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Analysis of a high temperature fouling unit for heavy hydrocarbon fractions Simard, Martial 2000

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ANALYSIS OF A HIGH T E M P E R A T U R E FOULING UNIT FOR H E A V Y H Y D R O C A R B O N FRACTIONS  By Martial Simard B . A . Sc., Uuiversite Laval, 1996  A THESIS SUBMITTED IN PARTIAL F U L F I L L M E N T O F T H E REQUIREMENTS FOR T H E D E G R E E O F M A S T E R OF APPLIED SCIENCE  in T H E F A C U L T Y OF G R A D U A T E STUDIES D E P A R T M E N T O F CHEMICAL AND BIO-RESOURCE ENGINEERING  We accept this thesis as conforming to the required standard  T H E UNIVERSITY OF BRITISH COLUMBIA  March 2000 © Martial Simard, 2000  In  presenting  degree freely  at  this  the  available  copying  of  department publication  thesis  in  partial  fulfilment  of  University  of  British  Columbia,  I agree  for  this  thesis  or of  reference  by this  for  his  and  scholarly  or  thesis  study.  her  for  I further  purposes  Department  of  C  H EM I CAL  The University of British Vancouver, Canada  Date  DE-6 (2/88)  Mr\GCh\  3f  &M6> A V ^ g g / A f c  Columbia  ^  __.Q0O  It  gain shall n o t  permission.  requirements that  agree  may  representatives.  financial  the  be is  that  the  Library  permission  granted  by  understood be  for  allowed  an  advanced  shall for  the that  without  make  it  extensive  head  of  my  copying  or  my  written  Abstract  W i t h the depletion and increase i n the price of light crude oil, the conversion of heavy oils and bitumens into distillable fractions i n upgrading units has become an important source i n meeting the demand for fuels and petrochemical products. Fouling, or the deposition of any undesirable material on heat exchangers surfaces, is a costly operational problem in conventional refineries because it increases the resistance to heat transmission and flow. T h e precipitation problem is worse w i t h heavy petroleum streams because of the higher concentration of fouling precursors such as asphaltenes and polar heteroatomic species and the higher temperatures of processing required to convert the high molecular weight components.  A t temperatures above 300°C, heavy o i l streams undergo thermal  decomposition or free-radical reactions which lead to the formation of coke defined as toluene insoluble carbonaceous solid which fouls processing units. In order to design and operate upgrading units w i t h m i n i m u m coke deposition, the chemical, thermal, and fluid mechanical factors causing the problem must be known. A research project which involved kinetic and thermal fouling studies on p i t c h , gas oils, and their blends was initiated to generate such information. A s part of this research, a recirculation flow loop had been constructed to study coke deposition during flow through a vertical tube placed i n an electrically heated  fluidized  bed.  T h e present work was  conducted to develop the apparatus, to analyze its behaviour, to evaluate the tendency of pitch-gas oils blends to form coke and to assess the capability of the unit to detect it under the appropriate conditions of bulk and surface temperatures. A series of fouling experiments was carried out by recirculating a 50:50% vol. pitchcoker heavy gas oil blend over 11-56 hour periods w i t h average bulk fluid temperatures of 200-375°C, tube side velocities of 0.3-2.2 m / s (laminar flow), and average fluid bed temperatures i n the range of 500-615° C. A number of improvements to the high-temperature unit were made to reach the desired temperature conditions, to provide the necessary measurements for adequate interpretation of results, and to increase the quality of the data. In order to determine the flow regime and to account for possible viscosity changes ii  during recirculation, the density of the above mixture and the viscosity of pitch, gas oils, and their blends were measured over a wide range of temperatures. Additional tests were performed to monitor the viscosity change during recirculation of the test fluid and also the change in the amount of toluene insolubles in the 50:50% vol. pitch-heavy gas oil blend. Coke deposition was determined by mass deposition and by thermal measurements. Interpretation of the latter was made by use of different data analysis techniques and of empirical correlations found between process variables. Moreover, in order to see whether the absence of fouling observed was due to the fouling unit and/or to the nature of the test fluid, a blend of de-asphalted oil known to give measurable fouling rates in turbulent flow and in similar periods of time as for the coking experiments was studied. Finally, measurements of heat transfer coefficients were made in order to estimate the sensitivity of the unit to detect fouling by thermal measurements. Correlations were developed over a wide temperature range for the viscosity (80310°C) and density (60-145°C) prediction of any blend of pitch and gas oil. As a result, the flow regime could be determined and the viscosity drop observed in some of the runs revealed a possible bias effect on the mass flowrate measurement. Moreover, the use of different data analysis techniques and empirical equations found between process variables confirmed the liquid flowrate variations as the reason for the observed changes in the thermal resistance for the runs with the 50:50% vol. pitch-gas oil blend. The liquid flowrate variations were essentially eliminated by modifying the configuration of the bypass circuit. Also, the thermal resistance of the fluid bed was found to be as high as 38% of the total resistance, which substantially reduced the sensitivity of the unit to detect coke deposition. Finally, no significant fouling was observed both from the thermal and mass deposition measurements with the 50:50% vol. pitch-gas oil blend over the range of conditions mentioned above. As for the experiments involving a blend of de-asphalted oil, the evidence obtained was judged insufficient to draw a definite conclusion as whether sufficient fouling actually took place.  in  Table of Contents  Abstract  1 1  List of Tables  viii  List of Figures  x  List of Symbols  xiii  Acknowledgement 1  2  xviii  Introduction  1  1.1  Background  1  1.2  Fouling by Coke Deposition  1  1.3  Objectives of Work  2  Literature Review  3  2.1  Introduction  3  2.2  The Fouling Problem - Fundamentals  3  2.3  Fouling in The Heavy O i l Upgrading Industry  6  2.4  Classification of Fouling  8  2.5  Chemical Reaction Fouling  9  2.6  2.5.1  Thermal Decomposition  10  2.5.2  The Role of Asphaltenes in Coke Deposition  11  Effects of Process Variables  12  2.6.1  12  Surface and Bulk Temperatures iv  2.6.2  3  iz  2.7  Models of C h e m i c a l Reaction Fouling  13  2.8  E x p e r i m e n t a l Techniques i n T h e r m a l Fouling  14  2.8.1  Fouling Surface Heating Techniques  15  2.8.2  Heat Transfer Coefficient i n a B u b b l i n g F l u i d i z e d B e d  16  C h a r a c t e r i z a t i o n of Feed M a t e r i a l s  21  3.1  Properties of F l u i d s  21  3.2  Density  21  3.3  3.4  4  Velocity  3.2.1  Density of 52%wt. Pitch-48%wt. C H G O B l e n d  21  3.2.2  Generalization of Results  23  Viscosity  24  3.3.1  24  H i g h Temperature Viscosity Measurements  M o d e l l i n g Viscosity D a t a  27  3.4.1  Evaluating E m p i r i c a l Equations  27  3.4.2  M i x t u r e Viscosity Equations  32  3.4.3  Generalization of Parameters  32  D e v e l o p m e n t a n d O p e r a t i o n of the F o u l i n g U n i t  35  4.1  O r i g i n a l Apparatus  35  4.2  L i q u i d Flowrate Measurement  37  4.3  Pressure Drop Measurement  37  4.3.1  37  Differential Pressure Transducer Design, Operation, and C a l i b r a t i o n  4.4  L i q u i d Flowrate E s t i m a t i o n  38  4.5  Test Section and F l u i d i z e d B e d  38  4.5.1  39  A i r Distributor v  5  6  4.5.2  Temperature Measurement and Control  41  4.5.3  Modifications  42  4.6  Data Collection and Loop Monitoring  42  4.7  Other Modifications and Final Apparatus  43  4.7.1  Initial Unsteady-State Period  43  4.7.2  Liquid Flowrate Fluctuations  43  4.7.3  Viscosity Reduction  44  4.7.4  Volatilization  44  E x p e r i m e n t a l Procedures  46  5.1  Thermal Fouling Measurements  46  5.2  Toluene Insoluble Formation and Deposition Measurements  48  Results and Discussion  50  6.1  Fouling Tendency of 50:50%vol. Pitch and C H G O Blend  51  6.1.1  Summary of Fouling Runs  51  6.1.2  Toluene Insolubles Measurements  53  6.1.3  Mass Deposition Measurements  57  6.2  6.3  Analysis of Variations in Liquid Flowrate  60  6.2.1  Experiments with Pressure Drop Measurement  60  6.2.2  Initial Experiments  64  6.2.3  A R M A Model and Variable Flowrate Approach  68  6.2.4  Elimination of Fluctuations  74  6.2.5  Viscosity Effect  75  Heat Transfer in a Bubbling Fluidized Bed  80  6.3.1  80  Heat Transfer Coefficient Around an Immersed Tube vi  6.3.2 6.4  6.5  Clean Coefficient For T h e O i l  87  Analysis of Variations i n F l u i d i z e d B e d  90  6.4.1  Power Spectral Density  90  6.4.2  E l i m i n a t i o n of Fluctuations  92  6.4.3  Sensitivity of U to A i r F l o w Variations  96  Q  Tests W i t h a K n o w n Fouling F l u i d  97  7 Conclusions Sz Recommendations  103  7.1  Conclusions  103  7.2  Future W o r k  106  -Bibliography  108  A Calibrations  117  B Properties of Fluids and Distillation TBP curves  120  C Size Distribution of Quartz Sand Used in Fluid Bed  122  D Sample Calculations  123  D.l  Tube Side Velocity, and Reynolds Number  123  D.2  Heat F l o w , Overall Heat Transfer Coefficient, and T h e r m a l Fouling Resistance  123  D.3  Superficial Gas Velocity, U, and M i n i m u m F l u i d i z a t i o n Velocity, U f.  D.4  E x p e r i m e n t a l Bed-to-Wall and O i l Side Heat Transfer Coefficients  124  D.5  Effect of h on Sensitivity of U n i t to detect Coke Formation  125  D.6  Calculation of parameters presented in Table 6.1  126  m  0  vii  . . . 124  List of Tables  3.1  S u m m a r y of Parameters i n Equation 3.3  23  3.2  D y n a m i c viscosity (mPa-s)-temperature data for p i t c h , C H G O , and their blends  26  3.3  S u m m a r y of Some of the Viscosity Correlations Tested  28  3.4  Constants Regressed i n the Viscosity Correlations Tested  29  3.5  Average Absolute Deviation ( A A D ) for Correlations Tested  30  3.6  Generalization of Parameters i n D u t t Correlation  33  4.1  E s t i m a t i o n of Pressure Drop Across A i r Distributor  39  6.1  S u m m a r y of variables investigated i n fouling experiments w i t h a 50:50%vol. blend of pitch and C H G O and w i t h F O - H O - D A O b l e n d '  51  6.2  Toluene insolubles content i n the i n i t i a l and final test fluid for all runs.  . .  6.3  Coke collected i n test section and equivalent liquid thickness which would  56  give rise to w  57  6.4  Cross-correlation between A Tft and m at lag zero  62  6.5  Parameters regressed i n Equation 6.11 for some experiments  72  6.6  Measured and calculated initial and final viscosities for Runs 17 and 18. . .  79  6.7  Predicted decreases i n flowrate i n Runs 17 and 18 based on two approaches.  79  6.8  E x p e r i m e n t a l and predicted h from various methods  82  6.9  Bed-to-wall temperature difference at three axial positions (Runs 16, 20, 23). 83  c  a  6.10 Measured, and predicted h , 0t  nax  from various correlations for Runs 16 and  20  86  6.11 Parameters involved in the calculation of /?.,viii  89  6.12 Measured (hi), and predicted (hi) coefficient from E q u a t i o n 6.22  89  6.13 Total, and fractional tube side and shell side resistances*  89  6.14 Magnitude and period of the peaks identified i n Runs 3 to 7  92  6.15 Parameters for the bandstop filters for Runs 5 and 6  94  6.16 Initial and final values of measured and calculated variables for all runs w i t h 95% confidence interval (CI)  98  6.17 Coke collected i n test section at the end of Runs 20 and 21  102  B.l  Properties of p i t c h and C H G O  120  B.2  Some properties of Fuel O i l , C o l d Lake Heavy O i l and D e - A s p h a l t e d O i l  D.l  Effect of h  Q  on the change i n 1/U .  .  0  ix  . 120  125  List of Figures  2.1  Schematic of T h e r m a l Resistances i n a Fouled Tube  5  2.2  Schematic of Hydrocarbon Pyrolysis  2.3  General multistep chemical reaction fouling mechanism where A is the  10  soluble precursor, B is insoluble foulant and C is the deposit  13  3.1  Density of mineral o i l and of 52%wt. pitch blend  22  3.2  A T y p i c a l n-S D i a g r a m (T = 190°C)  25  3.3  K i n e m a t i c viscosity-temperature data; fitted lines obtained using D u t t ' s (1990) equation and parameters given i n Table 3.4  26  3.4  Parameters &i and b from M e h r o t r a et al. (1989) and from this work. . . .  30  3.5  K i n e m a t i c viscosity-temperature data; fitted lines obtained w i t h E q u a -  2  tions 3.9 to 3.12  34  4.1  Original Apparatus  36  4.2  Test section, fluidized bed, and air distributor  40  4.3  F i n a l Apparatus  45  6.1  B a t c h coking experiments of 50:50%vol. P i t c h and V i r g i n Gas O i l B l e n d — E x p t s . Yue (1998)  6.2  54  Toluene insolubles content based on actual sample weight versus recirculation time for a l l runs (50:50%vol. pitch and C H G O blend)  55  6.3  Mass deposition measurement analysis; run number shown besides symbol.  59  6.4  Fluctuations in AT& caused by variations i n mass flowrate i n R u n 9  61  6.5  Relationship between A T t and rh; lines from Equations 6.6 and 6.7.  x  . . .  61  6.6  Cross-correlation function between AT& and m for Runs 8 and 16  63  6.7  Linear correlation found between ATf, and m  63  6.8  Slopes of Equations 6.6 and 6.7 (lines) versus corresponding slope i n i n d i -  6.9  vidual runs (symbols)  64  Drop i n ATf, i n R u n 1 caused by a flowrate increase  65  6.10 Correlations found between A T i  o s s  , ATI,, and rh for Runs 4-11  6.11 Correlations observed between A 7 )  O S S  and m and between A T t and  66  ATi .  67  oss  6.12 Slopes of Equations 6.8 and 6.9 vs. corresponding slopes i n i n d i v i d u a l runs. 67 6.13 Similarity of patterns i n ATJ,, ATi  and ra for Runs 4, 7, and 10  oss  69  6.14 Use of variable flowrate approach to reduce the effects of flowrate on Q; for Figure (a), a flowrate value measured at the end of the run was assumed.  .  70  6.15 Relationship between the heat flow to the test section and the mass flowrate. 70 6.16 Use of variable flowrate approach to reduce the effects of flowrate on Q. . .  70  6.17 B l o c k diagram of principle used to distinguish fouling from flowrate effects.  71  6.18 A p p l i c a t i o n of A R M A model to predict AT  73  b  based on A P  6.19 Standard deviation of flowrate versus flowrate for two bypass configurations. 75 6.20 Test for correlation between A T / 6.21 AT/oss,  o s s  and m for Runs 17 and 18  heat flow and mass flow measurements for Runs 17 and 18  6.22 Viscosity drop during recirculation of test  fluid  75 76 77  6.23 Discharge coefficient vs. Reynolds number for the 1/16" d i a m . orifice plate.  78  6.24 Measured and predicted h  according to different methods for R u n 20. . . .  81  6.25 Measured and predicted h according to E q u a t i o n 2.19 for Runs 16 and 23.  81  Q  0  6.26 F i t b y Equations 2.19 and 2.24; data from M a k h o r i n and Kharchenko (1964). 84 6.27 E x p e r i m e n t a l (symbols) w i t h air at varying bed temperatures and predicted h  0  (Equation 2.19); reproduced from Molerus and W i r t h (1997)  with permission  85 xi  6.28 E x p e r i m e n t a l and predicted  h,  0 max  (Equation  2.24) at different levels of  temperature; reproduced from Molerus and W i r t h (1997) w i t h permission.  