net open while trawling.  Chapter 2. OCCUPATIONAL SAFETY ON-BOARD FISHING VESSELS  12  accidents and related factors are useful in exposing the problem areas and detecting the patterns leading to an accident. The following is the review of some countries reported in the literature. 2.1.1  Canada  In Canada, there are more than 42300 vessels according to Transport Canada, Fisheries and Oceans Canada [66]. For the fishing industry, it is estimated that the number of fishing vessels operating in Canadian waters are approximately 40000, of which some 20300 are on register. The rest of the fleet is believed to be consist of unregistered small fishing vessels. In a report published by the Transportation Safety Board of Canada [66], accident reports in the Canadian fleet, including all types of vessels, during the period of 1981 to 1990 were studied and some of the statistical results were summarized. Tables 2.1 through 2.3 from [66] are important in showing the present situation in fishing vessels in comparison to other vessel types in Canada. In the tables, the category "other" represents vessels such as research and survey, ice breaking, laying and repair of seabed cables, search and rescue, pilotage, dredging, patrol, naval service, pleasure, etc. According to the tables, fishing vessels seem to be one of the most dangerous vessel types. However, a simple comparison of the number of accidents among the different types of vessels does not reveal much in terms of exposure to risk. In Table 2.4, the percentages of the number of casualties occurred in fishing vessels are given. As 10 year averages, calculated from Table 2.4, 36% of the aboard accidents, 40.18% of the total number of fatalities and 35.57% of the total number of injuries occurred in fishing vessels. This is followed by cargo vessels with 28.57%, 24.38% and 29.18% in accidents, fatalities and injuries respectively.  Chapter 2. OCCUPATIONAL  SAFETY ON-BOARD FISHING VESSELS  13  Table 2.1: Accidents Aboard Canadian Registered Ships by Vessel Type (Source : [66, pp. 36]) Vessel Type Cargo 0B0 Tanker Tug Barge Offshore Fishing Passenger Ferry Other  1981 37 1 7 11 3 3 59 6 7 12  1982 47 3 7 6 1 5 66 2 8 14  1983  1984  65 0 5 2 4 7 66 2 3 11  63 4 9 8 2 19 43 4 6 16  1985 65 0 9 14 3 14 75 10 5 29  1986 46 0 4 9 2 10 83 5 17 33  1987 61 2 5 5 1 3 105 6 9 45  1988 82 0 13 9 3 3 109 5 4 37  1989 80 2 21 9 5 8 112 8 13 101  1990 83 2 16. 6 6 3 80 6 7 115  Table 2.2: Fatalities Aboard Canadian Registered Ships by Vessel Type (Source : [66, PP- 36]) Vessel Type Cargo OBO Tanker Tug Barge Offshore Fishing Passenger Ferry Other  1981  1982  1983  1984  1985  1986  1987  1988  1989  1990  5 2 0 1 2 1 10 2 5 4  14 0 1 1 0 2 16 1 4 2  11 0 2 0 3 0 8 1 1 1  6 0 1 2 2 1 7 0 3 0  10 0 1 1 1 2 9 3 2 3  4 0 2 1 1 0 4 1 2 2  6 0 0 1 0 0 13 0 2 1  7 0 1 3 0 0 12 0 2 0  2 1 1 1 3 0 16 1 1 0  2 0 0 1 0 0 11 2 4 1  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  Figure 2.3: Tasks performed on-board after taking the catch is in (from [8, p  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  15  Table 2.3: Injuries A b o a r d Canadian Registered Ships by Vessel T y p e (Source : [66, pp. 36]) Vessel T y p e  1981  1982  1983  1984  1985  1986  1987  1988  1989  1990  35  49  59  58  61  43  58  78  80  88  OBO  1  3  0  5  0  0  2  0  1  2  Tanker  7  6  5  9  8  2  5  12  22  18  10  5  2  6  15  8  4  6  8  5  Cargo  Tug Barge  2  3  3  2  3  1  1  3  2  6  Offshore  2  4  7  19  16  10  3  3  8  3  49  54  65  38  69  80  101  109  110  76  Passenger  7  1  1  5  8  4  6  5  7  4  Ferry  2  7  2  3  3  15  7  2  12  6  11  12  10  18  30  32  46  38  105  116  Fishing  Other  Table 2.4: Based on Tables 2.1, 2.2, and 2.3, the percentages of aboard casualties occurred on Canadian Registered fishing vessels. 1981  1982  1983  1984  1985  1986  1987  1988  1989  1990  Accidents  40.41  41.51  40.00  24.72  33.48  39.71  43.39  40.91  31.20  24.69  Fatalities  31.25  39.02  29.63  31.82  28.13  23.53  56.52  48.00  61.54  52.38  Injuries  38.89  37.50  42.21  23.31  32.39  41.02  43.35  42.58  30.98  23.46  Year  Tables 2.6, 2.7 and 2.8 examine the casualties in terms of the primary contributing factors [66].  In these tables, "human factor" corresponds to operational errors on the  part of the people involved in fishing. "Environmental conditions" include atmospheric conditions, sea state and ice conditions.  T h e general status of the vessel and its cargo  are represented in the category of "vessel condition".  " Unfortunately, the values in  these tables are for all types of vessels given in Table 2.1, and not for fishing vessels only. 10 year averages of the contributing factors are given in Table 2.5.  According to  the tables, human factors, with 10 year averages of 61.58%, 70.45% and 59.02%, is the  Chapter 2. OCCUPATIONAL  SAFETY ON-BOARD FISHING VESSELS  16  Table 2.5: 10 year averages of percentage values of primary contributing factors in casualties aboard all vessel types Factor Human factor Environ, cond. Vessel cond. Equip./struc. Other Unknown  Accidents Fatalities Injuries 70.45% 59.02% 61.58% 3.61% 5.07% 4.31% 1.85% 2.77% 1.79% 3.55% 6.33% 3.55% 0.38% 0.00% 0.46% 26.93% 19.60% 27.31%  leading primary contributing factor in casualties aboard Canadian vessels. 2.1.2  France  In [32], Dorval mentions a statistical report prepared in France that had disturbing facts for life at sea. According to the statistics, the probability of a fisherman dying at sea is 3%, while the probability of dying due to an occupational accident during his/her career is 50%. He reports that the situation is not much different for other European countries. Dorval in [32] reported the results of four trawlers that were examined in terms of occupational safety. In that paper the integration of safety and working conditions onboard was discussed in the following categories : movements, accommodation, fishing gear, work stations and noise. The author used this to suggest some improvements in each category. Firstly, the movements of crew on-board during different stages of fishing, such as during the hauling of the net, were observed, and how the present layout designs of each vessel affected these movements were reported. Accessibility to different work stations on-board and communication between crew members were the main areas of concern for occupational crew safety. Furthermore, it was suggested that in the design, human  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  17  VESSELS  Table 2.6: Number of Accidents Aboard Canadian Registered Ships by Primary Contributing Factor. All vessel types mentioned in Tables 2.1, 2.2, and 2.3 are included. (Source : [66, pp. 38]) Factor Human factor Environment al conditions Vessel conditions Equipment /Structural Other Unknown  1981  1982  1983  1984  1985  1986  1987  1988  1989  1990  98  93  87  57  46  92  194  215  324  286  13  14  9  7  1  6  11  8  6  11  3  2  5  2  4  4  7  2  2  10  11 0 21  13 1 36  18 3 43  13 0 95  5 0 168  9 0 98  7 1 22  6 0 33  9 1 17  4 . 2 11  Table 2.7: Fatalities Aboard Canadian Registered Ships by Primary Contributing Factor. All vessel types mentioned in Tables 2.1, 2.2, and 2.3 are included. (Source : [66, pp. 38]) Factor Human factor Environmental conditions Vessel conditions Equipment /Structural Other Unknown  1981  1982  1983  1984  1985  1986  1987  1988  1989  1990  26  32  18  20  17  8  17  18  17  16  3  1  1  0  0  0  0  3  1  1  0  3  2  0  1  1  0  1  0  0  1 0 2  1 0 4  4 0 2  0 0 2  1 0 13  0 0 8  1 0 5  0 0 3  2 0 6  0 0 4  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  18  VESSELS  Table 2.8: Injuries Aboard Canadian Registered Ships by Primary Contributing Factor. All vessel types mentioned in Tables 2.1, 2.2, and 2.3 are included. (Source : [66, pp. 38]) Factor Human factor Environmental conditions Vessel conditions Equipment /Structural Other Unknown  1981 80  1982 75  1983 76  1984 42  1985 38  1986 85  1987 181  1988 205  1989 328  1990 285  12  15  10  7  2  6  17  10  5  11  3  0  3  3  3  4  7  1  3  13  12 0 19  20 1 33  19 4 42  17 0 94  6 0 164  9 0 91  7 1 20  9 0 31  7 1 11  4 2 9  factors' recommendations should be applied, such as the angle for a step ladder must be between 60° and 65°, unless there is an overriding need to do otherwise. Secondly, in the category of accommodation the suggestions for some of the trawlers examined were mainly related to the ventilation and living quarters having their own sink or washrooms. Thirdly source of potential accidents were arrangement and relative positions of the fishing gear and related systems, e.g. hoists and winches. The attention was drawn to the position of the fishing gear on the deck, (e.g at the bow or amidships), the way it is hauled or towed, the interference between the fishing gear and the other deck equipment. It has been suggested that fishing gear at the bow for stern trawlers (see Figure 2.4) is more advantageous than one amidships (see Figure 2.5). Fishing gear at the bow allows the net to be hauled on-board in a single operation, thereby reducing the physical effort required by the crew and the amount of time spent near the stern ramp. Forthly, on the fishing deck as a work platform, crew are exposed to the weather  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  19  conditions in all seasons, and depending on the sea conditions, spray and rushing sea water coming onto and clearing from the deck. Vessel motions are reported to be particularly important in terms of individual crew members' keeping their balance and the extra strain on the fishing gear. The broad suggestions listed for the general features of the work stations are : the working area should be uncluttered, have protection against falling overboard e.g. hand rail, have non-skid floors to minimize the probability of slipping and falling down; handling areas and work postures must follow the general ergonomic principles [32]. Fifthly, as far as the noise levels are concerned, two levels are mentioned. Firstly, a warning level , beyond which there is a danger of a hearing loss, is an exposure to 85 DB of steady noise for 8 hours a day and 40 hours a week. Secondly, when anyone is exposed to 90 db noise or greater, a significantly increased danger of a hearing loss and actions must be taken to change the exposure conditions. It was also noted that unlike land based work places, exposure to noise is continuous for the duration of a fishing trip, whether it is rest or working time. Their sample measurements in the 8 fishing vessels reveals that for one fishing trip: • 54% of the time the level of exposure was between 64 and 76 db • 39% of the time it was at 82 db • 7% of the time it was more than 90 DB with 3% of this time was above 100 db.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  Fishing Net  FISHING  VESSELS  20  Winches  Figure 2.4: Position of the fishing gear at the bow (from [32]).  2.1.3  United Kingdom  Chaplin and Burney [26] reported the casualties in United Kingdom Fishing Fleet for the period of 1980 - 1988. Table 2.9 divides the data with respect to deaths due to vessel casualties and personal accidents, which might also be called occupational accidents. As far as the total numbers are concerned, there is not much difference in the two categories. The authors also divided the data with respect to vessel size, that is vessels less than 24 meters in length and vessels longer than 24 meters. The total number of deaths for vessels longer than 24 meters in both casualty categories (vessel casualties and personal accidents) are small compared to smaller vessels. In the category of deaths due to personal accidents, the authors examined the death rates by taking account of the number of men at risk. For vessels below 24 meters number of deaths per 1000 at risk is 0.41, which is almost one third of the rate 1.48 for vessels above 24 meters [26]. As far as non-fatal accidents are concerned, these authors reported that during 1986  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  21  Winches  Figure 2.5: Position of the fishing gear in the middle (from [32]). to 1988, rates were 4.7 men per 1000 for vessels between 10 to 24 meters, and about 20 men per 1000 for vessels greater than 24 meters. According to this, the probability of a non-fatal accident happening on a vessel larger than 24 meters is almost 4 times greater than the probability on a smaller vessel. However, these authors suspect that there is significant under-reporting of non-fatal accidents in vessels below 24 meters. This may unfairly bias the data against vessels above 24 meters.  A s for the causes of accidents,  they report that between 50% and 60% of non-fatal accidents on vessels above 10 meters occur during handling or stowing of fishing gear, while 40% occur through different causes such as vessel movements, sea washing inboard or negligence. T h e authors caution about the distinction that an accident might occur while someone is working with fishing gear, yet the real reason might be the movement of the vessel.  2.1.4  Norway  According to Kjerstad [41], the mean length of the Norwegian fishing fleet is 21.9roer.ers.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  22  Table 2.9: Deaths in U n i t e d K i n g d o m Fishing Vessels during 1980 - 1988 (Source : [26]) Length < 24 [m]  Length > 24 [m]  Total  Personnel accidents  70  29  99  Vessel casualties  87  7  94  B o t h groups  157  36  193  Casualty group  Table 2.10: Ratio of number of fishers with respect to the length of the vessels in the Norwegian fishing fleet  [41] Vessel L e n g t h , meters  Ratio  Less than 12.1  1/3  Between 12.1 and 24.3  1/3  Greater than 24.3  1/3  T h e distribution of number of vessels in different length ranges is given in Table  2.10.  In another classification, the Norwegian fishing vessels are divided into three groups, namely inshore, coastal and deep sea fishing vessels. T h e vessels smaller than 8 meters in length, which are mainly inshore fishing vessels, are known to have very high roll frequencies (15 to 20 roll periods per minute [41]). T h e most conspicuous characteristics of the Norwegian fishing fleet is that in vessels with an L O A up to 15 meters, the main ergonomic concerns are due to lack of space on the working deck and little shelter in the work area, and the vessels' motions. However, as the sizes of the vessels increase, noise in the working-deck and the accommodation area cause some problems [41]. According to a statistical study of accidents on-board, the injury rate is mentioned as 58 per 1000 man-years in  [36]. In relation to the age group, the probability that the  youngest crewmen are injured is double the average. This is attributed to the less work experience.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  23  Table 2.11: Contributing factors to on-board casualties in the Norwegian fishing fleet ([34] in [41]) Factor Number of occurrence Vessel motions 10 Slippery/icy deck 10 Water on deck 5 Slippery/icy ladder 4 Missing gangway 2 Low temperature 3 Vibration 2 Exposure to unshielded equipment 2 Heavy work load 5 Numerous working hours/lack of sleep 3 Monotonous routines 2 Bad weather 8 Other 19  From the investigation of accident reports, Hansen [36], and Kjerstad and Grinde [41] give the following as the most important the contributing factors to accidents: • Large vessel motions • Slippery/ icy decks • Water on deck • Slippery/icy ladder • Heavy work load In Table 2.11 from [41], some additional factors, as well as those listed above are given with their number of occurrences.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  24  Table 2.12: The most important causes of injury in the Norwegian fishing fleet [36]. Values are % of the total disabilities or less serious injuries. Resulting in Cause Disability (%) Less serious injury (%) Falls 38 30 Crushing 36 20 Cuts, rips, pricks 16 15 Total 90 65  In [36], Hansen lists falls, crushing and cuts as the most important causal factors. Table 2.12 shows the types of injuries caused by these factors. According to the table 90% of the disabilities infishingis caused by these three groups. For less serious injuries, they constitute 65% of the whole. Hansen considers large vessel motions to be a very important contributory factor in all casual groups mentioned in the table. The estimated total annual cost of accidents infishingis approximately 32.3 millions Pounds according to Hansen [36]. The following presents the cost categories involved. Present value of human lives lost, injuries, and losses in production  Nkr. 187 Millions  Medical and institutional  Nkr. 40 Millions  Cost of founderings  Nkr. 48 Millions  Cost of casualties  Nkr. 80 Millions  Total annual cost  Nkr. 355 Millions (Pounds 32.3 Million)  Chapter 2. OCCUPATIONAL  SAFETY ON-BOARD FISHING VESSELS  25  Although the above analysis does not distinguish explicitly between the cost associated with vessel casualties and the occupational/personal accidents, Hansen [36] estimated the annual cost of each category to the society around 16 millions Pounds by assuming it is equally divided. In [41], Kjerstad and Grinde also focused on the effect of the working environment on accidents and health issues on-board vessels in the Norwegian fishing fleet. They highlighted the fact that high standards of living quarters on-board help to ease some of the stress during rest times. In their observations, since the off-duty living conditions on-board have reached a satisfactory high level in recently built vessels, more attention should be given to improve the working environment, e.g. the handling of gear and the catch. Kjerstad and Grinde [41] describe the working conditions on-board Norwegian fishing vessels as crowded with equipment, some of which are dangerous, in addition to the vessel's continuous motions. They also report a tendency, among the crew who work long hours, to complain of many ergonomic and mental strains. In their findings, the largest and newest vessels seem to have more comfortable work environments, in contrast to the smaller and older coastal fishing vessels, which are exposed to more severe working conditions, especially due to the long working hours and the excessive motions of the vessels. Also in these vessels the most frequently reported [41] factors are noise, strong vibrations and dangers while operating equipment on the deck. The sample measurements of noise levels reported in [1] (from [41]) are given in Table 2.13. According to the samples given in the table, in almost all of the areas, in which measurements were made, there is a concern about the high noise levels. After finding some complaints of the more strenuous working conditions on vessels that were 20 years and older, the authors compared the new and the old vessels in thefleetin terms of hard climate, use of out-of-date equipment, ergonomic strain and work stress. The conclusion of the authors was that the quality of working conditions were approximately the same,  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  26  Table 2.13: Survey on noise levels on 17 Norwegianfishingvessels ([1] from [41]) Area  Engine room Bridge Accommodation aft Accommodation forward Working deck  Full speed (min, max, middle) 99, 110, 104 64, 90, 79  Fishing condition (min, max, middle)  65, 85, 78  65,70  70, 90, 76 66, 90, 76  68, 77, 72 65, 81, 72  58, 72, 68  Max recommended level DB (A) 110 (unmanned) 65  60 - 65 70 - 85  although exposure to excess motions in rough seas, too much vibration and impure air was less in the newer vessels compared to the older ones. The authors also compared the casualty statistics for differentfishingtypes (see Table 2.14). Despite the high number of casualties, gillnet and longlining was not regarded as the most dangerous type offishingdue to the lighter levels of injuries. However, trawling is considered as a more dangerousfishingmethod as reflected in the serious nature of the injuries which occurred. The authors [41] claim that there would be a 10% reduction in the mortality rate if working conditions were improved for the 14% of thefishingcrew who work in the most dangerous conditions. According to the interviews with thefishingcrew in the Norwegianfishingfleet, the suggestions made to improve the working conditions on-board were [41]: • a reduction in the amount of time spent fishing, • reducing the work related stresses on-board.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  27  Table 2.14: Number of casualties for different fishing types in the Norwegian fishing vessels ([12] in [41]) Type of gear Handline Gillnet Longline Mechanized longline Seine Purse seine Trawl  2.1.5  Casualties per 1000 units 18 26 27 69 14 34 38  Spain  A survey team from CETERA-Spain (Technical-Maritime Study Center) investigated and reported the living and working conditions on several Spanish fishing vessels [22]. According to the interviews done with approximately 400 Spanish fishermen, 82% complained about disturbance from ambient noise, 65% about exposure to vibrations and 42% about high risk of suffering accidents. The team also focused on : • the technical characteristics of the fishing vessels' design, • the layout and the type of equipment used on-board, • the work procedures on-board, • the living conditions on-board, • the existence and efficacy of safety measures on-board. The most noticeable deficiencies observed are given as follows: • High risk of falls into the sea and on deck,  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  28  • Excess effort due to arduous operations in confined spaces,  • Deficient lighting , especially for high risk tasks,  • High noise levels, • Uncomfortable accommodation, lacking in privacy,  • Insufficient means of fire extinction.  According to their survey the highest work accident rate corresponds to deck staff (see also Tables  2.15 and  2.16). This is explained, by first, a higher representation of  drifter and trawler vessels in the vessels examined and the higher percentage of deck staff in the whole fishermen population. Secondly, the deck area is the most dangerous work place on the vessel. Table  2.17 shows the places where accidents occurred in Spanish  fishing vessels. In parallel to the above, the deck area and fish bay are the places where the highest number of accidents happen. T h e engine room and gangway follow that as second and third respectively. In respect to the gangway, an area that includes the means of access to the vessel, the possible causes of accidents given by the team are as follows:  • insufficient protection of steps or planks,  • lack or scant of handrail,  • dirty or slippery rungs,  • large height difference between vessel and dock,  • insufficient lighting of the gangway.  Having established some statistical picture of the conditions on-board Spanish fishing vessel, the team studied the agents (e.g. robes, cables, etc.) which were involved in work  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  29  Table 2.15: % number of accidents on deck by type of crew member in Spanish fishing vessels [22] Category Sailors(working on fishing gear, handle the catch, etc.) Skippers Petty officers Refrigeration Deckhands Officers Mastmen  % number of injuries 65.97 20.14 6.94 2.08 2.08 1.39 1.39  Table 2.16: % number of accidents by type of crew member in Spanishfishingvessels (Source [22]) Category Total deck Total machines Total catering  % number of injuries 75. 19.79 5.21  accidents. The list of agents and the types of consequences are given in Table 2.18. Falls, three categories mentioned in Table 2.18, is the most numerous work accident in the Spanishfishingvessels. Accidents involving winches and blows against miscellaneous objects are among the other most common types. Some of the possible causes of the accidents are given : • Slippery / dirty decks or floors, • Failure to wear suitable foot wear with non-slip soles, • Movements of vessel due to the state of the sea, wave shock, etc.,  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  30  Table 2.17: Places of accidents in Spanish fishing vessels [22] Place Number of accidents % number of accidents 192 On board 97 Going to/coming from the vessel 6 3 Vessel at sea 84 157 Vessel in port 30 16 Deck andfishbay 108 69 Engine room 15 10 On gangplank 12 8 Holds 7 4 Steps 4 3 Freezer rooms 3 2 Accommodation 3 2 Bridge 2 3 Kitchen 2 1  • Objects,fixedor notfixed,which hinder free, movement and are capable of causing trip or slip, • Insufficient protection at edges of vessel, low height of gangway etc., • Insufficient protection from moving parts, • Failure to use protective gloves or other elements, • Lack of coordination between the person who controls, the winch and the one who carries out other tasks. The survey team [22] also reported that falls into sea are the most serious accidents, in which 15 accidents with 14 deaths and 1 crushing between vessel and dock occurred. Apparently, they occurred during the course of work on deck. As for the falls at different levels, there were some miscellaneous bruising and fractures reported.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  31  Table 2.18: Work agents causing the most serious injuries in Spanish fishing vessels Agent Robes, cables  Amputation  Crush  Bruise  Injuries  1  2  Boxes 6  Falls from height Falls into sea  Fracture  Wound  %  2  1  5.00  2  1  2.50  7  10.83  1  0.08 14  Falls same level  2  Cuts Straps, belts  2  [22]  1  14.17  5  4.17  1  2.50  Struck by fixed objects  4  6  2  10.00  Struck by mobile 4  1  8.33  Power tools  1  1  1.67  H a n d tools  1  3  1  3  items  Winches Haulage doors  5  11 2  1  3.33 1  1  3.33  F i s h handling  1  Pulley, etc.  2  Doors  1  2  Chemical products  13.33 0.08  2  5.00  2  2.50  1  0.08  Check stoppers, break  1  0.08  1  4.17  Breakage: ropes, cables Net  1  2  2  5  1  5.83  In the accidents involving winches, the possible reasons mentioned are:  • lack of communication between the person in control and the others,  • lack of sufficient protection from moving objects, e.g. cables, ropes, fish, etc.,  • failure to use protective gloves.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  32  Main consequences in these accidents are amputations of fingers, broken fingers, bruising and wounds. In relation to blows against miscellaneous objects, the authors [22] report that in one third of the accidents, the effects could have been reduced if the corresponding protective elements, such as gloves and helmet had been used. Approximately, 5% of the total accidents occurred when dealing with nets or seines on deck during fishing. The common injury types in this group are amputations of fingers and fracture. 2.1.6  Japan  In a different survey, Amagi and Kimura [5] analyzed the injuries to fishermen in scallop beam trawlers in Japan. According to their observations, the most common accidents are as follows : • Two dredge nets on the deck move and strike fisherman • Fishermen are caught between dredge and hull • Fishermen accidentally run into the hull, bulwark, hatch or dredge net. 2.2  Some notes on accident statistics  Kose [42] also studied the fishing vessel casualties in the world. According to his analysis, human error was found to be the most important cause of the total loss of the vessel. It was then suggested that in order to reduce human error, motion and noise levels on-board fishing vessels should be reduced [42, page 107]. In most of the cases reviewed above, there was a general agreement that the working conditions on-board fishing vessels needed improvement. The primary contributing  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  33  factors to the on-board accidents are vessel motions, slippery floors and ladders, noise, fatigue due to long and arduous working hours and insufficient work space. Vessel motions are also believed to be a contributory factor in most of the accidents. In fact, in determining the how an accident occurred, there might be more than one contributing factor involving at the time. In the prevention of these types of accidents, some of the contributing factors, such as slippery floors, can be dealt with more easily than some others such as vessel motions.  2.3  Impact of Ship Motions on Fishing  Vessel motions can impact on fishing in different ways. As reported by some authors above, vessel motions can contribute to accidents on-board. This means lose of life or injuries, and lost working hours. In another way, vessel motions interfere with fishing operations and causing it to be halted as explained in the next paragraph. In either way, Tupper [67] reported that it has undesirable consequences in monetary terms. In [67], Tupper examined the New England Groundfish industry. After studying the good weather fishing performance in terms of number of fishing trips and fish landings throughout one year, he reported a good correlation among the three. Based on this correlation, he concluded that the amount of catch per unit effort is approximately constant. However, dockside fish prices vary almost by 50% between a high during winter and a low during summer. This was explained by the varying number offishingtrips due to weather conditions. His conclusion was that due to deteriorated weather conditions, which also imply larger vessel motions, the New England fishing industry operates at 50% of its potential efficiency and effectiveness. Based on his interviews with fishermen and a survey on the motions' effect on fishing, he reported six ways in which vessel motions interfere with fishing:  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  34  • danger to vessel, • gear does not fish, • vessel can not stay on gear, • loose gear on deck poses threat, • water on deck poses threat, • motion impact on crew. Danger to the vessel, includes the danger of swamping, capsize, loss of directional control and structural damage due to slamming. Heave and pitch mainly affect fishing and "gear does not fish" because the net and doors experience a pulsing motion. This reduces the mouth of the net and disturbs fish before they go into the net, hence the catch rate is reduced dramatically. Loose gear on deck can cause a threat to the vessel, crew or itself. Similarly, water on deck can be a danger to the crew, fish that is being processed on deck, and to the gear. The effects of ship motions on crew are seasickness, slipping and sliding, jerking around and exhaustion from fighting motion. By the frequency of occurrence, Tupper ranked the above items in halting fishing. The most frequently reported reasons are • gear does not fish • fishing vessel can not stay on gear • jerking around • exhaustion from trying to counteract the motion of the boat.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  35  Slips and slides, and water on deck are cited as moderately frequent reasons. Perhaps surprisingly, danger to vessel was the least frequent reason listed. The motion interference with the crew could be in two ways. The immediate effects are to impair crew members' balances and thus they may have to simultaneously adjust their position. In the second case, the effect is cumulative and in the longer term showing up as fatigue and exhaustion. In general,fishermenare exposed to different types of body motions and accelerations due to ship motions in different sea conditions. The injuries related to the excessive motion can be grouped as sudden acceleration impact injuries and injuries due to motion sickness. The symptoms of motion sickness vary between individuals and depend on the environmental conditions, e.g. surrounding scenery, smell, etc. The development of symptoms of motion sickness can take many minutes in ships in contrast to the exposure in laboratory conditions which may result in vomiting in a few seconds or in a few minutes [35]. To study motion sickness phenomena and its relation to motion characteristics O'Hanlon and McCauley [54] subjected a number of students to platform motion in a laboratory conditions. They were exposed to motion frequency in the range of 0.083 Hz to 0.5 Hz. and acceleration levels in the range of 0.03 g to 0.4 g, where g is the acceleration due to gravity. The results showed that the highest motion sickness incidents occur around 0.2 Hz. frequency and number of incidents increases with acceleration. They proposed a formula for predicting motion sickness incidence (MSI) as a function of the acceleration magnitude and frequency.  (2.1)  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  36  where M S I is the percentage of subjects in the experiment who experienced vomiting within two hours; x is a variable of a log-normal distribution with the following definition for p and cr.  p  =  0.659 + 3.840 l o g / + 2.467(log/)  cr  =  0.40 log a  2  p corresponds to the log a value associated with a 50% M S I value for a particular level. Lower p values indicate that less acceleration is required to produce the same M S I . a is given as a = 0 . 6 3 7 a  max  — 0 . 9 0 1 a , where a  in each half-wave cycle, and a  rm  m a x  r m 5  is the root mean square of acceleration  is the absolute value of peak acceleration.  For motion sickness incidents, ISO 2631 part 3 ( International Organization for Standardization, 1985c) suggests the magnitudes of vertical oscillation expected to produce a 10% incidence of motion sickness in sitting or standing over the 0.1 - 0.63 H z . frequency range as follows:  a t =  constant  where a is the rms (root mean square) acceleration and t is the exposure time. British Standards 6841 (British Standard Institution, 1987a) also defines a realizable frequency weighting (Wg) to be used for assessing low-frequency motion with respect to motion sickness. Realizable weighting implies greatest sensitivity in the range 0.16 - 0.2 Hz. Having defined some criteria for motion sickness, Aboulazm Lloyd  [2], and Andrew and  [6] proposed methods for designing ships with reduced number of motion sickness  incidences.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  37  In [2], A b o u l a z m describes the ship motion characteristics causing seasickness and presents the human tolerance, based on the human physiological factors, and the severity of ship motions. In a different study, Andrew and Lloyd [6] suggested a method of assessing the subjective motion magnitude (SM) of ship motion to be used in motion sickness evaluation as follows :  1.43  SM  = A  (2.2)  where A defines a frequency weighting (A = 30 4- 13.53(ln / ) ) , a is the amplitude of the 2  vertical acceleration (m/s ) 2  , g is the acceleration due to gravity (9.81ra/.s ), and f is 2  frequency in H z . To extend this relation to random motion, it is assumed that  a = s(rri4.) /  1 2  where 7714 and  and  are the variance of the vertical acceleration and the rate of change  respectively. Andrew and Lloyd [6] proposed a limiting value of 12 for S M for a 12 hour exposure. In this study discomfort were considered only in the frequency range of 0.25 H z . and 4.0 H z . W h e n the criteria mentioned above for motion sickness are compared, Equation  2.1  (O'Hanlon and M c C a u l e y [54]) relates motion sickness incidence to the magnitude and frequency of the acceleration. However, it is mathematically involved compared to the other criteria mentioned above. T h e ISO's criterion seems simpler to use and relates the magnitude of the acceleration to the exposure time.  It is interesting to note that the  frequency ranges for greater sensitivity to motion sickness incidence are approximately the same for the three criteria (around 0.2 H z for the criterion of O'Hanlon and McCauley, 0.1 to 0.315 H z . for ISO criterion [35, p 308] and 0.16 to 0.2 H z . for British criterion).  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  38  T h e criterion for motion sickness suggested by Andrew and Lloyd [6] is not intended to predict motion sickness incidence. However, it gives a measure of merit to evaluate subjective discomfort due to the oscillatory motion in 0.25 to 4.0 H z . frequency range. For the other effects of ship motions i.e.  other than motion sickness, A m a g i and  K i m u r a [5] suggested a method to reduce the number of human casualties in which ship motions are believed to be an important factor.  In order to reduce the effect of ship  motions the authors proposed a forebridge type vessel with the working deck astern of the bridge. In this way the effect of pitching on the working deck area is to be reduced. K i m u r a et al developed the following formula in [40] for evaluating the conditions on-board of fishing vessels in regard to maintaining one's balance. A T (threshold) value of 0.22, above which a crew member can no longer maintain his balance, was suggested after their experimental analysis. T is given by Equation  T = Ml  x  + 0.1659 Ml  y  2.3.  + 0.1133 Ml  z  (2.3)  where M l is the first moment of power spectrum of the acceleration on deck, x,y and z subscripts represent the coordinate axis x,y and z.  /•oo  M l = / u S{u)dw Jo  (2.4)  In their formulation, the acceleration components due to g (gravity) are neglected. From their experience, they claim that for small angles of pitch and roll motions g sin9 and g  cos^t  are negligible.  In a different study, Pingree [56] reported that for personnel performing tasks of a continuous nature the upper limits quoted for tolerable root mean square (rms) vertical acceleration as a proportion of g -acceleration due to gravity, is  • 0.2 (at bridge) in U S A ,  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  39  • 0.16 (at 0.2L) in Netherlands, • 0.18 (at 0.0L) in Germany, • 0.14 (weighted average) in the U.K., • 0.20 (at 0.2L from the forward perpendicular) in Canada. Furthermore, it was noted that there is an agreement of a seakeeping design criteria applicable to personnel for continuous exposure in rms values of 4.5° roll, 3.0° pitch and 0.18g vertical acceleration. The author also remarked that since many human motor processes are sensitive to the orientation in relation to the predominating motion, the personnel work stations should be designed with this in mind. The favorable orientation for an operator depends on the tasks being undertaken.  2.4  Design considerations for improved working conditions on-board based on warships  Towards improved working and living environment on-board fishing vessels, there have been number of suggestions made in the literature. Tupper [67] categorized design considerations in three groups: • designing vessels with reduced motions • arrangement of tasks on-board with the motions of the vessel in mind (e.g. amidship is being the most preferable place on the deck in terms of vessel motions) • arrangement of details of body supports at the work stations. Reducing the vessel motions pitch and roll implies an increase in the effectiveness of fins, bilge keels, chines and paravanes [67]. Tupper draws attention to the complaints that  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  40  vessels with sharp chines that have too jerky a motion. He also suggests G M (metacentric height) could be another control parameter. Larger G M values are needed for the stability of the vessel. Also, larger G M s tend to reduce roll motion amplitude, thereby reducing the acceleration and jerk levels. However, care should be taken in that increased G M values also mean higher roll frequency, which leads to higher acceleration and jerk. A s a note for simple sinusoidal periodic motion, acceleration and jerk amplitudes are (amplitude frequency ) 2  and (amplitude  * frequency ) 3  *  respectively.  Another design parameter mentioned by the author is the vessels' windage. a station keeping in rough weather stand point, windage should be kept down.  From Vessels  with high bow and low stern might have problems in staying on course when working over the gear at low speed and in high winds. For arrangements where tasks are carried out, Tupper reports that the positioning the pilot house very high and close to bow is very common. Although from a motions point of view, such a place is one of the worst locations on board, it can give a good all-round visibility from the pilot house. For body supports at work stations, the author suggest that handhold/handrails and body supports require more attention.  In designing the tasks, consideration should be  given to reduce the amount of distance a crew member required to traverse on a pitching a n d / o r rolling deck, and to eliminate the handling of heavy objects. Towards a safer ship in terms of occupational accidents, Stoop  [63] suggested a node  called "working conditions (safety) " be included into the design spiral.  He analyzed  some of the drawbacks in D u t c h beam trawler design and gave some guidelines for what the properties of a so called "Beamer 2000", a newly designed beam trawler including safety aspects, should be.  Similarly, in  [8] types of tasks performed on-board fishing  vessels were examined. Suggestions were made for a better working environment such as design of equipment etc, with respect to fishermen's safety.  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  41  In [55], Payne defined a method to quantify ride quality. He suggested that in the presence of a vehicle's motions with induced shocks or impulsive velocity changes, rms (root mean square) acceleration is not a good criteria to quantify ride comfort. Some useful evidence of experience in the design and operation of warships is given by Brown  [18], who examined the adverse effects of ship motions on the degradation of  performance. Due to bad weather, some of the consequences are course altering, reduction in speed, weapon operations becomes impossible and human performance degradation. For a given sea state, ship speed and heading, ship motions will vary depending on the angle between the ship's heading and the mean direction of the waves in the sea. Due to excessive ship motions, it may become necessary to alter the course of the ship. However, it may not always be possible as reported by Brown, for example during mine hunting. This kind of voluntary course altering is considered as a restriction of the operational capability of a warship. Another influence of bad weather is on speed. Generally, there will be involuntary speed reductions due to the increased resistance in waves, however, Brown reports that in most cases, there is a voluntary reduction in speed in order to avoid excessive motions, wetness, slamming and possible structural damage. T h e following are some of the limiting cases that he listed in  [18].  • In a 15 minute period, the peak slam induced whipping acceleration is 0.09g at the bridge.  • Subjective motion amplitude equals to 14. • T h e frequency of deck wetness is around one in every 40 seconds For helicopter operations in warships, Brown gives the following limiting values on some of the motion characteristics.  • Roll (single amplitude) up to 3 ^ ° , unrestricted, impossible over 5 ° .  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  42  • Combined heave and pitch vertical velocity is unrestricted up to lm/s, and the limit is at 2m/s. • Maximum transverse velocity is lm/s. Brown also mentions two aspects of ship motions induced effects on humans, these are when tasks on-board become more difficult to perform and when the human performance degrades over the period of time. The first is related to the amplitudes and accelerations of the motions, while the second depends on the cumulative effects of fatigue, loss of sleep, and nausea. For a 3000 ton frigate, the loss of fighting effectiveness is 10% in a sea state of 5, 30% for a sea state of 6 and 95% for sea states of 7 and over. Brown  [18, pp 44] estimates that "...the cost of bad weather to the assumed ship  (Leander - 3000 tons, 108 m in length) at 1985 values is Sterling 1.29 Million per year". On the basis of model tests on a similar size hulls, he concludes that "...It is unlikely that changes in shape will lead to further improvement, and only increased size or a change to a novel configuration such as SWATH remains". Furthermore, he assumed that in a ship fitted with active roll fins, the loss of effectiveness will be mainly due to heave and pitch motions. He then compared a 108 m ship and a 125 m ship in terms of loss of effectiveness. In the example he gives, the 108 m ship loses 11.7 days a year, whereas 125 m ship losses 7 days a year. In monetary terms, choosing the larger ship (125 m), there will be 404,200.00 Sterling cash savings per annum, that also amounts to Sterling 4,000,000.00 discounted @ 5% over 20 years. The author argues that although thefiguregiven for the savings has an error margin of ± 50%, there is a clear large savings possible. According the his estimations, the additional cost of opting for a larger, more spacious ship will be paid off in three years.  Chapter 2. OCCUPATIONAL  2.5  SAFETY ON-BOARD FISHING VESSELS  43  Methods for reduced motions  Walden and Grundmann [68] suggested methods to be used in the early design stages in order to investigate seakeeping characteristics of frigate and destroyer type hull forms, and estimate freeboard. They improved the method of the seakeeping rank factor originally given by Bales [11]. Bales' calculated seakeeping rank factor R as the average of the normalized rms values of eight ship motion related quantities, namely pitch, heave, relative motion at station 0 (forward perpendicular), absolute acceleration at station 0, slamming parameter at station 3 i.e. 15% of length from forward perpendicular, heave acceleration, absolute motion at station 20 (aft perpendicular), relative motion at station 20. Bales gives the estimation equation for the normalized hulls with respect to a 4300 ton hull as follows (also see [68]):  R = 8.42 + 45.1CW + 10.1CW - 378- + 1.27-=- - 2Z.5C p L  L  V  F  - 15.9C PA V  (2.5)  In Equation 2.5 : R  : Estimated seakeeping rank factor  CWF  '• Waterplane area coefficient forward of midships  CWA  '• Waterplane area coefficient aft of midships  T  : Mean draft  L  : Length  c  : Longitudinal location of cut-up, aft or forward perpendicular  CVPF  '•  CVPA  '•  Vertical prismatic coefficient forward of midships Vertical prismatic coefficient aft of midships  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  44  VESSELS  Walden and Grundmann report that the parameter (c/L) in Equation 2.5 is difficult to define and has negligible influence on the estimation. They also computed a correlation matrix between the reciprocals of the 8 ship motion related quantities mentioned above and the calculated seakeeping estimation factor R (see Table 2.19). According to this table, except for the quantity corresponding to the relative motion at station 20, all other quantities show a good correlation with the R value.  Table 2.19: Motion Correlations given by Walden and Grundmann [68]  R 1/0  V*  1/i'o l/*o c.  1/5 1/-S20 1/^*20  R 1/0 1/z 1 0.97 1 0.96 0.94 1 0.84 0.75 0.81 0.98 0.98 0.92 0.68 0.62 0.56 0.98 0.96 0.98 0.92 0.87 0.84 0.05 -0.11 -0.10  1/io  c.  1 0.82 1 1 0.42 0.67 0.79 0.95 0.62 0.86 0.90 0.47 0.31 -0.01 -0.08  1/5  1/aao  1 0.87 -0.07  1 0.34  1/^20  1  In Table 2.19 : R  : Calculated seakeeping rank factor  1/6  : Pitch  1/z  : Heave at the longitudinal center of gravity  l/r*o  : Relative motion at the forward perpendicular  1/i'o  : Absolute acceleration at the forward perpendicular  C  : Slamming parameter at station 3  1/5  : Heave acceleration at the longitudinal center of gravity  s  Chapter 2.  2.6  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  1/^20  : Absolute motion at the aft perpendicular  I/V20  : Relative motion at the aft perpendicular  VESSELS  45  Design margins  Generally, margins are used to increase the probability of success in an event or process with uncertainty in its outcome. However, there is also a cost associated in providing margins. Ship design and construction is no exception. Walden [68] mentions three categories of margins in warship design: Design and Construction Margins, Future Growth Margins and Assurance Margins. Design and Construction Margins involve three categories of uncertainties : 1. Prediction errors associated with estimating techniques, 2. The unknowns during the prediction, 3. Anticipated minor changes in the design specifications during the design process. Future Growth Margins are defined as the allowances made upon the request of the customer in anticipation of future installations in a ship. These type of margins enhance the ship's flexibility for successful adaptation to future needs. Assurance Margins are accommodated in the design for three reasons: 1. In order to maintain a required level of operating capability even under certain adverse circumstances 2. To offset the progressive and predictable degradation of equipment and subsystems in a ship  Chapter  2.  OCCUPATIONAL  SAFETY  ON-BOARD  FISHING  VESSELS  46  3. To account for the uncertainties involved in the loading and the capabilities of the systems being designed. In order to reduce ship size and cost associated with the margins, the author explored the feasibility of reducing design margins. For the example naval ship studied by Walden and Grundmann  [68], it is reported that weight and K G margins resulted in excess  area and volume. They concluded that the Future Growth Margins can be excluded, and Assurance Margins nearly so, if the reductions inflexibilityand performance can be accepted. On the other hand, Design Margins prove to be a more difficult case as the feasibility of producing a ship to meet design requirements is in question. Some of the Design Margins may be essential, and unless they are initially provided, the ship may have to be enlarged and the reiteration of the design may become necessary.  Chapter 3 A N OVERVIEW OF SHIP DESIGN  In the past each ship design was mostly based on one or more existing successful ships. T h a t is if a ship was observed to complete the delivery of cargo and return safely to the home port she was considered to be a "successful ship". Shipyards or the designers then included the features of such a "successful ship" in their own designs. Over the years ships grew in size, new materials were used and new production methods were developed and the installed power increased. During recent decades the developments in "Advanced Marine Vehicles" brought new practical hull configurations such Multi-hulls, hydrofoils, S W A T H s , S E S etc. T h e design procedure for such ships is now somewhat better understood and is aided by extensive use of computing systems and application programs. Once the geometry of a ship is known as a result of the preliminary design, there exist computer packages for commercial applications that can take the ship design from the lines drawing to the material ordering and assembly stages. T h a t is the design and manufacturing processes are now computerized and interconnected. While the advances listed above took place, the physical laws pertaining to the design and development of ships remained the same.  Similarly the preliminary design cycle  of a ship consists of almost the same number of steps, almost in the same  sequence.  There is a mathematical reason for this. In general the equations representing the owner requirements and the physical laws for ship resistance, stability, seakeeping, cost etc. are nonlinear. T h a t is the quantities that naval architects must establish, such as the length, beam etc. of the ship, influence ship stability and ship resistance in a complex  47  Chapter  3.  AN OVERVIEW  OF SHIP  DESIGN  48  way usually involving at least powers of the principal dimensions. In particular the linear theoretical wave resistance depends on the square of the beam and in a very complex way on ship speed. Similarly the value of metacentric radius depends on the square of the beam. While it is desirable for efficient powering to reduce the beam, the stability requirements might dictate otherwise.  Essentially a number of the equations a naval  architect solves, one way or other, are nonlinear in terms of the basic ship particulars. There is, in general, no simple procedure to solve such a set of nonlinear equations. In view of the above, the general ship design procedure can be outlined as follows: A naval architect collects information from successful ships, designed in the past. This forms the basis of a trial or a first order solution.  A method such as a perturbation  procedure or a trial and error procedure suitable for the solution of nonlinear equations is then followed.  T h e solution is expected to satisfy the owner requirements and the  physical laws for flotation, stability etc. T h e nonlinear nature of the equations suggests that the existence or the uniqueness of the solution are never guaranteed. In fact the wide variety of ships that essentially satisfy the same set of user requirements is a good proof that solutions are not unique. In another real life example, a press extract (Meek [49]) related to the bidding of 3 very large ro-ro vessels for a consortium reports that the consortium received 10 different tenders that prompted a ship-owner from the consortium as saying "we have now got 10 technical solutions and we have to pick out the best points and get them into one grand specification". We can conjecture that there may be some room to increase the nodes in the design cycle or the number of equations in the design process. T h a t is more conditions could be added as owner requirements or the number of equations in the set of equations to be solved can be increased. O f course the main questions are whether there is a need for this and what type of benefits one can have if more equations or conditions are added to the definition of the design problem.  Chapter  3.1  3.  AN OVERVIEW  OF SHIP  49  DESIGN  Overview of Literature for Ship Design  Height Groups Stability  Occupational Safety  Resistance k Powering  Economics  Seakeeping  Q i uD i ment  Figure 3.1: Design Spiral. Traditionally, the ship design process is represented by a design spired after Evans [33] in 1959. A similar ship design spiral to Evans's spiral is shown in Figure 3.1. The spiral representation depicts the very iterative nature of the process. Bremdal  [16]  describes the ship design process as a goal directed, iterative and creative process. The design starts with the mission requirements and proceeds through the nodes of the spiral towards a detail design. Buxton [21] in 1972 introduced economics into the design spiral.  Chapter  3.  AN OVERVIEW  OF SHIP  DESIGN  50  In his representation the spiral is divergent rather than convergent as shown in Figure 3.1. This shows the amount of increase in the knowledge acquired about the final design as the design process proceeds round the spiral.  Later Andrew represented the ship  design process as a helical corkscrew in an attempt to account for the open nature of the design process [7] in 1981. He incorporated into the spiral type approach some additional constraints related to the design process plus some constraints originating from the design environment. In these spiral type approaches, the characteristic of the ship design process is that it has a sequential and iterative nature. Mistree et al.  [50] criticized the design spiral  approaches mentioned above as the process of design they represented is sequential and difficult to incorporate life cycle considerations into it. Hence, they suggested so called decision-based design in 1990. frustum of a cone.  T h e y represented the design process by a funnel or the  In their representation, the design process takes place inside this  frustum in contrast to the other spiral approaches of  [33],  [21], and  [7]. E a c h phase  of the design such as preliminary design is depicted as an irregular disc-like shape inside the frustum (see Figure  3.2). In this representation, converging to a solution means the  irregular shaped disc becomes circular.  Weight Estimation /  Stability /  Powering  Ring of interaction  Figure 3.2: Representation of design process by Mistree et al.  [50].  Chapter  3.  AN OVERVIEW  OF SHIP  DESIGN  51  There are uncertainties involved in ship design. Some of them related to the environment that the ship will operate in such as market conditions, sea conditions, etc. Another group of uncertainties involve the estimation of ship characteristics such as weight and costs. Sen [59] gives an overview of some of the techniques to take uncertainty into account in preliminary ship design. Ray et al. [57] used a probabilistic modeling of uncertainty. In their simulation for a bulk carrier, the principal uncertain factors that have the greatest influence on NPV (net present value) are the load factor and the freight rate. Speed of the vessel, cost of fuel oil, crew wages and port charges are, of course, important and influential on NPV. According to Taggart  [64], there are four steps involved in the sequence of ship  design. These four steps, embodied in the spiral, are conceptual design, preliminary design, contract design and detail design . The concept design includes technical feasibility studies and creation of alternative solutions, e.g. different ship arrangements. In this stage, some of the main ship characteristics such as length, beam and power of the candidates are determined approximately. In the preliminary design phase, these and other ship characteristics are further refined. Some of the ship parameters e.g. length and beam are not expected to change after the completion of the preliminary design. At the contract design stage further the preliminary design definition is refined and extended e.g. hull form is faired, power estimation is more precise perhaps based on model testing.  Structural schema and some details are denned in this stage. Final  general arrangement is then developed. In the detail design as the final stage of ship design, detailed work plans are produced. These include constructional details, installation plans, instruction to welders, outfitters, etc. One important feature of this stage is that at this point the final product of the design is passed to the production teams.  Chapter  3.  AN OVERVIEW  OF SHIP  DESIGN  52  In the past, there have been different methods developed for the preliminary design part of the ship design. One of them, Mistree [50], is called design-through-enumeration. All design variables are expressed in terms of vessel length and the length is varied until a feasible design is reached. Another approach mentioned in [50] is conceptualizing the preliminary design as an optimization problem. In this context, Murphy et al.  [51],  Nowacki et al. [53] and Smith and Woodhead [62] are cited as examples of preliminary ship design modeled and solved as a single objective optimization problem. For the multiobjective formulation of the preliminary ship design, Lyon and Mistree [46] introduced some generic algorithms. Bower [14] developed a nonlinear optimization tool to be used during the preliminary design stage offishingvessels for an operational scenario reflecting the conditions off the West Coast of Canada. Another ship design tool using optimization techniques is reported by Ivanov and Apollinariev [38]. They developed a program for the design offishingvessels. They used steepest descent method for the optimization process. For the mathematical model, they used statistical information based on existing vessels. In the second part of the design package, the user is provided with a simulation tool forfishingvessel operations in order to evaluate the design further. Zanic in [71] introduced a different approach and developed a multi-attribute decision making system based on the random generation of nondominated solutions for fishing vessel design. However, this system requires fast computers. In fact, the program was run in a Prime EXL 7330 RISC workstation and during an example run for the design of a trawler, it is reported that a total of 159000 different alternatives were produced. Lee et al. [44] report an interactive computer system for the design of merchant ships. The program is integrated by using a relational database management system. It also has graphic user interface features. For a given set of owner requirements, it computes the  Chapter 3. AN OVERVIEW OF SHIP DESIGN  53  principal particulars, plus the shape of midship section and hull form. Furthermore, it performs structural design, strength analysis and evaluates hydrodynamic performances. The implemented design process utilizes the information on a similar ship, which is selected by the designer from the available database, i.e. the design from a base ship. In the absence of a base ship, the program performs preliminary design calculations based on the empirical formulae provided in the code. Once the hull form definition is completed, it can perform structural design and analysis, vibration analysis (i.e. natural frequencies and mode shapes of hull girder vibration based on beam theory), resistance and powering based on the statistical analysis of a database consisting of 397 model test data, propeller design and performance analysis and maneuverability prediction. In parallel to the foregoing, there have been developments in artificial intelligence based paradigms. Some applications of these new developments applied to ship design are reported in [3], [30], [72], [24], [25] and [4]. The examples listed here are by no means exhaustive. Akagi and Fujita [3] developed an expert system for engineering design. The system is based on an object-oriented knowledge representation. In [3], they report a case study applied to the basic design of ships. The domain specific knowledge was implemented for cargo ships, bulk carriers, and container ships. Initially, the system uses a trial and error method to determine the appropriate ship parameters that satisfy the design requirements, e.g. owner requirements. If the requirements are not satisfied, the designer selects the design variables to be modified by the system. By making a unit change in the selected design variables, the system computes the amount of changes in all other parameters. According to the effect of the unit change, the designer then applies appropriate amounts of change to the selected variables. In cases of failure to meet some of the design requirements and as an alternative to make unit changes they implemented optimization by sequential linear programming [3]. After a few trial and error searches  Chapter  3.  AN OVERVIEW  OF SHIP  DESIGN  54  for the solution, at the point reached they assume that the current position is in the neighbourhood of the solution. The gradient of the objective function (i.e. one of the design objectives such as the required hold capacity by the ship-owner), which has not been satisfied by then, is assumed to be not very steep in that region. Hence, in order to find a solution an optimization is performed. In their system, the design is implemented as shown in Figure 3.3. In [30], Daizhong and Forgie report another expert system developed for a general engineering design procedure. In their methodology, basic design units are used as building blocks of different concepts. Then different concepts formed by the basic units are evaluated by allocating marks to concepts which can then be ranked. At this stage, the designer can modify existing concepts or generate new ones. Once a concept is selected, this stage of the design is followed by the detail design. In this stage, the design parameters are determined. It is followed by initial layout design, individual component design and final layout design. For the layout design, they utilize some interactive graphical aids during the design. Zhou et al.  [72] describe an artificial intelligence based system, named CLEER,  developed to assist equipment arrangements on warships. The system is aimed to help improve electromagnetic compatibility among on-board systems and other equipments. It consists of the necessary databases of systems, equipments, etc. as well as knowledge bases for constraint definitions, information on existing arrangements on other warships and heuristic knowledge accumulated from previous experiences. Welsh et al. [69] developed an expert system environment for preliminary ship design. The system also has graphic display capabilities in order to visualize the final design product. Dai et al [29] describes a hybrid system integrating a knowledge-based system and a numerical optimization technique for ship propeller design so that propeller induced  Chapter  3.  AN OVERVIEW  OF SHIP  DESIGN  55  vibration is minimized. The design process is iterative and requires the experience of a propeller designer. In this hybrid system, the knowledge-based part of the system quickly produces a potentially good design point. Then the numerical optimization part of the hybrid system searches for the optimum in the neighbouring design space. The authors report reduced preliminary design time for propellers in comparison with other techniques. Calisal and McGreer  [24] developed an expert system for the preliminary design  of monohull type fishing vessels based on information on the series developed at the University of British Columbia (UBC series). Later, the same system was converted into a different A l environment based on constraint propagation [25]. In [4], a system for preliminary design of SWATH ships is reported.  3.2  Overview of the Ship Design Process (Design Spiral)  Figure 3.1 on page 49 shows a design spiral. This figure is important in illustrating the iterative nature of the design, although more recent representations of ship design are mentioned earlier, a cork screw  [7] and the frustum of a cone  [50], which are  also described as spiral type. Neither the number of nodes nor the order of nodes are standard in general. Each node of the spiral is associated with different aspects of the design, such as weight estimation or stability of the vessel. At each node in the spiral new information becomes available to the designer. As the design proceeds through the spiral, an abstract artifact, becomes more concrete. Most of the parameters that define a ship are nonlinearly related to each other. A change in one of the parameters may induce a snowball effect of variations in other parameters. In fact, this aspect of the design is well illustrated by Burcher and Rydill [20]. They compare a good design with a jigsaw, in which all the pieces are arranged to form the whole picture. If one of the  Chapter  3.  AN OVERVIEW  OF SHIP  DESIGN  56  pieces is altered in shape some of the adjoining pieces have to be modified in order it to complete the whole picture again. These consequential modifications may cause more pieces to be displaced, perhaps until almost all of the pieces may undergo modifications to generate a picture again. The amount of the modifications will depend upon the type of picture as well as the initial piece itself. Likewise, inappropriate choices made in previous design stages may have undesirable consequences in terms of cost of the design. Furthermore, freedom to make a choice is reduced as the designed artifact, in this case a ship, is realized. Design teams include specialists in different fields such as structures, hydrodynamics, fish handling, bridge design, electronics, etc. The communication or technical management aspect of the process becomes very important. The problem of conflicting design requirements especially in the detail design is a very familiar problem to most designers. From the stability point of view a beamer vessel might be desirable, while resistance and human comfort considerations may dictate otherwise. It is also not uncommon to observe the conflict between a structural designer trying to keep the hull structure as continuous as possible, while piping and electrical wiring designers request holes and openings in the design. The detection of such design conflicts at an early stage will reduce the cost of production and ensure a better designed vessel.  3.3  Summary  The preceding sections provided an overview of some of the characteristics of ship design. The following points can be made. • There is no unique way of designing ships. Historically, ship design has been the reproduction of successful ships. One way of designing ships has been to use a very similar ship as a basic ship/design and then to apply some modifications to the  Chapter  3.  AN OVERVIEW  OF SHIP  DESIGN  57  basic design in order to satisfy the current design requirements. In this category, ship designs are based on stereotyped arrangements of compartments, disposition of equipments to form operational systems, etc. These are generally resized. Another way is to use the information on existing ships in the form of empirical formulae. This way is more involved compared to the first one. In the case of a relatively new ship type such as a SWATH, the design is initially even more involved because of the lack of accumulated design experience in the new concept. On the other hand, SWATH type of configuration provides new opportunities for new internal arrangements, deck layouts, etc. • There is no unique solution for a set of given design requirements. Some of the parameters involved in ship design are nonlinearly related to each other in general. Therefore, not only a solution to the ship design problem in general but also, if there is any solution, its uniqueness is not guaranteed. • Ship design is a nonlinear and iterative process. There are conflicting requirements involved in ship design. Earlier detection of these conflicting requirements will reduce the cost of design. Furthermore, it may even prevent undesirable costs induced during production.  Chapter  3.  AN  OVERVIEW  OF SHIP  DESIGN  58  Ship Owner's Requirements  Determination of Principal Particulars  Estimation of Ship's Performance  Selection of Main Engine  Lines  I  Hull Resistance and Propulsion i  General Arrangement and Capacity Plan \  Hydrostat ic Curves  1 Trim and Stability Simulation I  Loading Plan  Figure 3.3: The process of basic design of ships in Akagi and Fujita's expert system (from [3])-  Chapter 4 DESIGN, K N O W L E D G E - B A S E D SYSTEMS A N D ECHIDNA  Brown and Chandrasekaran [17, p 1] compare artificial intelligence (Al) type computations (e.g. expert systems) with traditional computational methods such as finite element stress analysis programs. They propose a view to characterize intelligent behavior such that "a collection of general strategies that use knowledge in such a way that the complexity of computation inherent in certain tasks is minimized" [17, p 3]. Furthermore, they use the definition (originally described by Newell [52] as the Problem Space Hypothesis) to distinguish some types of intelligent algorithms (methods), "... explore a problem space, implicitly defined by a problem representation, using general search strategies which exploit typically qualitative heuristic knowledge about the problem domain" [17, p 4]. For example, an algorithm designed to find the greatest common denominator is not qualified as an intelligent algorithm in the above sense based on the definition given. The authors [17] are of the opinion that A l based techniques such as expert systems are more appropriate when the underlying solution spaces are very large and solution algorithms of restricted complexity are not available as in diagnosis and design problems in general. In a broad sense, Taylor [65] defines expert systems as "the collected rules of thumbhuman experience in a computer". Another definition is given by Buchanan [19] (in [27]), which is that "knowledge-based systems are computer systems in which operable human knowledge about some domain is captured and rendered". One of the characteristics of a knowledge-based system is that the knowledge it contains must be explicit in such a way that it can be inspected and understood independently of the way in which it  59  Chapter 4.  DESIGN,  KNOWLEDGE-BASED  SYSTEMS  AND  ECHIDNA  60  is controlled. Knowledge exists as a discrete entity and can be processed in different ways  [27, p 35]. The goal in knowledge-based systems is to represent knowledge in  such a way that it is comprehensible to both humans and computers. A knowledgebased system is different from a traditional computer program as generally understood, in which the domain knowledge under consideration is coalesced with control statements such as variable declarations, loops, conditionals, etc. According to Bratko the distinction between an expert system and a knowledge-based system is that an expert system has the capability of explaining its decisions and the underlying reasoning [15, p 332]. One can describe expert systems (or knowledge-based systems in general) as merely procedural programs with a sufficient number of if-then-else structures. Ideally, one answer to such a criticism based on the definition given above is that an expert system differs from a if-then-else procedural program in that the control structure is separated from the knowledge base. Modifying the knowledge base does not affect the control structure. However, once the domain specific knowledge representation is formalized it may, in most - if not all, cases require some recoding so as to be able to use the same representation in another shell. Expert systems as new computer tools will eventually change the role of computers. One of the outcomes according to Mistree : "designers . . . will be able to use a computer not just as a tool, but as an advisor, a critic, and ultimately as a partner in the process of design". This will also affect the role of designers. "They will be involved primarily with the unstructured or partially structured parts of problems (that is, with establishing system goals, partitioning the system in terms of its functional subsystems and planning the design process itself) rather than with the structured part (that is the design of components of the decision process) which will be automated" [50].  Chapter  4.1  4.  DESIGN,  KNOWLEDGE-BASED  SYSTEMS  AND  ECHIDNA  61  Design in a Knowledge-Based Environment  According to Brown [17], a design problem is a search problem in a very large space [17]. Fundamentally, each element of the space could be a possible candidate for the design problem under consideration. Simon [61, p 151] suggests that in the design of complex systems it is important to represent the highly desirable variants in the design process rather than to create systems that will optimize some hypothesized utility function. He argues that in real life examples, it is usually the case to find a satisfactory solution ,as Simon calls satisficing, rather than to choose between satisfactory and optimal solutions as rarely a method of finding the optimum is available. Artificial intelligence based tools may offer a useful tool for the design of complex systems. In the following paragraphs, first a knowledge-based model of design will be introduced. Then, Echidna, the knowledgebased system used in this study will be described. Coyne et al. [27] consider three important concepts in a knowledge-based model of design: • Representation  - how information is represented in a computer. Representation  involves facts, knowledge and control. In this context, knowledge is defined as statements about mappings between facts. Then, control is characterized in terms of mappings between items of knowledge. •  Reasoning  - involves what design reasoning is about. Deduction, induction and  abduction (see the table below, from [27]) could be named as different modes of reasoning.  Deduction (fact, knowledge and inferred fact) is associated with  interpretation of databases to derive attributes of the design not explicitly defined in the description. For example, given a ship we might be interested in knowing the resistance of the ship in certain speeds (performance issue). However, the designers' primary aim is the production of design descriptions (e.g.  ship particulars e.g.  Chapter  4.  DESIGN,  KNOWLEDGE-BASED  SYSTEMS  AND  ECHIDNA  62  principal dimensions, hull geometry, etc.). Unlike the previous case, they start with some rules and performances to arrive at a description. This is considered analogous to abduction. Coyne et al [27] give the following example for abduction. If the rule "all houses are buildings"  and the conclusion "this is a building"  are  known, but the original statement "this is a house" is not known, the step that one might decide "this is a house" is called abduction.  •  Syntax  Deduction :  case  + rule  —>  result  Induction :  case  + result  —»  rule  Abduction :  rule  -f result  —>  case  - the role of syntactic knowledge. Analogy is made to the natural language,  i.e. vocabulary and grammar. An example set for vocabulary elements for a ship might be bridge, engine, propeller, shaft, hull, etc.  Grammar then provides a  formed way to represent knowledge about composition, i.e. how these elements are put together. The authors categorize two separable tasks in the design process: • Interpretation  - the mapping between the design descriptions and their perfor-  mances. • Generation  - the composition of designs  Coyne et al [27] suggested a linguistic model of design. In the analogy, vocabulary of a language i.e. words, related to the elements that compose a design. Hence, grammar (rules of syntax) in language helps determine whether a sentence is legal. It could also be expressed as actions for constructing a sentence. The analogies they considered are given in the following table ( [27]).  C h a p t e r 4.  DESIGN,  KNOWLEDGE-BASED  SYSTEMS  AND  Language  Design  Vocabulary :  words  parts  Syntax :  grammar  actions for configuration  Utterances :  sentences  designs  Semantics :  meaning  interpretation of designs  ECHIDNA  63  as performances, e.g. propulsive performance  They characterize design as a search within a space defined by the knowledge concerned with interpretation and design syntax (generation). Given a set of performances, the aim of designer is to produce designs that will be within the intersection of the two design spaces (see Figure 4.1). Design as process (or activity) is concerned with the definition of the spaces being searched and the search process itself.  4.2  Echidna Expert System Shell  Echidna is an expert system developed at Simon Fraser University's Expert Systems Laboratory. It is briefly described as a logic programming language embedded in an object-oriented framework [60]. It supports the following features: 1. Constraint-based  reasoning  - In general, any choice made for some aspect of the  design constrains the choices available for remaining aspects of the design. 2. Model-based  reasoning  -  Models of sub-systems and components play an important  role in the design of an artifact. The artifact can be seen as a complex system with an inherent hierarchical structure: The top-level represents the entire system, the bottom level represents the parts and pieces which make up the various components.  Chapter  4.  DESIGN,  KNOWLEDGE-BASED  SYSTEMS  AND  ECHIDNA  64  Space of interpretations  Generative knowledge  Interpretive knowledge  Generation  Abduction  Spaces of designs  Figure 4.1: Generative and interpretive knowledge in defining spaces of designs (from [27]). Instead of representing the top level object as a mere collection of bottom level objects, it is more useful to model the subsystems and components as such: Each model describes the relationships between the input and output parameters of the object modeled. A corresponding representation must be supported in a powerful design system. 3.  Logic programming  -  Logic programming allows a declarative representation of the  task. Declarative representations are common in design. For example, the declaration that "the preferred length to beam ratio for the UBC Series fishing vessels is between 2.6 and 4.0". Declarative representations are concerned with the relations  Chapter  4.  DESIGN,  KNOWLEDGE-BASED  SYSTEMS  AND  65  ECHIDNA  denned in the program, hence the outcome. Whereas the procedural aspects of a program are concerned with how these relations are evaluated by the program. In other words the two. approaches deal with the two different questions respectively : " What are the relations/goals is the output  in the program,  and what is the output?\  and  "How  ". The programmer , in the former, is encouraged not  obtained?  to think about the executional details and to concentrate on the meaning of the program. Therefore, this declarative approach generally makes the programming easier [15, pp. 25 - 26]. The Echidna expert system incorporates a new type of constraint logic programming. Traditional logic programming systems allow only the representation of one special type of constraint: equality. For example, a traditional system may return a result such as "length = 5 OR length = 6 OR length = 7". A more powerful system also allows the representation of more general types of constraints such as inequalities. Here a representation corresponding to the above result could be "5 < length < 7". Echidna permits the definition of constraints such as ranges, and weight functions for vessel parameters such as length, beam, and hold volume. The system is very suitable for design tasks in general since the built-in constraint processing easily facilitates the narrowing of parameters during the progress of the design. For example, constraints such as "5.2 < length < 20.1" and "12.4 < length < 30.0" could appear at different times during processing and appropriately combined to "12.4 < length < 20.1". 4. Hypothetical  reasoning  -  Design tasks require search. Partial designs must be first  proposed, then integrated into the evolving solution and their suitability evaluated under design constraints. The system must be able to investigate proposed solutions, and return to an earlier solution if a proposal proves infeasible. The integration of partial designs is controlled by rules which specify both design strategies  Chapter 4. DESIGN, KNOWLEDGE-BASED  SYSTEMS AND ECHIDNA  66  preferred by expert designers and constraints inherent in the model. 5. Intelligent  backtracking  -  This is essentially an issue of the performance of Echidna.  In the traditional chronological backtracking approach, the system searches for a solution to the (design-) problem and upon failure backtracks to the most recent choice point and selects a different alternative. This alternative may not resolve the problem, i.e., the failure persists and the process repeats until no more alternatives are available at that choice point. The system then chronologically backtracks to the next-most recent choice point and selects a different alternative there, etc. The choice that causes a failure is often made many steps before the failure can actually be detected.  Chronological backtracking results in an unacceptable amount of  obsolete processing and is inadequate for any problem of realistic complexity. To make the product commercially viable, intelligent backtracking is essential. Here the system keeps track of the dependencies between choices and their effects. Thus, when a failure occurs, all most-recent choices that are irrelevant to the particular failure are skipped and the system backtracks directly to a choice point that is likely to resolve the problem.  6.  Mixed  initiative  -  This is required to support a cooperative problem solving between  the expert system and the human designer. It would be unrealistic to expect that all design tasks and subtasks can be properly identified, analyzed and formally represented in an efficient way. Therefore any adequate system will aim at assisting the user in solving the design problem, not at replacing him. A peer relationship is essential in such an approach: The user must be able to take the initiative and to interact with the system in order to actively take part in the (computer-assisted) design process. Likewise the system must be able to take the initiative, for example, if the user breaks important design rules and needs to be warned. The integration of  Chapter  4.  DESIGN,  KNOWLEDGE-BASED  SYSTEMS  AND  ECHIDNA  67  constraint processing and intelligent backtracking within Echidna has the potential for a more efficient interactive design system than traditional rule-based expert system shells. The Echidna expert system also takes advantage of object-oriented programming to easily model a design. Objects are used to represent both physical objects, such as the vessel itself and its components (such as hold volume), as well as intelligent agents, each with domain knowledge in a particular aspect of design (such as vessel stability, crew safety, and comfort). Other design applications for the Echidna Expert System shell include heat exchanger design, Stirling engine design, and residential log home design. In the development of the Echidna expert system at UBC for fishing vessel design our interest is to use the Echidna Expert System for all of its features listed above. Computer-aided fishing vessel design and small boat design need all of the facilities supported by the Echidna system. The purpose of the application of the Echidna expert system is to synthesize the main characteristics of a marine system, that is able to float with sufficient stability in calm water, determine the resistance of the vessel so that a sufficient propulsive system required to go fishing, search, fish and return in possibly rough seas. Furthermore, prediction of ship motions and assessment of sea-kindliness in the preliminary design stage is fully incorporated into the Echidna Expert System.  Chapter 5 M O N O H U L L VESSEL DESIGN K N O W L E D G E BASE (UBC-MONO)  The design knowledge representation in general is discussed in Chapter 4. In this chapter, the knowledge base developed for monohull fishing vessel design is described. The design algorithms used in it are given in Appendix B. The approach employed in UBC-MONO preliminary monohull fishing vessel design knowledge base is similar to the design spiral. Perhaps, one of the reasons for this is the nature of the process. Each node on the spiral requires some of the information obtained in the previously visited nodes. Hence, in order to help the program reach a solution faster, the same model of the design process has been adopted here. First of all, a schema "Monohull" representing monohull vessels has been written. 1  This schema contains all the necessary information related to the vessel characteristics, from geometrical dimensions to its resistance characteristics, etc. However, the code that is necessary to compute these characteristics have been coded in different schemas. One can consider these schemas as task performing schemas. The tasks are basically to estimate vessel characteristics at different stages of the design. For example, this could be the estimation of design waterline length based on some other parameters. Analogous to the design spiral, the task performing schemas are for the estimation of geometric dimensions, weight groups, stability checking, resistance, required horse power and cost estimation. Additionally, there are also schemas to estimate some of the motion characteristics (related to heave and pitch amplitudes, see Chapter 7) of the current •"^See Appendix A for the definition of a schema.  68  Chapter 5. MONOHULL VESSEL DESIGN KNOWLEDGE BASE (UBC-MONO) 69  design. The above approach enables the user to do partial designs, as well as evaluating existing ones. By performing partial designs means taking the design process up to a certain node in the design spiral, or running only a desired schema , e.g. schema for power estimation, on a given schema "Monohull". Another important aspect of the Echidna knowledge based system, and for that matter knowledge based systems in general, is that alternative design methods can co-exist in the system. For example, in [47, p 18] the overall length of a SWATH vessel is given in Equation C . l . Macgregor [47] reported that although the coefficient of the equation was obtained as "5.33" after a regression analysis, there was a ± 2 variance in the coefficient. In fact, the ratio of LOA/A* [3.33,7.33].  in the existing, as-built designs varied in the range of  Hence, in the Echidna knowledge base, it is possible to have two alternative  design rules in the estimation of LOA-  orderchooaeLengthOverAll.  (5-1)  chooseLengthOverAll(LoA) '• — LOA — 5.33 * A s . chooseLengthOverAll(LoA) : -  LA 0  = [3.33,7.33] * A * .  (5.2) (5.3)  In the above design methods, the first line ensures that Echidna will choose the methods in the order of appearance. In other words, it willfirstattempt to create some designs where  LOA/A'  ratio satisfies Equation  5.2.  In case no solution is possible by  using this method of estimation, it will then try the alternative, i.e. Equation 5.3. If the line 5.1 is omitted, Echidna randomly chooses a method. Therefore, this feature of Echidna allows implementation of the kind of actions to be taken in case of a failure to produce a design.  C h a p t e r 5.  