85  6.29 Instantaneous h on a vertical tube; adapted from M i c k l e y et al.(1961). . . .  87  6.30 Samples of the periodogram obtained from the F F T ( D a t a from R u n 5).  .  91  6.31 B o d e diagram of the band-stop filter used to reduce oscillations i n R u n 5. .  93  6.32 Samples of the periodogram for the raw and filtered ATb for R u n 5  94  6.33 R a w and filtered heat flow for Runs 5 and 6  95  6.34 Test revealing the effect of air pressure on air temperature, T  a t r  6.35 Correlation between U and the fluid bed temperatures i n R u n 20 0  95 97  6.36 Heat flow, (1/C/ ), and mass flowrate i n Runs 19 to 21  101  A.l  A i r rotameter calibration curve  117  A.2  Orifice 1/8" calibration and discharge coefficient  118  G  A . 3 Orifice 1/16" calibration and discharge coefficient  119  B. l  S I M D I S T for V i r g i n and Coker H G O s  121  C. l  Size distribution of quartz sand used i n fluidized bed; mean particle diameter^.34 mm  122  xii  List of Symbols  constants  A, a  inner and outer tube surfaces, respectively  B, b,bi,b  constants  C  constant (Chapter 3), discharge coefficient elsewhere  2  heat capacity of test fluid, particles, and gas, respectively CR  ratio of heat transfer coefficient for vertical tube to that for tube located on bed axis  D  rate of shear (p.25) and tube diameter elsewhere  D  diameter of orifice throat  d  particle diameter  th  p  D  bed internal diameter  E  activation energy-  G,g  superficial mass fluidizing velocity and gravity constant, resp.  h  convective heat transfer coefficient  h j  predicted convective heat transfer coefficient  v  thermal conductivity of tube wall, deposit, gas, and l i q u i d , resp.  K  instrument factor  L  length of vector (Section 6.4), length of heated tube elsewhere hydrodynamic and thermal entry lengths, respectively  U  laminar flow length scale  m  mass of deposit per unit heat transfer area  m, m  mass flowrate, average (over time) mass flowrate  Am,,  change i n m predicted from viscosity data change i n m predicted from Eq. 6.16  71  test speed (Eq. 3.6), number of data points elsewhere  N  number of data points  xin  p  period  AP  pressure drop across orifice plate  ^•Pdist  pressure drop across air distributor  A P  t  , A P  total pressure drop, and pressure drop across the fluid bed  v  Q, Q  heat flow, average (over time) heat flow  q  heat flux  q~  backward shift operator  R  universal gas constant  l  Rf, R , R  thermal resistance (fouling, total, and tube wall, respectively)  Rf  thermal fouling rate  ?•  tube radius  Tfc  cross-correlation function at lag k  S, s  torque, and constant, respectively  t  w  S, S  periodogram, and power spectral density, respectively  T, T  temperature, and average temperature, respectively  TI  toluene insolubles  t  time index  p  p  t  recirculation time  AT  temperature difference  r  AT/,„, ATi,  n  ATi , ATi oss  oss  log mean temperature difference ( L M T D ) , and average L M T D temperature difference between bulk temperature of test fluid in the tank and bulk inlet temperature, and average A T /  U  o s s  gas superficial velocity  Ui, U  overall heat transfer coefficient (based on inner and outer surfaces  0  of tube, respectively) U  gas velocity at air distributor nozzle  V, v  volatile yield, and liquid velocity, respectively  w  defined by Eq. 6.27  OT  w  weight of coke in test section at the end of a run  c  %wt  p  •  weight percent of pitch  xiv  W  defined by E q . 6.24  X  discrete fourier transform of sequence  x  tube length  Xd  deposit thickness  Xfd,T,x/d,H  thermal and hydrodynamic entrance regions  Xi  weight fraction of component i  x  weight fraction of pitch  N  p  {x } t  x  equivalent liquid thickness of residue which would give rise to w  x  time series  y  data  z  coordinate  res  c  t  Dimensionless groups Ar  Archimedes number  Gz  Graetz number  Nu  Nusselt number  Pr  P r a n d t l number  Re  Reynolds number  Greek letters  P  orifice-to-pipe diameter ratio  e  fluid  bed voidage  8  frequency  /i  dynamic viscosity of liquid  f.i  dynamic viscosity of gas  v  kinematic viscosity of liquid  p  density of liquid  Pd  density of deposit  g  xv  p  density of gas  g  p  density of particles  p  density of residue  a  standard error  r  shear stress  p  res  Subscripts 0  initial  air  air entering the fluid bed  b  bulk  hot  bottom of fluid bed  c  calculated with a constant flowrate value measured at the end of each run  cb  at calibration  d  deposit  /  final  fb  fluid  bed  h  hot medium  1  inside (or inner) of the tube or liquid side  in  inlet  j  component j  M  by Molerus  m  mixture  max  maximum  mf  minimum fluidization conditions  mid  middle of fluid bed  o  outside (or outer) of the tube or fluid bed side  out  outlet  p  pitch  .s  surface xvi  T  at a given temperature  t  time index  top  top of fluid bed  v  calculated w i t h actual flowrate value  Abbreviations  AAD  average absolute deviation  CHGO  coker heavy gas o i l  CI  confidence interval  DAO  de-asphalted oil  FO  fuel oil  HO  heavy oil  LHS  left hand side  MCR  micro carbon residue (amount of solid left behind when a sample is pyrolyzed i n an inert gas)  RHS  right hand side  SS  time required to get to thermal steady-state  xvn  Acknowledgement  I would like to thank m y supervisors, D r . P a u l W a t k i n s o n and D r . E z r a K w o k , for their support, guidance, and helpful suggestions throughout m y research. Special thanks must go to D r . K . L . Pinder for his help regarding viscosity measurements and to D r . D . Posarac who helped me solve several technical difficulties. Support and technical advice from the staff of Mechanical workshop, E l e c t r i c a l shop, Stores, and C h e m i c a l Engineering office are truly appreciated. Also I would like to thank m y colleagues M i c h a e l C h o n g P i n g , Petar K n e z e v i c h , E m a n A l - A t a r , and Ian Rose for their friendship and assistance. T h e financial support of Syncrude Canada L i m i t e d and N S E R C are gratefully acknowledged. Finally, to m y family for their encouragement and love, this thesis is dedicated.  xvni  Chapter 1 Introduction  1.1  Background  The increase iii the price of conventional crude oil and its depletion have increased the interest for exploitation of alternate sources such as the vast reserves of heavy oils and bitumens found in tar sands of Western Canada. These feedstocks contain much larger amounts of residuum—the 524° C+ fraction of a crude oil or bitumen—than conventional crude oil, and hence require more processing. The current practice consists of converting the residua, and pitch—524° C+ product from processing a crude oil or bitumen—to produce synthetic crude oil that is suitable for conventional refinery processing. Gray (1994) has provided an excellent description of the upgrading processes of heavy oils and bitumens.  1.2  Fouling by Coke Deposition  Fouling can be defined as the accumulation of unwanted material at a phase interface. Fouling of heat exchanger surfaces in which organic streams are heated is the cause of important economic, penalties that have been discussed by Van Nostrand Jr. et al. (1981), by Bott (1995), and others. At temperatures above 300°C, heavy oil streams undergo thermal or free-radical reactions which lead to the formation of coke, defined as tolueneinsoluble carbonaceous solid. In processing petroleum streams, coke frequently deposits on the surface of processing equipment and causes fouling. Precipitation of carbon-rich material is worse with heavy petroleum streams such as bitumen from oil sands because of the higher temperatures of processing required and the higher concentration of precursors to coke formation such as asphaltenes and polar heteroatomic species.  1  Introduction  1.3  2  Objectives of Work  As heavier feedstocks are processed in upgrading and refinery units, efforts are made to know the conditions which lead to coke and deposit precursors formation and deposition. The design and operation of units with minimum deposits require an understanding of the chemical, thermal and fluid mechanical factors which govern the processes leading to solids formation. The ultimate goal of this research is to generate information on deposition processes taking place in heavy hydrocarbon streams, such as pitch and gas oil blends, through thermal fouling studies. To this end,, a re-circulation flow loop capable of reaching high surface and bulk temperatures was constructed. The objective of the present work was to develop the new fouling unit, to analyze its behaviour, and to evaluate its capability to detect coke formation in pitch-gas oil blends so that progress towards the primary goal stated above can be achieved. More specifically the objectives of this study are • To modify the fouling unit so that viscous hydrocarbon streams can be processed and such that higher bulk temperatures are achieved. • To provide additional measurements to ensure adequate monitoring and control of the unit and to facilitate the analysis of the fouling data. • To characterize pitch, heavy gas oils, and blends by measuring the density and viscosity in the temperature range of thermal fouling studies to permit the flow regime to be determined. • To perform a series of fouling experiments to test the coke detection limits in the fouling unit. • To distinguish fouling from other process variable effects, to improve the quality of the data by eliminating known effects, and to reduce variations in process variables.  Chapter 2 Literature Review  2.1  Introduction  The build-up of undesired material on a surface, or fouling, is a widespread problem that has been observed to occur in many applications of heat exchangers. Because the subject matter of such a universal problem is quite broad, only the issues directly relevant to the present work are briefly discussed. This literature review is intended to provide a general background to the fouling problem and covers some aspects which occur in processing heavy petroleum streams typical of the heavy oil upgrading industry.  2.2  The Fouling Problem — Fundamentals  The accumulation of deposits considered here is the one occurring on the surface of a heat exchanger. In the following paragraphs, the basic equations governing the rate of heat transfer in heat exchangers will be recalled along with implications of fouling. Consider a simple double pipe heat exchanger. An energy balance around a differential control volume for the flow in a tube leads to the following equations after certain assumptions are made—fluid is not undergoing a phase change, negligible potential and kinetic energy changes, constant mass flow rate, and negligible heat transfer between the exchanger and its surroundings—and integration from the tube inlet in to the outlet out (Incropera and DeWitt (1996)): dQ = m • C • dTt, p  Q = m • Cp • (T , .- T ) b oul  btin  (2.1)  where the subscript b refers to mean (or bulk) temperature of the fluid at a given crosssection. The total heat flow, Q, can also be related to the heat exchanger surface area 3  4  Literature Review  and the temperature difference between the cold and the hot medium (denoted by the subscripts b and h, respectively). If an overall heat transfer coefficient U is used in place of a single convection coefficient, an extension of Newton's law of cooling is obtained, which applies to the entire tube: Q = Uo-Ao- A T / = Ui • A, • AT m  (2.2)  lm  where AT/,,, is an appropriate log mean temperature difference to account for the axial variation of the radial temperature gradient and the subscripts i and o indicate that U can be based on either the inner (Ai — TtDiL) or outer (A = nD L) tube surface area. a  0  The specific form of AT depends on the flow configuration and can be derived by applying energy balances to differential elements in the hot and cold media. For a smooth, and clean single-tube heat exchanger, the overall heat transfer coefficient is given as:  = Ui • A, = 4-  U •A 0  ;  0  =  -. \hiAi  (2.3)  r-  2nkL  T  lioAoJ  The thermal resistance under clean conditions is therefore: »  1  1  =  '  =  U -A 0  0  =  Ui-Ai  f  1  , ^(r /ri) 0  \hiAi  2M  1 \ hA) 0  0  {  '  }  During normal heat exchanger operation, surfaces are usually subject to deposit formation and this represents an additional heat transfer resistance which increases with time. The technical problems associated with this layer are numerous and have been discussed by several authors, among them Bott (1988), but can be summarized in terms of two major effects. The thermal conductivity of the fouling layer is generally lower than the other resistances and this results in a loss of heat transfer efficiency. Also, the reduction of the flow area due to the presence of the deposit causes a blockage effect, which coupled with the usually rough surface presented by the foulant, increases the pressure drop through the heat exchanger. This layer can be accounted for by introducing a fouling resistance, Rj. If we now consider deposit formation only on the inside surface of the tube, then the increase in  5  Literature Review fouling resistance inside the tube over time t can be described as:  _  xj{t)_  =  m(i)  ^ ^ 6  where m is mass deposited per unit heat transfer area, pj is deposit density, and kj is deposit thermal conductivity. Equation 2.6 is valid only for thin deposits. This situation is illustrated in Figure 2.1 which also shows the various thermal resistances acting in series. In addition, the initial fouling rate is an important parameter in thermal fouling studies and is given by:  The two special cases of interest in heat transfer—constant hot fluid temperature and constant surface heatflux-—havesome important implications on fouling. The former is  T  b  l^h.  R /A f  i  R  w  l/A h o  o  T  h  •—VW—\AAHWWWV—•  Figure 2.1: Schematic of Thermal Resistances in a Fouled Tube.  6  Literature Review  closely approximated, for example, when the surface is in contact with a freezing liquid or a condensing vapor while the latter may be realized from an electric heater. If we consider a local heat transfer at any axial position z, the heat flux may be obtained from Equation 2.2 where AT/, simplifies to yield: n  q(z, 0) = U (z, Q)[T {z, 0) - T (z, 0)] 0  h  (2.8)  b  At time t we have by making use of Equation 2.5: =  !  , j  , TsPU*,*) - T (z,t)}  D  U (z,0) "I" Ai  (2.9)  b  f,'\ ' >  K  o  Z  T  For constant local T/,, as i?/ - increases, the local heat flux decreases over time. Provided )t  that T/ is constant over time, the total heat flux will decrease whether or not the hot t  fluid temperature is uniform over the surface. If T), is also uniform over the surface and the surface temperature is an important factor determining fouling, the measured initial fouling rate is expected to apply to the whole tube. However, when constant hot fluid temperature conditions prevail, the deposit/fluid interface temperature decreases as the surface fouls. Equations 2.8 and 2.9 also reveal that to maintain a constant local heat flux implies that the local hot fluid temperature must be increased as i?/ - increases: jt  U (z,0)[Tk{z,0) o  -r (z,0)] -  i  t  X  L,  Uo(zfl) + Ai  (2.10)  ATh{z,t)-T (z,t)] b  fA ^)  K  Z  If the heat flux is also uniform over the surface, it can be shown (Incropera and DeWitt (1996)) that the mean temperature T varies linearly between b  Ti bt  n  and  T  t\  byOU  the variation  of the mean temperature along the tube may also be obtained if q is a known function of the distance. Note that a uniform heat flux implies that the surface temperature varies along the tube. Furthermore, in the case of a thin and hydrodynamically smooth deposit, the local deposit/fluid interface temperature remains constant at the clean wall temperature value as the surface fouls. 