5.1  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  70  Remarks  This section reports the results of the investigation on the validity of the knowledge base for preliminary monohull fishing vessel design. The aim of the investigation was to compare the performance of Echidna with another knowledge-based system called PC Plus Consultant, in which the same fishing vessel design algorithms, excluding seakeeping considerations, were implemented by Calisal and McGreer [24]. Furthermore, an existing vessel, namely Kynoc, was redesigned in Echidna system and the outcome was compared with the original Kynoc. It should be noted that in obtaining the results given below, no ergonomic design considerations (i.e. ship motion criteria for crew safety and comfort) were included in the knowledge base. In the investigation, there were two main points : • Echidna was required to demonstrate a similar trend, which is reported by Calisal and McGeer in [24] (Figure 5), for the comparison of steel and aluminum vessels. ("Can  Echidna  and especially  reproduce  similar  by conventional  results  design  obtained  in another  design  environment  practices? '') 1  • After being provided with sufficient information related to an existing fishing vessel, Echidna was required to conclude if this was a valid design for the Echidna knowledge base as well. ("Can  Echidna  reproduce  an existing  designf)  A valid design in Echidna is a set of parameters that characterize a vessel, and each of which Echidna is able to assign a value such that all of the constraints of the fishing vessel design in the knowledge base are satisfied. The most important constraint in the knowledge base is that displacement of the vessel should be equal (or greater than by a predetermined amount) to the total weight of the vessel, i.e. Archimedes's principle. Some of the other main constraints worth mentioning are  the vessel should  have  sufficient  Chapter  5. MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  71  Table 5.1: Input to Echidna for Kynoc. "[ ]" indicates an input as an interval. Parameter  Fishing method Hull material Design speed Displacement Length Beam Draft Block coeff. Mid ship coeff. Hold volume  initial  stability,  power  and cost  Input  Value  seiner aluminum 10.3 [knots] [80.0, 85.0] [LT] 56.7 [ft] 20.0 [ft] 4.92 [ft] 0.519 0.728 [23.0, 27.0] [LT]  limitations.  For the first part of the investigation, an existing monohull seiner type vessel, namely Kynoc, was chosen. Kynoc operates off the Pacific coast of Canada. Table 5.1 shows the main particulars of Kynoc used as input to Echidna. The results of the comparison are presented in Table 5.2, which proves that Kynoc is a valid design in Echidna's knowledge base. This conclusion stems from the fact that Echidna was able to produce a design and this design is very close to Kynoc. The Echidna version of Kynoc satisfies the constraints of the ship design, which were implemented in the knowledge base, i.e., the vessel floats, has sufficient initial stability, and the power requirements sire comparable between the existing one and the Echidna version as shown in Table 5.2. In the second phase of the knowledge base validation, in order to reproduce the trend reported by Calisal and McGeer in [24] (Figure 5), a number of steel and aluminum vessels have been designed for the same hold volume and other input parameters. Hold volume has been varied between 5 [LT] and 300 [LT]. For this investigation the input to Echidna is given in Table 5.5. During this phase, the intervals given as solutions by  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  72  Table 5.2: Comparison of Echidna produced design with real Kynoc. Parameter  Kynoc  Fishing method Hull material Design speed Displacement Length Beam Draft Depth Block coeff. Mid ship coefF. Prismatic coeff. Hold volume Hull weight Machinery weight Engine Hull Cost Machinery Cost Total Cost  seiner aluminum 10.3 [knots] 82.0 [LT] 56.7 [ft] 20.0 [ft] 4.92 [ft] N/A 0.519 0.728 0.712 25.0 [LT] N/A N/A 420 [HP] N/A N/A N/A  Echidna  seiner aluminum 10.3 [knots] [82.52, 85.0] [LT] 56.7 [ft] 20.0 [ft] 4.92 [ft] [5.08, 6.02] [ft] 0.519 0.728 [0.711, 0.717] [23.0, 25.5] [LT] [12.38, 14.86] [LT] [3.09, 3.91] [LT] [134.31, 378.35] [HP] [137042, 164440] [Can.$] [29842, 84062] [Can.$] [1106250, 1275000] [Can.$]  Echidna were sometimes very large, therefore, Echidna was forced to select arbitrarily smaller intervals (subintervals) from these initial solutions. In order to clarify this point, a hypothetical example is given as follows: For the sake of simplicity, assume that there is only one relationship among the parameters given in Table 5.3, that is Equation 5.1. Table 5.3 shows the intervals given as a solution. Both in Table 5.3 and Table 5.4, the relationship given above holds for the intervals given.  Displacement  volume  = Block  coefficient  x Length  x Beam  x  Draft  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  73  Table 5.3: Example for the intervals after Echidna reaches a solution. Parameter  Solution  Length  [60.0, 65.0]  Beam  [20.0, 25.0]  Draft  [6.0, 9.0] [0.61, 0.62]  Block coefficient Displacement volume  Table 5.4:  intervals  [4392, 9067.5]  Example for the parameters' intervals after Echidna completes design and  further arbitrarily refines them. Parameter  A solution  Another  solution  Length  [60, 60.01953]  [60, 60.01953]  Beam  [20, 20.01953]  [24.49219, 24.51172]  Draft  [6, 6.011719]  [6, 6.011719]  Block coefficient Displacement volume  [0.61, 0.6100391]  [0.61, 0.6100391]  [4392, 4406.697]  [5378.381, 5395.503]  Theoretically speaking, the intervals given in Table 5.3 may contain an infinite number of solutions.  However, any randomly chosen Displacement volume, Block coefficient,  Length, B e a m , and Draft values from the intervals in Table 5.3 may not  necessarily  construct a solution, since a solution implies that the new sub-intervals (e.g.  the ones  given in Table 5.4), should satisfy Equation 5.1. Similarly, for the second phase of the validation process, the solutions given below (Figures 5.1 to 5.7) are arbitrarily selected by Echidna from the original, much larger intervals given as solutions. A given interval as a solution, may contain an infinite number of smaller intervals (or discreet values) that might correspond a solution. However, the design constraints (rules) will determine sets of smaller intervals that form a solution.  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  74  Table 5.5: Input to Echidna for the second phase of validation for afleetof varying hold capacities. Parameter  Input  Fishing method Hull material Design speed Hold volume  Value  seiner aluminum and steel 10.3 [knots] from 5 [LT] to 300 [LT]  The effects of different hull material type on some of the vessel parameters as well as the total cost of the vessel are presented in Figures 5.1 to 5.7. Figure 5.1 illustrates the change in the length of the designs due to different hull material. Thefigureshows no particular difference in the length of steel and aluminumfishingvessels, except in the region of 25 [LT] hold volume capacity. This discontinuity could be associated with the alternative estimation rules incorporated in the Echidna knowledge base. Methods used to estimate initial ship dimensions order  length.  (5.5)  Method  I  :  Length  =  3.3(28.5 Hold-volume)  Method  II  :  Length  =  [1.0,  03669  (5.6)  200] J^engthlnFeet  (5.7)  The examination of the length estimation methods used in the knowledge base (Equations 5.6 to 5.7), reveals that there are two distinct methods to estimate length. The first one, i.e."Method  I",  is based on the hold volume capacity required for the vessel.  This formula has been derived from the information on existing designs [24].  "Method  II" merely defines an initial interval in which any solution, if it exists, should occur. In this case, the other constraints of ship design will determine the subintervals that include a solution. The effect of preferring one method for a given hold capacity requirement  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  75  and the other method for a similar hold capacity requirement during the design can be observed by an abrupt change in the trend in the figures presented. As for the beams of the designs, steel and aluminum designs have almost the same values in general. However, in the regions of 25 [LT] and from 45 [LT] to 80 [LT] hold volume capacity (see Figure 5.2), steel vessels have up to 20% larger beams than aluminum ones. The jump between 50 to 75 [LT] hold capacities in the figure, could be related to the alternative estimation rules used for a design variable in the knowledge base. The effects of material type on draft is shown in Figure 5.3. In the whole hold capacity range considered, aluminum vessels have shallower drafts than steel vessels. This is in confirmation with the present picture of existing fishing vessels. In Figure 5.4, the hull weights of the aluminum and steel vessels are compared. As the figure depicts, steel vessels have heavier hulls throughout the hold capacity range under consideration. In order to compare different vessels in terms of their sizes, displacements of the vessels are good indicators. The results obtained in this investigation suggest as expected that steel vessels are heavier (or larger) than aluminum vessels designed for the same design speed and hold capacity (see Figure 5.6). This result can be observed among existing vessels as well. In the investigation, power requirements of steel and aluminum vessels have also been compared (see Figure 5.5). Up to 75 [LT] of hold volume capacity, power requirements of the two groups are approximately the same, although the mid points of the intervals for steel designs seem greater than those for aluminum designs. For hold volume capacities larger than 75 [LT], steel designs clearly require more power than aluminum designs. Finally, for this investigation some cost terms have been compared. Figures 5.7 illustrates the variations of total costs with respect to hold volume and building material. Up to 75 [LT] of hold capacity, there are cross overs between the mean lines of the  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  76  intervals. This result suggests that region of up to 75 [LT] hold capacity, aluminum vessels might offer a less expensive alternative to steel vessels, as also reported by Calisal and McGeer [24] (Figure 5).  5.2  Summary  In this part of the study, the aim was to see if the knowledge base in Echidna produces reasonable designs before incorporating some ship motions criteria (for crew comfort and safety reasons) into it. The above results can be seen as a validation of the knowledge base in Echidna, UBC-MONO, for monohull vessel design. From the above results, it can be concluded that • By using UBC-MONO, it was possible to obtain similar results reported earlier [24]. • Echidna was able to reproduce an existing vessel within reasonable differences from the existing design. • The validation for UBC-MONO was at an acceptable level of confidence. Hence, the UBC-MONO knowledge base could be used in our investigation as a design tool.  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  77  Figure 5.1: Comparison of Echidna generated aluminum and steel designs' lengths (vessel type : seiner). The jump could be because of alternative estimation rules embedded for some variables in the knowledge base.  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  78  Figure 5.2: Comparison of Echidna generated aluminum and steel designs' beams (vessel type : seiner). The jump could be because of alternative estimation rules embedded for some variables in the knowledge base.  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  79  Figure 5.3: Comparison of Echidna generated aluminum and steel designs' drafts (vessel type : seiner). The jump could be because of alternative estimation rules embedded for some variables in the knowledge base.  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  80  1.4E02  1.2E02  1.0E02  Steelj Vessels " 8.0E01  \y\  3 6.0E01 3  j  yf  4.0E01  \  /  : /  s  S  /  Alumiiium Ves sels  2.0E01  j  O.OEO 50  J  100  1  I  150  1_  200  250  300  Hold Capacity [LT]  Figure 5.4: Comparison of Echidna generated aluminum and steel designs' hull weights (vessel type : seiner).  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  81  1E03 9E02 8E02 ST 7E02 X  6E02 '3  £  5E02 4E02 3E02 2E02 0  50  100  150  200  250  300  Hold Capacity [LT]  Figure 5.5: Comparison of Echidna generated aluminum and steel designs' required powers (vessel type : seiner).  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  82  6E02  5E02  4E02  e g 3E02 o  •  I  / /// / s  CO  2E02  1E02  N  /  i  ; /  1  Y  !  /• / ../' y / /; <• / / <  y / A /  ,/  /  /  A l u m i n am Vesf els  !  ,.s /  :  i  i  V  :  //  0E0  50  100  ,  i 150  •  i 200  250  300  Hold Capacity [LT]  Figure 5.6: Comparison of Echidna generated aluminum and steel designs' displacements (vessel type : seiner).  Chapter  5.  MONOHULL  VESSEL  DESIGN  KNOWLEDGE  BASE  (UBC-MONO)  83  3.5E06 -  3.0E06 A l u m i n u m Vessels 2.5E06  ^2.0E06 •*-» o U o H  zy-  <^  Steel Vessels  i  1  >  1.5E06 VS  1.0E06  j  i  ;  A/  5.0E05 -  i  0.0E0 50  100  ,  i 150  i  200  250  300  H o l d Capacity [LT]  Figure 5 . 7 : Comparison of Echidna generated aluminum and steel designs' costs (vessel type : seiner).  Chapter 6 SWATH PRELIMINARY DESIGN AND UBC-SWATH  6.1  Multi-hull vessel for fishing role  In nowadays' ever-changing economic and environmental conditions, the traditional specialized one-technique fishing vessel is rapidly disappearing. Ideally, a modern fishing vessel should be flexible in its approach, enabling any number of techniques such as, deep or shallow trawl and long line fishing. This versatility, through the use of a multipurpose vessel, would mean greater employment security through the vessel's ability to adapt to different species, new sustainable fisheries management programs, or better adaptation to changes in climatic conditions or selective harvesting techniques. The adaptability in variety of deck configurations, in a multi-hull vessel's large stable box-shaped upper hull, could provide an effective deployment of existing fishing equipment. As a multi hull vessel, SWATHs have been receiving considerable attention due to their superior seakeeping behaviour. Together with the other features as reported by Atlar et al in [10] such as Vehicle Motions, namic  Characteristics,  etc.,  Safety,  Operations,  Habitability,  Hydrody-  the SWATH concept offers advantageous features for fishing  operations. It has also been reported by Kennel in [39] that in 1992, 10 of worldwide built 25 SWATH ships with 40,000 tons of cumulative tonnage accomplish their missions as both multi-purpose work boats andfishingvessels.  84  Chapter  6.2  6.  SWATH  PRELIMINARY  DESIGN  AND  UBC-SWATH  85  General Features of Multi-hull Design  The design process of a SWATH vessel is considered to be very similar to a conventional monohull design. The novelty in the SWATH concept is in its hull form. Hence, its design process follows the traditional form i.e. the owner requirements are at the outside the design spiral and a completed design at the center obtained through successive steps of iterations. The multi-hull design as being a weight sensitive design represents a difficult case requiring greater attention to its design. In conventional monohull ship design, the main design parameters are usually decoupled or less dependent upon each other. However, for a multi-hull vessel, this is not the case due to the increased number of design parameters and the higher order of inter-dependence of these parameters. SWATH vessels even represent the most difficult case of a multi-hull design, mainly due to its unconventional underwater hull form, combined with small waterplane area. Moreover, the lack of a historical SWATH design database and the immaturity of the validated empirical design methods require the use of sophisticated design analysis tools even in the early design process. The Echidna expert system environment provides the necessary tools for high speed evaluation and iteration of the design through its constraint propagation techniques and intelligent backtracking. However, the current version of the Echidna shell does not have any design analysis tools. In Atlar [9] and MacGregor [47] SWATH designers have cautioned on the special features of SWATH vessels and of the high interdependence between many of the basic SWATH design parameters. Two of the main characteristics reported in comparison to a monohull of the same displacement are reduced length and increased beam in SWATH vessels. However, in terms of the size of the weather deck area SWATH vessels are similar, though with more usable area due to their rectangular shape, compared to monohull vessels. Despite the fact that the large depth, draft, and freeboard are of importance  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  UBC-SWATH  86  mainly to the operation of the ship, to a certain extent, these parameters will also affect, the design of some of the subsystems (e.g. the larger the draft, the better the propulsion characteristics while the higher the deck height, the poorer the steering and maneuvering and structural integrity due to greater structural loads). The larger wetted surface area affects the powering requirements, hull painting systems, and cathodic protection system. As far as the hydrostatic properties are concerned, the trim and weight related issues for SWATH ships take the first priority in design decision-making to the SWATH designer in contrast to the monohull design. Unanticipated weight growths due to estimation errors during the design can jeopardize SWATH's effective use and even in extreme cases might lead to the design of an unacceptable ship. Lastly, since a SWATH vessel has the same heel sensitivity as the monohull designed for the same application, the selection of the appropriate beam and waterplane area is an important key factor in the determination of the adequate transverse stability and seakeeping capabilities of the vessel.  6.3  SWATH Design Algorithms and Discussion  The SWATH preliminary design expert system, developed at UBC, performs its preliminary design computations from empirical formulae originally developed at the University of Newcastle upon Tyne [9] and Glasgow University, United Kingdom [47]. These algorithms are given in Appendix C. It is important to note that the current expert system produces satisfactory solutions. To elaborate more, the intervals given as solutions satisfy the relevant constraints in the knowledge base. However, it should be noted that these solutions may not necessarily be the optimum solutions in the sense of a conventional optimization process (e.g. Simplex method). However, the convergence to the solution obtained by a conventional optimization routine might be achieved, applying further constraints, such as on weight and/or  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  UBC-SWATH  87  cost, once Echidna reaches a solution. Another approach could have been to start to design from an existing vessel. However, this has not been implemented in the present version of the knowledge base. For the validation of our SWATH vessel preliminary design expert system, 41 existing designs from [47] were used as test cases. The aim was to reproduce each existing design in Echidna. Table 6.1 shows the input to the expert system. The choice of some of the parameters such as hull material  may be left unspecified at the input if they are not  known initially.  Table 6.1: Input parameters for SWATH vessel design expert system. Parameter  Domain  Hull material Lower hull type Strut type Machinery type Displacement Cargo Maximum speed Cruise speed Range at maximum speed Range at cruise speed Number of passengers Number of crew  {mild  steel, aluminum,  {circular, {long,  noncircular  hybrid  }  }  short }  {high speed diesel, medium  speed diesel, gas turbine  }  In the formulation of the SWATH vessel design problem the main constraint is floatation i.e. in UBC-SWATH (displacement  >  [1.0,1.03] *  total-weight).  Some of the results obtained from this analysis are given in Figures 6.1 to 6.5. The expert system developed here is planned to be used in designing fishing vessels up to approximately 1000 tons of displacement. Therefore, whenever possible the performance of the expert system in the 0 to 1000 ton displacement range is also given.  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  88  UBC-SWATH  Table 6.2: Statistical analysis of % variations for A after excluding the pathological cases (4 cases out of 41 total number of cases). The 4 existing designs are as follows: a 305 ton fishing vessel, a 225 ton ferry, a 225 ton crew boat and a car ferry with a 1250 ton displacement. % Variations Average Standard deviation Minimum Maximum  All Data Lower Upper 20.58 28.98 42.73 55.73 -28.57 -28.10 179.82 219.88  A = [0,1000] Lower Upper 18.90 24.60 38.12 50.01 0.0 0.0 116.92 162.30  In Table 6.2, the percentage variations was calculated by %Vaviation = 100 *  eter -SWATH - Parameter Parameter Existing Design  PaTam  UBC  ExUting  D e  ,  i g n  Generally speaking, the variation of the design parameters given by Echidna follows a trend similar to that of the design parameters of existing designs. Figure 6.1 shows how Echidna performed with respect to the displacement. In this figure, it seems that UBC-SWATH produces a similar trend in the displacement values of the Echidna designs. During the validation process, it has been noticed that for some particular designs such as passenger ferries and fast attack boats, UBC-SWATH was not able to perform as expected. As also discussed in [47], the current lower hull form design algorithms are only for simple type lower hulls. Therefore, for the existing SWATH designs with different type of lower hull forms, UBC-SWATH experienced difficulties in obtaining similar values of design parameters to those of existing designs. It is interesting to note that usually the same designs have caused higher standard deviations. Almost the same pathological pattern repeats itself in the study of other parameters such as LOAFigure 6.1 shows the comparison of displacement values by Echidna vs existing designs  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  UBC-SWATH  89  in different displacement ranges. In this figure, except 3 cases, two of which with 225 tons of displacements, the third one with 305 tons of displacement, the variation in [0, 1000] ton displacement range seems reasonable. These three cases are a ferry, a crew boat and a fishing boat. The exclusion of any design by Echidna having three or more times larger displacement than that of the existing design, which are the above three cases and a car ferry with a 1250 ton displacement, improves the average percentage variation in A , and its standard deviation considerably. The number of cases excluded is only 4 cases out of 41 total number of different design cases. Table 6.2 gives the new statistical results for the design parameter A only. In Figure 6.2 LOA values are compared. It is noticeable that much of the discrepancies occurred in the same existing design cases mentioned in the previous paragraph. As seen from Figure 6.3, average variation between the "Beam" of the existing and Echidna designs is within a reasonable range. However, there still exists some discrepancies. The parameter "Draft" values also exhibit a similar variation to the beam parameter, as in Figure 6.4. The last design parameter obtained by Echidna compared with existing designs' is the "Installed  Powei '  } 1  (see Figure 6.5). This is the parameter that cannot be said to have  been estimated with confidence. The main reasons for the discrepancies between the expert system given and existing design parameters are believed to be : • Not in all of the cases, the mission of the vessel to be designed i.e. the speed, endurance, amount of cargo, and number of passengers and crew, was available. In these cases, these variables were guessed from similar existing design cases. However, as a SWATH is a weight sensitive design, these somehow arbitrary assignments affected the procedure.  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  UBC-SWATH  90  • It has been observed that final solutions are usually very sensitive to changes in the coefficients of the empirical formulae, especially related to weight groups estimation. For example, the weight of the passengers (and crew) with effects is assumed to be 0.143 tons, i.e. 7 people with their effects weigh 1 ton.  However, any change in  this assumption seems to dramatically affect the solution produced for passenger ferries, and navy vessels, where a large number of people are on-board. • The empirical formulae used here were developed for all types of SWATH vessels. It is believed that these formulae fail to capture type specific (e.g. pertaining to passenger ferries, or patrol boats, etc.) features of SWATH vessels. However, this was again due to the lack of historical data or well developed "knowledge base" in SWATH vessel design. • Regarding the power estimation, the current system (UBC-SWATH) fails to predict the power requirements with confidence. One of the reasons for this might be the resistance estimation. Figure 4.11 in [47, pp. 126 ], shows excessive scatter in the residual resistance data. Therefore, this is also believed to be one of the contributing factors.  6.4  Remarks  As mentioned earlier, when compared to a monohull, a SWATH design is weight sensitive. In the absence of well defined input parameters, it is not surprising that the procedure in Echidna converged to a solution with different designs, usually larger SWATH vessels. In other cases, Echidna was able to produce similar designs to the existing designs. In the following figures, the x axis represents the displacement values of the existing designs.  C h a p t e r 6.  SWATH  PRELIMINARY  DESIGN  AND  91  UBC-SWATH  It should also be noted that since in Echidna the calculations are done in real intervals thus the results are given as real intervals. Therefore, in the figures, and  "Echidna  upper*'  "Echidna  lower"  represent the lower and upper bound of the interval. The line in  the figures shows the trend in the existing design parameter.  Chapter 6.  SWATH  10  PRELIMINARY  2  DESIGN  10  3  AND  UBC-SWATH  10  92  4  Displacements of existing designs [tons]  Figure 6.1: Comparison of UBC-SWATH and existing design A's. The horizontal axis represents existing designs' displacement values.  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  160  •  UBC-SWATH  I  Echidna designs  - Q — Existing designs  140  120  100  03 O  80  60  40  20  I I I I 1 III  0 10  100  I  I I I 1 I III  1000  I  l  I  I  I L  10000  Displacements of existing designs [tons] (log scale)  Figure 6.2: Comparison of U B C - S W A T H and existing design £ O A ' S .  93  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  UBC-SWATH  70.0  60.0  y/  Existing designs  O  Echidna designs  t  50.0  -o 40.0  a  03 PQ  30.0 —  20.0  10.0  I  0.0 10  I I I 111ll  100  I  I I I 11 III  1000  I  I  I  I  I  I I  10000  Displacements of existing designs [tons] (loglO scale) Figure 6.3: Comparison of U B C - S W A T H and existing design B e a m ' s .  94  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  95  UBC-SWATH  16.0  •  14.0 —  — e -  Echidna designs - Existing designs  12.0  10.0  as Q  8.0  6.0  4.0  j  2.0 10  i i m?ii 100  i  i i i 111in 1000  i  10000  Displacements o f existing designs [tons] (log 10 scale)  Figure 6.4: Comparison of U B C - S W A T H and existing design  Draffs.  Chapter  6.  SWATH  PRELIMINARY  DESIGN  AND  UBC-SWATH  IT  ((log 10 - log 10) scale)  i  -0—Existing designs  100000  •  I  Echidna designs  "8  10000  1  •  J  1000 10  I  I I hi Mil  100  I  I  1000  I  l i l l  Mill  I  I I I  10000  Displacements of existing designs [tons] Figure 6.5: Comparison of U B C - S W A T H and existing design Installed  Powers.  Chapter 7  SEAKEEPING  CONSIDERATIONS  In the previous chapters, the work related accidents on board fishing vessels and their possible contributing factors have been discussed from the point of view of the effects on human performance and safety. Among the factors, vessel motions were mentioned as one of the most important contributing factors to accidents by various authors in the literature (e.g. [67], [56], [31]). It was suggested that reduced motions would mean a better living and working environment on board fishing vessels. However, the cost of modifications to existing vessels to obtain reduced levels of acceleration and amplitudes to achieve a worthwhile improvement in the quality of living and working conditions on board or incorporating into the new designs needs to be investigated. This must also be done within the relevant constraints imposed by the physics of the problem (e.g. stability) and owner related monetary constraints that are life cycle costings and benefits. There are different strategies that can be used to reduce vessel motions in practice. These are: 1. Active and passive roll and pitch stabilizers for example fins, bilge keels, bossings, gyroscopic stabilizers, tank stabilizers, jet flaps and rudders are mentioned in [13] and [58]. Each of these systems has advantages and disadvantages. Their efficiency, added cost and added weight, the space required for the stabilizing system are factors in selecting one system or another. Naturally, there is a limitation on the amount of improvement that these systems would offer.  97  Chapter  7.  