2.3  Fouling in The Heavy Oil Upgrading Industry  Heavy oils and bitumens are solid and semi-solid petroleum materials consisting of high molecular weight hydrocarbons, and contain large quantities of residuum which is defined  7  Literature Review  as material boiling above 524°C. The conversion of heavy oil residua to distillates (C + 5  to 524°C-) is of particular importance in Canada because of the vast bitumen reserves in Western Canada. These feedstocks are considerably heavier and more difficult to process than traditional crudes; the current practice consists of converting the residua and pitch to produce synthetic crude oil that is suitable for conventional refinery treatment. Primary upgrading followed by hydrotreating are the two stages in which residua are upgraded, as explained by Gray (1994). Primary upgrading requires breakage of the carbon-carbon bonds in the residua and there are two approaches for doing this: hydrocracking and thermal processes. In the latter, the residuum is heated in an inert atmosphere and carbon in the form of coke, is rejected. Thermal-cracking processes are commonly used commercially to convert residua into distillable liquid products. Example processes include visbreaking, delayed coking and fluid coking. Within the coking units, coke formation is desired and promoted, leaving a lighter liquid as gaseous products. The coke is recovered as a by-product. When bitumen is processed under the severe temperature conditions of these thermal processes, there is usually a tendency for coke formation outside the units as well, and this can lead to technical difficulties. Fouling of processing equipment and heat exchanger surfaces by coke deposition is especially severe during the upgrading of heavy oils because of the higher temperatures of processing. These deposits must ultimately be removed from the equipment and disposed of. The processing of heavy oils with minimum deposit formation hinges on understanding the reaction fundamentals of the heavy ends and the thermal and fluid mechanical factors which govern the process. However, hydrocarbon processing deals with undefined mixtures. Trace metal contaminants, heteroatoms (S, N , 0 containing species), shortlived radicals, catalytic, effects and the large number of components combine to make the chemistry involved in this type of fouling exceedingly complex (Watkinson (1992)). The complicated nature of fouling chemistry in turn affects the thermal and physical processes involved. In the remaining sections, some of the literature dealing with the key factors involved in the chemical and physical processes which lead to solid formation will be briefly reviewed.  Literature Review  8  Experimental techniques that have been used in previous thermal fouling studies will also be described. Finally, principles and correlations for heat transfer in a bubbling fluidized bed will be discussed, since a fluid bed unit was used in the current work.  2.4  Classification of Fouling  In order to facilitate analysis of fouling and to provide a conceptual framework for systematic research, Epstein (1983) has classified fouling into five primary categories. Crystallization fouling includes precipitation and solidification fouling. The former is due to formation of crystals from dissolved substances on the surface while the latter refers to the freezing of the process fluid—or constituents—onto a subcooled surface. Particulate fouling is the accumulation of suspended solids from the fluid stream on a surface. Deposit formation at the heat transfer surface resulting from chemical reactions in the flowing fluid in which the wall is not a reactant has been called chemical reaction fouling. Corrosion fouling occurs when the wall is involved in the formation of indigenous corrosion products on the surface. Biofouliug was another category defined which accounts for the deposition and growth of organisms on a heat transfer surface. Epstein (1983) also proposed a general sequence of events which may play a role in all of the above fouling types: 1. Initiation 2. Transport of foulant 3. Attachment to the surface 4. Removal of the deposit 5. Aging of the deposit on the surface The deposits resulting from organic fluid fouling are usually strong such that no removal processes are significant (Watkinson (1992)). On the other hand, aging of deposits is particularly important (Watkinson and Wilson (1997)).  Literature Review  9  This classification should be used with care since it is not likely that practical heat exchanger fouling is due to only one type. Most fouling problems are the result of combinations and interactions of factors which belong to more than one of the above categories. This was pointed out by Murphy and Campbell (1992) who discussed fouling in refinery heat exchangers under seven categories, of which the following four—inorganic salts, sediments, filterable solids, and corrosion products—arise from impurities. Three others— oxidative polymerization, asphaltene precipitation, and coke formation—arise from chemical reactions of constituents of the oil. Nevertheless, fouling in organic fluids is generally regarded as belonging primarily to chemical reaction fouling, but may be intrinsically related to other categories.  2.5  Chemical Reaction Fouling  Chemical reaction fouling was defined by Watkinson (1988) as a deposition process in which a chemical reaction either forms the deposit directly on a surface or is involved in forming precursors (or foulants) which subsequently become deposited. Unlike corrosion fouling, reaction does not take place with the wall itself. Reviews of chemical reaction fouling by organic fluids include those by Watkinson—Watkinson (1988), Watkinson (1992), Watkinson and Wilson (1997)—, by Crittenden (1988), and by Bott (1995). Watkinson (1988) attributed chemical reaction fouling for organic fluids to three general classes of reactions: autoxidation, polymerization, and thermal decomposition. Other terms for thermal decomposition include thermolysis, pyrolysis, cracking, etc. A final polymerization step to form iusolubles occurs in both autoxidation and thermal decomposition and, when precursors are already present, iusolubles can be directly formed by polymerization. Although these reaction classes overlap in many fouling problems, at temperatures typical of thermal processes (i.e. T> 350°C), thermal decomposition becomes the predominant route in the production of fouling precursors.  10  Literature Review 2.5.1  Thermal Decomposition  Since coke formation from pitch and residuum involves the liquid phase and the gas phase, it is important to consider the reactions that can occur in both phases. Reviews of carbon deposition from gas-phase pyrolysis have been given by Oblad et al. (1979) and by Albright et al. (1983). Coke, is formed from light feedstocks such as methane, ethane, propylene, butadiene or medium cuts such as naphthas, which are pyrolyzed at temperatures over 700° C. The gas phase reactions result in formation of aromatics which then react to produce coke. The kinetics of possible thermal reactions of olefins has been reviewed by Albright et al. (1983) and by Sakai (1983). These systems are also discussed by Froment (1981) in his review of chemical reaction fouling. More recent information includes the works by Kumar and Kunzru (1987), Kopinke et al. (1993), and Huntrods et al. (1989). Also a survey of recent work in the light hydrocarbon pyrolysis area has been given by Bach et al. (1995) in which additional mechanisms for deposit formation in transfer line exchangers are given. Pyrolysis reactions in the liquid phase occur from temperatures below 300-350° C on upwards. Accumulation of high molar mass species on heat transfer surfaces may be the result of degradation reactions followed by synthesis of high molecular weight compounds. Synthesis reactions include cyclization, aromatization and ring condensation. These observations have been described by Fitzer et al. (1971) in an extensive, review of pyrolytic conversion of organic compounds related primarily to carbon or coke formation. Their schematic for the conversion of organic compounds to carbonaceous solids can be summarized as shown in Figure 2.2. The same authors pointed out that unsubstituted aromatics  Dehydrogenation Hydrocarbon Mixture  Cracking u  Cyclization  _ ^  Aromatics C y c l i c Residues  D e a l ky l a t i o n  P o l y c y c l i c aromatics Heavy residues  Polycondensation  ^  Coke  Semi coke  Figure 2.2: Schematic of Hydrocarbon Pyrolysis. react by chemical condensation to produce polynuclear aromatics; anthracene was found very active as was also reported by Madison and Roberts (1958). These thermal decom-  Literature Review  11  position reactions proceed via free radical mechanisms and have also been discussed by Lewis (1980) who emphasizes thermal polymerization reactions for polynuclear aromatics.  2.5.2  The Role of Asphaltenes in Coke Deposition  Since petroleum residua are. complex mixtures of thousands of compounds, the identification of specific fouling precursors involved in the reactions leading to coke deposition is not possible. For that matter, a common approach has been to separate residua and their reaction products into pseudocomponents by the use of solvents and then to identify the pathway for chemical change by the conversion of each pseudocomponent into others. One such pseudocomponent is the asphaltenes that are soluble in aromatic solvents (e.g. benzene, toluene) and insoluble in paraffinic solvents (e.g. u-pentane, n-heptane) and are high-molecular weight substances. Strausz et al. (1992) proposed a structure for asphaltene which was consistent with recent research and reported aromatic clusters with side chains and heteroatoms in its structure. The predominant role of asphaltenes in crude oil fouling under nonoxidative conditions has been claimed by several authors including Murphy and Campbell (1992), Eaton and Lux (1984) and Dickakian and Seay (1988), although confusion remains about the role of the physical and chemical processes involved. Mechanisms for deposit formation by asphaltenes have also been given by Dickakian and Seay (1988), Eaton and Lux (1984) and by Lambourn and Durrieu (1983). The residuum processing literature suggests some approaches for dealing with fouling and coke formation in processes such as those described in Section 2.3 (see e.g. Lott et al. (1996)). The thermal reactions of asphaltenes leading to coke formation under conditions typical of these processes have been discussed by many authors including Speight (1991), Trimm (1983), Lott et al. (1996) and have been recently reviewed by Asomaniug (1997). Furthermore, an important model of residuum thermolysis based on asphaltene solubility and phase behaviour has been developed by Wielie (1993).  12  Literature Review  2.6  Effects of Process Variables  2.6.1  Surface and B u l k Temperatures  The effect of surface temperature is certainly a critical factor i n deposition processes which are chemically controlled and has been reviewed by Watkinson and W i l s o n (1997), B o t t (1995), Crittenden (1988), and others. Since there may be several reactions leading to coke deposition, and given that selectivity may be a strong function of temperature, a simple dependence of fouling rate on temperature is not always exhibited. Nevertheless, several investigations—see e.g.  Watkinson and Epstein (1969), Vranos et al.  (1981), B r a u n  (1977), Crittenden et al. (1987), Taylor (1969)—have shown that the i n i t i a l fouling data can be correlated by an Arrhenius-type equation, i.e.  ^ ( O ) a e x p ^ j  (2.11)  where T is the surface temperature. Watkinson (1988) provides a summary of published s  activation energies. T h e role of bulk temperature for fouling i n which chemical reactions are involved must also be investigated. However, where bulk temperature effects have been studied, its effect, as opposed to that of wall temperature, has not been clarified as mentioned by Watkinson (1992).  2.6.2  Velocity  The effects of velocity on organic fouling at a fixed wall temperature are contradictory as described by B o t t (1995), Watkinson (1992), and Crittenden (1988). It is generally accepted that the problem of hydrocarbon fouling can be reduced to some extent by the use of higher velocities and this idea is reinforced by T E M A (1978), w h i c h gives design fouling resistances that conform to this trend. However, many investigations discussed i n the preceding articles—see e.g. Vranos et al. (1981), Crittenden et a l . (1987)—do not agree w i t h this result. T h i s confusion may be attributed to the effects of velocity on heat and mass transfer which complicate the analysis to find the dominant effect. For example, if the fouling rate is solely controlled by a chemical reaction, then enhanced mass transfer  Literature Review  13  to the surface as a result of increasing the velocity will not change the situation. As well, increasing the velocity may reduce the wall temperature through the heat transfer coefficient thereby affecting the reaction kinetics of the deposition process. On the other hand, if the fouling process is mass-transfer controlled, an increase in velocity will result in an improved mass transfer, thereby promoting the deposition process.  2.7  M o d e l s of C h e m i c a l Reaction Fouling  As was shown in Sections 2.5 and 2.6, chemical reaction fouling is explained through chemistry and operating variables effects. As a result, understanding of chemical reaction fouling may require (Watkinson and Wilson (1997)): 1. Identification of the reactants and precursors; 2. Determination of the kinetics of reactions that form precursors; and 3. Determination of whether the solid fouling phase is initially formed in the bulk, in the thermal boundary layer, or on the heated surface. A general multistep chemical reaction fouling model that can take into account the chemical and physical processes involved has been proposed by Watkinson and Wilson (1997)— see also Watkinson and Panchal (1993)-—and is reproduced in Figure 2.3. Based on this  Figure 2.3: General multistep chemical reaction fouling mechanism where A is the soluble precursor, B is insoluble foulant and C is the deposit.  Literature Review  14  model, they have described several pathways leading to deposit formation. T h e critical issues discussed i n the literature associated w i t h modeling chemical reaction fouling and i n this paper i n particular, are bulk reaction versus surface reaction and adhesion or attachment versus mass transfer. T h i s m o d e l has been used to visualize different controlling mechanisms.  2.8  Experimental Techniques in Thermal Fouling  According to Equations 2.5 and 2.6, we may measure fouling by thermal resistance  Rf,  deposit thickness, xj, or mass per unit heat transfer area, m. T h e r m a l fouling studies refer to cases i n which the thermal fouling resistance is the p r i m a r y response measured whereas i n mass deposition studies, the fouling deposit is weighed. T h e experimental techniques used i n fouling studies have been reviewed by B r a u n and Hausler (1976), subsequently by Knudsen (1981) and Fetissoff (1982), and more recently by B o t t (1995). T h e r m a l fouling resistances may be obtained from laboratory studies and from plant data. In-plant measurements are useful but do not usually lend themselves to the degree of control necessary for acquiring reliable fouling data. M u c h of the literature associated w i t h fouling of heat exchangers is based on laboratory work. However, laboratory data have also important shortcomings which have been discussed by B o t t (1995). Because fouling i n refinery exchangers can take weeks or months to reach significant levels, it is common practice i n the laboratory to modify one or more of the operating parameters so that an accelerated test lasting only hours or days can be achieved. T h u s , processes which m a y occur i n industrial exchangers over periods of months are measured under more severe conditions over periods of days or weeks. T h e uncertainties introduced by using  such an apjDroach are undoubtedly worse i n chemical reaction fouling than i n the other types of fouling, since the nature of the reactions occurring and the selectivity to certain reaction products may be a strong function of conditions as stated by Watkinson (1988). Furthermore, i n laboratory thermal fouling studies, recirculation of the process liquid is generally employed i n order to use reasonable quantities of fluid. Recycle of the fluid across a simulated heat exchanger surface that is at a raised temperature may bring about permanent chemical changes i n the fluid so that the fluid is no longer representative of  15  Literature Review  the process fluid. T h i s phenomenon is particularly acute where chemical reaction fouling occurs. Despite these concerns however and given the generally poor state of knowledge i n chemical reaction fouling from residua, laboratory investigations can provide insights into fouling mechanisms and as such, give valuable data that m a y be useful i n formulating models of fouling. It is also possible to study the effects of velocity and temperature on the fouling process that w i l l be invaluable i n the design and operation of full scale heat exchangers.  2.8.1  Fouling Surface Heating Techniques  Numerous methods for heating a fouling surface have been used i n the past and have been discussed and described by Fetissoff (1982) and by others. However, none of them were suitable for reaching the high surface temperatures required for the present study. To address this issue, other kinds of devices were considered. W h e n the fouling process occurs inside a tube and is measured v i a an overall heat transfer coefficient, say U , representing several resistances i n series (see E q u a t i o n 2.4), it 0  is crucial that U be sensitive to /i,- i n order to detect fouling. If the other resistances are Q  large compared to the resistance inside the tube, the measurement of U w i l l be insensitive Q  to fouling inside. T h e fluidized bed was selected for the heating m e t h o d because of the high temperature it can reach and of its well-known temperature uniformity that exists in both the radial and axial directions. Heat transfer coefficients i n gas fluidized beds have been found to be considerably higher than i n single-phase gas flow i n an empty tube (see Gelperin and Einstein (1971)). Hence the fouling unit consisted of a vertical tube i n a heated fluidized bed. T h e heavy oil flowed i n the tube, and the bed was fluidized with air. A quantitative value of the heat transfer coefficient between surface and bed is often required when dealing w i t h fluidized beds—for example i n estimating the surface temperature or the relative importance of the resistances involved as discussed above. In the present work, three tests were performed i n which wall temperature measurements were obtained for this matter. In the following paragraphs, some calculation procedures for h  Q  16  Literature Review  (see E q u a t i o n 2.4) that have been reported i n the literature and which are applicable to the fouling unit w i l l be given and briefly discussed. It should be noted that these correlations are far from universal and most are l i m i t e d to a narrow range of conditions because of the complex nature of fluidized contacting. Also, their predictions usually differ widely as stated by Grace (1982) who mentioned that the accuracy of several correlations should not be assumed to be better than ± 5 0 % w i t h i n their ranges of application. Because the present work does not focus on heat transfer i n a fluidized bed, a general background relevant to the system used is outside the scope of this thesis. A good summary of the principles involved w i t h several references can be found i n K u n i i and Levenspiel (1991).  2.8.2  Heat Transfer Coefficient in a Bubbling Fluidized Bed  T h e hydrodynamic and thermal behavior of fluidized beds are commonly characterized by the powder classification scheme proposed by Geldart (1973) or by that of Saxena and G a n z h a (1984), which is based on the Archimedes number defined by: Ar =  {  9  r  P  9  (2-12)  )  where g is the gravity constant and p and p are the gas density and viscosity respectively. g  g  T h e sand used i n the fouling unit belongs to Group B of Geldart's scheme which comprises particles of mean diameter, d , and density, p , l y i n g i n the range of 40 p p  / i m , and 1400 k g / m < p 3  p  < d  p  <500  < 4000 k g / m . Under the conditions studied i n the present 3  p  work, the sand used belongs to group I powders of Saxena and G a n z h a (1984), which are defined by 3.55 < A r < 21700. Numerous empirical and semiempirical formulae have been proposed for calculating heat transfer coefficients and they can be classified into two groups, one of which relates to the determination of the m a x i m u m heat transfer coefficient, h  m a x  , and the other to  the dependence of h on fluid velocity. Because of the shortcomings of these equations, a number of models have been developed to explain the mechanism of heat i n fluidized beds.  transfer  T h e calculation procedures given below were selected based on their  validity w i t h the system used, which was characterized according to the above schemes, and on the availability of the parameters required i n the equations. Previous reviews of  17  Literature Review  heat transfer in fluidized beds have been given by Gelperin and Einstein (1971), Grace (1982), Xavier and Davidson (1985), Baskakov (1985), and more recently by Saxena (1989).  Theoretical Studies  From his review, Saxena (1989) observed that the heat transfer rate from an immersed surface in a gas-fluidized bed depends upon a number of factors, such as the size, size range, shape, and properties of the bed particles; operating conditions, namely, temperature, pressure, fluidizing velocity, and properties of the gas; shape, size, surface finish, and orientation of the heat transfer surface; the relative size of the heat transfer surface and the fluidized bed; and on the design of the gas distributor plate. Many models have been proposed to explain the mechanism of heat transfer (see e.g. Mickley and Fairbanks (1955), Bock and Molerus (1983), Martin (1984), etc.). However, the majority of them could not be applied to our system due to a lack of data required in the computations. The model developed by Kunii and Levenspiel (1991) was selected because it was general enough to account for many of the above factors and because of the availability of the information required. They developed a general expression for the heat transfer coefficient between a bubbling fluidized bed and an exchanger surface. The expression accounts for the fact that part of the time the surface is bathed by gas and part of the time by emulsion packets: h  =  (^bubble at surface) ' $w  H" { h  e m u  l i s  o n  ( surface) '  a  (1  (2.13)  where S is the volume fraction of bubbles in the vicinity of the surface, and is equal to the w  time that the surface is bathed by bubbles. The bubble term represents the contributions of convection and radiation from the gas: . hbubble present  = (h + h ) r  g  (2.14)  When the emulsion packet is present on the surface, the heat transfer occurs in series—at the wall region followed by transfer at the emulsion packet. In addition, both convection  18  Literature Review  and radiation occur throughout the wall region. C o m b i n i n g a l l of the above terms yields:  h = [S • (h w  r  + h )]bubble at surface +  +  g  (2.15)  1 hpacket  emulsion at surface  T h i s model has been applied w i t h success for b o t h horizontal and vertical tubes (see K u n i i and Levenspiel (1991) for more details about the different terms of E q u a t i o n 2.15).  Empirical and Semiempirical Correlations T h e theories and mechanisms that have been proposed, such as the one outlined above, show the general features of bed-to-surface heat transfer i n gas-fluidized beds and the importance of different variables. However, despite the elaboration of a number of mechanistic models, e m p i r i c a l and semiempirical correlations are s t i l l the most common means for predicting heat transfer rates (Grace (1982)). E x p e r t s i n the field (see e.g. B o t t e r i l l and Hawkes (1989)) prefer empirical equations such as the one given by Zabrodsky et al. (1976). T h e heat transfer coefficient for an immersed surface i n a gas-fluidized bed of systems belonging to groups I and I I A w i l l depend upon the orientation of the surface w i t h the flow of gas i n the  fluidized  bed (Saxena (1989)).  E x p e r i m e n t a l investigations of h for  vertical tubes are relatively more scarce than for horizontal tubes, as reviewed by Saxena (1989). One of the best-known correlation for heat transfer to a single vertical unfinned tube positioned on the axis of a cylindrical c o l u m n is that due to Vreedenburg (1960), who obtained:  h(D -D )(D k v  0  0  g  where D  v  df  2  g  0 f g  x  0  (2.16)  \p (d g)^  2  p  is the gas thermal conductivity, and c  g  p  2  - D)  V  9  T h i s equation is valid for (G d  g>  G(D  -3  g  g  heat capacity. 0  v  0.105 x 10  is the bed diameter, k  v  D )/p  1/3  d \D (D -D ) i c J  p /p p  g  p, ) g  > 2.5 X 10  3  is the gas  and G(D  V  —  < 1070. A c c o r d i n g to a review of Saxena (1989), the correlations by  Vreedenburg (I960) reproduced the available experimental data w i t h i n ± 1 0 0 % . However, these do not predict a m a x i m u m in the plot of h versus superficial mass fluidizing velocity, G , as was found i n the experiments.  19  Literature Review B o r o d u l y a et a l . (1980) reported h data for an 18-mm vertical heat transfer  probe  immersed i n a 45-cm deep and 10.5-cm diameter fluidized beds of quartz sand ( d = 1 2 6 p  1220 ixm. T h e y proposed:  Nu  = 0.96 Re 0  p  Pr  71  0.31  (2.17)  for Re < 20. T h e agreement of experimental data of V e r m a and Saxena (1983) w i t h the predictions of E q u a t i o n 2.17 was considered inadequate. T h e following dimensionless correlation given by Wender and Cooper (1958) has also been widely used: h  kg(l -  C) \Cg  for 0.01 < (dp  G/p,g)  = 3.5 x 1 0  J  g  P  - 4  C  d„G\  0.23  CR  /  \ 0.8 /  (c \ K^J  f  v  \/W  100. In E q u a t i o n 2.18,  <  si\  ,  0.43  oL  \  0.66  p  p  \pgj  is a correction factor and is unity if  tube is i n the center of the fluid bed, e is the bed voidage, and c is the particle heat p  capacity. A n average deviation of ± 2 0 % was found for the 323 data points used to develop this expression. Saxena (1989) found that this correlation reproduced their data best and was recommended as being about the best. T h e following recent correlation to predict h has been given by Molerus et al. (1995) in the intermediate range of 10 < Ar < 10 : 2  5  -l  11 + 33.3 {  0.125(1 - e ) mf  ]^  (^ (U 3  -  U ) mf  hh k  u,m / u-u ,  n  m  1/3  +0.165 P ? -  Pg  1 / 3  PP -  1 + 0.05 Pg  -1  U-U  mf  u,mf  2/3  ll  =  (2.19) .9°*(J>P-Pg)\  where U is the gas superficial velocity and the subscript mf  denotes m i n i m u m  fluidization  conditions. T h e correctness of the prediction was tested by comparison w i t h more than 20 measurements covering a relatively wide range of system data and operational conditions. The accuracy of the deduced correlation was judged excellent.  20  Literature Review  M a x i m u m Heat Transfer Coefficient T h e correlation of Zabrodsky et a l . (1976) covers a relatively broad range of data, i n cluding beds operated at high temperature and m a y be applied for vertical or horizontal tubes or for transfer to the external wall: h N  U  m  a  x  =  ™ * " d  0.88 A r 0  =  10 < Ar < 2 x 10  2 1 3  2  (2.20)  5  Kg  A similar correlation has also been given previously by V a r y g i n and M a r t y u s h i n (1959): Nu  =  max  k  m  a  x  d  = 0.86 Ar  p  30 < Ar < 1.35 x 10  02  (2.21)  5  Kg  T h e following correlations have also been given to predict experimental data: • Grewal and Saxena (1981): Nu  = 0.9 (0.0127 Ar/D )°- (c /c ) 21  max  0  75 < Ar < 2 x 10  0 2  p  g  (2.22)  4  • Denloye and B o t t e r i l l (1978): Nu  = 0.843 Ar - * + 0.86 Ar°- d° 0  max  1  39  1 0 < Ar < 2 x 1 0  5  3  p  (2.23)  6  • Molerus a n d M a t t m a n n (1992): Nu  max  =  r- + 0.146 (Ar P r )  1 / 3  10 < Ar < 2 x 10 2  5  (2.24)  M a t h u r et al. (1986) have compared some of the above correlations w i t h experimental data of 13 different workers comprising 86 data points and a brief summary of their comments is given i n Saxena (1989). T h e percentage deviations between experimental and predicted values, based on the correlation of Zabrodsky et a l . (1976), range between the limits of -34.5% and 59.6% w i t h a root-mean-square deviation of 25.1%. E q u a t i o n 2.20 predicts 90% of the data points w i t h i n ± 3 5 % . O n the other hand, most of the 86 data points were underpredicted by the correlation of V a r y g i n and M a r t y u s h i n (1959).  T h e deviations  range between -46.9% and 12.6% w i t h a root-mean-square of 19.4%.  T h e correlation  of Denloye and B o t t e r i l l (1978) was also found to underpredict a l l the data points; the deviations were about -10% to -55%. Finally, comparison of 61 experimental points with prediction by Molerus and M a t t m a n n (1992) suggested that an excellent estimate can be expected from E q u a t i o n 2.24.  Chapter 3 Characterization of Feed Materials  3.1  Properties of Fluids  The deposition of coke-like materials was studied by recirculating through the fouling unit a blend of p i t c h and coker heavy gas o i l (52%wt. pitch-48%wt. C H G O or 50:50%vol. under ambient conditions). These fluids were supplied by Syncrude C a n a d a L t d . and are typical of the streams associated w i t h their coking units. Some characteristics of these fluids provided by Syncrude L t d . are given i n Table B . l . T h e high temperature simulated distillation T B P curve for coker heavy gas oil is given i n Figure B . l . Note that whenever the term '52%wt. pitch m i x t u r e ' is used, the balance is C H G O . Other tests were done w i t h a blend of fuel o i l (75%wt.  F O ) , C o l d Lake heavy o i l  (10%wt. H O ) , and de-asphalted o i l (15%wt. D A O ) to evaluate the capability of the unit to detect fouling by thermal measurement.  T h i s blend was chosen because of the high  fouling rates measured when recirculated i n another fouling unit. T h e composition and properties of these fluids are reported i n Table B . 2 .  3.2  Density  Density is a fundamental physical property used to characterize b i t u m e n and is required as an input i n many process calculations. In this section, the density measurements on the 52%wt. p i t c h blend are presented. Also, density-temperature equations are derived to model the variation of density w i t h temperature for other blends of p i t c h and C H G O .  