SEAKEEPING  CONSIDERATIONS  98  2. Another strategy of reducing the motions is to design larger vessels. The amount of increase in the vessel size and associated first building and operating costs are important to the owner, although they need to be traded off against the change in earnings throughout the expected lifetime of the ship. 3. In some cases, it may not even be possible to increase the size of the vessel due to some regulations such as the Canadian fishing vessel replacement rules. A more dramatic strategy would be the use of a different concept altogether in the design, for instance to use a SWATH (Small Waterplane Area Twin Hull); this has inherent advantages over monohulls especially in regard to the vessel motions ([9] and [47]). In this thesis, a methodology, more along the same lines of the second and third strategies mentioned above has been developed, especially applied to monohull vessels. Among the reasons for the development of these design strategies include the criticisms that • the appendages extended outward of the hull e.g. fins, are not really favored by fishermen, • the active or passive stabilizing systems are usually considered for one of the vessel motions only such as roll motion, • the systems mentioned are fairly well understood in terms of their efficiency, costs and benefits. In the strategies used in this thesis, the goal of reducing motions was not achieved by explicitly asking the Echidna knowledge base to design a larger vessel, though at the end, sometimes larger designs may have been obtained as solutions. Rather, the approach was to incorporate some rules implied from the relationship between the vessel motions and the human comfort on board, and let Echidna find a solution.  Chapter  7.  SEAKEEPING  99  CONSIDERATIONS  In an attempt to reduce motions, two different sets of rules have been developed and used for monohull vessel design in this thesis. These sets of rules are described in the following sections. The comparison of the two sets of rules in terms of their effects on the size and costs of the monohull vessels can be found at the end of this chapter. Another presentation in this chapter is the comparison of the monohull designs, obtained with these two sets of rules included in their design, to SWATH vessels with the the same hold capacity.  7.1  Rule Set I  In general when a dynamic system is excited near one of its natural frequencies the amplitude of motion is (expected to be) larger. Similarly under normal circumstances, for a given sea state, a ship will be most vulnerable to such large amplitude motions when the frequencies of the high energy waves coincide with the peak natural frequencies of the ship (see Figure 7.1 on page 107). Hence, a way of reducing large vessel motions and related discomfort would be to design vessels in such a way that their natural frequencies will not coincide with the frequencies of the high energy waves in the sea for a given sea state. However, the amount of shift in the peak resonance and the peak energy is an important factor and should be determined in conjunction with cost, improvements in the ship motion levels for crew safety and comfort, and other physical rules of design such as the ones related to stability. For this approach, a design parameter (Equation 7.1) has been defined to quantify the amount of ratio of the frequency of the sea state's highest energy waves and the natural frequency of the vessel.  „ . Ratio  , , of peaks  =  Vessel's  response peak frequency —£ . Sea states peak frequency %  (7.1)  Chapter  7.  SEAKEEPING  100  CONSIDERATIONS  In this equation, peak frequency for a sea state corresponds to the frequency of highest energy waves, whereas for the vessel it is the peak natural frequency for a particular motion, e.g. pitch motion. . In order to implement this strategy in the Echidna knowledge base, the following set of rules have been used. Rule Set I t  order  ratio.of-peaks. 1st rule  (7-2) :—  Ratio  > 3.0.  (7-3)  2nd rule  :-  Ratio  > 2.4.  (7.4)  3rd rule  :-  Ratio  > 1.8.  (7.5)  As mentioned earlier in the thesis (see page 69 in Chapter 5), the first rule (7.2) in the knowledge base, i.e. "order ratio_of_peaks.", ensures that the rules are exhausted in the order of appearance. Hence, Echidna will first try to produce designs whose "Ratio" values are greater or equal to 3.0. In the above rules, shifts of the ship responses peaks towards lower frequencies (e.g. "Ratio  < 1.0") are not implemented, simply because the natural frequencies of smaller  vessels tend to be in the higher frequency range compared to larger vessels. Furthermore, as the sea state becomes more severe, the peak of the sea states energy spectrum shifts to lower frequencies. Therefore, at first a shift towards higher frequencies might seem more preferable. As far as the frequency of the exciting forces on a vessel is concerned, in the case of motions due to waves at the sea, it is not the frequencies of the waves, but the encounter frequencies that define the excitation frequency. The encounter frequency, which is given  Chapter  7.  SEAKEEPING  101  CONSIDERATIONS  by Equation 7.6, depends on the speed and the heading with respect to waves encountered by the vessel, as well as the frequency of the waves. u> = u>  Vcosx  e  (7'6)  9 Where u> is the frequency of the waves in the ocean to a fixed observer, uj is the e  encounter frequency, g is the acceleration due to gravity, V is the speed of the vessel and x is the heading of the vessel with respect to waves encountered. One of the implications of Equation 7.6 is that for a given sea state and vessel's heading, it is possible to reduce the vessel's excitation at its natural frequency by reducing or increasing the speed of the vessel. However, unlike reducing the speed, it is not always possible to increase the speed because of the rapidly growing power requirements that cannot be matched by the engine in the vessel, and/or the increased probability of increasing structural damage to the hull. Since the sea state, the speed and the heading were all constant in all of the example designs, a shift of the vessels natural frequency to higher frequencies means smaller vessels in general. It is also interesting to note that the higher the sea states are, the easier it is for the design process to get higher values of the ratio, as there is a shift of high energy waves to lower frequencies for increased sea states. In regard to the determination of the limits used in the above rules, 3.0 is considered to be a fairly satisfactory value for the ratio of the frequencies in Equation 7.1. Whereas after selecting 3.0, it was desirable to keep the number of rules to a minimum in order not to increase the solution space unnecessarily. Although in larger solution spaces, the chance of finding a solution is greater, it may take longer time to reach a solution. Thus, it was decided to include two more alternative rules i.e.  7.4 and 7.5, after some numerical design experimentation on the values for  these limits and the number of the rules that a designer can use in the design process.  Chapter 7. SEAKEEPING CONSIDERATIONS  102  Table 7.1: Input values to Echidna knowledge base for monohullfishingvessel.  Parameter  Value  Gear type Material type Design speed [kn] Ballast (% of V) Hold capacities [LT]  seiner aluminum 10.0 0 - 10 10, 25, 50, 75, 100, 125, 150, 200, 250, 300  In order to examine the effects of introducing Rules 7.2 to 7.5 into the knowledge base, for 10 different hold capacities 10 different designs were obtained without the rules in effect. Except for the hold volume capacity, the input to Echidna was the same as given in Table 7.1. Subsequently, this process was repeated for 5 different sea states, namely for 1, 2, 3, 4, and 5, and with the rules in effect resulting in 60 example designs in total, including the case without the rules. In obtaining the examples, the knowledge base (UBC-MONO) was the same for all cases except for the values of the required hold capacity were used as inputs. In the Echidna environment, it is possible to further reduce an interval solution by either applying additional constraints on it i.e. in this case the interval range for the ratio or using a built-in function, split, which randomly selects a subset of the original interval, specified by one of the rules of 7.3 to 7.5, that satisfies all the constraints of these rules. However, this option was not exercised because randomly shrinking the intervals in different examples can have different effects, and this would not conform with using exactly the same set of rules for all of the examples. Figures 7.3 to 7.7 depict the comparison of using and not using Rule Set I (Rules 7.2 to 7.5). Since the output values given by Echidna are expressed as real intervals for each ship design parameter, the interval solutions are represented as vertical bars in the  Chapter  7.  SEAKEEPING  CONSIDERATIONS  103  figures. The length of the bar indicates the size of a corresponding interval. In order to show the trend in the figures, lines are passed through the midpoints of the intervals. In principle, there could be several solutions enclosed in the interval, and none of them may be at the midpoint. However, if a uniform probability distribution is assumed for the values included in an Echidna interval to represent a solution, choosing the midpoint in the interval as a solution would minimize the error associated. Therefore, the midpoints have been selected as the representative values of the solutions within the intervals. Also, there are two types of lines in the figures, solid and dashed lines. The dashed lines in the figures correspond to the case in which Rules 7.2 to 7.5 were not incorporated during the design, i.e. they correspond to "no sea state criteria" case. Whereas the cases with the rules imposed during the design were represented by solid lines, i.e. "Sea state 5" case. The following results are presented for the comparison of the example designs with and without (control case) the new rules for a design-sea-state 5 only. Figure 7.2 on page 108 shows the values of ratios, defined by Equation 7.1, with and without Rule Set I in effect. The general conclusion from the Figure 7.2 is that Echidna was able to shift the natural frequencies of the designs. By studying the figure, it seems that even before the activation of the rules in Rule Set I, the majority of example designs for their minimum values in the intervals satisfy Rule 7.5. By taking the midpoints of the intervals into account, most of the example designs with Rule Set I in effect, satisfy Rule 7.3 and Rule 7.2 for heave and pitch motions respectively. The effects of Rule Set I on the ship size were investigated through Figures 7.3 to 7.6. Figure 7.3 on page 109 displays the effect of the shift of the vessel's natural frequency on the length. The general implication from this figure is that Rule Set I caused an increase of up to 20% in the length, (excluding 10 [LT] hold capacity with 50% increase) if the mid points of the length intervals of the example designs are considered. The  Chapter  7.  SEAKEEPING  CONSIDERATIONS  104  lengths show an increasing trend with increasing hold capacity for both cases, whether the rules are in effect or not, except in the interval between the hold capacity of 50 to 150 [LT] for cases with rules in effect and 100 to 300 [LT] for cases without the rules in effect. The lengths of the vessels are approximately the same for the example designs for the hold capacities contained in these regions. The reason of this irregularity in the trend is due to the methods used in the estimation of length in the knowledge base. Rule 7.7 and 7.9 shows the rules in Echidna for vessel's length estimation.  Vessel's length estimation : order  estimate length. 1st rule 2nd rule  (7-7) : — Length estimated < Licenselength. : — Use estimated Length as it is.  (7.8) (7-9)  These rules initially cause Echidna to produce designs whose lengths are less than or equal to the license length (see Equation 7.8). In the knowledge base, the method used in the estimation of license length is based on the design speed alone (see Equation B.2 in Appendix B on page 206). In our investigation the parameters that were held constant were design speed and the license length for different hold volume capacities. In effect, Echidna attempted initially to generate designs whose length satisfy Rule 7.8. For the cases without Rules 7.2 to 7.5 incorporated, Echidna was able to generate designs by only using Rule 7.8. However, when Rule Set I was in effect, two features can be observed in the figure. Firstly, License length limitation was reached earlier and secondly, it was no longer possible to produce designs which satisfy Rule 7.8, for hold capacities greater than 150 [LT]. The general tendency in the lengths of the example designs can be summarized as: the example designs are lengthened in the cases when Rules 7.2 to 7.5 were activated. Figure 7.4 illustrates the changes in the beams of the example designs due to activation of Rule Set I (Rules 7.2 to 7.5). Up to 75 [LT] hold capacity, beams of both example  Chapter  7.  SEAKEEPING  CONSIDERATIONS  105  designs have an increasing trend with hold capacity, however, with different slopes. At 75 [LT] hold capacity the increase in beam due to Rule Set I is around 24%. After 75 [LT], the beam values of the different example designs, one with the new rules and the other without (control case), first converge to each other between 125 and 150 [LT] and then diverge as hold capacity increases. In the case of "No sea state criteria" example design for 300 [LT] hold capacity, the initial interval prior to the design was preserved during the design process, thus causing a very large interval as a solution value for the beam. For this specific hold capacity, Figure 7.4 suggests an approximately 37% decrease in the beam due to the new rules in the design if the mid points are to be considered. However, this percentage would be reduced if additional constraints or built in "split" function were used. In connection with the changes in the lengths, for 150 [LT] hold capacities Echidna solutions for sea state 5 case opted for larger L / B ratios, since the variation in lengths seem to be larger than the variation in beams. Overall, the set of example designs with Rule Set I, present beamer vessels. Increases to the beam may mean increased displacement. Hence, the larger added mass and damping coefficients are expected to reduce motions. However, wave excitation forces increases due to the increased waterplane area. Generally, a large (beam/length) ratio is reported to reduce absolute vertical acceleration while relative motions are increased ( [45, p 471]). Figure 7.5 suggests that vessels with shallower drafts emerge after incorporating Rules 7.2 to 7.5 into the design process. Contrary to the changes in length and beam, the changes in draft presents a clearer picture. Similar to Figure 7.4, 300 [LT] example design of the group, Control case, in Figure 7.5 shows a very large interval. In Figure 7.6, displacements of the example designs with and without the rules are compared. Except the two cases of hold capacities at 10 and 300 [LT], the example designs with the rules in effect during the design have larger displacements in general. Although the solution intervals in both cases overlap each other to some extend, if the mid points  Chapter 7. SEAKEEPING  CONSIDERATIONS  106  of the intervals are considered, an increase in the displacement values is suggested in the figure. One of the most important parameters from an owner's point of view is the vessel's cost. Unfortunately, most of the solution intervals overlap heavily in Figure 7.7, which illustrates the variation of the cost between the designs with and without Rules of Method I, 7.2 to 7.5, thereby making it more difficult to reach a clear conclusion. However, up to 100 [LT] of hold capacity the average percentage increase in the cost is 24.4% with a standard deviation of 31.9% when the mid points of the intervals are considered. However, the overall values of percentage increase for average and standard deviation are 16.4% and 26.4%, respectively, for the mid points of the intervals.  Chapter  7.  SEAKEEPING  107  CONSIDERATIONS  S e a spectrum  \  sea  Sea  Frequency  Ship r e s p o n s e  Frequency  •  ship Figure 7.1: Frequencies that maximize sea spectrum and ship response spectrum.  Chapter  7. SEAKEEPING  108  CONSIDERATIONS  3.5 With Rule Set I  3.0 -  •£3  «© 2.0  I  I-  15  Control case  1.0 0.5  50  100  150  _L  _L  200  250  _L  300  350  300  350  Hold capacity [LT] 6.0 5.0  With Rule Set I  ,4.0 -  2 2.0 Control case 1.0  J_  50  _ J  I  .  I  100 150 200 250 Hold capacity [LT]  L  Figure 7.2: The variation of the ratios (Equation 7.1). Control case shows the ratios without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5.  Chapter  7.  0  SEAKEEPING  50  109  CONSIDERATIONS  100  150  200  250  300  350  Hold capacity [LT]  Figure 7.3: The effects of Rule Set I on the lengths. Control case shows the lengths without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  110  Figure 7.4: The effects of Rule Set I on the beams. Control case shows the beams without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  111  Figure 7.5: The effects of Rule Set I on the drafts. Control case shows the drafts without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  112  Figure 7.6: The effects of Rule Set I on the displacements. Control case shows the displacements without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  113  3.0  Figure 7.7: The effects of Rule Set I on the costs. Control case shows the costs without any seakeeping rules included in the design. Design-sea-state is 5; operational-sea-state is 5.  Chapter  7.2  7.  SEAKEEPING  CONSIDERATIONS  114  Evaluation of the Example Designs by Rule Set I  In the next step, the example designs obtained by the shifts in the frequencies corresponding to the peak motions are evaluated in terms of rms motion characteristics. This is in line with reported studies in the publicly available literature discussing discomfort due to ship motions - all are related to rms characteristics. In order to calculate rms characteristics for amplitudes or accelerations, an algorithm developed by Howard [23] is used. The algorithm is presented in detail in Appendix D. In obtaining the rms values using Howard's algorithm some issues had to be resolved. Since Echidna is not a suitable platform for intense computations, it was necessary to compute those values outside of the Echidna system. However, in choosing a system other than Echidna, there is a difficulty in representing real interval values in mathematical computations such as numerical integrals. In order to overcome this problem, three values for each interval were selected: the minimum value, the mid point and the maximum value of each interval. In doing this, the following assumptions have been made: • By arbitrarily selecting values from the intervals, we are not guaranteed that the set of selections represents a valid design, which satisfies the design constraints. However, if the intervals are sufficiently small and the nonlinearity in the mathematical model is low, it may be assumed that the set of selections is close to a design. • Secondly, using a set of arbitrarily selected values from the intervals one may cause the resultant intervals to shrink. The nonlinearity in the model and the size of the interval is the determining factor on the amount of shrinkage.  Chapter 7.  SEAKEEPING  115  CONSIDERATIONS  With these assumptions a FORTRAN code was written by the author to compute rms heave and pitch motion characteristics by the algorithm given in [23]. For the example designs obtained by Rule Set I, rms motion characteristics (motion amplitudes and accelerations) were computed for the three values (minimum, mid point and maximum) selected from the intervals that define an example design (e.g. length, beam, etc.). In Figures 7.8 to 8.31, the legend " (Echidna  interval,  lower  bounds)"  means that  in obtaining the results presented in the figure, the minimum values of the related intervals were used. Similarly, "(Echidna upper  bounds)"  interval,  mid points)"  and "(Echidna  interval,  correspond to computations using mid points and maximum values of  the intervals. In the figures showing "% Change" due to Rule Set I in rms heave and pitch motions (among Figures 7.8 to 8.31), "% Change"  was calculated with respect to the control  case, in which no seakeeping rules were incorporated in the design (see Equation 7.10).  0 / /-rz.  7o Change  ->nn  r  m  S  Value h wit  RuleSet I ~ TmS Value trol Con  — 100  case  1 a N  (7.10) rms  ValueControl case  In Figures 7.8 to 8.31, rms heave and pitch values and the % Change in them are plotted for different design-sea-states and for an operational-sea-state of 5. The different curves in these figures correspond to different design sea states. For example, "designsea-state  : 5"  means that during the design, Rule Set I ( 7.2 to 7.5) were in effect for  Sea State 5. In other words, in a sea state of 5, the frequencies corresponding to the ship's peak response (for heave and pitch motions) of the vessel being designed should be greater than the frequencies of the high energy waves in the sea state 5 by the amounts indicated by Rule Set I ( 7.2 to 7.5). Figures labeled "Operational-sea-state  : 5",  display how different designs, which are  designed for different design-sea-states, would perform in sea conditions of state 5.  Chapter 7.  SEAKEEPING  CONSIDERATIONS  116  For the investigation of the effects of Rule Set I, operational-sea-states of 3, 4 and 5 were used. After examining the results obtained, the largest effects of introducing Rule Set I into the design were for operational-sea-state of 5. Therefore, Figures 7.8 to 8.31 shows only the results for operational-sea-state of 5.  Discussion of the information in Tables 7.2 and 7.3; Tables 7.2 and 7.3 (on pages 117 and 118 respectively) summarize the information given in Figures 7.8 to 8.31. In these tables, the averages of the changes in motion amplitudes or accelerations for different hold capacities, i.e. for each design-sea-state, sum of the % changes in the rms motion amplitudes divided by 10, which is the number of different hold capacities used. The negative signs imply a reduction in the rms values. For example, the first row in Table 7.2 shows that if the minimum values in the Echidna intervals are used, there will be 2.647% increase on the average in the rms heave amplitude. For any given design-sea-state, as shown in Tables 7.2 and 7.3, selecting larger values from the Echidna interval e.g. maximum value (upper bound), seems to reduce the rms motion amplitudes more than any other value from the interval. Perhaps, this is because selecting larger values from the Echidna intervals also imply larger vessels, thus the motion amplitudes are smaller. Furthermore, for the same set of values of intervals, e.g. minimum, midpoint or maximum values, and the same sea state conditions, e.g. sea state 5 as in the figures, as the design-sea-state becomes larger, so does the improvement in general, that is the reduction in motion amplitude. Although there is not always a reduction in the average rms motion amplitude, see first row of Table 7.2, as the design-sea-state becomes larger the change in the average rms amplitude is in the right direction, i.e. decreasing.  Chapter  7.  SEAKEEPING  117  CONSIDERATIONS  Table 7.2: The averages and standard deviations (over hold capacities) of the % Changes obtained in rms heave and pitch motion amplitudes. The vessel is assumed to be operating in Sea State 5. Motion Heave  Design sea state  Value selected from the interval  % Change Average Stand, deviation  3 3 3 4 4 4 5 5 5  lower bound mid point upper bound lower bound mid point upper bound lower bound mid point upper bound  2.647 -0.842 -2.259 -0.982 -6.621 -9.167 -1.398 -6.423 -8.811  2.524 1.246 0.500 4.321 4.236 4.992 4.580 3.734 4.226  3 3 3 4 4 4 5 5 5  lower bound mid point upper bound lower bound mid point upper bound lower bound mid point upper bound  4.813 2.785 -1.371 -6.001 -11.411 -16.661 -6.081 -11.504 -16.428  1.859 1.713 1.717 10.763 9.530 8.818 10.662 9.645 8.865  Pitch  Discussion of the information in Figures 7.8 to  8.31;  Some of the general points worth mentioning about Figures 7.8 to 8.31 here are: • For design-sea-state 3, Echidna was able to find only two solutions, i.e. for hold capacities of 10 and 25 [LT]. For other hold capacities, Echidna failed to find a solution, which could have meant there is no solution under the circumstances. However, there was a final message of  "System  error,  exiting"  upon the termination  Chapter  7.  SEAKEEPING  118  CONSIDERATIONS  of Echidna. Therefore, this implies that for those particular cases of hold capacities, the answers are inconclusive, i.e. there could be a solution but "system error" messages from Echidna prevented the normal conclusion. Hence, in the figures missing data points correspond to such inconclusive cases.  Table 7.3: The averages and standard deviations (over hold capacities) of the % Changes obtained in rms heave and pitch accelerations. The vessel is assumed to be operating in Sea State 5. Motion  Design sea state  Value selected from % Change the interval Average Stand, deviation  3 3 3 4 4 4 5 5 5  lower bound mid point upper bound lower bound mid point upper bound lower bound mid point upper bound  4.328 -0.176 -3.901 ' -3.588 -10.199 -14.813 -3.856 -10.192 -14.595  3.016 2.124 1.287 7.779 6.657 6.662 7.034 5.559 5.300  3 3 3 4 4 4 5 5 5  lower bound mid point upper bound lower bound mid point upper bound lower bound mid point upper bound  5.073 5.850 1.717 -9.031 -11.970 -16.540 -9.038 -12.502 -16.929  0.258 0.666 1.702 14.600 12.967 11.053 15.963 15.336 13.333  Heave  Pitch  • The lines in the figures join the data points given by Echidna for corresponding hold capacities. In the absence of any symbol e.g. solid rectangle, hollow triangle,  Chapter  7.  SEAKEEPING  CONSIDERATIONS  119  etc., at the data point, this implies that Echidna was not able to find a solution for the corresponding hold capacity. When the minimum values of Echidna intervals are considered (see Figures 7.8 and 7.9), there is a slight improvement in the rms heave amplitude, which is 1.4% reduction on the average for the design-sea-state 5. When the mid points of Echidna intervals were used in the rms calculations, there is an overall improvement for the all hold capacity range (see Figures 7.10 and 7.11). For the maximum values of intervals (see 7.12 and 7.13), the difference in % Change increased. Figures 7.14 to 7.19, show a similar case study for rms pitch motion amplitudes. Figures  7.14,  7.16 and  7.18 display rms pitch motion amplitudes for the cases in  which minimum, midpoint and maximum values of Echidna intervals were used in the rms calculations, respectively. The largest reductions in rms pitch amplitudes occur in the hold capacity ranges of 50 to 100 [LT] and 250 [LT] and greater. Irrespective of the which values of Echidna intervals i.e. minimum, mid point or maximum, are used in the rms calculations. The decreases in rms pitch amplitudes are greater in design-sea-state 5 than in the case of design-sea-state 4. Similar results are presented for rms heave and pitch accelerations in Figures 8.20 to 8.31. In Figures 8.20, up to 125 [LT] of hold capacity, the rms heave acceleration seems to be reduced for design-sea-states 4 and 5. A similar case is depicted in Figure 8.21, which shows % changes rms heave accelerations. In the 0 - 125 [LT] hold capacity range, % changes are negative for the most part, thereby showing an up to 10% reduction in rms heave acceleration. Whereas for hold capacities larger than 125 [LT] % changes are positive, implying an undesirable increase in the rms values. However, the situation improves dramatically when midpoints (Figure 8.23) and maximum values (Figure 8.25) of the Echidna intervals were used. Nevertheless, the same pattern of larger reductions as  Chapter  7.  SEAKEEPING  120  CONSIDERATIONS  in the rms heave amplitudes below 125 [LT] hold capacities, has emerged in Figures 8.23 and 8.25. Figures 8.26 to 8.31 display the information related to rms pitch acceleration. The hold capacities of 25 and 50 [LT] appear to be the most difficult cases to improve. The overall pattern is also repeated in the figures related to rms pitch accelerations. Using maximum values in the rms calculations results in the largest improvement. As the design-sea-state becomes higher, the improvement in the rms pitch accelerations decrease considerably.  7.2.1  Remarks about the ship dimensions and displacement  With the introduction of Rule Set I ( 7.2 to 7.5) into the design, some changes in the particulars of the example designs as well as their costs were obtained. These changes due to Rule Set I are as follows (Figures 7.3 to 7.7): • Length; There is up to approximately 20% increase in the lengths (see Figure 7.3). • Beam; For the beams of the smaller example designs (less than 100 [LT] hold capacity), there is up to 25% increase in the beams.  Whereas for larger hold  capacities (greater than 100 [LT]), there is up to approximately 35% decrease in the beam values (see Figure 7.4). • Draft; Drafts of the example designs were reduced by up to approximately 30% (see Figure 7.5). • Displacement; If mid points of the intervals are considered, the designs with Rule Set I in effect have up to around 25% larger displacements (see Figure 7.6). • Cost: An up to 25% increase in costs of the designs were observed due to Rule Set I (see Figure 7.7).  C h a p t e r 7.  SEAKEEPING  CONSIDERATIONS  121  In return, the following changes were obtained in the rms heave and pitch motion characteristics of the example designs. In the results reported below, mid points of the Echidna intervals were used. Additionally, the sea state in which the vessel is assumed to be operating is 5 (see Tables 7.2 and 7.3 for more details).  • For design-sea-state 3: — Heave: The above mentioned changes in the vessels' particulars due to Rule Set I, resulted in an average of c. 0.8% decrease in the rms heave amplitudes of the example designs.  Similarly, there was a decrease in the rms heave  accelerations of the example designs due to the rules used. — Pitch: There were 2.78% and 5.85% (on the average) increases in rms pitch amplitudes and accelerations respectively, when compared to the control case (no seakeeping considerations).  • For design-sea-state 4 : — Heave: There were 6.6% and 10.2% (on the average) reductions in the rms heave motion amplitudes and accelerations respectively due to the rules used. — Pitch: For rms pitch motion amplitudes and accelerations 11.4% and 11.97% reductions were obtained respectively by using the rules during the design.  • For design-sea-state 5: — Heave: c. 6.4% and c.  10.19% (average) reductions in rms heave motion  amplitudes and accelerations were achieved. — Pitch: For rms pitch motion amplitudes and accelerations, the reductions were 11.5% and 12.5% respectively on the average.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  1.11 1.08 1.05 v T 3  ft  s  <u > <u ffi  1.02 Qperational-s.ea-sta.te..:. 5.  0.99 0.96  (Echidna interval, lower bounds) — e — Design-sea-; state : none - E 3 - - Design-sea state : 3 i •• Design-sea-state •: 4 \ -br - Design-seai-state : 5 i  ,y..  3  t  0.93 0.90  1  1  I  As.  50  100  150  200  250  Hold Capacity [LT]  Figure 7.8: Values of rms for heave.  10  Hold Capacity [LT]  Figure 7.9: % change in rms heave values.  300  Chapter  7. SEAKEEPING  CONSIDERATIONS  1.10  1.00  Operational-sea-statei: 5 (Echidna interval, mid points) Desigri-sea-state n o n e - Q - - Design-sea-state : 3 . . . . . . Design-sea-statie : 4 Design-sea-state : 5  53 0 . 9 0  a  0.80  50  100  150  200  250  300  H o l d Capacity [LT]  Figure 7.10: Values of rms heave.  0 -2 -4 -6 -8  : Operatidnal-sea-state : 5 I I (Echidna interva^ mid points)  _.q..  A  ; 4f  .' / :  / 7 : " / : / / :  v  • ; • / • ;  . v.  -10 1(  -12 -14  7  :/ [I ,7  ••  — B— Design-sea-state : 3 .'.l. ...Design-sea-state m  :4  4—.De$ign--sea-state : .5.  50  100  150  200  250  H o l d Capacity [ L T ]  Figure 7.11: % change in rms heave values.  300  Chapter  7. SEAKEEPING  CONSIDERATIONS  1.1  1.0 • — — — A -  0.9  - -  CTperat^ohal-sea-state : 5 : (Echidha interval, upper bounds) — e — Design-sea-state : none - - Desigri-sea-state ':" 3 ...m--- Design-sea-state : 4 - -zV - Design-seia-state : 5  0.8  0.7  50  100  150 200 Hold Capacity [LT]  250  300  Figure 7.12: Values of rms for heave.  Operational-j-sea-statei : 5 ~ ~u (Echidna interval, upper bounds) C3  -5  I  \  :  /  -10  A  v  :-  50  100  Ddsign-sea-istate : 3 . . . Design-sea-istate : 4 rr. Design-sea-state : 5  ;-£Jl . .  •15 -20  ^  • i-  m  150  200  250  Hold Capacity [LT]  Figure 7.13: % change in rms heave values.  300  Chapter 7.  SEAKEEPING  CONSIDERATIONS  15  Operational-sea-state : 5 (Echidna interval, lower.bounds) — e — Design-sea-state : nohe - 4 3 — Design-sea-state : 3 \ . . . . . . Design-sea-state : 4 ; - D^sign-sea^state : 5 i  14 -a  13  m  12 -a 3  11  t  10  p  9  PS  8 50  100  150  200  250  300  Hold Capacity [LT]  Figure 7.14: Values of rms for pitch.  s  03  o "OH  U  100  150  200  Hold Capacity [LT]  Figure 7.15: % change in rms pitch values.  300  Chapter  7.  SEAKEEPING  CONSIDERATIONS  Operational-sea-state : 5 (Echidna interval, mid points) — e — pesign-sea-state : none - - Q - - Design-sea-state : 3 L'l'-'m-"-'- Pesigh-sea-state :"4 - - A - - Pesign-sea-state : 5  50  100  150  200  250  300  Hold Capacity [LT]  Figure 7.16: Values of rms for pitch.  Operati6nal-sea-state : 5 \ (Echidna interval!, mid points) i: >  i: \ it-  -  \ :: \ ...  l!  /,'  - • •• Ii • •• f,  i  I - • - Design-searstate : 3 \— --- Design-sea-state : 4 ; . L--^-. Design-searstate..; .5.-..  t l  m  t I  0  50  100  150  200  250  Hold Capacity [LT]  Figure 7.17: % change in rms pitch values.  300  Chapter  7.  SEAKEEPING  CONSIDERATIONS  13  Operational-sea-state : 5 :. (Echidna interval; upper bounds) o Design-sea-tstate : none - - Q - - Design-sea-state : 3 ; — m-- Design-searstate : 4 i Desigri-seafstate : 5 •  12 11 10 9 8 50  100  150  200  250  300  Hold Capacity [LT]  Figure 7.18: Values of rms for pitch.  Operational-sea-state : 5 \ (Echidna interval^ upper bounds)  0 -5  VV  -10 t  -15 .  •• i t  -20 -25 -30  •/•/•  t  / - E 3 - Design-sea-state : 3 Pesign-sea-state ; 4 V Jmrr.-. -ky- - Design-sea-stiate : 5  i  L....I.. /  _i  50  i  100  i  150  ,  i  200  ^  ,  250  Hold Capacity [LT]  Figure 7.19: % change in rms pitch values.  300  Chapter  7. SEAKEEPING  CONSIDERATIONS  1.5 1.4 1.3 Qperational-sea-state : 5 (Echidna interval,Tower bounds) — Design-sea-state : none -iq--Design-sea-state : 3 ..Am--- Design-sea-state : 4 - 4A- - Design-sea-state : 5 i , i , i , 100 150 200 250  1.2 1.1 _i 1.0  ,  i  .  50  300  Hold Capacity [LT]  Figure 7.20: Values of rms for heave accelerations (Rule Set I).  10 5 — • -v 0 -5 -10 -15  I t  1 1  •m  i\ • \  • •• I / / I  /f: ' i_ -  .  '"/  I I  /• -y  • //  /r-Operational-sea-state  \.//...  :5 i X !• (Echidna interval^ lower bounds) : - - Q - - Design-sea-state : 3 I  N  l.-.-.-.«-.r..-.Design-seatstete..: 4 . ;  I  -20 50  Design-sea-state : 5 : j i i , i i 100 150 200 250  .  300  Hold Capacity [LT] Figure 7.21: % change in rms heave accelerations (Rule Set I).  Chapter  7.  SEAKEEPING  CONSIDERATIONS  1.5  2  Operational-sea-state : 5 (Echidna iriterval, mid points)  1.4 1.3  2  CD  8  1.2  o  <  Design-sea-state none Pesign-sea-state : 3 ..-m--- Design-sea-state : 4 Design-sea-state : 5  1.1  >  •-Q--  CD  1.0  50  100  i  i  150  i  i  200  ,  i_  250  300  Hold Capacity [LT]  Figure 7.22: Values of rms for heave accelerations (Rule Set I).  CD  o o  03  0  <U >  -5  :  \ s:  -10  ./A..v,  CD  a  -15 L. -20  50  100  „ —4...  \ // Operationai-sea-state : 5 Y (Echidna interval, mid points) - -of - Design-sea-state : 3 . . . p L . . Design-sea-state : 4 - - A j - Desigrii-sea-statp : 5 150  200  250  300  Hold Capacity [LT]  Figure 7.23: % change in rms heave accelerations (Rule Set I).  Chapter 7. SEAKEEPING CONSIDERATIONS  1.5  -ej— Design-sea-state - Q - - Design-sea-state .Desigh-sea-state - Desigh-sea-state  : none : 3 :4 : 5  dperational-sea-state : 5 (Echidna interval, upper; bounds)  1.0  1  1  50  100  I  1  150  200  i  I  i  250  300  Hold Capacity [LT]  Figure 7.24: Values of rms for heave accelerations (Rule Set I).  o o o  03  > 03  i Operational-sea-state : 5 \ ; (Echidna interval, upper bounds)  -5  A  -10 /  .S  -15  / > - - - - - . .... *  •A : 'A : \\ .  /:V  - 1 \ ;  C  6  -20  -  /  \ .  / :  //..I  / w  CD 03  /  n  \  /  U  - : - C 3 -  :.t  6S  -25  50  100  150  - Design-sea-state : 3 :: Design-sea-state : 4 Design-sea-state : 5 200  250  300  Hold Capacity [LT]  Figure 7.25: % change in rms heave accelerations (Rule Set I).  Chapter  7.  SEAKEEPING  CONSIDERATIONS  Operational-sea-state : 5 (Echidna interval, lower bounds) — — Design-sea-state : none - H Q - - Design-sea-state : 3 Design-sea-state : 4 Design-sea-state ':" 5  100  150  200  250  300  Hold Capacity [LT]  Figure 7.26: Values of rms for pitch accelerations (Rule Set I).  20 I \ I \  10  7 /  0 i:  -10  I  -20  P-  •; x  T\ /; /.'  v  •  X  \  \  : \  ; V  A.  ....; \  \  //.  1  >4 /Operational-sea-state : 5 . ^ i . _ ^ (Echidna interval, lower bounds) — Q - - Design-sea-state : 3 ;..||... Design-sea-state : 4 •-A-Design-sea-state : 5 _ i  -30 - / -40 50  100  150  200  250  300  Hold Capacity [LT]  Figure 7.27: % change in rms pitch accelerations (Rule Set I).  Chapter  7. SEAKEEPING  CONSIDERATIONS  0.55 FT  0.50 U V * .  ^0 3  0.45 k  §  0.40- <  iOperational-sea-sitate : 5 (Echidna interval,; mid points) I - oDesign-sea-jstate : none — - Q - - Design-sea-state : 3 j L-i-fli.-:Design-seaistate••: 4 - \  Design-sea-jstate : 5 ;  03  £  0.35^  o  <  0.30  |  0.25 k  -A  .  _l  0.20  50  100  150  200  250  300  Hold Capacity [LT]  Figure 7.28: Values of rms for pitch accelerations (Rule Set I).  20  'i  : Operational-sea-:state : 5 , . . . ^ ( E c h i d n a . i n t e r v a l , mid points).  10 l_  B ~ Jm  s,  I  -10  .5 &  -20  i  \  A \ \ \\  C3  o  -30 -40  \ /'  \  /  s  ,p  ^ :  ;  •  ^  > ^-  :  :  v - - Q - - Design-sea-state : 3 , „.m— Design-sea-state 4 - Design-sea-state : 5  r_  ,  50  i  ,  100  i  i  150  200  >  250  300  Hold Capacity [LT]  Figure 7.29: % change in rms pitch accelerations (Rule Set I).  Chapter  7. SEAKEEPING  CONSIDERATIONS  0.50  r  0.45 -  ±L  0.40  1  iOperatidnal-sea-sitate : 5 •(Echidna interval^ upper bounds) I—e— Dessign-sea-istate : none L . - G - - Design-sea-state : 3 : ; ~ - H - ~ Design-sea-state : 4 ! - A - - Design-sea4state : 5 :  s o  '3 §  0.35 0.30  S  0.25  < OH  0.20  50  100  150  200  300  250  Hold Capacity [LT]  Figure 7.30: Values of rms for pitch accelerations (Rule Set I).  ne. v.. —  /; // //  \ '  \:  Operational-sea-state : 5(Echidna interval, upper b o u n d s ) . - - Q - - Design-seja-state : 3 ---m--- Design-sea-state : 4 Design-sea-state : 5  H  i: i: i:  •(  A  ; / /  7 V  50  11  100  150  200  250  300  Hold Capacity [LT]  Figure 7.31: % change in rms pitch accelerations (Rule Set I).  Chapter 7. SEAKEEPING  7.3  CONSIDERATIONS  134  Rule Set II  In the previous section, a way to incorporate sea keeping considerations in the preliminary design process is described. In that approach, achieving the goal of lesser discomfort due to vessel motions was attempted by shifting the vessel's natural frequencies away from the frequencies of the high energy waves in the sea (Rule Set I, on page 100). However, in this section a different approach is described. Instead of shifting the peak frequencies, some of the rms values of the vessels' motions were constrained during the preliminary design. A new set of rules was specified, in order to implement these new rules during the design in a knowledge-based system without extensive calculations, the rms values of different motions under consideration, e.g. pitch motion, need to be estimated. For heave and pitch rms motion amplitudes, two estimation formulae are developed. The details of these algorithms can be found in Appendix F. The rules incorporated in the Echidna knowledge base are given in Rules 7.12. The first rule is related to rms heave motion amplitude. The value of upper limit has been decided upon after examining the rms values of example designs without rules. Although the acceleration levels are mentioned in the literature as one of the parameters that affect human performance, some of the suggested constraints (e.g. [67] and [56]) were on some of the ship motions amplitudes. Therefore, in this case study constraints on the amplitudes were used.  Rule Set II  rms  heaveamplitude  rms pitchamplitude  < 0.7 [m]  (7.11)  < 5.0°  (7.12)  These two rules we added to the knowledge base and used during the preliminary design, both Rules 7.11 and 7.12 were activated simultaneously. However, Rule Set I  Chapter  7.  SEAKEEPING  CONSIDERATIONS  135  ( 7.2 to 7.5) in the knowledge base were switched off while Rule Set II ( 7.11 and 7.12) was active. For each of the hold capacities mentioned in Table 7.1, with the other inputs to Echidna being the same as these used in Rule Set I then, 10 new example designs were obtained while Rule Set II was in effect during the design process with Echidna. In Figures 7.32 to 7.43, the effects of incorporating Rule Set II ( 7.11 and 7.12) in the preliminary design are presented. The lines in the figures join the midpoints of Echidna intervals for the same case study, e.g. the knowledge base with Rules 7.12 in effect, similar to the figures in the previous sections. The dotted lines represent the case, in which Rules 7.12 were not activated during the design. Whereas the solid lines are for the case study with the rules in effect. All were applied for sea state 5. In these series of figures, the first two figures, Figures 7.32 and 7.33, display the amount of changes in rms heave and pitch motion amplitudes respectively, after Rule Set II was added in the knowledge base. In the case of heave motion (Figure 7.32), prior to the addition of Rule Set II to the knowledge base, rms heave motion amplitudes were greater than the assigned limit values in almost all of the example designs. The example designs obtained with Rule Set II show reasonable reduction in rms heave motion amplitude particularly in the lower range of hold capacities below approximately 75 [LT]. As shown in Figure 7.33, Echidna intervals for rms pitch motion amplitudes overlap significantly over the range of hold capacities, thereby suggesting Rule Set II have almost no effect on the current example designs, except in the small hold capacities up to approximately 75 [LT]. The effects of Rule Set II on the cost and the vessel's sizes, are illustrated in Figures 7.34 to 7.43. In the figures, the percentage change is calculated as follows:  Chapter  7.  SEAKEEPING  % Change  In the above equation,  136  CONSIDERATIONS  =  100  Design  Design  Parameteri Design  Parameteri  included during the design, Design  — Design Parameter^  Parameter  (7.13)  represents the case where Rule Set II was  Parameter^  is for the case without any seakeeping  rules (control case). Figure 7.34 shows the change in the lengths of example designs due to the addition of Rule Set II. Whereas, Figure 7.36 displays this change in the length as percentage of the lengths of the designs without the rules included in their design. The percentage change in the length has its largest values in the small hold capacities up to 75 [LT], after which it remains approximately constant. If the mid points of the intervals are considered in Figure 7.36, the line is in the positive side of Y-axis, thereby implying an increase in length for all hold capacities. In Figure 7.36 there is a jump in the current trend of % change in the length for 250 [LT] hold capacity. However, the size of the % change interval remains almost the same as those neighbouring it. Perhaps, one explanation for this might be that this region is a transient one where the license length limitation had to be violated during the design. This part of the curve is another case that could be investigated in detail for its deviation from the earlier trend in length depicted in the figure. It is interesting to note that the same situation also occurs for the beam, draft and displacement values of the example designs. Another interesting point related to this figure is that there is no observable difference in the intervals of the two cases, with and without the rules, for 300 [LT] hold capacity. If some extreme points such as the one for 250 [LT] hold capacity are neglected, considering the mid points in Figure 7.36, there is nearly a 3% increase in the lengths of the example designs larger than 75 [LT] hold capacity. For smaller hold capacities, the increase in length reaches as much as c.9% for mid points of the intervals.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  137  Figures 7.35 and 7.37 displays the effects of Rule Set II on the beams of the example designs. Rule Set II tends to increase both beams and lengths. Almost the same patterns as in Figures 7.34 and 7.36 emerge in the figures for the beams of the example designs. As mentioned earlier, the jump for the 250 [LT] hold capacity is also present in Figure 7.37. If the mid points of the intervals are considered, there is approximately 5% increase in the beams. Figures 7.38 and 7.40, are difficult cases as there is no clear trend in the changes of the drafts due to Rules 7.12. Generally speaking, the sizes of the intervals of % changes are comparatively larger for smaller hold capacities of up to 75 [LT] in Figure 7.37 as these are relatively small boats and they are significantly improved by increasing their lengths. Again, the intervals in both cases (with and without the rules) remained the same for 300 [LT] hold capacity. Up to 50 [LT] hold capacity, % changes imply an increase in the draft, whereas, between 50 to 100 [LT] hold capacities, a reduction in draft seems more plausible from the figure. Between 100 to 200 [LT] hold capacities, the midpoints of the intervals are very close to 0% change, however, for greater hold capacities, there may be shallower drafts suggested in the figure, except 300 [LT] hold capacity, in which there is no change in the draft intervals of the example designs (with and without the rules). Displacements of the vessels are more appropriate to compare the sizes of different vessels. Hence, Figures 7.39 and 7.41 reveal the changes in displacements of the example designs before and after the introduction of Rules 7.12 in the design. Figure 7.39 shows the displacements of example designs in long tons. The two lines in the figure, which join the mid points of the intervals, are nearly parallel to each other. This suggests an increase due to Rules 7.12 in the sizes of the vessels, which is generally expected. However, the important factor in this investigation is the amount of increase to satisfy the constraints on rms heave and pitch motions. Figure 7.41, in which the change is given as % of  Chapter  7.  SEAKEEPING  CONSIDERATIONS  138  the displacements of the example designs obtained without Rules 7.12 present in the knowledge base, is helpful in determining the necessary increase. If the mid points of the intervals are taken into account, the trend in displacement is remarkably similar to the trends in lengths and beams of the example designs, as shown previously in Figures 7.36 and 7.37 respectively. For small hold capacities up to 75 [LT], a larger increase in displacement is suggested, with the largest being 20% for 10 [LT] hold capacity. Above 75 [LT] hold capacities, the mid points of the % change intervals oscillate around 5%. On the other hand, if the whole intervals are considered, the sizes of intervals are relatively greater up to 150 [LT] hold capacity, thereby increasing the uncertainty in the % change. Additionally, the intervals of the % changes extend below X-axis, implying a possible reduction in the displacements, thus in the sizes of the example designs. However, the sections of the intervals extending below the X-axis are smaller than those remain above the axis. Therefore, an increase in the displacements is assumed to be more probable. The example designs for 300 [LT] hold capacity presents a particular case, in which the introduction of Rules 7.12 changes neither the size of the displacement interval nor its location in the figure. Hence, the mid point of the interval for this hold capacity in Figure 7.41 is located at 0%, suggesting this large vessel may already satisfy Rules 7.12. From the owners' point of view, the costs of the vessels are possibly of more importance than the other parameters examined above. Figures 7.42 and 7.43, which are similar in content to the previous figures mentioned above, reveal the cost of including Rules 7.12 in to the preliminary design. Figure 7.42 suggests an increase in the cost of example designs after the addition of the rules. In the figure, the Echidna intervals of the two cases, that are with and without the rules, overlap for most of the hold capacities. When mid points of the intervals are considered, however, there is a clear increase in the costs as illustrated in the next figure (Figure 7.43). In percentage, the mid points of the % change intervals are distributed in close neighbourhood of 10% for hold capacities  Chapter  7.  SEAKEEPING  CONSIDERATIONS  139  between 75 to 250 long tons. Up to 75 [LT] hold capacity, satisfying Rules 7.12 may cost as much as approximately 30% more, if the mid points of the intervals are considered. However, within this hold capacity range, the line has a negative slope, thus as the vessels become larger the amount of cost increase due to the rules decreases for the mid points of the intervals. Similar to the case of percentage change in the displacements, the sizes of the % change intervals are larger for the smaller hold capacities. Hence, up to 250 [LT] hold capacity, the intervals extend into the negative region, implying a reduction in the cost, as in the previous case. However, approximately 2/3's of the intervals are in the positive region in Figure 7.43. Therefore, an increase in the costs of the example designs is believed to be the case. There is no change in either the cost or the % change intervals of the example design for 300 [LT] hold capacity vessel (in Figures 7.42 and 7.43 respectively). Considering the fact that the size of the example design for this hold capacity also remained the same after introducing Rules 7.12, one may regard 300 [LT] hold capacity as the upper limit, beyond which Rules 7.12 may no longer be effective.  Chapter  7.  SEAKEEPING  140  CONSIDERATIONS  1.4 1.2 1.0 0.8  M 0.6  "\ -1 \  |  eav  CD  a  0.4  With Rule Set II  0.2  — Control case  0.0  I  50  o  I  I  I  100 150 200 Hold Capacity [LT]  250  L  300  Figure 7.32: The effects of Rule Set II on rms heave amplitudes. Design and operational sea states are 5.  20  i—  W i t h Rule Set II '15 Control case 10  i  M  5  0 OH  0  50  100  150  200  250  300  Hold Capacity [LT] Figure 7.33: The effects of Rule Set II on rms pitch amplitudes. Design and operational sea states are 5.  Chapter  7. SEAKEEPING  90  141  CONSIDERATIONS  — —  80  —  70  ~  s  /k— 1^:::::^-  x r  60  3 50  ....  /  .Afc.  JL  **SJgP  r  -\/Y  40  b' '  _.±• /  — : /•  30  0  i  ^^^^^^  1 50  i  i  100  i  With Rule Set II Control case  1 150  ,  1 , i 200  250  300  Hold Capacity [LT] Figure 7.34: The effects of Rule Set II on lengths. Design-sea-state is 5. 28  26  24  B d  /A  22  CD  PQ  20  With Rule Set II 18  —  Control case  16 0  50  100  150  200  250  300  Hold Capacity [LT] Figure 7.35: The effects of Rule Set II on beams. Design and operational sea states are 5. J  Chapter  7.  SEAKEEPING  142  CONSIDERATIONS  20  0  50  100  150  H o l d Capacity  200  250  300  [LT]  Figure 7.36: % Change in the lengths of the example designs. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  143  Figure 7.37: % Change in the beams of the example designs. Design-sea-state is 5.  Chapter  S  1  7.  12  r—  11  —  10  —  SEAKEEPING  144  CONSIDERATIONS  A-  /  _ /  9  o3  Q  8  7  With Rule Set II  6  Control case J  o  50  100  150  I 200  i  I  i  250  300  Hold Capacity [LT] Figure 7.38: The effects of Rule Set II on drafts. Design and operational sea states are 5. 500  400  _  300  CD  s  r  CD  -fL 2 0 0  With Rule Set II  G/2  100  Control case J  0  50  L 100  j  150  200  250  I 300  Hold Capacity [LT] Figure 7.39: The effects of Rule Set II on displacements. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  145  Figure 7.40: % Change in the drafts of the example designs. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  146  Figure 7.41: % Change in the displacements of the example designs. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  147  CONSIDERATIONS  2.5E06 r —  2.0E06  d O  1.5E06  o  With Rule Set H 1.0E06  Control case j  5.0E05 50  L  _L  100  150  200  250  300  Hold Capacity p_T] Figure 7.42: The effects of Rule Set II on costs. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  CONSIDERATIONS  100  Figure 7.43: % Change i n the costs of the example designs. Design-sea-state is 5.  148  Chapter 7.  7.4  SEAKEEPING  149  CONSIDERATIONS  Comparison of the outcomes of Rule Sets I and II  In the previous sections two strategies (Rule Sets I and II) are described to try and improve the working and living conditions on board fishing vessels by reducing some vessel motions amplitudes. In Rule Set I, the peak frequencies of a vessel's response spectrum and the given sea state spectrum are considered to be the important design factors, hence, the concept of shifting the vessel's peak frequency away from the frequencies of the sea state. A fundamentally different strategy was employed in Rule Set II, in which rms values of heave and pitch motions were constrained. In both of the strategies (Rule Sets I and II), the same vessel motions, namely heave and pitch motions, are used as basis for the design criteria at the case studies. The following discussion compares the two rule sets in terms of the amount of changes they have caused to the control cases, when neither Rule Sets I and II were used during their design (control case). The difference in the ship costs predicted involved in the two rule sets is also examined. In Figures 7.44 to 7.48, the percentage change is the change in parameter values used in the two rule sets (Rule Sets I and II), and calculated by Equation 7.14.  wnu  ,nn  Parameter  ToCnange — 100  Rule  S e t  n  - Parameter  Rule  ParameteTR i  u e  Set I  t  Se  I  / r r  ,  («-14)  One characteristic feature of Figures 7.44 to 7.48 is that the difference between the two rule sets converges to zero as the hold capacity increases. This is in close agreement with the previous findings that for each rule set the amount of change from the original example design (control case) diminishes as hold capacity increases. This could be explained as larger vessels experience less severe motions than smaller ones for a given sea state. Otherwise, they need to be designed for a higher sea state. The following differences in the design parameters due to Rule Sets I and II can be  Chapter  7.  SEAKEEPING  CONSIDERATIONS  150  seen in Figures 7.44 to 7.48 : • Length : In general, Rule Set II resulted in longer designs in comparison to the designs obtained by Rule Set I (see Figure 7.44). • Beam : When the mid points of the intervals are considered, Rule Set I caused wider designs than those obtained using Rule Set II for hold capacities larger than 50 [LT] (see Figure 7.45). • Draft : Rule Set II resulted in deeper draft designs in comparison to Rule Set I designs, with diminishing difference as hold capacity increases. • Displacement : For larger hold capacities than 50 [LT], the designs obtained using Rule Set I have larger displacements than those obtained by Rule Set II (see Figure 7.47). • Cost : It is difficult to say with confidence from Figure 7.48) that one rule set produced less expensive vessels than the other. % Change values in thisfigure,start from ±50% at the lowest hold capacity, oscillates around the 0 line and converges to 0 as the hold capacity increases.  Chapter  7.  SEAKEEPING  151  CONSIDERATIONS  150  100  c c  o  50  03  0  -50 0  50  100  150  200  250  300  Hold Capacity [LT]  Figure 7.44: % Changes of the lengths of example designs obtained using Rule Sets I and II. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  152  CONSIDERATIONS  50  40  30  20  10  IP 0  •10  -20  -30  -40 0  50  100  150  H o l d Capacity  200  250  300  [LT]  Figure 7.45: % Changes of the beams of example designs obtained using Rule Sets I and II. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  153  CONSIDERATIONS  200  150  CO  100  50  0  -50  0  50  100  150  200  250  300  Hold Capacity [LT] Figure 7.46: % Changes of the drafts of example designs obtained using Rule Sets I and II. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  154  CONSIDERATIONS  120  90  «s  I  —  60  o OS  ^  .s  30  J 3  u  0  -30  -60  0  50  100  150  200  250  300  Hold Capacity [LT]  Figure 7.47: % Changes of the displacements of example designs obtained using Rule Sets I and II. Design-sea-state is 5.  Chapter  7.  SEAKEEPING  155  CONSIDERATIONS  150  100  -S3  50  O  o CD  A  /  0  -50  100  J 0  50  i  I 100  i  I 150  i  L_ 200  250  300  Hold Capacity [LT]  Figure 7.48: % Changes of the costs of example designs obtained using Rule Sets I and II. Design-sea-state is 5.  Chapter  7.5  7.  SEAKEEPING  156  CONSIDERATIONS  The Criterion Suggested by Kimura et al. [40]  Earlier in Section 2.3, it was mentioned that Kimura et al. [40] suggested a criterion (Equation  2.3 on page 38) for quantifying the relationship between maintaining the  human balance and the ship motions. In this section, the example designs obtained above by the two rule sets have been evaluated further using Equation 7.15. This equation is slightly different from the original equation (Equation 2.3) such that 0.1659 M l  y  term  has been omitted. The omitted term correspond to the accelerations due to roll, sway and yaw motions. Considering the fact that roll motion is very much dependent on the center of gravity of the vessel and therefore loading conditions, and the example designs are assumed to be in head seas conditions (although one can not obtain a pure head sea condition in a real sea), the contribution to the acceleration due to roll motion has been neglected. Sway and yaw motions are considered to be small, thus they are neglected in Equation 7.15.  T  m  = M l . + 0.1133 M l ,  [m /* ] 2  5  (7.15)  where M l is the first moment of power spectrum of the acceleration on deck, x,y and z subscripts represent the coordinate axes x (longitudinal), y (transverse) and z (vertical). T  m  values (Equation 7.15) were evaluated at three locations for each of the example  designs, namely on the deck at the stern, at midships and at the bow. The stern has been chosen as the place where crew members perform some of the tasks such as handling the net or doors (see Figure 7.49). The midship area is generally the location of bridge and accommodation. At the bow, crew may have to handle the anchor or lines. In calculating of the acceleration terms, the following equations have been used:  Chapter  7.  SEAKEEPING  157  CONSIDERATIONS  Figure 7.49: A crew member working at the stern.  