3.2.1  Density of 52%wt. Pitch-48%wt. C H G O Blend  Several standardized procedures issued by the A m e r i c a n Society for Testing and Materials can be used for determining the density of bituminous materials ( L u (1989)). The density  21  22  Characterization of Feed Materials  of the 52%wt. p i t c h blend was measured by use of a pycnometer according to the standard designated as A S T M D70 using a constant-temperature bath M o d e l 1130-2 from V W R Scientific which was filled w i t h mineral o i l . In this method, due to the high viscosity of the materials involved, the pycnometer is partially filled w i t h the m i x t u r e and water is n o r m a l l y added to fill it completely. For this work, since densities at  temperatures  higher than 100° C were desired, a mineral o i l from Fischer C o . (same as i n the constanttemperature bath) for use up to 176°C was used instead of water for a l l the density measurements. T h e pycnometer was first calibrated w i t h water i n a water bath at several temperatures up to 89° C and a constant volume of 27.560 c m was found. T h e densities 3  of mineral oil and of the 52%wt. pitch m i x t u r e were measured between 60 and 145°C and the following linear relationships were fitted: = 866.7 - 0.621 • T  (3.1)  = 1042.4 - 0.621 • T  (3.2)  PT, .oii m  PT,52%  T h e results are shown i n Figure 3.1 w i t h the fitted lines.  Density of 52:48 wt% Pitch-CHGO Blend versus Temperature. 1020) l  1  1•  CO  E £ 980 co  ) l~7TT-7-r.—_  960  J  i  940 60 i  70  80  840 I  '  i  I  70  80  90  90 100 110 120 Density of Mineral Oil versus Temperature.  130  140  150  130  140  150  ) -  ;800 w c CD  Q  7601 60  i  i  100 110 Temperature, C  120  Figure 3.1: Density of mineral o i l and of 52%wt. pitch blend.  23  Characterization of Feed Materials 3.2.2  Generalization of Results  T h e data of B u l k o w s k i and P r i l l (1978) on four Athabasca b i t u m e n samples w i t h different treatment histories i n the 0 to 150°C temperature range were reported by L u (1989). T h e y developed the following linear relationship between temperature and density: PTJ  = P T ' j - A-T  (3.3)  In this equation, pr and pr° refer to the densities i n k g / m at temperatures T and T° 3  ( = 0 ° C ) respectively. T h e constant A was assigned a value of 0.62 ° C  _ 1  , which is the  same as the constant derived from our measurements (see E q u a t i o n 3.2).  Furthermore,  the densities measured by Polikar (1980)—as reported by L u (1989)—in the temperature range 0°C to 260° C for b i t u m e n extracted from high-grade Athabasca o i l sands can also be represented by E q u a t i o n 3.3 w i t h A=0.62 ° C of 0 . 6 2 ° C CHGO,  _ 1  - 1  . Based on these findings, a value of A  was assumed for any blend of pitch and C H G O . T h e intercepts for pitch and  PT",pitch  and  PT°,CHGO,  were found based on the knowledge of their densities at  25°C. T h e parameters are summarized i n Table 3.1 for pitch, C H G O , 52% wt. pitch blend, mineral o i l from this work and Athabasca b i t u m e n from B u l k o w s k i and P r i l l (1978). T h e 95% confidence interval is given for the 52%wt. pitch mixture and for mineral oil.  The  densities of any blend of pitch and C H G O at a given temperature can then be estimated from the following m i x i n g rule using Equation 3.3 for component densities: PT,,n  = x  p  •PT,  P  + (1 -  Xp) • PT,CHGO  (3.4)  For the 52%wt. p i t c h m i x t u r e , the deviation between the predicted and the measured densities is 1% over the temperature range 6 0 - 1 4 5 ° C .  Table 3.1: S u m m a r y of Parameters i n E q u a t i o n 3.3 Fluid  p o (kg/m )  A ("cr )  Source  Pitch  1086.8  0.62  Syncrude  CHGO  975.0  0.62  Syncrude  52%wt. pitch  1042.4±0.6  0.621±0.005  Present work  Mineral Oil  866.7±1.4  0.62±0.01  Present work  Athabasca  1025  0.62  Lu (1989)  3  T  1  24  Characterization of Feed Materials  3.3  Viscosity  Viscosity is the property of a fluid that measures resistance to movement of adjacent  fluid  layers (Miadonye and Puttagunta (1996)). F o r Newtonian fluids, viscosity is defined as the measure of the internal fluid friction, which is the constant of proportionality between the shear stress at any point and the velocity gradient (Tassios and Goletz J r . (1977)). In the literature, absolute viscosity is generally symbolized by /J. arid kinematic viscosity is denoted by u and this common practice has been adopted i n this chapter. Conversion from one to the other is obtained through the following relation:  '  v=t  (3.5)  P  A knowledge of the viscosity is essential for fluid flow and heat transfer calculations inherent to this project. A l t h o u g h many calculation procedures for b i t u m e n and heavy o i l viscosity have been presented i n the literature, most of them are not applicable to the fluids studied here. Some of them are based on parameters such as boiling points, molecular weight, specific gravity, and accentric factors which are not available for p i t c h and C H G O . Also, most of the available data used to derive or to evaluate these procedures have been measured at temperatures lower than 200° C on lighter fractions than C H G O and pitch. Therefore, given the very high sensitivity of the viscosity of heavy fractions of petroleum to temperature change, extremely large errors are bound to occur when extrapolating to temperatures i n the range 3 0 0 - 3 5 0 ° C where the fouling runs were carried out. A l t h o u g h measurements were obviously needed, the determination of viscosity of highly viscous materials handled at such high temperatures is difficult as explained by Miadonye and P u t t a g u n t a (1996). In Section 3.3.1, new data are presented for the effect of temperature on the viscosity of pitch, C H G O , and their blends i n the  temperature  range of 80-340° C . M o d e l i n g of the data was attempted and the results are given and discussed i n Section 3.4.  3.3.1  High Temperature Viscosity Measurements  The viscosity data were obtained at atmospheric pressure using a Rotovisco R V 1 2 from Haake C o . using the viscosity sensor system M V 400 I. T h i s sensor system was designed  25  Characterization of Feed Materials  for viscosity measurements from -60° C to 300° C and could be used w i t h or without an inert gas cover. It consisted of a rotor and cup which were surrounded by an electronically controlled metal block heater, and temperature control was maintained by means of a thermistor control T P 2 4 from Haake C o . . For a Newtonian fluid i n the absence of turbulence, the rate of shear D ( s ) is _ 1  directly proportional to the shear stress r (mPa) and the viscosity is defined by the Newton equation:  " - %= i  <->  R  3  6  D u r i n g each test, the value of the torque S is plotted against a series of preset test rotational speeds n and the viscosity is obtained by m u l t i p l y i n g the slope by an 'instrument factor' K, specific to each drive unit and sensor system.  T h e calibration was carried  out w i t h a standard liquid of known viscosity and the factory calibration factor A'=1374 (mPa-s/scale grad.-min.)  was confirmed.  M o r e details on the equipment and proper  measuring procedure can be found i n the Haake Rotovisco Instruction M a n u a l . A l l measurements generated linear n — S diagrams (see Figure 3.2), indicating Newtonian fluids. T h i s result is consistent w i t h the literature since b i t u m e n is generally regarded  Torque S versus rotor speed n.  n, min'  Figure 3.2: A T y p i c a l n-S D i a g r a m (T = 190°C). as a Newtonian fluid (Miadonye and P u t t a g u n t a (1996)). Table 3.2 contains the detailed viscosity-temperature data and all of the viscosities are plotted against temperature i n Figure 3.3. T h e kinematic viscosities were obtained from E q u a t i o n 3.5 by using density relationships established i n Section 3.2.  Characterization  2b  of Feed Materials  Table 3.2: D y n a m i c viscosity (mPa-s)-temperature data for pitch, C H G O , and their blends. %wt. pitch  Temperature  °C  0  25  51.7  75  100  80.0  25.9  130.9  1187  19116  -  100.0  12.7  52.2  340.0  3429  -  110.0  -  -  -  -  43462  120.0  -  -  -  -  17727  128.0  6.1  -  -  -  -  130.0  -  18.6  85.0  519.6  7581  160.0  3.3  9.1  32.2  134.6  1129  190.0  2.9  5.1  16.3  52.6  300.9  220.0  -  3.2  9.6  24.9  106.5  250.0  -  2.9  6.7  14.6  49.1  260.0  2.4  -  -  -  -  280.0  -  2.6  4.9  9.3  27.4  290.0  2.1  -  -  -  -  310.0  -  2.4  3.9  6.5  15.9  340.0  -  -  -  4.0  10.4  Viscosity of Pitch, Coker Heavy Gas Oil (CHGO), and their blends (%wt. Pitch).  1  1—  1  — 1  CHGO 1 25%  A o V  0X  — 1  _l  100  I1  150  I 1  200  IO  1 1  1  250  * 0  51.7% 75% Pitch Dutt (1990)  I•  I  300  350  1  Temperature, °C  Figure 3.3: K i n e m a t i c viscosity-temperature data; (1990) equation and parameters given i n Table 3.4.  fitted  lines obtained using D u t t ' s  27  Characterization of Feed Materials  3.4  Modelling Viscosity Data  T h e viscosity prediction of p i t c h , C H G O , and their blends based on some readily available characterization would be most convenient. Reviews of viscosity correlations and calculation methods for the viscosity of petroleum liquids have been given by M e h r o t r a et al. (1996) and M i a d o n y e and P u t t a g u n t a (1996). Due to the complicated and undefined nature of heavy petroleum liquids, their viscosity is usually calculated from semi-empirical models or empirical equations.  Most semi-theoretical models for liquid petroleums are  based either on the corresponding state approach or on the modified Chapman-Enskog theory. These methods require boiling points and therefore can not be applied to heavy oils and pitch which, unlike light crude oils, cannot be distilled completely (Miadonye and P u t t a g u n t a (1996)). Also, i n the corresponding state approach, the M W , S G , and N B P for each of the pseudo components characterizing the whole heavy petroleum l i q u i d must be available for calculating critical parameters ( T , P , V ) and the accentric factor. T h i s c  c  c  is not the case w i t h C H G O and pitch. E m p i r i c a l methods make use of the m a n y relationships that have been proposed to correlate viscosity and temperature and, i n few cases, the parameters have been generalized. However, the parameters are essentially expressed i n terms of average boiling points which are not available for p i t c h and blends w i t h C H G O . This prevents the application of those methods or similar generalizations of parameters. T h e objective of this work was to develop an estimation method for the correlation and prediction of the viscosity of the fluids studied based on the experimental data obtained and other available information.  3.4.1  Evaluating Empirical Equations  T h e first step i n modeling was to find an equation that would correlate reasonably well the viscosity data over the whole measurement temperature range and for a l l the components and blends. For that purpose, several empirical equations previously used for viscosity modeling (Miadonye and Puttagunta (1996)) were tested and some of them are summarized in Table 3.3. T h e constants were regressed i n all the equations and are listed  28  Characterization of Feed Materials in Table 3.4.  Throughout the literature, the criterion for evaluating the adequacy of a viscosity calculation procedure is the average absolute deviation ( A A D ) defined as: 1 AAD = 100 X — ^  N  |p  -  exp  H rr CO  I /Pexp  (3.7)  t'=l  Table 3.3: S u m m a r y of Some of the Viscosity Correlations Tested Comments  Equation  Author(s)  Inv — A  Dutt  +  v is viscosity i n m m / s , 2  JT^C  T i n °C  lnv  Dutt Mixture  -  m  YTj=\ i  ^ i  x  nv  Xj is the mass fraction of component j T i n ° F , p, i n poise,  log p. — A + B logT  Herschel  A and B are constants  fi = A exp  Litovitz  /i i n mPa-s, T i n K , A is a constant, R is the gas constant, a is activation energy  Mehrotra  log  log(/i + 0.7)  = bi + b logT 2  ii i n mPa-s, T i n K , b i and b2 are constants  Mehrotra  log{p  m  J2'j=i i  + 0.7) =  x  °9(Pj + 0-7)  l  of component j  Mixture Vogel Puttagunta  Xj is the mass fraction  lnp = A(^  +  l)  logv = / , , T-3O v + j  V  u i n mPa-s, T i n K  T c  p i n Pa-s, T h i ° C  c  '303.15 /  C=-3.002; b = l o g / i o ° c - C 3  s=0.0066940 b + 3.5364 Andrade Andrade G e n .  v in mm /s, T in °C,  Inv = InA + (j;) A=-0.4004 % w t 13=803 % w t  2 p  2 p  2  R  + 0.2699 % w t + 0.9204 p  + 226.33 % w t + 287.86 p  R  2  2  = 1  = 0.9937  Characterization of Feed Materials  Table 3.4: Constants Regressed i n the Viscosity Correlations Tested %wt.  100  0  25  51.7  75  185.6  279.3  488.5  671.5  863.9  pitch A Vogel  Herschel  Litovitz  Dutt  B  942341  942341  942341  942341  942341  C  -296.8  -297.9  -286.1  -287.3  -304.4  A  -2.099  -3.387  -4.924  -6.369  -8.094  B  3.962  7.559  11.976  16.3  21.516  In A  -0.255  -0.574  -0.389  -0.522  -0.390  a  1.199E+09  194E+09  2.687E+09  3.75E+09  5.11E+09  A  0.359  -0.597  -1.084  -1.840  -1.951  B  147.2  475.1  851.7  1299.8  1565.0  C  -31.267  5.087  23.802  30.872  13.870  0.27067  4.44142  202.10  25312.95  63353826  bi  6.1121  8.1486  8.3472  8.9351  8.8042  b  -2.3667  " -3.0850  -3.0917  -3.2613  -3.1528  In A  -0.0831  -0.4890  -0.3937  -0.7095  -1.3843  B  266.0  440.3  613.2  872.0  1337.0  Puttagunta (Pa-s) Mehrotra  Andrade  2  The criterion was computed for all equations applied to each oil fraction. It is shown i n Table 3.5 w i t h the average deviation for each method. In the following paragraphs, each of them w i l l be discussed. • A S T M or Walther E q u a t i o n M e h r o t r a et al. (1989) applied the double-log equation to correlate the viscosity of C o l d Lake b i t u m e n and its fractions and the two parameters, & i and 62, were related to the molar mass. T h e y reported overall A A D s w i t h i n 6%. T h i s is consistent w i t h the A A D results for pitch and 75%wt. pitch mixture. A l s o , M e h r o t r a et al. (1989) applied a linear regression to their data for C L b i t u m e n and the results are shown i n Figure 3.4 along w i t h the results obtained i n this work. T h e measurement temperature range ( ° C ) is indicated. Over the whole measurement temperature range for our results, the parameters obtained for pitch and 75%wt. pitch blend are close to the values they reported for C u t 5. However, as the pitch content decreases, the fit becomes unacceptable as indicated i n Table 3.5 and  Characterization of Feed Materials  Table 3.5: Average Absolute Deviation ( A A D ) for Correlations Tested %wt. pitch Equation  0  25  51.7  75  100  Average  Vogel  7.7  18.6  19.1  34.9  23.6  20.8  Mehrotra  24.3  17.7  9.7  6.2  6.2  12.8  Mehrotra Mixture  n/a  69.4  57.7  60.8  n/a  62.6  Dutt  8.5  10.0  3.0  4.0  1.4  5.4  Generalization 1  29.0  36.4  18.1  7.3  12.3  20.6  Generalization 2  10.4  10.7  9.3  7.2  20.6  11.7  Generalization 3  12.3  17.8  4.0  8.6  3.8  9.3  Dutt Mixture  n/a  55.2  47.9  52.6  n/a  51.9  Puttagunta  19.2  13.9  8.7  14.4  22.3  15.7  Litovitz  18.5  12.6  7.6  7.9  7.6  10.8  Herschel  26.4  25.5  24.1  34.4  33.5  28.8  Andrade  12.7  10.4  8.8  16.5  4.7  10.6  Andrade Gen.  21.5  15.5  9.2  28.9  10.6  17.1  the parameters deviate significantly from the range of values they reported. Now, the m a x i m u m measurement temperature for their heaviest cut was 210°C and around 100°C for the lighter cuts. W h e n the correlation is applied to our data up to 220° C for 52 and 25%wt. pitch mixtures and up to 160°C for C H G O , the A A D s become w i t h i n the values they reported. A l s o , all the regressed parameters become consistent w i t h their results. It  b versus b for Cold Lake bitumen and its fractions (Mehrotra et al. (1989)), Pitch, CHGO, and blends (current work). 2  -2.5 -3 N  -3.5 -4 -4.5  CL bitumen Pitch (110-340°C) 75% (80-340°C) 52% (80-310°C) 25%(80-310°C) CHGO (80-290°C) 52% (80-220°C) 25% (80-220°C) CHGO (80-160°C) Best fit CL bitumen  .Cut 5 (120-210 oC)  + x Cut 4 (30-106 oC) Cut 3 (26-100 oC)|  Whole CL bitumen (24-121 oC)  Cut 2 (30-90 oC) Cut 1 (22-94 oC) 9 b.  10  |  11  12  Figure 3.4: Parameters b and b from M e h r o t r a et al. (1989) and from this work. {  2  Characterization of Feed Materials  31  is suggested that the double-log equation can only be applied to heavy cuts such as pitch and the 75%wt. p i t c h blend over the full temperature range involved; for lighter fractions, the correlation should not be used over the full temperature range and for extrapolation. Puttagunta et al. (1993) proposed a correlation which was shown by M e h r o t r a (1994) to be essentially the Walther equation. T h e correlation requires one viscosity data point at 30°C and was found by iteration for each o i l fraction. A s shown i n Table 3.4, the viscosity at this temperature is extremely high for fractions w i t h high p i t c h content and the A A D s show that the correlation is not well suited for the data.  Furthermore, no  compositional dependence or m i x i n g rule is provided, i m p l y i n g that one viscosity d a t u m is required for every new m i x t u r e (Mehrotra et al. (1996)). • Andrade and Vogel Equations A l l a n and Teja (1991) calculated the viscosity of several crude o i l fractions w i t h A A D s of 5-15% by using their Effective C a r b o n N u m b e r ( E C N ) approach to estimate the coefficients i n the Vogel equation. However, Gregory (1992) showed that the method gives an incorrect viscosity-temperature trend for E C N > 2 2 . Since the E C N values for the fluids studied were found greater than 22 and given the A A D s obtained (see Table 3.5), this form of the Vogel equation should not be used. T h e A n d r a d e equation was applied to model the kinematic viscosity of several crude oil fractions by A m i n and M a d d o x (1980) and B e g et al. (1988); overall A A D s between 5.5% and 11.1% were obtained.  A n average A A D of 10.6% was obtained for our data  but the parameters could not be generalized. Also, M e h r o t r a and Svrcek (1988) showed that an Andrade-type equation was inadequate to model the effect of temperature on the viscosity of bitumens. D u t t (1990) applied the Vogel equation to model the kinematic viscosity of crude o i l fractions using the 50% boiling point as the only input. W i t h parameter C obtained as per Tassios and Goletz Jr. (1977) and parameters A and B generalized, overall A A D s between 3.8% to 6.8% were obtained. T h e method was applied to C H G O using the S I M D I S T curve (see Figure B . l ) , but the data could not be fitted linearly. Also, the regressed constant C for C H G O i n Table 3.4 did not predict the 50% boiling point based on the Goletz-Tassios equation. Note that a S I M D I S T curve was not available for p i t c h as is usually the case  32  Characterization of Feed Materials for cuts having very few constituents w i t h B P < 5 5 0 ° C ( M e h r o t r a et a l . (1989)).  However, by fitting to the data the equation used by D u t t , the best average A A D of 5.4% was obtained w i t h a m a x i m u m of 10% as indicated i n Table 3.5. The parameters could also be generalized as w i l l be shown later. T h e correlated viscosities are shown as smooth curves i n Figure 3.3. • Other Correlations T h e correlations by Herschel (1922) and by L i t o v i t z (1952) were not retained as suitable equations for modeling the viscosity of pitch, C H G O , and their blends.  A l t h o u g h the  L i t o v i t z equation gave an average A A D of 10.8%, the parameters could not be generalized.  3.4.2  M i x t u r e Viscosity Equations  Several l i q u i d - m i x t u r e viscosity correlations are available for calculating the viscosity from the component viscosity data. Some of them require viscous interaction terms and are not applicable to b i t u m e n fractions (Mehrotra et al. (1989)). M o s t of the simple correlations for l i q u i d - m i x t u r e viscosity can be generalized ( R e i d et al. (1977)) as: n  /()«".) = £ s i J > ; )  (3-8)  J=l  where  f(/.i)  may be  (/i), (1/V), ln(/j,),  log(n),  etc., and  Xj  may be either of the liquid  volume, mass or mole fraction. A n equation proposed by M e h r o t r a et al. (1989) was applied to the calculated viscosities from the double-log equation. A similar approach was used w i t h the Vogel equation (Dutt (1990)). In b o t h cases, the A A D s were extremely high as seen i n Table 3.5 and the approach was abandoned.  T h e results achieved by M e h r o t r a et al. (1989) were also i n  that range.  3.4.3  G e n e r a l i z a t i o n of Parameters  A generalization of parameters was attempted w i t h the A n d r a d e and D u t t equations. T h e results were more successful w i t h the correlation used by D u t t (1990) as shown i n Table 3.5. Several generalizations were performed and they are summarized i n Table 3.6.  33  Characterization of Feed Materials  The best fits for parameters B and C were obtained w i t h linear and quadratic functions of the weight fraction of pitch, respectively. T h i s was the only characterization parameter available for generalization.  For parameter A , the lowest average A A D of 9.3% was  achieved w i t h the t h i r d generalization, although the second generalization gave slightly lower A A D s for C H G O and the 25%wt.  p i t c h blend. T h e following model is therefore  recommended for the viscosity prediction of C H G O , p i t c h , a n d any blend of the two, especially for those w i t h a high pitch content:  Inu  B  = A+  T  +  (3.9)  c  (3.10)  A  =  -0.1885 • (InB)  + 1.3342 • InB - 1.6161  B  =  1463.08 • x + 131,2386  (3.11)  C  =  - 1 3 3 . 5 6 - x ' , + 179.93 • x„ - 31.56  (3.12)  2  p  2  Here x refers to the weight fraction of pitch, T is i n ° C , and v is i n m m / s . This model 2  p  covers a wide temperature range—up to 3 4 0 ° C — a n d accounts for the compositional effect. Figure 3.5 shows how well the data are fitted using these generalized parameters. Table 3.6: Generalization of Parameters i n D u t t Correlation. Generalization  Equation  Comments  1  A=-2.3458-z +0.1584  R =0.950  B=1463.08 x +131.2386  R =0.994  C=-133.5612 x- +179.93x -31.56  R =0.995  2  A=-0.9386 1nB+5.0524  R =0.958  3  A=-0.1885-(lnB) +1.3342 1nB-1.6101  R =0.993  p  p  2  p  2  2  2  2  2  2  34  Characterization of Feed Materials  Viscosity of Pitch, Coker Heavy Gas Oil (CHGO), and their blends (%wt. Pitch).  Temperature, °C  Figure 3.5: Kinematic viscosity-temperature data; fitted lines obtained with Equations 3.9 to  3.12.  Chapter 4 Development and Operation of the Fouling Unit  4.1  Original Apparatus  Initial experiments were performed w i t h the recycle flow loop shown i n Figure 4.1 which had been designed and installed by others (see Y u e and W a t k i n s o n (1998)). T h e test fluid was kept at a constant temperature i n a 2.5 L stainless steel stirred tank and heated by two ceramic elements. A gear p u m p for high temperature ( V i k i n g p u m p series 115, model G115, capacity of 1.8 U S G P M at 20 psi) driven by a 1/2 H P , 1750 R P M electric motor pumped l i q u i d through a test section consisting of a 1.10 m long vertically mounted 1/4 in. O . D . stainless steel tube (0.5334 m m I.D.). T h e test section was heated externally over 0.46 m of its length by a quartz sand fluidized bed surrounded by two ceramic heaters. After being heated during upflow i n the test section, the test fluid returned to the tank supply. W h e n necessary, a water cooler was used to avoid temperature build-up, and an in-line filter could be used for suspended solids removal. T h e first bypass configuration included a pressure relief valve and a needle valve i n series to prevent eventual pressure build up (e.g. i n case of blockage) and to allow the excess flow to return to the tank. T h e first tests and experiments carried out made it clear that the original design could not properly handle the viscous fluids studied nor reach the desired temperature conditions, and it exhibited several fluctuations that made the analysis of the results difficult.  A l s o , the design d i d not permit convenient verification of the flowrate and,  given the nature of these experiments, safety and data monitoring were inadequate. Therefore, instead of studying the effect of process variables on fouling, most of the experimental work i n this project has been devoted to improving the unit and evaluating its ability to generate fouling results. Several equipment malfunctions such as two pump failures and breakage of the fluidized bed heating system required rebuilding of parts of  35  Development and Operation of the Fouling Unit  b, out  Filter  Water Out  Vent  Supply Tank  Gear Pump  AR - Air Regulator FB - Quartz Sand Fluidized Bed P - Pressure Gauge R - Rotameter Tb - Bulk Temperature TS - Test Section * Fluid Bed Equidistant Thermocouples  BV OP PRV Rec. TC -  Bypass Valve Orifice Plate - Pressure Relief Valve - Receiver Thermocouple  Figure 4.1: Original Apparatus  Development and Operation of the Fouling Unit  37  the u n i t , and hindered the course of this project. T h i s chapter describes the unit i n detail and discusses the modifications made over the duration of the project.  It ends w i t h a  diagram representing the final state of the loop which summarizes a l l the changes made.  4.2  Liquid Flowrate Measurement  To provide a measure of the l i q u i d flowrate i n the test section which could verify the actual flowrate, a high temperature three-way valve (Swagelok, m o d e l # S S - 6 3 X T S 8 - F 8 ) was inserted downstream of the test section. A t the end of each r u n or during calibration of the orifice, the flow was diverted into a 1 L pyrex beaker. Initially, only a volumetric flowrate could be measured; since the quantity of liquid available is small, this leads to important inaccuracies i n the time and volume measured. A l s o , the flowrate measured i n this manner would have to be corrected to give the true flowrate, since the temperature i n the test section was higher than the temperature i n the beaker. These problems were solved when a digital balance ( A & D C o . , ser.# J8003182) connected to a computer was used to record the mass collected versus time; the mass flowrate measurement was obtained from the slope of a plot of weight versus time and required a small amount of liquid. T h e data acquisition was done using Lab Tech Notebook version 5.0.  4.3  Pressure Drop Measurement  Initially, the pressure drop across the orifice plate was measured by two silicone filled pressure gauges.  However, due to the high viscosity of the fluid studied, the gauges  were often blocked preventing pressure drop measurements to be obtained for flowrate estimation and monitoring. A new scheme involving a differential pressure transducer ( D P T ) was designed and implemented successfully.  4.3.1  Differential Pressure Transducer Design, Operation, and Calibration  T h e D P T (Omega E n g . , m o d e l # PX771-025DI) was connected to the orifice plate v i a two 1/4 i n . tubes which were wrapped w i t h heating tape to reduce the viscosity of the  Development and Operation of the Fouling Unit  38  fluid during the startup period. Zero differential pressure was set from the ball valve (Swagelok, m o d e l # SS-4P4T) connecting b o t h lines, while the two remaining ball valves allowed air removal through the sampling valves and prevented possible damage to the D P T from excess pressure. Since the D P T was incompatible w i t h the highly viscous fluids involved, the lines were filled w i t h coker heavy gas o i l which is less viscous than the test fluid.  D u r i n g filling, traces of air were removed using the D P T purge valve.  T h e D P T was factory calibrated and a linear relationship was used to convert the 4-20 m V output to 0-25 psid. T h e readings were confirmed by applying known pressure loads to the cell between 0 to 25 psid.  L i q u i d Flowrate Estimation  4.4  C o m b i n i n g the techniques described i n the last two sections provided a method to estimate the flowrate that proved reliable and accurate.  A relationship between mass  flowrate  and pressure drop was obtained. D u r i n g calibration, care was taken to ensure that the temperature conditions remained constant. D u r i n g the course of this study, two orifice plates were used.  T h e first eleven ex-  periments were done w i t h a 1/8 i n . diam. orifice plate (B—0.2); however, as no fouling seemed to form i n the test section, lower fiowrates were studied, requiring a 1/16 i n . diam. orifice plate (0=0.1) to be used for the remainder of the project. B o t h orifice plates were calibrated under the conditions of their use and the calibration curves are shown in F i g ures A . 2 and  A . 3 . A s seen on Figure A . 2 , the larger orifice plate gave two curves for  the same temperature conditions. T h e upper curve was discarded as measurements done at the end of some runs showed that the other was more consistent. T h e smaller orifice plate was calibrated under two operating temperature conditions and measurements at the end of some runs also revealed that both curves were constant.  4.5  T e s t Section and F l u i d i z e d B e d  The test section was a 1/4 i n . O . D . stainless steel tube 1.10 m long (0.01 i n . wall thickness T P 316/316 L Seamless, 0.5334 m m I.D.) heated by quartz sand particles (d =349 fj.m, p  39  Development and Operation of the Fouling Unit  density=2631 k g / m ) contained i n a 0.46 m longx0.05 m I . D . stainless steel cylinder. 3  Figure 4.2 shows the details of the fluidized bed and test section. T h e test section was replaced w i t h a new one for each experiment. Operating temperatures were obtained from two ceramic heating elements surrounding the cylinder and by preheating the air upstream of the air distributor. A i r flowrates were measured using a calibrated rotameter (Porter Instrument C o . , model # B-250-6) which has the calibration curve shown i n Figure A . l , and a pressure gauge was used to correct for the bed back pressure. A pressure regulator (Bellofram C o . , p a r t # 241-960-068, range 0-60 psi) was used to m a i n t a i n a constant air pressure to the rotameter.  4.5.1  A i r Distributor  Four 1/8 i n . O . D . stainless steel tubes having two 0.6 m m diam.  holes were used to  introduce the fluidizing air into the bed (see Figure 4.2). T h e pressure drop across the distributor was estimated using the following equation K u n i i a n d Levenspiel (1991) based on orifice theory:  where the orifice coefficient, C , or  Reynolds number, Re  v  is selected from a table as a function of the vessel  = D Up /p v  9  for the total flow approaching the distributor. T h e  g  results of these calculations are shown i n Table 4.1 for different air flowrates, ra >. AP^ist ai  represents a significant portion of the total pressure drop, or AP  t  According to Zuiderweg (1967), i n the early years of  fluidization  = AP  V  AP,  (g/s)  (psid)  Uor  (m/s)  APd,-„  AP ,t/AP di  t  (psid)  (%)  0.206  5.7  97.3  1.39  24.4  0.297  8.1  125.3  2.58  31.8  0.484  12.8  169.5  5.69  44.4  0.526  13.7  178.4  6.51  47.5  0.663  17.0  201.4  9.26  54.5  AP i . cyc one  engineering, rules of  Table 4.1: E s t i m a t i o n of Pressure Drop Across A i r D i s t r i b u t o r 771 air  +  Development and Operation of the Fouling Unit  Test section (1.10 m long) 0 0.635  Outlets for test section, air, thermocouples, and thermocouple wires  Swagelok sealing  A, B, C - 1/16" Type K thermocouples (top, middle, bottom respectively) D, E, F - 26 gauge type K thermocouple wires (Runs 16, 20, 23 only) Dimensions are in centimeters  Figure 4.2: Test section, fluidized bed, and air distributor.  