zcosO + ^ 6 Vertical  acceleration  — < ZCOS& zcosO —  Horizontal  acceleration  =<  at the  bow  at the  midship  at the  (7.16)  stern  zsinO  at the  bow  zsinO  at the midship  zsin8  at the  (7-17)  stern  In these equations, 8 is the pitch amplitude, 6 corresponds to the amplitude of the pitch acceleration, z terms are due to the heave acceleration. In these equations, centrifugal acceleration due to pitch motion have been neglected as it is usually very small compared to the other terms ([13], [58]). T h e vertical and horizontal accelerations i n the above formulation are the accelerations of the ship. W h e n considering the compound  Chapter  7.  SEAKEEPING  158  CONSIDERATIONS  accelerations (for that matter any other ship motions related terms such as velocities) in vertical, transverse or longitudinal directions the phase differences between the different type of ship motions, for example between heave and pitch motions, are important. However, it is considered a good approximation to assume that heave and pitch motions are in phase at the bow and out of phase at the stern of a ship. This assumption has been used in establishing Equations 7.16 and 7.17. For amidships, the effect of pitch in the horizontal accelerations has been neglected, this leaves only a heave related term in the horizontal acceleration in Equation 7.17. In Figures 7.50 to 7.61, T values have been computed for sea states of 2 and 5 for m  the three groups of example designs (Control case and with Rule Sets I and II). It was therefore possible to quantify the effects of Rule Sets I and II on the conditions on board of the fishing vessels with respect to the criterion (Equation 7.15). In the evaluation 3 vessel speeds have been used, which are 0.01, 5 and 10 knots. 0.01[fcn] corresponds to a stationary vessel, which could be taking the catch in. 5[kn] speed is chosen in regard to trawling speed. This speed may vary from 3 to 5 knots. Finally, a speed of 10[fcn] may not be achievable in especially smaller vessels in a sea state of 5, however, it is done as an extreme case study. The T values obtained in this thesis are dramatically larger m  than T (Equation 2.3) values given in [40] especially for the ship speeds of 5 and 10 knots. However, the details of the calculations in the original paper were not clear in [40]. Therefore, Equation 7.15 is used as a merit of ranking for the example designs rather than the way it is suggested in [40]. For the following paragraphs (see also Figures 7.50 and 7.61) , % Change have been calculated by  /w s~i i % Change  .,  n  n  = 100  I -*m iRule Set I or II  K-'-m/Control case  —T=-r  \-l-m)Control case  /  n  1 r )  (7.18)  \  Chapter  7.  SEAKEEPING  159  CONSIDERATIONS  Figures 7.50 and 7.53 are for operational-sea-states of 2 and 5 respectively. These two figures corresponds to a stationary vessel case. Up to approximately 75 [LT] hold capacities, there is not any clear difference between the three cases (Control case, Rule Sets I and II). However, for larger hold capacities (hence larger vessels) than 75[LT], Rule Set I has a visible improvement in T values. m  For sea state 2 (Figures 7.50 and 7.51), including Rule Set I ( 7.2 to 7.5), into the design resulted in approximately 20% reduction in T values on the average. Whereas m  Rule Set II ( 7.11 and  7.12) produced around a 10% reduction for the larger hold  capacities, between 150 and 300 [LT]. For the designs obtained using Rule Set I, at the same vessel speed but an operational-sea-state of 5, T values were decreased by m  approximately 15% at the bow, 20% at the amidship and 15% at the stern on the average. On the other hand, Rule Set II produced 2%, 5% and 0.7% (average) reductions on T  m  values at the bow, amidship and stern respectively. Figures 7.54 and 7.57 are for operational-sea-states of 2 and 5 respectively but for a vessel at the speed of 5 [kn]. As in Figures 7.50 and 7.53, the larger reductions in T  m  values have been obtained for an operational-sea-state of 5. In the operational-sea-state 2 (see Figures 7.54 and 7.55), there were reductions of approximately 8% and 45% on the average at the bow and amidship respectively for the designs obtained using Rule Set I. For those obtained using Rule Set II, the reductions in T at the bow and amidship m  are 3.7 and 16% respectively. For T values at the stern, there are 10% and 1.8% average m  increases for Rule Sets I and II respectively. However, this situation has been improved for an operational-sea-state of 5, in which there are approximately 6% and 5% reductions for the stern values for Rule Sets I and II respectively. At the bow and amidship, T  m  values have been reduced by 17% and 43% for Rule Set I and by 7% and 16% for Rule Set II. As mentioned earlier in this section, a 10 [kn] speed in an operational-sea-state of  Chapter  7.  SEAKEEPING  160  CONSIDERATIONS  5 especially for small vessels is unrealistic to achieve. In any case, the analysis has been carried out for an operational-sea-state of 5 and a vessel speed of 10 [kn]. Figures 7.58 and 7.59 is for the operational-sea-state of 2 and 10 [kn] vessel speed and for the operational-sea-state of 5 the results are presented in Figures 7.56 and 7.57. As it appears in Figure 7.58 (operational-sea-state of 2), three cases (Control case, Rule Sets I and II) have very close values to each other after hold capacity of 75 [LT]. As far as the average values of T are concerned, reductions in T for an operational-sea-state of 2 was m  m  possible for amidships only (by 45% and 10% for Rule Sets I and II respectively). At the bow, Rule Sets I and II have 20% and 28% increases on the average in T , although at m  some hold capacities there were reductions. The average increases at the stern were 5% and 17% for Rule Sets I and II respectively. The situation seems to be improved for the operational-sea-state of 5 (Figures 7.60 and 7.61). On the average, there were reductions for the designs obtained using Rule Sets I and II. The largest average reductions were at the amidship with 48% and 18% for Rule Sets I and II respectively. For the bow, T  m  values have been reduced by 5% and 4% for Rule Sets I and II respectively. At  the stern, Rule Set I produced approximately 5% increase unlike Rule Set II which has approximately 1% reduction on the average. However, if the results for hold capacities less than 75 [LT] are neglected, the new averages are around 25% and 5% reductions for stern for Rule Sets I and II respectively.  7.5.1  Summary  In summary, the following are the outcome of the evaluation of the example designs obtained using Rule Sets I ( 7.2 to 7.5) and II ( 7.11 and 7.12) in the design in terms of T  m  values, Equation 7.15 on page 156, (see Figures 7.50 to 7.61).  Chapter  7.  SEAKEEPING  161  CONSIDERATIONS  • For Rule Sets I and II, most of the reductions in T values were achieved for larger m  hold capacities. • Rule Sets I caused lower T  m  values than Rule Set II in general.  • In using Rule Set I in the design, approximately 20% reductions in the T  m  values  of all three locations on the deck (stern, amidship and bow) was achieved for a vessel speed of 0.01 [kn] and an operational-sea-state of 2. Whereas Rule Set II caused an approximately 10% reduction on the average for the same speed and sea conditions. For the same speed (0.01 [fen]) but an operational-sea-state of 5, the average reductions in T values were around 15% for Rule Set I and 2.5% for Rule m  Set II for all of the three locations on deck. • In the case of 5[kn] vessel speed, the largest reduction in T  m  values occurred at  the mid ship with approximately 40% and 15% reduction for Rule Sets I and II for both of the operational-sea-states. This is important because amidships is usually the place where the bridge is located and some other work activities of the sort of cleaning and the transferring the of the catch occur.  Chapter  7.  SEAKEEPING  162  CONSIDERATIONS  Figure 7.50: Values of T (Equation 7.15), where T measures conditions to assess the ability of a crew member to maintain his balance (see page 38). Design-sea-state is 5 and operational-sea-state is 2; ship speed = 0.01[fcra]; midpoints of Echidna intervals were used. m  m  Chapter  7.  SEAKEEPING  CONSIDERATIONS  S CD  gP c«  40.0 20.0  S  0.0  CD  -20.0  f  -40.0 -60.0 -80.0 -100.0 40.0 S T E R N  20.0  E E-  0.0  CD  -20.0 -40.0  With Rule Set I  -60.0 -80.0  -A  /  With Rule Set H _L  -100.0 0.0  50.0  100.0  150.0  200.0  250.0  300.0  Hold Capacity [LT]  Figure 7.51: % Change in the values of T with respect to "Control case", in which was no seakeeping considerations, (for the data in Figure 7.50). m  Chapter 7. SEAKEEPING  164  CONSIDERATIONS  0.8 Kimura et al's threshold value (0.22) ^  0.6  <  =8=-  Control  s 0.2  -6  case  W i t h R u l e Set 1 Wijth R u l e ,Set LT  0.0  t o  !^ 0.06  E  Kimura et al's threshold value (0.22) <  e  X  0.10  X--  0.05 | — 0.00 0  50  100  150  200  250  300  Hold Capacity [LT]  Figure 7.52: Values of T (Equation 7.15), where T measures conditions to assess the ability of a crew member to maintain his balance (see page 38). Design-sea-state is 5 and operational-sea-state is 5; ship speed — 0.01 [kn]; midpoints of E c h i d n a intervals were used. m  m  Chapter  7.  SEAKEEPING  CONSIDERATIONS  Figure 7.53: % Change in the values of T with respect to "Control case", in which was no seakeeping considerations, (for the data in Figure 7.52). m  Chapter  7.  o.o  SEAKEEPING  0  166  CONSIDERATIONS  50  100  150  200  250  300  H o l d Capacity [ L T ]  Figure 7.54: Values of T (Equation 7.15), where T measures conditions to assess the ability of a crew member to maintain his balance (see page 38). Design-sea-state is 5 and operational-sea-state is 2; ship speed = 5[fen]; midpoints of Echidna intervals were used. m  m  Chapter  7.  SEAKEEPING  CONSIDERATIONS  167  Figure 7.55: % Change in the values of T with respect to "Control case", in which there was no seakeeping considerations, (for the data in Figure 7.54). m  Chapter  7. SEAKEEPING  168  CONSIDERATIONS  Figure 7.56: Values of T (Equation 7.15), where T measures conditions to assess the ability of a crew member to maintain his balance (see page 38). Design-sea-state is 5 and operational-sea-state is 5; ship speed = 5[fen]; midpoints of Echidna intervals were used. m  m  Chapter 7. SEAKEEPING  CONSIDERATIONS  Figure 7.57: % Change in the values of T with respect to "Control case", in which was no seakeeping considerations, (for the data in Figure 7.56). m  Chapter  7.  SEAKEEPING  170  CONSIDERATIONS  a E-1  Figure 7.58: Values of T (Equation 7.15), where T measures conditions to assess the ability of a crew member to maintain his balance (see page 38). Design-sea-state is 5 and operational-sea-state is 2; ship speed = 10[fcra]; midpoints of Echidna intervals were used. m  m  Chapter  7.  SEAKEEPING  CONSIDERATIONS  Figure 7.59: % Change in the values of T with respect to "Control case", in which was no seakeeping considerations, (for the data in Figure 7.58). m  Chapter  7.  SEAKEEPING  172  CONSIDERATIONS  Control  case  W i t h R u l e Set I W i t h R u l e Set H  Figure 7.60: Values of T (Equation 7.15), where T measures conditions to assess the ability of a crew member to maintain his balance (see page 38). Design-sea-state is 5 and operational-sea-state is 5; ship speed = lOffera]; midpoints of Echidna intervals were used. m  m  Chapter  7.  SEAKEEPING  CONSIDERATIONS  B c CD  s .s CD  a  fr->  a  gP CO  -a 100  150  H o l d Capacity  200  250  300  [LT]  Figure 7.61: % Change in the values of T with respect to "Control case", in which was no seakeeping considerations, (for the data in Figure 7.60). m  Chapter 8 SWATH MONOHULL COMPARISON  In this chapter, a comparison of monohull and SWATH type designs for the same hold capacity is presented. The unit costs per unit of displacement are assumed to be the same for both a monohull and a SWATH vessel [9]. Figure 8.1 displays the comparison of displacements, hence total costs are implied with the above assumption. In Figure 8.2, ratio of SWATH displacements versus monohull displacements are shown. Macgregor [47, p 5] reports that a SWATH and a monohull combatant displacement values differ by 30 to 60% (SWATH designs being the heavier one), and a SWATH would cost about 20% more than a monohull. These difference are lower than the ones found in the figures mentioned above. Bhattacharya [13, p 398] gives a comparison of heave and pitch motion amplitudes between a monohull and a SWATH vessel. Up to the ratio of (ship length/wave length) c. 1.8, the SWATH vessel's response is almost an order of magnitude less than that of the monohull. Considering the amount of improvement in monohull example designs reported above, Bhattacharya's findings suggest that SWATH concept has superior seakeeping characteristics. In another study, Cumming [28] reports the finding from a comparative seakeeping trial between a SWATH vessel M.V. Frederick G. Creed and a monohull vessel F.P.V. Louisbourg. The principal particulars of the two vessels are given in Tables 8.1 and 8.2. Some of the results from the sea trial are given in Table 8.3. Although the monohull F.P.V. Louisbourg is at least 3 times larger than the SWATH M.V. Frederick G. Creed 174  Chapter  8.  SWATH  MONOHULL  175  COMPARISON  Table 8.1: Principal particulars of the SWATH M.V. Frederick G. Creed (from [28]). Length over all Pontoon length Beam Full load draft Full load displacement Light ship displacement Maximum forward speed Complement  20 [m] 18.3 [m] 9.91 [m] 2.44 [m] 74.2 [tons] 55.9 [tons] 25.5 [kn] 5  Table 8.2: Principal particulars of the monohull F.P.V. Louisbourg (from [28]). Length over all Length between perpendiculars Beam (moulded) Depth Draft (maximum) Displacement Maximum forward speed Complement  38.1 [m] 31.7 [m] 8.23 [m] 3.40 [m] 2.49 [m] 247.06 [tons] 12 [kn] 11  in terms of their displacements (see Tables 8.1 and 8.2), generally the SWATH vessel shows comparable motion characteristic to the monohull F.P.V. Louisbourg (see Table 8.3). According to Cumming, "... there was a general consensus among the observers that the 'Creed' was the superior seakeeping platform relative to the monohull". This is an important observation in relation to fishing, as a SWATH vessel can offer a more comfortable platform for the crew. However, as Figure 8.1 suggest, a SWATH fishing vessel is almost as twice large as a monohull for the same hold capacity requirement. It should be noted that in monohull design in Echidna the aim was not to achieve the same seakeeping characteristics as a SWATH. If one is still to continue with the  Chapter  8.  SWATH  MONOHULL  COMPARISON  176  Table 8.3: Comparison of some of the significant motion characteristics between M . V . Frederick G . Creed and F . P . V . Louisbourg (from [28]).  Wave heading (degrees) 0 45 90 135 180 0 90 180  Forward speed (knots) 12 12 12 12 12 5 5 5  M.V. Frederick G Creed Roll Pitch Heave (degrees) (degrees) accel. (g) 3.2201 4.7178 0.0668 7.4474 8.2371 0.1236 5.0258 3.2415 0.1607 3.7182 3.9646 0.2217 1.6312 3.0755 0.2316 6.3533 6.5355 0.2048 7.3999 5.4146 0.2485 7.1862 6.1317 0.1791  F.P.V. Louisbourg Roll Pitch Heave (degrees) (degrees) accel. (g) 3.9391 3.1698 0.0405 12.5545 4.8151 0.1437 18.5344 3.8132 0.2176 18.1182 5.6987 0.3634 7.9494 7.0737 0.3914 11.9796 6.4274 0.1903 20.0605 6.7927 0.2738 16.6082 6.9605 0.2490  comparison, as Figures 8.1 and 8.2 suggest S W A T H might still cost c. 1.5 to 2.2 times more than a monohull.  Chapter  8.  SWATH  MONOHULL  1000  COMPARISON  177  — Monohull - Control case -O  Monohull - with Rule Set I Monohull - with Rule Set LT /  800  5  SWATH  600  S3  s jo  Q  400  200  -  0  50  100  150  200  250  300  Hold Capacity [LT] Figure 8.1: Comparison of the displacements of SWATH and monohull type of fishing vessels obtained using Echidna. For monohulls, Control case corresponds to the case in which there was no seakeeping considerations in the design. For SWATH designs, no seakeeping considerations were used during the design.  Chapter  8.  SWATH  MONOHULL  178  COMPARISON  - SWATH/(Monohull - control case) •  -1  i  -1  0  -e-  - S W A T H / (Monohull - with Rule Set I) S W A T H / (Monohull - with Rule Set II)  50  100  150  200  250  300  Hold Capacity [LTJ Figure 8.2: For the mid points of Echidna intervals, the values of the ratios (SWATH displacements over monohull displacements, for data given in Figure 8.1). Control case is the one, in which there was no seakeeping considerations in the design.  Chapter 9 CONCLUSIONS  In this study, the objective was to develop a design tool, which will allow some ergonomic considerations to be incorporated into the preliminary design offishingvessels. Considering the nonlinear nature of ship design, at the beginning of the author's research it was not known if it was possible to obtain a solution by increasing the number of criteria (equations and/or constraints) used in ship design. The study showed that by the inclusion of crew safety/comfort considerations in the ship design cycle and for an assigned design-sea-state, the design tool is able to find a solution. While the solutions might not be unique and depend on the criteria used in the crew safety considerations the results (see Chapter 7) suggest that: • Such crew safety considerations can be included in the preliminary ship design procedure. • For a specific design-sea-state and a set of owner requirements one can establish preliminary principal ship dimensions that will increase the crew safety/comfort. • 2 simple rule sets (Rule Set I on page 100 ( 7.2 to 7.5) and Rule Set II on page 134 ( 7.11 and 7.12)) that were developed and tested suggest that similar simple rules might be used to improve seakeeping. The results obtained so far suggest that a solution is obtainable using the procedure developed (algorithms and criteria developed for the UBC series hull forms) and as explained in thesis. This however does not limit the application of the process as UBC 179  Chapter  9.  CONCLUSIONS  180  Series hull forms can be applied to any small craft design. In the detailed results of incorporating some seakeeping considerations for crew comfort and safety (Rule Sets I and II), into ship design is presented in Chapter 7. The following conclusions are from the results presented in that chapter (considering the mid-points of the Echidna intervals): • The effects of introducing Rule Set I into the design are increases in displacement and costs of the designs. An approximately 25% on the average increase in displacements suggested up to 100 [LT] hold capacities. For the same hold capacity range the average increase in cost is also around 25%. The overall average increases that covers all hold capacity ranges are approximately 22% and 17% for displacements and costs respectively. • In the second group, Rule Set II produced an increase in displacements by up to 20% on the average up to 75 [LT] hold capacity. For larger hold capacities the average is around 5% for increase in displacements. The effects in the cost were similar to the case of displacements with roughly 30% and 10% average increases for 0 to 75 [LT] and 75 to 250 [LT] hold capacity ranges. • The example designs of SWATH type for the same hold capacity as monohull versions cost between 1.5 to 2.2 times more than an equivalent monohull design with some crew comfort criteria. However, the motion levels of the same SWATH vessel for a given sea conditions can be assumed superior to that of monohulls based on the information given by Bhattacharya [13] and Cumming [28].  Chapter  9.1  9.  CONCLUSIONS  181  Suggestions for Future Work  The rules used in Chapter 7 to improve seakeeping qualities are important in terms of demonstrating the concept. " What rules to use?" and "How many rules to use?" might be an interesting follow-up research in this area. A plausible extension to Rule Set I ( 7.2 to 7.5) might be to include the ratio between the amplitudes of the sea state's energy spectrum and the ship response spectrum at the peaks. Rule Set I define a frequency shift to higher frequencies. An alternative might be to attempt shifting the ship peak response frequencies to lower frequencies. This might be a more difficult case to obtain a solution, since there is a shift of the wave spectral peak towards lower frequency range for higher sea states. In Rule Set II ( 7.11 and 7.12), rms motion amplitudes were used. In these rules, only heave and pitch motion amplitudes were considered. The contributions of the roll motion to the overall motion characteristics of a ship (i.e. compound amplitudes, accelerations etc.) are also very important. However, roll motion is strongly dependent on the weight distribution in the vessel. In the thesis, the effects of roll motion were neglected. This was because the vessel is assumed to be heading into waves. In real life situations, there is not a pure head seas condition. A future research extension might be incorporation of roll motion considerations into the knowledge base for different scenarios (i.e. different headings and loading conditions). Furthermore, the following improvements to the current system might also be considered. • The empirical formulae used in the preliminary design of monohull and SWATH vessels could be improved. Especially for SWATH designs there is a need for some revisions.  Chapter  9.  CONCLUSIONS  182  • If the system is intended to be used in real design cases, clearly the cost information incorporated in the knowledge base may soon become obsolete. Therefore, the cost terms, e.g. unit material costs etc., in the knowledge base must be updated regularly. The current cost model is very simple and could be improved. • Currently, for comparison of the designs total building cost is used. However, NPV (net present value) could be a better term to compare two designs. This could be implemented in the knowledge base. However, the implementation of NPV has its own difficulties such as the prediction of income throughout the lifetime of the vessel. There are some techniques suggested in the literature for dealing with such uncertainties [59], [70]. However, one can postulate plausible income/cost streams into the future to see to what extend NPV's affect the design parameters derived with Echidna. • Development of possibly other seakeeping rules similar to the ones developed in the thesis. The number of crew comfort/safety rules should be increased. There could be additional rules related to motion accelerations and jerk levels. However, one problem with such rules is that their highly nonlinear nature makes it very difficult to come up with an estimating formula that is reasonably simple yet accurate enough. Including several such rules simultaneously may not be necessary as some of the rules might become redundant. • Layout design of ships seems the next logical step towards safer vessels. Detailed layout design could be a follow up research in this context. Need to develop a guidance manual for use by designers. • In view of the comments by Dorval [32] that a crew member is 15 times more likely to die due to an occupational accident, one future extension of this thesis might  Chapter  9.  CONCLUSIONS  183  be devoted estimating the life cycle savings obtained by reducing motion levels at sea and comparing them to the increased cost predicted for these boats. This will allow to quantify the crew comfort/safety in monetary terms from the owners point of view. • Extend the strategy developed in this thesis to SWATH ships and evaluate them economically.  Nomenclature  B  Ship's beam  Cb  Block coefficient  C  Prismatic coefficient  D  Ship's depth  p  F  Froude number (F =  g  Acceleration due to gravity (9.801 [m/s ] or 32.2 [ft/5 ]  H  Average wave height  if(i/3)  Significant wave height  #(1/3)5  Significant wave height for sea state 5  k  Wave number ( =  Lbp  Ship's length (between perpendiculars)  Loa  Ship's length (over all)  LT  Long tons (1016 [kg])  Li  Ship's length (water line)  n  n  V/Jg/L) 2  w  NHi/  z  2ir/(WaveJength))  Non-dimensional significant wave height {NHi/3  =  #1/3/^(1/3)5)  NPV  Net Present Value  OBO  Ore/Bulk/Oil carrier  rms  Root mean square  SES  Surface Effect Ship  T  Ship's mean draft  T  Average wave period for a given sea state 184  2  Nomenclature  T  max  The wave period that maximizes wave energy spectrum for a given sea state  V  Ship speed  z  Heave displacement  z  r m s  rms heave amplitude  z  Heave acceleration  6  Pitch displacement  6  Pitch acceleration  B ,  rms pitch amplitude  A  Wave length  A  Average wave length for a given sea state  w  Encounter frequency [rad/s]  Tm  oj  Non-dimensional encounter frequency (u> = u>/^Jg/T)  Umax  Frequency that maximizes the sea state's energy  n  n  spectrum [rad/s] ijJnz  p  Non-dimensional frequency that corresponds to the ship's peak heave response (see Appendix E)  u) e n  p  Non-dimensioned frequency that corresponds to the ship's peak pitch response (see Appendix E)  Bibliography  [1] H. Aasjord. And^ ya-prosjektet, - tiltaksplaner for 15 fart<£ yer. Technical report, FTFI Report, September 1984. [2] A. F. Aboulazm. Ship motion and crew safety with application to fishing vessel. In International  Symposium,  Safety  and  Working  Conditions  aboard Fishing  Vessels,  Actes Proceedings, pages 228 - 235, Quebec - Canada, August 1989. [3] S. Akagi and K. Fujita. Building an expert system for engineering design based on the object-oriented knowledge representation concept. In Proceeding of the 1988 ASME Design Technology Conference - the Design Automation Conference, number 14, pages 287 - 296, 1988. [4] A. Akinturk, M.Atlar, and S. M . Cah§al. Preliminary design of multi-hull fishing vessels using an expert system environment. In The Sixth International Symposium on Practical Design of Ships and Mobile Units, volume 2, pages 2.1288 - 2.1299, South Korea, September 1995. [5] K. Amagi and N. Kimura. A proposal to prevent occupational accidents in scallop beam trawlers. 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Multi-attribute decision making system based on random generation of nondominated solutions: An application to fishing vessel design, pages 2.1443 - 2.1459. [72] H . H . Zhou, B . G. Silverman, and J . Simkol. Cleer : An ai system developed to assist equipment arrangements on warships. Naval Engineers Journal, pages 127 137, May 1989.  Appendix A Echidna - Knowledge Base Environment  E c h i d n a is an expert system developed at Simon Fraser University's Expert Systems Laboratory.  It is described as a logic programming language embedded in an object  oriented framework  [60].  Some of its general features have been described earlier. In  this appendix, programming aspects is summarized. T h e E c h i d n a shell can perform computations on variables defined as real intervals (e.g. length = [50.0, 60.0]). Hence most of the solutions in this study were in form of real intervals. Echidna refines the intervals of variables by propagating constraints on them. Once a solution is reached, one can further refine a particular interval given by Echidna. This could be done either by additional constraints or asking the Echidna to refine specific variables randomly. T h e following hypothetical example is given to illustrate this point clearly. Example:  Lets design a hypothetical simple barge that can carry 25 [tons] of material.  For simplicity, we are only concerned if the barge floats at its design draft reading when loaded. Hence, the total weight of the barge should be equal to its displacement.  The  following equations are used to calculate relevant terms.  Hull  weight  Displacement Total  weight  PlateJthickness 1.025Length Cargo  + Hull  193  x Total-surf * Beam  *  weight  Draft  ace-area  (A.l) (A.2) (A.3)  Appendix  A.  Echidna  - Knowledge  Base  194  Environment  The following constraints are also used in the example.  0.97  Displacement  <  Total 2.0 2.0  Displacement  (A.4)  (Length/Beam)  <  5.0  (A.5)  (Beam/Draft)  <  5.0  (A.6)  weight < <  <  The knowledge base written for this example, run time commands issued in the Echidna shell and the corresponding example output are given at the end of this appendix. In Table A . l , the second column shows the initial intervals assigned to the design parameters, "unbound" means the parameter defined as a real interval variable, however, the initial interval is not defined explicitly. In the third column, when Echidna reached a solution, some of the parameter intervals shrank, some did not change and the previously "unbound" ones were assigned an explicit interval. However, these intervals are too large to define a barge explicitly. One can impose more constraints. The effect will be some (or all) of the intervals will be further shrunk (see the fourth column in the table). If the intervals given by Echidna are still not sufficiently small, Echidna can randomly selects "a" set of smaller parameter intervals that satisfy the design constraints given above, as is the case in the fifth column in Table A . l . In the following texts, the rest of the line after a % character is a comment. A schema is a definition of a class. It contains the description of the structure and composition of every possible instances of the class. A  class  is defined as "... a family of objects having the same structure and behaviour.  It describes a set of data and a set of procedures or functions." [48, page 16]. A class then has two parts, a static part, which are the fields holding the data, and a dynamic part, which represents the common behaviour of the objects, i.e. the procedures or the methods. The following example shows a class definition for rectangles.  Appendix  A.  