40  41  Development and Operation of the Fouling Unit thumbs were followed, such as:  AP  dist  = (0.2 - 0.4) • AP  V  (4.2)  T h e current distributor clearly exceeds the design recommendation and the gas velocity at the nozzle, U , or  also exceeds the jet velocity from orifices i n commercial distributors (up  to 30-40 m / s ) . T h i s may result i n erosion and breakage of particles and an undesirable shift i n size distribution—see Chapter 4 of K u n i i and Levenspiel (1991)—, which i n turn affects the heat transfer (Molerus et al. (1995)).  4.5.2  Temperature Measurement and Control  For a l l experiments the temperature of the bed was measured by three 1/16 i n . chromelalumel thermocouples equally spaced (11.2 c m apart) i n the axial direction—see F i g ure 4.2. T h e uppermost thermocouple was 11.2 c m from the top of the bed. A l s o , each thermocouple was approximately 1.2 c m away from the test section, although vibrations of the thermocouples due to  fluidization  of the sand may have affected this distance.  Moreover, for Runs 16, 20, and 23, three additional thermocouples were silver soldered on the outside wall of the test section at the same axial positions as the three others to provide a measure of the wall temperature. T h e y consisted of 26 gauge type K thermocouple wires. T h e temperature of the air entering the bed was also measured. T h e bulk inlet and outlet o i l temperatures were measured by type K thermocouples located at each end of the test section. A n entrance length of 40 c m was provided to ensure a fully developed velocity profile i n the heated section. T h e bulk inlet temperature was controlled by keeping constant the temperature i n the supply tank using an analog proportioning controller w i t h a 5 ° C display resolution (Omega E n g . , model 49 controller). T h e fluidized bed temperature was controlled by the middle thermocouple w i t h the same k i n d of device which had a 10° C display resolution.  4.5.3  Modifications  As w i l l be discussed i n Chapter 6, evidence was obtained that a significant amount of deposit is formed when the flow of liquid is stopped at the end of a run, i f the  fluidized  42  Development and Operation of the Fouling Unit  bed is at a temperature at which batch coking is believed to occur. A successful technique used to avoid this p r o b l e m has been to cool the bed w i t h air before shutting down the pump. To shorten the cooling period, thereby reducing the chances of disturbing possible fouling deposits, a sand discharge was installed. It consisted of a stainless steel cylinder connected v i a a 1/2 i n . tube to a 1/3 i n . N P T hole drilled at the b o t t o m of the bed. T h e container was also provided w i t h an air outlet consisting of a piece of tube filled w i t h stainless steel wool. T h i s prevented ejection of hot sand dust from the sand discharge. T h e choice of the valve separating the sand discharge from the bed was complicated by the high temperatures involved (500-600° C ) . T h e difficulty was resolved by using a gas cock valve made of brass which had no plastic seal. Finally, since the temperature of the air entering the fluidized bed was found to fluctuate, an air mass flow meter (Matheson C o . , model 8160) was added for closer monitoring of the flowrate and to identify the cause(s) of the  fluctuations.  A voltage regulator (SL  Waber, type PC2400) was used after it was found that some of the  fluctuations  were  caused by variations i n the power supplied.  4.6  Data Collection and Loop Monitoring  Given the length of these experiments (24-60 hr), the addition of a data acquisition system to the original setup was clearly needed. To this end, temperature, differential pressure and mass flow meter measurements were sent to a Digitrend 235 datalogger (Doric Scientific) that converted analog signals from the measuring devices into digital signals.  These signals were then transmitted to a personal computer to be displayed  and saved at any specified time interval on the hard disk. A l l the measurements were also displayed on a local instrumentation panel that consisted of digital meters, selector switches, and pressure gauges. Due to the nature of these experiments and to an inadequate automatic safety system, during operation an operator was always present to monitor the apparatus. To improve the safety of the unit, an alarm device was designed, implemented, and tested. It consisted of a controller (Omega E n g . , m o d e l # C N 7 6 1 3 0 - P V ) which received an output from the differential pressure transducer. A n output from this controller was sent to a magnetic  Development and Operation of the Fouling Unit  43  relay switch which controlled power to the entire system except the controller itself. W h e n the pressure drop across the orifice plate exceeds the low and high a l a r m setpoints on the controller, the magnetic relay switch is opened and a l l power to the system is shut down. This protects the unit from overheating i n case of p u m p failure or o i l line blockage. If desired, the a l a r m can be bypassed.  4.7  Other Modifications and Final Apparatus  4.7.1  Initial Unsteady-State Period  One p r i m a r y objective of the fouling experiments was to measure i n i t i a l fouling rates. Since meaningful values can only be determined when the system is essentially at themal steady-state, care must be taken to reduce the initial unsteady-state period when the temperature set points have not been reached. This is especially valid for this unit w i t h constant surface temperature operation since the temperature of the deposit i n contact w i t h the liquid is decreasing as fouling forms. A t several times during this project, the insulation of the loop was improved to reduce the start-up period. Also, the amount of liquid added to the tank was increased from 2 to 2.5 L . T h e i n i t i a l unsteady-state period was further reduced by p u m p i n g the stream i n the bypass circuit only and diverting the flow i n the loop once the setpoint was reached. These changes caused the i n i t i a l unsteady-state period to drop from 200 minutes to reach 284° C to less than 50 minutes to achieve 300° C.  4.7.2  Liquid Flowrate Fluctuations  Throughout this project, a major and persistent problem has been to explain and eliminate important fluctuations i n the liquid flowrate which confound the heat transfer measurements. First, an air chamber was installed i n the bypass circuit to reduce the effect of pulsations caused by the p u m p on the pressure drop measurement across the orifice plate and to provide a readable measurement. Also, the original bypass design included a pressure relief valve (Swagelok, m o d e l # S S - 4 R 3 A 5 - A ) and a needle valve (Swagelok, m o d e l # S S - 6 N B S 8 - G ) i n series as shown i n Figure 4.1. T h e first pressure relief valve  Development and Operation of the Fouling Unit  44  (nominal cracking pressure range 50-350 psig) resulted i n pressures higher than what the p u m p could handle so that the excess flow from the pump could not return to the tank and damage was actually done to the p u m p . A more appropriate relief valve (Swagelok, m o d e l # S S - R L 3 M 4 - F 4 , cracking range 10-225 psig) was therefore installed allowing the excess flow to return to the tank and lowering the operating pressure i n the bypass circuit. In order to reduce the fluctuations i n the liquid flowrate, the bypass circuit was completely redesigned. T h e pressure relief valve and the needle valve were installed i n parallel. T h e effect of this modification on the results w i l l be discussed i n Chapter 6.  4.7.3  Viscosity Reduction  O n several occasions, the p u m p could not be started due to the high viscosity of the test fluid involved.  Heating tapes were installed around the bypass circuit and the tubing  upstream and downstream of the p u m p . T h i s section of the loop could be heated before starting the p u m p to reduce the viscosity of test liquid trapped i n this section of the loop which would otherwise prevent the p u m p from starting.  4.7.4  Volatilization  Finally, as higher feed temperatures were studied, a significant amount of i n i t i a l feed was volatilized from the tank vent. T h i s phenomenon led to an insufficient amount of l i q u i d left i n the loop and certainly changed the properties of the test liquid over the duration of the run. In order to m i n i m i z e this effect, a water condenser consisting of a 3/8 i n . tube in a 1.5 i n . pipe (shell) was installed vertically on the supply tank. T h e volatiles condensed on the wall and returned to the tank by gravity. A l l the modifications and additions to the loop described i n the preceding sections are summarized i n the diagram shown i n Figure 4.3, which represents the final state of the apparatus.  Development and Operation of the Fouling Unit  AR - Air Regulator DPT - Differential Pressure Transducer MFM - Mass Flow Meter P - Pressure Gauge R - Rotameter SD - Sand Discharge SV - Sampling Valve TC - Thermocouple * - Fluid Bed Equidistant Thermocouples  Figure 4.3:  C - Condenser FB - Quartz Sand Fluidized Bed OP - Orifice Plate PRV - Pressure Relief Valve Rec. - Receiver ST - Surge Tank Tb - Bulk Temperature TS - Test Section  Final Apparatus  Chapter 5 Experimental Procedures  5.1  Thermal Fouling Measurements  A fouling experiment involves three major steps which are: the preparation of the test fluid, the acquisition of thermal fouling measurements, and the cleaning and preparation of the fouling unit for the next fouling test. For each fouling experiment, 2.5 L of test fluid is prepared; for obtaining the 50:50%vol. p i t c h - C H G O blend, 1339 g of pitch is broken i n small pieces and 1252 g of C H G O prewarmed on heating plates is poured on top of the pitch. T h e blending is perfomed i n pyrex beakers placed under a fume hood on heating plates. T h e m i x t u r e is made homogeneous by stirring and when it is fluid, it is then poured into the feed tank of the fouling unit. T h e next morning, i n order to lower the viscosity of the test fluid, the feed tank heaters are turned on, the feed tank stirrer is set to low speed (percent speed=20), and the feed tank temperature controller is set to the desired setpoint. T h e speed of the feed tank stirrer is subsequently increased to 60 when the viscosity is reduced to facilitate heating of the test  fluid.  W h i l e the m i x t u r e is being heated, the power to the air preheater is  turned on and the air flowrate to the fluidized bed is set to a suitable value which depends on the bed temperature.  T h e power to the fluid bed heaters is also turned on and the  temperature controller is set to the desired value. A t the same time, the power to the heating tape surrounding the tubing located between the feed tank and the bypass circuit is turned on i n order to lower the viscosity of the test fluid trapped i n this section of the loop. It is heated for one hour allowing the temperature to reach 150°C. T h e power to the heating tape is controlled v i a a variable autotransformer which is adjusted manually. T h e n , the data logging system is started and sampling of a l l the measurements is made every five minutes. W h e n the bulk temperature i n the feed tank has reached the setpoint, 46  Experimental Procedures  47  the p u m p is started w i t h both the needle valve i n the bypass circuit and the needle valve upstream of the orifice plate completely opened. T h e power to the heating tape discussed above is turned off and the power to the heating tape surrounding the tubing to the D P cell is turned on. A temperature of about 100° C is maintained by means of the same variable autotransformer. T h e n , the ball valve connecting the two D P cell lines is opened and closed to obtain a value of 0 psid across the orifice plate. W h e n the liquid m i x t u r e trapped i n the D P cell lines is fluid, each of the two purge valves between the orifice plate and the transducer is opened i n turn to remove traces of air, and then closed. A t that point, about 200 m L of test fluid is taken from either of these purge valves which w i l l constitute the ' i n i t i a l sample'. T h e n , the two ball valves between the purge valves and the D P cell are opened for the rest of the run i n order to create a pressure drop signal. Once a reading is obtained, the needle valve upstream of the orifice plate is then adjusted to get the desired pressure drop across the orifice plate which corresponds to a known liquid flowrate according to a calibration curve (see Figures A . 2 and A . 3 ) . F r o m that moment, the test fluid circulates i n the unit for 24 hours on average while the process variables are maintained constant. Towards the end of the run, a digital balance covered w i t h a sheet of asbestos wrapped i n a l u m i n u m foil is placed under the three-way valve of the unit. T h e balance is connected to the computer and the software Labtech Notebook 5.0 is used to record the weight collected every second. This requires the data logging program for the thermal measurements to be stopped first since each program uses a different operating system. T h e n , a 1 L pyrex beaker is placed on the balance, the flow is diverted from the three-way valve until about 300 m L of liquid has been collected, and the data are saved in an A S C I I file. - After that, the fluidized bed and the feed tank heaters are turned off.  W h e n the  fluid bed temperature has dropped below 260°C, the p u m p is shut down. It should be mentioned that for the first seven experiments, the p u m p was shut down at the same time as the fluid bed and the feed tank heaters. F r o m R u n 22 onwards, the hot sand was dumped into a sand discharge to improve the cooling process. Finally, the power to the unit is shut off and the air flowrate to the fluid bed is closed. A p p r o x i m a t e l y 200 m L of test fluid (the 'final sample') is taken from the feed tank through the needle valve located  48  Experimental Procedures  below the tank and the rest is discharged into pyrex containers. T h e fouling data are saved i n an A S C I I file. In the next stage, the test section is removed and replaced by a new one. Also, the sand left i n the fluidized bed and collected i n the b i n below the cyclone is removed and 1000 g of sand are added to the fluidized bed. T h e unit is then re-insulated and is ready for the next fouling experiment. T h e spent sample collected i n pyrex beakers is disposed in suitable containers and the pyrex beakers are washed w i t h solvents under the fume hood. W h e n a different test fluid is to be studied, the unit is washed w i t h toluene and subsequently dried w i t h ambient air.  5.2  Toluene Insoluble Formation and Deposition Measurements  A clean glass liner is weighed and then about 1.5 g of the i n i t i a l sample is placed i n the glass liner. T h e glass liner w i t h its sample is then weighed again and submerged i n a sealed flask w i t h 100 m L toluene without agitation for 16 hours. T h e resulting suspension is filtered through a 0.2 /zm G e l m a n Science TF-200 (Teflon) filter at r o o m temperature using a vacuum provided by a water aspirator as described by Sanaie (1998). T h e glass liner and flask container are then flushed w i t h 50 m L toluene i n order to remove any possible adhering insolubles, and the resulting suspension is also filtered through the same filter. T h e wall of the glass funnel containing the suspension is also flushed with toluene and the residue on the filter is washed w i t h toluene u n t i l the filtrate becomes clear. T h e n the filter and its residue are removed from the filtration system into a watch glass using a forceps, and dried for 16 hours at 90°C i n air at atmospheric pressure before weighing. Also, after removing the filter from the filtration system, any possible residue stuck to the glass funnel is scraped and added to the residue on the filter i n the watch glass prior to drying.  