Echidna  - Knowledge  Base  195  Environment  Table A . l : Refinement of intervals during the example barge design in Echidna Parameter Length [m] Beam [m] Draft [m] Depth [m] Freeboard [m] A [tons] Hull weight [tons]  Initial [1, 200] [1, 200] [1, 200] [1, 200] unbound unbound unbound  1st solution [1, 200] [1, 100.5] [1, 50.75] [1, 56.968] [0.115, 5.83] [1.02, 10052.4] [0.26, 9698.4]  For (L/B) > 4.95 [4.1, 200] [1, 41.42] [1, 21.21] [1, 24.32] [0.115, 2.44] [1.02, 3862.06] [0.26, 3689.4]  Randomly refined [11.445, 11.448] [2.360, 2.363] [1.030, 1.033] [1.14, 1.15] [0.123, 0.123] [29.19, 29.26] [4.19, 4.20]  Class { Rectangle  Fields Length Beam  Methods Area  =  LengthxBeam  Circumference  = 2 (Length  +  Beam)  Figure A . l : An example class definition for rectangles (the object in this example).  Appendix  A.  Echidna  - Knowledge  Base  196  Environment  The syntax of a schema is given as follows: schema name:superclass_name  •c the code that define schema instance v a r i a b l e s , method d e f i n i t i o n s , e t c . }  A.l  Run-time user commands '/, Load knowledge base f i l e "barge.kb" load barge.kb */, Define a schema v a r i a b l e of the type "weights"} weights V e s s e l l . '/. I n s t a n t i a t e the schema v a r i a b l e defined above} V e s s e l l i s a weights([25.0, 25.001] _Hold_l, '/, P r i n t the schema v a r i a b l e a f t e r  instantiation}  print (Vessell). '/, Access some of the schema instance  variables}  V e s s e l l : l e n g t h ( i n t e r v a l LWL). Vessell:beam_overall(interval  [0.97, 1.0] B a l l a s t _ l ) .  Beam).  Vessell:depth_of_vessel(interval  Depth).  Vessell:draft_of.vessel(interval Draft). V e s s e l l : f b o a r d ( i n t e r v a l Freeboard). V e s s e l l : l t o b ( i n t e r v a l Lwl_to_Beam) . V e s s e l l : b t o t ( i n t e r v a l Beam_to_Draft). V e s s e l l : b t o d ( i n t e r v a l Beam_to_Depth).  Appendix  A.  Echidna  - Knowledge  Base  Vessell:ttod(interval  Environment  Draft_to_depth).  Vessell:disp(Displacement). */, A d d i t i o n a l user defined run-time constraint '/, the  on  (length/beam) r a t i o  Lwl\_to\_Beam >=  4.95.  '/, P r i n t the schema v a r i a b l e i n order to see the e f f e c t s of '/, the constraint print  of the  (length/beam) r a t i o  Vessell  '/, Ask  the Echidna to randomly r e f i n e length, beam, d r a f t  '/, and  depth parameters  split(LWL, Beam, Draft, Depth),  precision(16).  '/, P r i n t the schema v a r i a b l e i n order to see the e f f e c t s of '/, random refinement of the parameters i n t e r v a l s print  Vessell  '/, Show the queries issued so f a r queries  A.2  Knowledge base for the  barge example  '/, General constants d e f i n i t i o n s ftdefine  density  7.8  '/, Density of s t e e l  7.8  [ton/nT3]  #define p i 3.141592654 '/, Sea water density ft3/longTon #define seadensft3LT 35.00458671  Appendix  A.  Echidna  - Knowledge  Base  Environment  '/, User defined types h u l l . m a t e r i a l = {aluminum, gear.type  steel},  = { s e i n e r , trawler}.  range_for.length  = [1.0,  200.0].  '/, Length i n m  range_for_beam  = [1.0,  200.0].  '/, Beam i n m  range.for.depth  = [1.0,  200.0].  '/, Depth i n m  range.for.draft  = [1.0,  200.0].  % Draft i n m  schema  barge  i 7, P e r s i s t a n t instance range_for_length  variables...  Length. '/, Length i n m  range_for_beam Beam.  '/, Beam i n m  range_for_depth Depth.  '/, Depth i n m  range_for_draft  '/, Draft i n m  Draft.  i n t e r v a l Freeboard.  '/, Freeboard i n m  '/, Non-dimensional parameters.. . i n t e r v a l LB. i n t e r v a l BD. i n t e r v a l BT. i n t e r v a l TD. '/, The f o l l o w i n g are i n long tonnes. interval  Hold.capacity.  i n t e r v a l HullWeight. i n t e r v a l TotalWeight. interval  Displacement.  Appendix  A.  Echidna  - Knowledge  Base  Environment  i n t e r v a l B a l l a s t . '/, As percentage of displacement  '/, Accessors. .. hold_capacity(Hold_capacity). length(Length). beam_overall(Beam). depth_of.vessel(Depth). draft_of.vessel(Draft). fboard(Freeboard). ltob(LB). btot(BT). btod(BD). ttod(TD). disp(Displacement). hullWeight(HullWeight). ballast(Ballast). }  schema  particulars:barge  •C '/, Instance i n i t i a l i z a t i o n methods. . . particulars. p a r t i c u l a r s ( H o l d _ c a p a c i t y ) :length(Length), beam_overall(Beam),  Appendix  A.  Echidna  - Knowledge  Base  Environment  depth_of.vessel(Depth), draft_of.vessel(Draft), freeboard(Freeboard), Draft =:= Depth - Freeboard, lb(LB), beam_to_draft(BT), beam_to_depth(BD), draft_to_depth(TD).  '/, Methods used to estimate i n i t i a l ship dimensions  y, order l b . lb(LB)  :-  LB =:= Length / Beam, LB >= 2.0, lb(LB)  LB =<  5.0.  :-  LB =:= Length / Beam, order  beam_to_draft.  beam_to_draft(BT)  :-  BT =:= Beam / D r a f t , BT >= 2.0,  BT =<  beam_to_draft(BT)  5.0. :-  BT =:= Beam / D r a f t . beam_to_depth(Beam_to_depth) : Beam_to_depth =:= Beam / Depth, draft_to_depth(TD)  :-  Appendix  A.  Echidna  - Knowledge  Base  Environment  TD =:= Draft / Depth, order freeboard, freeboard(Freeboard) :Freeboard =:= 0.115 * D r a f t . '/, from UBC s e r i e s models, freeboard(Freeboard).  >  schema  weights:particulars  i '/, Instance i n i t i a l i z a t i o n methods . . . weights(Hold_capacity, B a l l a s t ) :particulars(Hold_capacity), displacement(Displacement), hullWeight(HullWeight), totalWeight(TotalWeight), ballast(Ballast).  '/,  DISPLACEMENT  displacement(Displacement)  :-  Displacement > 0, Displacement =:= 1.025*Length*Beam*Draft.  '/. WEIGHT GROUPS '/. HULL WEIGHT  201  Appendix  A.  Echidna  - Knowledge  Base  Environment  hullWeight(HullWeight)  :-  i n t e r v a l Thickness =:=  (0.056*Length + 5.5)/1000.0,  i n t e r v a l Surface_area =:= HullWeight =:=  2.0*(Length*Beam+Beam*Depth+Length*Depth),  7.8*Thickness*Surface.area,  HullWeight > 0. '/.  TOTAL WEIGHT  '/. order totalWeight. totalWeight(TotalWeight)  :-  i n t e r v a l Sum_of.Weights =:= HullWeight + Hold_capacity, i n t e r v a l LowerLimit =:= B a l l a s t * Displacement, i n t e r v a l UpperLimit =:= Displacement, TotalWeight  =< UpperLimit,  TotalWeight >= LowerLimit, TotalWeight =:= Sum_of.Weights. }  A.3  A sample output for the barge example  Echidna Version 0.947 beta Compiled: Thu Nov 25 14:42:16 PST 1993 (c) Copyright I n t e l l i g e n t  Systems Lab.  Simon Fraser U n i v e r s i t y , 1991, A l l r i g h t s reserved  1993  Appendix  A.  Echidna  - Knowledge  loading data base f i l e  Base  Environment  "rina.db" . . .  weights.O = { range_for_length Length = [1, 200]. range_for_beam Beam = [ i , 100.5]. range_for.depth  Depth = [1, 56.96875].  range_for_draft  Draft = [1, 50.75],  i n t e r v a l Freeboard = [0.115, 5.836948]. i n t e r v a l LB = [1.994697, 5.003655]. i n t e r v a l BD = [0.01755348, 100.5]. i n t e r v a l BT = [1.998462, 5.000922]. i n t e r v a l TD = [0.01755348, 50.75]. i n t e r v a l Hold_capacity = [25, 25.001]. i n t e r v a l HullWeight = [0.260004, 9698.486]. i n t e r v a l TotalWeight = [25.25999, 9723.487]. i n t e r v a l Displacement = [1.024969, 10052.48]. i n t e r v a l B a l l a s t = [0.97, 1], }weights.0 = { range_for.length Length = [4.109375, 200]. range.for_beam Beam = [1, 41.42188]. range_for.depth Depth = [1, 24.32031]. range_for_draft  Draft = [1, 21.21094].  i n t e r v a l Freeboard = [0.115, 2.439956]. i n t e r v a l LB = [4.948725, 5.003655]. i n t e r v a l BD = [0.03901885, 41.42425]. i n t e r v a l BT = [1.998462, 5.000922]. i n t e r v a l TD = [0.04077695, 21.21129].  Appendix  A.  Echidna  - Knowledge  Base  Environment  i n t e r v a l Hold_capacity = [25, 25.001]. i n t e r v a l HullWeight = [0.260004, 3689.481]. i n t e r v a l TotalWeight = [25.25999, 3715.073]. i n t e r v a l Displacement  = [1.024969, 3862.061].  i n t e r v a l B a l l a s t = [0.97, 1]. }  weights.O = { range_for_length  Length = [11.68544, 11.68848].  range_for.beam Beam = [2.360352, 2.363388]. range_for_depth Depth = [1.148788,  1.151825].  range_for_draft  1.033401].  Draft = [1.030365,  i n t e r v a l Freeboard = [0.118492, 0.1188412]. i n t e r v a l LB = [4.95, 4.952007]. i n t e r v a l BD = [2.049228, 2.057288]. i n t e r v a l BT = [2.28406, 2.293739]. i n t e r v a l TD = [0.89455, 0.8995577]. i n t e r v a l Hold_capacity = [25, 25.001]. i n t e r v a l HullWeight = [4.197202, 4.206248], i n t e r v a l TotalWeight = [29.19718, 29.20726]. i n t e r v a l Displacement  = [29.19546, 29.26168].  i n t e r v a l B a l l a s t = [0.97, 1 ] .  done #0 . done #1 V e s s e l l i s a weights, Vessell:weights(_Hold_l,  Ballast_l).  204  Appendix  A.  Echidna  - Knowledge  Base  Environment  done #2 p r i n t ( V e s s e l l ) . done #3 Vessell:length(LWL). done #4  Vessell:beam.overall(Beam).  done #5  Vessell:depth_of.vessel(Depth).  done #6  Vessell:draft_of.vessel(Draft).  done #7 Vessell:fboard(Freeboard). done #8 Vessell:ltob(Lwl_to_Beam). done #9  Vessell:btot(Beam_to_Draft).  done #10  Vessell:btod(Beam_to_Depth).  done #11  Vessell:ttod(Draft_to_depth).  done #12  Vessell:disp(Displacement).  done #13 Lwl_to_Beam >= 4.95. done #14 s p l i t ( L U L , Beam, D r a f t , Depth), done #15  precision(16).  i n s i d e echidna 33>  Appendix B Monohull Design Algorithms  The following design formulae are originally developed by Calisal and McGreer [24]. The units for linear dimensions and weight groups are feet and [LT] respectively. B.l  Linear Dimensions  Cubic Number (N ): c  N  c  N  c  =  (Hold  Capacity  + 28.496)/l. 1313  (if  hull  material  is  =  (Hold  Capacity  + 15.395)/0.6606  (if  hull  material  is steel)  License Length  (L  (B.l)  ):  licence  Licence = Speed, /1A  (B.2)  2  Length estimate based on hold capacity X i = 3.3 (28.5  (Li):  Holdcapacity)  c  L = (100 N (4)  ^)  2  2  c  (B.3)  03669  Length estimate based on (L/B), (B/D) and N  Waterline length  aluminum)  B  0 3 3 3 3 3 3  D  (L ): 2  +5  (B.4)  (LWL)'-  LWL = smaller  of  206  (Li ,L ) icence  2  (B-5)  Appendix  B.  Monohull  Design  Algorithms  Length between perpendiculars  (LBP)I  i-'WL  LBP  Length over all  207  (B.6)  1.066  (LOA)'LQA — 1.066  (B.7)  LWL  Beam over all (B): B  >  B  <  LLW  JLW  (B.8)  0 . 0 1 7 7 W + 1.690323  Depth (D): D  <  -^-^  D  < ~  —— 2.2  (if  hull  material  is  (if  hull  material  is  w  aluminum) steel) '  (B.9)  Draft (T):  T  Freeboard  <  D-Freeboard  (based on U B C series model data):  Freeboard  §  (L =  (B.10)  = 0.1157/  (B.ll)  LWL)-  — = 0.017742 L  X  B  + 1.690323  (B.12)  Coefficient C„ C  m  —  LWL  B  100  D  (B.13)  Appendix  B.2  B.  Monohull  Design  208  Algorithms  Weight Estimation  A more detailed description of the formulae given below can be found in [25]. Hull Weight W, (New Brunswick Department of Fisheries): These equations determine the weight of hull, deck and deckhouse in [LT] for both steel and aluminum construction.  W — k 0.00002813(x - 173.52a; + 41880a; - 0.0000158) 3  (B.14)  2  a  where k = 1 for steel, and k= 0.55 for aluminum.  a  _ 0 (MB±m i 1  O  V  3000  /  v  (B.15) ;  Outfit Weight W : 0  This weight includes the joiner work, interior, piping, and miscellaneous equipment.  W = 0.25 L 0  W  L  B  (B.16)  Machinery Weight W : m  This weight includes the main engine, gear box, shafting, and the propeller.  where C is the cubic number C — ^ f ^ p n  n  Stores Weight W : w  The stores weight includes the fuel, water, water ballast and provisions.  W  w  = 3.618L - 39.03  (B.18)  Appendix  B.  Monohull  Design  Algorithms  209  Gear Weight W : a  For a seiner vessel the gear weight includes the net and the skiff, W  g  = 7.23  and for a trawler the gear weight includes the net and wire rope.  W  g  = 3.05  Hold capacity: F i s h , ice and storage containers in hold. T h e Echidna program balances the displacement of the vessel with the sum of the various weight groups. T h e constraint that the displacement must be greater than the weight determines the ranges for the principal dimensions of the vessel.  B.3  Resistance and Powering  T h e next step i n the Echidna system is the determination of the calm water resistance for the vessel. T h e Echidna program utilizes a resistance algorithm developed for the U B C Series. This algorithm is based on regression analysis of model test data of the series. T h e algorithm is based on an equation developed by Oortmerssen for small vessels.  C  r  = de  + Ce  9  2  + Ce * 3  sin F  2 n  + C e 'S cos F 4  2  (B.19)  where  Ci = di, + di ji 0  and  tl  + d  i>2  (I)  + 4, | + d 3  iA  (|)  (B.20)  Appendix  B.  Monohull  Design  210  Algorithms  Table B.l: Coefficients for UBC Series Resistance Algorithm for C\> = 0.615 i difl di,i di,2 di,3 di,i  1 0.074654 0.001879 -0.000701 -0.05158 0.009871  2 0.076958 7.7 x 101.8 x 10-0.005247 0.000572  3 -0.000162 7.4 x 10~ 0.000907 -0.001137 -0.000661  5  5  5  m = 0.14347C"  4 -0.018642 1.05 x 100.000119 -0.001944 0.001169  5  21976  (B.21)  with C defined as the prismatic coefficient of the vessel. p  The coefficients, diwere  determined from regression analysis of model test data for  the UBC Series. An example set of coefficients for one block coefficient, Cb=0.615 are given in Table B . l . Once the wave resistance coefficient, C , is determined, the total resistance coefficient P  of the vessel, Ct, is determined by the addition of the frictional resistance coefficient, Cj, which is based on the Reynolds number, ft, of the vessel, and an allowance of 0.0004 to account for the roughness of the vessel. The frictional resistance is given by: 0.075 (log  ft-2)  2  (B.22)  and  C = C + C + 0.0004 t  r  f  The total resistance of the vessel, R, is estimated from the standard equation:  (B.23)  Appendix  B.  Monohull  Design  Algorithms  211  R = C \pSV  (B.24)  2  t  where p is the water density, V is the vessel speed, and S is the wetted surface area of the vessel.  B.4  Stability  T h e center of gravity of the vessel is calculated and compared to maximum center of gravity criteria developed for the U B C series. T h e stability criteria used in the knowledge base was developed for the U B C Series  [25].  T o calculate the center of gravity of the vessel, the center of gravity of each weight group is estimated by the following equations. T h e value ^jj- is the ratio of the height of the center of gravity above the baseline of the vessel to the overall depth of the vessel. T h e equations for hull weight and outfit were adjusted by adding 0.05 and 0.15 respectively to give a lightship center of gravity closer to those measured by the inclining tests of 10 typical vessels  [25].  T h e center of gravities for the weight groups as follows:  Hull Weight:  f  = ^°- m  < B' 25>  Outfit Weight:  4? D  =  8820  + 1-19  v  (B.26) '  Machinery Weight:  D  1309000  1  '  Appendix  B.  Monohull  Design  212  Algorithms  Stores Weight: KG  —  = 0.75  (B.28)  =jf- = 1.66  (B.29)  = 0.60  (B.30)  Gear Weight: KG  Hold Weight:  B.5  Cost Estimation  Hull Cost [Can. $]:  HulLcost  =  11064 W,  Hull-cost  =  4155 W  s  (if hull material is aluminum) (if hull material is steel)  (B.31)  Outfit Cost [Can. $]: Outfit-cost = 120-OL^  (B.32)  SHP = EHP/(0.97 * 0.58)  (B.33)  Machinery-cost =:= 250 SHP  (B.34)  Shaft horse power [HP]:  Machinery cost [Can. $]:  Appendix  B.  Monohull  Design  213  Algorithms  Fuel consumption [Gallon/hr]: GalJir  (B.35)  = ^SHP  Fuel cost [Can. $]: Fuel-cost  =  J °°, GalJir 5  2.5  (B.36)  Speed  Gear cost [Can. $]: Gear-cost  =  200000  (B.37)  Capital cost [Can. $]: = 1.3221 (Hull-cost  C apital-cost  + Outfit-cost  + Mach-cost  + Gear-cost)  (B.38)  Morgage cost [Can. $]: Mortgage-cost  =  Interest  rate  Capital  cost  ——-  (B.39)  Depreciation cost [Can. $]: Depreciation-cost  = 0.045  (B.40)  Capital-cost  Insurance cost [Can. $]: Insurance-cost  = 0.020  Capital-cost  (if  Capital-cost  Insurance-cost  =  0.015  Capital-cost  (if  500000 <  Insurance-cost  =  0.010  Capital-cost  (if  Capital-cost  <  500000)  Capital-cost  <  > 2000000)  2000000) (B-41)  Total cost [Can. $]: Total-cost  = C apital-cost  + Mortgage-cost  + Depreciation-cost  +  Insurance-cost  (B.42)  \  Appendix C SWATH design algorithms  In the preliminary S W A T H vessel design knowledge base the algorithms given in [47] and [9] have been used. The algorithms given in this appendix are derived from the available data published in the literature by Macgregor[47] and Atlar and Guner [9].  T h e data given in [47]  suggest that a variety of S W A T H vessels' (from fishing vessels to patrol boats) principal particulars were included in the data. Therefore, the accuracy and range of applicability of the following algorithms depend upon the reliability of the data from which these algorithms were derived.  C.l  Linear Dimensions  T h e first step in the S W A T H fishing vessel design is to estimate the principal dimensions. T h e following estimating formulae are given in detail in [47, 9] :  Overall length ( L Q A ) :  LQA = 5.33A3  (C.l)  Length between perpendiculars ( L B P ) :  L  B  P  = 0.886LQA -  Overall beam (BOA) :  214  0.47  (C.2)  Appendix  C. SWATH  design  215  algorithms  BOA = 3.05[A3]°-  with  972  1.1 < ^ A3  < 3.3  (C.3)  Draft (T)  0.588[Ai] -  972  T = 0.583[A3] -  917  T =  0  0  Circular  hulls  Non - circular  hulls  Depth (D) D —B  c  (C.4)  +T  Also,  DWD  = 0.833A 3  DMD  =  1.167A " 3  to to  wetdeck  (C.5)  maindeck  (C.6)  Or,  DWD = 1.55T DMD  = 2.10T  to to  wetdeck  (C.7)  maindeck  (C.8)  Box clearance (Be) : Be  = 0.041 + 0.038F  n  (C.9)  Freeboard freeboard  =  0.134 + 0.593As  (CIO)  Appendix  C.  SWATH  design  216  algorithms  Lower Hull (LH) Dimensions Lower hull cross section characteristics :  Circular  hull  :  Diameter  = 0.134 + 0 . 5 9 3 A s  DIA  LH  (C.ll)  Non  — circular  hull  :  Non  — circular  detph  DJJ = 0 . 8 3 3 A '  (C.12)  Non  — circular  hull  :  Non — circular  beam  Bg = 1 . 1 6 7 A  (C.13)  5  Length of lower hull L H :  Long  strutted  Short  strutted  L  H  = 0 . 9 3 1 I O j 4 - 0.91 LH — LOA  (C14) (C.15)  Lower hull cross sectional area A H :  Non-  Circular  hull  A  = 0.0124L^  6 7 6  (C.16)  circular  hull  AH = 0 . 0 1 8 2 L #  6 5 4  (C.17)  H  Lower hull prismatic coefficient C p : H  C  PH  = 1- 0.333^ - 0.467^ LH  LH  Where LH is lower hull length, LT is tail length, and Xjy is nose length (Lg = LT + Lparallel-body +  ).  (C.18)  Appendix  C.2  C.  SWATH  design  algorithms  217  Strut(S) Linear Dimensions  Length Ls :  Long  strutted  Short  strutted  L  s  = 0.21 + 0 . 9 0 3 L x O  L  s  = 0.75L A O  (C.19) (C.20)  Thickness ts : For  single  struts  :  t  s  = 0.149As  (C.21)  Strut coefficients : Waterplane area coefficient, (Cw) :  C  w  = 1.0215^ - 0.333^  (C.22)  Slenderness coefficient (^-) : Long  strutted  = 0.02 • • • 0.04  (C.23)  Short  strutted  = 0.03 • • • 0.05  (C.24)  Strut setback ratio (f^ -) : v LOA ' 8  S  s  ~0.07  (C.25)  •>OA  C.3  Weight Estimation  Structural weight (Ws) '• In [47] gives following formulae for the overall structural weight (Ws) versus displacement  Appendix  C. SWATH  design  218  algorithms  ratio. Mild  = 0.425 - 1.75 * 10~ A  (C.26)  ^  = 0.417 - 8.5 * 10~ A  (C.27)  ^  = 0.388 - 3.11 * 10 A  (C.28)  6  steel  Hybrid Aluminium  6  _5  where Ws and A are in tons. It has also been noted that aluminum and hybrid designs are limited to vessels of less than 6000 tons, which is not of any particular concern in our case.  Machinery weight (WM) High  '• = 0.007Pjif  [tons]  (C.29)  WM  = 0.00113Pflf  [tons]  (C.30)  WM  = 0.543-P^  [tons]  (C.31)  speed diesel machinery  Medium  WM  speed diesel machinery Diesel  electric  machinery  679  where PM is the installed power at 900 fixed RPM and is in metric HP.  Auxiliary system weight W  AUX  (WAUX)  •  = 0.147A-  0002  [tons]  (C.32)  Outfit weight (Wo) : = 0.1890.147A"  0119  (C.33)  [tons]  Fuel weight (WF) : W  F  = (WFM + W  FC  + W )(m FG  + 1)  [tons]  (C.34)  where m is the margin for extra time and the trapped fuel in the tanks. WFM is the fuel required at the design speed and given by  Appendix  C. SWATH  design  W  219  algorithms  = ^-{PMSFCM)10-  (C.35)  [tons]  6  FM  V  M  Wpc is the fuel required at the cruise speed and given by P-C , „  W  r,^,-,  X  = -^{PcSFCc^O' vc  FC  6  1  „ _  6  [tons]  (C.36)  WFG is the fuel required for generator and given by W  FG  = [^  + ^](P SFC )lO-  [tons]  6  G  VM  G  (C.37)  VC  In the above equations : are design and cruise speeds in knots respectively,  VM,VC  P-MiRc are operational requirements of range in nautical miles for the design and cruise conditions respectively, are required propulsive power in [kW] in design and cruise conditions  PMIPC  respectively, PQ is the average generating load required by the vessel services and given by P  = 0.25(1.002A°- )  [kW]  924  G  In the following equations (C.39,C.40), SFCM,C,G  (C.38)  are specific fuel consumptions in  [ Ballon 1  In the case of • High speed diesel (direct and electric drive) : SFCM.C  =  200  if  SFC ,c  =  250 -  if P Ps « m [kW] TI.M71 if < 1 1810  M  Medium speed diesels  905 2  P > 1810  [Kw]  (C.39)  Appendix  C. SWATH  design  220  algorithms  SFCMC  =  178  if  P > 11190 [Kw] L  SFC ,c  =  M  230 -  J  (C.40)  if P < 11190 [kW]  In equations C.39 and C.40, P is the total required mover power in [kW] at cruise or design speed. And, for  SFCG  '•  SFC  G  Stores Weight  (W to)  210  (C.41)  :  S  Wsto = W  Prov  Provisions weight (Wp )  =  + Was + W  FW  [tons]  (C.42)  :  rov  W  Prov  = 0.005 {NC)  + ^]  [tons]  (C.43)  Where NC is number of crew and 0.005 is the required provisions per person per day in tons. General stores weight (WGS) '• W  GS  = 0.0011 (NC)  + ^] VM  [tons]  (C.44)  [tons]  (C.45)  VC  Fresh water (WFVT) : W  FW  = 0.125 {NC)  VM  +7^] VC  Equation C.45 is valid if (WFW < 50 [tons]). In the case of (Wpw > 50 [tons]), a distillation plant will be necessary.  Crew and effect  (WCREW)  '•  WCREW  =  0.143  (NC)  That is 7 crew member with effect represent 1 ton.  [tons]  (C.46)  Appendix  C.  SWATH  design  Design margin ( W  221  algorithms  ) :  marfltn  W  = 0.0755 W %  5  margin  Ug  [tons]  (C.47)  Where WugHt = W + W s  C.4  M  +W  AUX  + Wo  [tons]  Resistance and Powering  Installed Power ( P M ) : In the preliminary design stage the installed power is estimated [47] by PM =  {SM + 1)  [kW]  (C.48)  n  Where RT  :  total resistance [kN]  VM  :  design speed [m/s]  SM  :  percentage service margin  •q  :  overall propulsion system efficiency  For preliminary calculations SM  =  0.15 and n = 0.70  are assumed. Total Resistance (RT) : Total resistance is given as the summation of frictional (RF), (RAP),  and aerodynamic drag R  T  (RAA),  residuary (RR), appendage  all in [kN].  = RF + RR + RAP + RAA  [kN]  (C.49)  Appendix  C. SWATH  design  222  algorithms  Frictional Resistance (RF) : The following formula is given for frictional resistance [9] : R F - = \ P  (C  F  + C) A  [kN]  S V  M  (C.50)  Where P  density of water (for sea water, it is approximately 1025 [j^])  CF  frictional resistance coefficient  C  correlation allowance  S  wetted surface area [m ]  A  2  CF is calculated using ITTC formula of 0.075 C  And Reynolds number  f  ~ (lo  g l o R n  -2)  2  (  C  -  5  1  )  is VM LOA Kn =  v  with kinematic viscosity u = 1.19a;10 \ ~ \ for 15°C sea water. _6  Correlation allowance coefficient C is approximately 0.0005 [47, 9]. A  Wetted surface area is given by Equation C.52, and if lowerhull slenderness ratio is approximated to |j w 14, Equation C.53 can then be used instead [47, 9]. S = V» [13.6 - 0.31(20 - ^)] [m ]  (C.52)  S = 11.74 V f [m ]  (C.53)  2  2  Residuary Resistance (RR) : RR = \p  (GFF + C ) S V w  M  [kN]  (C.54)  Appendix  C. SWATH  design  223  algorithms  Where p  :  density of water (for sea water, it is approximately 1025 [^])  CFF  '  form resistance coefficient and approximated to 0.0005 [47, 9]  Cw  '• wave making drag coefficient  S  :  wetted surface area [m ] 2  However, a new term CR, which is the summation of CFF and Cw, is introduced into Equation C.54 and calculated by the regression formulae (See Table C.l) based on the analysis of the available SWATH data [47, 9].  Table C.l: Residual drag coefficient as a function of volumetric Froude number. CR  0.003 rp 0.688 • "  0 < F < 0.688 n  0.688 <F <  0.865  0.865 <F <  1.300  n  n  1.300 < F < 1.808 n  F  n  >  = Cpp + Cw r  0.003 -  (F - 0.688)  0.001 + S  ( F - 0.865)  n  n  0.005 - S g (F - 1.300) n  1.808  0.002  Appendage Resistance (RAP) : RAP  =  0.15  {R  F  + R) R  [kN]  (C.55)  Appendix  C.  SWATH  design  224  algorithms  Aerodynamic Resistance (RAA) : RAA  = \  PairC A V D  F  [kN]  M  (C.56)  Where Air drag coefficient : CD — 0.7  C.5  Frontal area :  A  — QML  Density of air :  p  = 1.293  F  air  [m ] 2  OA  [^]  Cost Estimation  For comparison purposes, it has been suggested that the unit cost per unit displacement is the same in both monohull and SWATH vessels [9].  Appendix  C.  SWATH  design  225  algorithms  Super sturcture II. Super sturcture I  Main deck Wet deck  . ±iauQcn_regjarL. Strut Lower hull  H OA  Super sturcture II Super sturcture I Main deck BOX (cross structure) Wet deck THaunch i l  K  _SZ_  Strut  Strut  Lower hull  Lower hull  A  Figure C.l: Schematic of a SWATH vessel  A  Appendix D Prediction of a vessel's heave and pitch motions  Howard [23] analyzed data obtained from the model testing of UBC series models at the Ocean Engineering Centre at BCR Corp. in British Columbia. After a statistical analysis, the following equation is given for a UBC series type of vessel's response spectrum.  1  1  +  e  ( a - * « . )  8  1 + e^-i"')  ^ '^ D 1  Where n is the non-dimensional heave or pitch amplitude, z /£ a  a  and 9 /{k£ ) a  a  respec-  tively. The coefficients in the above equation are as follows: For heave : A  =  0 . 8 5 9 1 ^ ^ + 1.5804^  (D.2)  a  =  1.816 + 3 1 . 4 2 ^  (D.3)  S =  16.48-^- 0.7485-^Lpp  (D.4)  t> B 0  8  =  6.436^^ + 163.1^^  (D.5)  7  =  2.870^^+40.36^  (D.6)  i . i 3 i 3 ^ H ? ! + o.9264^|  (D.7)  B  B  z  For pitch A a  =  =  C T  0.7904 + 45.47-^Lpp  226  (D.8)  Appendix  D.  Prediction  of a vessel's heave and pitch motions  5 = 16.82-^- - 0.8621-^— Lpp  8  =  18.34^^+37.35^|^  (D.10)  7  =  7.211^^+3.039^  (D.ll)  if  D  Lpp  Length between perpendiculars  B  Beam  Cb  Block coefficient  F  Froude number -- V/ J*L^g  g  Gravity  k  Wave number (2ir/(Wave  T  Mean draft  V  Velocity  z  Heave amplitude  a  6  Jength))  a  Pitch amplitude  a  Wave amplitude  e  Nondimensional encounter frequency  £ u  (D.9)  Cblj  In the above equations the following notation is used:  n  227  scaling factor for u> is j'Lpp/g e  Appendix E Frequencies of Peak Heave and Pitch Responses  Based on the formulation given by Howard (see also Appendix D), a number of heave and pitch response spectrums have been generated by systematically varying the parameters used in Equation D . l (Appendix D). Using the data obtained in this analysis, the following empirical formulae have been developed for the Echidna knowledge base. More complex estimation models (such as ones involving exponential etc.) have been avoided for the sake of simplicity and ease of use in the Echidna knowledge base.  ^  (38.8668 - 11.5286C - 5.2002^ - 1.1912§)  2  2  6  (0.8652 - 0.2816F„) (49.6354 - 20.4321C - 6.8076^ + 0.644lf ) 2  2  (E.l)  b  (2.4541 - 0.7280C - 0.3283^ - 0.0752f f  2 W n $ p  b  ~ (0.9481 - 0.3086F ) (2.8599 - 1.1773C* - 0.3922^ + 0.037lf ) 2  2  n  Where u>  n2p  and  are non-dimensional circular frequencies that maximize ship re-  uj e n  p  sponse spectrum for heave and pitch motions respectively.  a;u z n  p  or uj  n6p  -  or we p  (E.3)  In Equation E.3, u> or u>e are dimensional [radians/second] circular frequencies that Zp  p  maximize ship response spectrum for heave and pitch motions respectively, g is the gravitational acceleration, and T is the mean draft reading.  228  Appendix F  R M S Heave and Pitch Responses  In order to be able to estimate some of the rms motion characteristics of UBC series models, SHIPMO - a ship motion estimation program, was used.  Table F . l : Sea state information. [Sabuncu, 1983] Sea State 1 2 3 4 5  H  [m] 0.18 0.55 0.88 1.55 2.40  #1/3  [m] 0.30 0.88 1.40 2.45 3.65  T[s]  2.4 3.9 4.6 5.7 6.8  Tmax [s]  3.4 5.4 6.5 8.1 9.7  A[m] 6.1 15.9 21.6 34.0 49.0  Table F.2: Scaling factors for the raw regression data obtained from the software SHIPMO Motion Heave Pitch  Non-dimensionalizing scaling factor # 1 / 3  u> H /g 2  1/3  After a regression analysis on the data obtained from the runs of SHIPMO for 13 UBC series models the following empirical formulae have been developed. The same ranges as the ones used in the Echidna knowledge base are valid for the parameters used in Equations F . l and F.2.  229  Appendix  F. RMS Heave and Pitch  230  Responses  F  = 0.17244257 - 0.10902408-?- - 0.062345772(- -)  F  = 0.92116235 + 9.26182543-  F  = 1.25445302 + 0.015068303C(,  F  = 0.37459542 + 0.33475563F + 0.69543449F, - 0.62937284F  F  = 0.51156287 + 1.67664716-^- - 0.60058403(-^-) + 0.065781060(-^-)  F  = 1.27331482 - 1.02535654(7V# /3) + 0.56388486(/v"# )  B  zl  Lbp T  z2  Lbp T  17.01219503(—)  2  Lbp  z3  2  Lbp  2  zi  3  n  2  z5  Lbp  3  Lbp  Lbp  2  z6  1  TP TP  TP  r  — r \r  z  z  =  Hi/  TP  TP  r r f  z2  z3  zi  1/3  TP TP  rQ  z5  z  F + 0.74616424F - 0.46955309F 2  z  (F.l)  3  Z  yl/3  yl/3  Fi 0  = 0.465143 -2.343704-—+3.482758(-—)  F  02  = 1.323205 + 13.947877-^- - 26.389156(-^-)  Fez  = 0.346817 - 24.620275-^- + 37.557687(-^)  F  = 0.044729 + 1.003151C(,  F  = -0.182212 - 0.296472F + 0.059477F - 0.245965F,  Lbp  2  Lbp  2  6A  Lbp  Lbp  2  Lbp  Lbp  3 2  65  n  n  Fee = -0.181446 + 4.924184-^- - 0.834965(-^-) + 0.074877(-^-) 2  Lbp  F  rp  Hx/^ lg max  Lbp  Lbp  = 2.16213525 - 2.78020823(^/3)+ 1.54756589(/Vif )  2  e7  Br  3  1/3  TP  TP  TP  TP  TP  TP TP  •• F - 0.46697339F, + 0.56576473F/ 2  9  (F.2)  

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