These precautions ensure that all the solids precipitated by the  toluene are collected on the  filter.  T h e solids left on the filter are termed the toluene  insolubles ( T J ) , or coke. T h e same procedure is applied to the final sample. Following a fouling experiment, the inside of the test section is soaked i n toluene for about 16 hours and the suspension is then filtered according to the same procedure as given above. W h e n the test section is dried, the inside of the test section is scraped w i t h  Experimental  49  Procedures  stainless steel wool to collect any possible residue stuck to the wall of the test section. This material is added to the residue on the filter used to filter the suspension from the test section. T h e solids thus obtained are termed w and represent the amount of coke c  present at the end of a r u n i n the whole test section, which includes b o t h a heated and a non-heated portions. Note that the insolubles obtained i n the runs perfomed w i t h the 75 wt.% F O - 1 0 wt.% H O - 1 5 wt.% D A O blend were measured according to the same method except that varsol was used instead of toluene. T h i s is because the deposits obtained w i t h such a m i x t u r e are of asphaltene-type, which are soluble i n toluene, not i n varsol. After draining the varsol from the test section, it was flushed w i t h acetone.  Chapter 6 Results and Discussion  Throughout this project, twenty fouling experiments were performed i n which the coke formation and deposition tendencies of a mixture of p i t c h and coker heavy gas o i l (50:50% vol.) were investigated by changing the surface temperature of the test section, the bulk temperature of the test fluid, the fluid velocity, and the recirculation time. For each run, the fouling process was measured by thermal measurements and the final amount of deposit was evaluated by weighing the mass deposited inside the test section; the change i n the toluene insolubles content of the test fluid, which represents the coke precursor concentration, was also measured.  T h e results w i l l be presented i n the first  section. In several runs, interpretation of the thermal fouling measurements was confounded by the sensitivity of the measurements to fluctuations i n process variables. A n analysis of the variations i n the latter w i l l be given to provide an understanding of the unit behavior, and to eliminate their effects on the thermal fouling data.  T h e effects of a series of  improvements to the high temperature fouling unit are also illustrated. The effect of the air flowrate and temperature on the heat transfer coefficient i n the fluidized  bed  was also investigated.  T h e data obtained w i l l be compared to different  semi-empirical models taken from the associated literature i n order to discuss the possible factors that may have affected the heat transfer during the experiments. A l s o , the heat transfer coefficient on the l i q u i d side was calculated i n order to check the consistency i n the measurements and w i l l be compared to predictions from available correlations. Finally, to assess the ability of the unit to detect fouling by thermal measurement, three experiments were carried out w i t h a known fouling fluid. T h e results w i l l be given and discussed.  50  51  Results and Discussion 6.1  Fouling Tendency of 50:50%vol. Pitch and C H G O Blend  6.1.1  Summary of Fouling Runs  T h e conditions of temperature, mass flowrate (m i>), fluid velocity i n the test section (v b), c  c  recirculation time (t ) and flow regime investigated (Re b) are summarized i n Table 6.1. r  c  Table 6.1: S u m m a r y of variables investigated i n fouling experiments w i t h a 50:50%vol. blend of p i t c h and C H G O and w i t h F O - H O - D A O b l e n d . 1  Run no.  Tin  (°C)  CC)  ATb  Tb  Vcb  tr  rhcb  (°C)  (°C)  (m/s)  (min)  (g/s)  Re b c  s.s.  Q  1/Uo  (min)  (kW)  (m -K/kW)  (°C)  2  AT  i m  1  520  196  7.0  198  1.61  1560  33.1  559  85  0.64  4.4  311  2  514  277  7.7  280  1.09  730  21.1  1039  200  0.40  5.3  233  3  503  245  4.5  247  1.70  740  33.8  1159  265  0.36  6.3  246  4  507  286  9.5  290  0.81  1070  15.6  849  216  0.40  4.1  180  5  499  288  4.1  291  2.31  972  44.5  2395  55  0.46  4.2  208  6  503  290  3.9  292  2.36  1057  44.5  2490  75  0.45  4.4  212  7  507  277  14.7  285  0.63  887  12.2  632  100  0.48  4.3  226  8  498  291  4.4  293  1.57  646  30.2  1690  100  0.34  5.7  203  9  503  284  13.1  291  0.69  917  13.3  731  75  0.42  4.7  215  10  502  277  19.9  287  0.48  762  9.2  487  55  0.43  4.6  216  11  502  281  16.3  289  0.48  1085  9.2  522  85  0.42  4.7  214  12  501  286  19.0  295  0.43  762  8.3  469  70  0.39  4.8  207  13  600  289  18.8  298  0.83  1123  16.0  935  120  0.75  3.7  304  14  598  282  34.1  300  0.41  1148  7.9  470  200  0.63  4.4  299  15  508  199  15.4  207  0.79  2009  16.1  311  200  0.56  4.9  299  16  615  286  33.8  302  0.40  1122  7.7  465  355  0.62  4.7  313  17  601  286  31.2  302  0.40  3359  7.7  472  300  0.59  4.6  300  18  596  329  31.0  346  0.36  3353  6.6  563  300  0.51  4.5  250  19  236  87  16.6  95  0.31  1304  5.8  206  166  0.19  6.8  139  20  449  95  73.4  132  0.17  1889  3.2  266  300  0.50  5.9  317  21  444  107  25.4  120  0.68  2019  12.7  813  200  0.66  4.5  323  22  612  348  25.6  358  0.45  2059  8.3  762  200  0.50  4.4  240  23  615  363  25.3  375  0.44  1720  8.0  824  200  0.51  4.3  238  'Only Runs 19, 20, and 21 were performed with the 15% DAO-10% HO-75% F O blend.  52  Results and Discussion  The fluidized bed temperature reported, T/b, refers to the temperature in the sand which is not the same as the wall temperature. This fluidized bed temperature is the average of the three axial temperature measurements described in Section 4.5.2 and is calculated after the time the system takes to achieve thermal steady-state (S.S.). The average bulk temperatures of the test fluid entering and leaving the test section, T  t n  and T , are out  also calculated at steady-state and Tb represents the bulk average temperature in the test section, which is the average of T{ and T . ATb is the average bulk temperature n  out  difference across the test section, calculated at steady-state.  The average heat flow,  <3, the average inverse overall heat transfer coefficient, 1/U , and the average log mean Q  temperature difference, A T / , are also calculated at steady-state. The equations used to m  calculate these parameters are given in Appendix D.6. Finally, the mass flowrate, the fluid velocity, and the Reynolds number in the test section are based on the calibration measurement performed at the end of each experiment. Since one of the objectives was to establish the conditions at which significant fouling is formed, the approach adopted in the experiments was to vary the process variables in the direction in which fouling formation is believed to increase. As a result, the fluid bed temperature, the bulk temperature and the recirculation time were increased, while the velocity was decreased. For the first experiments, the average fluid bed temperature was around 500°C. As no significant fouling was observed, the temperature was increased to its maximum value of 600° C for most of the remaining runs. The average bulk temperature in the test section was set initially at 198° C and was subsequently increased to around 290° C for the majority of the runs.  Since no significant fouling was detected, it was  further increased reaching 375°C in the last experiment. Moreover, the velocity in the test section was varied from 0.2 to 2.2 m/s and the flow regime was laminar for all runs. Since Q was determined from the temperature rise of the oil, AT},, if flowrates were too high, and ATb was too low, then Q would be subject to significant error. As shown for Run 6, at Re=2490, AT was around 3.9°C. Higher velocities (turbulent flow) would b  have resulted in an even smaller AT which might not have been accurately measured, b  given a resolution of one decimal place. It is also generally accepted that reducing the fluid velocity increases the fouling tendency (see Chapter 2), hence reducing velocity was  53  Results and Discussion desirable for detecting fouling.  6.1.2 Toluene Insolubles Measurements For fouling involving coking reactions, the amount of coke precursor in the test fluid and its change with recirculation time may provide clues for an understanding. For each run, the coke precursor content in the initial and final sample was measured as explained in Chapter 5. From the knowledge of the weight of the sample and that of the coke, the concentration of coke is expressed as TI=  Weight of coke recovered — *100 b ample weight  (6.1)  Inorganic mineral matter in the fluid will contribute to the toluene insolubles as defined above. The yield of coke is then given by (TI — TI ), 0  where TI  Q  is the value of TI at  time zero. Upon heating of these blends, a fraction of the initial test fluid is lost due to a combination of evaporation and bond-breaking with volatilization of light fragments, this effect increasing with the severity of conditions. This weight loss, or volatile yield, is calculated as V =  Initial total weiqht — Final total weiqht — ; —, — * 100 Initial total weight  (6.2)  For the heavy gas oils, evaporation is expected to be a major factor, given the boiling curves shown in Figure B . l . For pitch, little evaporation is expected at the temperatures investigated, and volatilization of light reaction products will dominate. Watkinson et al. (1998) carried out batch heating experiments on 50:50% vol. pitchvirgin gas oil blends in order to determine the kinetics of coke, precursor formation. Their TI and weight loss results are reproduced in Figure 6.1 to show how those important parameters are affected by temperature and reaction time.  For all runs in the present  work, except one, the amount of volatile matter released was not measured and, as a result, the toluene insolubles are given in terms of the weight of the final sample. To provide a more suitable basis for comparison, the toluene insoluble results of Figure 6.1 are also shown on the basis of the final sample weight. Note that from Figure 6.1c, 250  54  Results and Discussion  (a) Experimental volatile yield for the blend of 50:50%vol. pitch-virgin gas oil. I—  60 - A "  50  -O-  380  •  1  j  _ _ _ _ _  °C  -O  400°C  40 •  ; 30 20  -  .^.rr.A.-^.r-:.  A - . - . - .  \^&-' o •-~• ~Ar  10 0 (  \  \  i  50  100  150  —I 250  200  Time, min . , , (b) E x p e r i m e n t a l T l % i n t e r m s o f t w o s a m p l e w e i g h t b a s i s ( s a m e b l e n d ) . 1  20  15  :  1  - ° -  Initial W t . B a s i s , 4 0 0 ° C  - x -  Final Wt. Basis, 4 0 0 ° C  -A-  Initial W t . B a s i s , 3 8 0 ° C  -O-  Final Wt. Basis, 3 8 0 ° C  1  1  X  0  :. .  5  :  D-.  - - " : _ - a - - ~ ~~ •'  He -  0  -«» n =ipS = _ = =,= =  =c2=  = = = = = = = =S= = = = = = = = =& T  250  200  150  100  50  Time, min , , (c) S a m e a s F i g u r e (b); y a x i s e x p a n d e d .  (  1  1  1  Initial W t . B a s i s , 3 8 0 ° C  1.4  -O-  Final Wt. Basis, 3 8 0 ° C  1.2  Or A - ' - —A- "  0.8  0.6  50  i  i  i  100  150  250  200  Time, min . , (d) E x p e r i m e n t a l T l % v s . v o l a t i l e y i e l d i n t e r m s o f t w o s a m p l e w e i g h t b a s i s ( s a m e b l e n d ) . 20  15  •  r —••  I  -O-  Initial W t .  Basis  - x -  Final Wt.  Basis  / / /  :  1  /  0  /  /  rr  5 i  10  ©  (9  r®= = = = & = 20  30  Figure 6.1: B a t c h coking experiments of 50:50%vol. Expts. Yue (1998).  _.---©" 40  50  60  P i t c h and V i r g i n Gas O i l B l e n d —  55  Results and Discussion  minutes of heating at 380°C results i n T / = 0 . 9 0 % and, w i t h T70=0.77%, a coke yield of about 0.12%. W h e n the toluene insolubles are plotted against volatile yield i n Figure 6.Id, all data calculated on the same sample weight basis collapse to a single curve. Similar results were also observed for gas oils, pitch, and other mixtures of gas oils and p i t c h i n the range 3 6 0 - 4 0 0 ° C . For pitch, it was noted that toluene insolubles formation only starts after a 23%wt. loss has been reached for any of the reaction times and temperatures investigated. For the 50:50%vol. p i t c h - V G O mixture, the TI appears to increase when about 30%wt. loss has been reached, as shown on Figure 6.Id. Table 6.2 contains the toluene insoluble weight percent for the i n i t i a l and final test fluid samples for all runs performed as part of this thesis. T h e same results are shown i n Figure 6.2 as a function of recirculation time, t . r  T h e outliers are attributed to difficulties  i n the filtration procedure or contamination of the unit w i t h toluene. The 95% confidence  Tl% versus recirculation time, t T"  T"  16 14 12 10  o • x + A V 0  023  initial sample Outliers T„ =498-520°C; T. =196-291 °C in  ID  T =598-615°C; T. =282-289°C to 'in T =596 C; T. =329°C fb in T =612 C; T. =348°C fb „ in T =615 C; T. =363°C m  lb  V22  . Q. r •>*  500  14 16, 3 x.#*:::: to 12 1000  15 . .x..  95% Confidence interval  •A-  18, 17]  .•"I  1500  2000  2500  3000  3500  t , min  Figure 6.2: Toluene insolubles content based on actual sample weight versus recirculation time for all runs (50:50%vol. pitch and C H G O blend).  56  Results and Discussion  interval on the average initial TI content is given where the errors were assumed N(0, cr ). 2  T h e batch coking data of Figure 6.1 d i d not permit prediction of the volatile yields i n the current work i n order to present the toluene insoluble results for the final sample o n the basis of the weight of the initial sample. F o r that reason, the confidence interval given cannot be directly applied to the data of the final sample. However, it can be expected that the TI i n final sample would be lower i f they were reported i n terms of the weight of the i n i t i a l test fluid sample. Table 6.2: Toluene insolubles content i n the initial and final test fluid for a l l runs. Run no.  f  *TI  final  Run no.  tlinitial  *77final  (%wt.)  (%wt.)  11  1.44  1.36  1.62  12  1.35  1.21  n.m.  1.21  13  1.27  1.49  4  n.m.  1.46  14  1.25  1.26  5  n.m.  1.20  15  1.44  1.22  6  n.m.  1.30  16  1.27  1.30  7  n.m.  1.05  17  1.45  1.07  8  n.m.  0.84  18  1.29  1.02  9  1.36  0.98  22  1.46  9.87  10  1.29  1.08  23  1.08  16.07  (%wt.)  (%wt.)  1  'n.m.  0.50  2  n.m.  3  n.m.:not measured; 'calculated based on actual sample weight.  T h e TI measurements i n the present work are consistent w i t h the experimental data given previously i n Figure 6.Id. T h e recirculation times were 3 to 14 times longer than the m a x i m u m reaction time of four hours i n the batch coking experiments, however the bulk temperatures were markedly lower. In R u n 22, 23%wt. weight was recovered by condensation.  of the i n i t i a l test fluid  T h i s amount is lower than the total volatiles  actually released since part of i t could not be condensed. T h e data therefore suggest that substantial toluene insolubles formation only starts after a critical volatile yield close to 30%wt. has been reached for any reaction time and temperature.  A s long as a lesser  amount of volatiles has been released, no significant increase i n the toluene insolubles w i l l occur. Finally, i n 7 cases out of 10, a small decrease i n TI was observed (see Table 6.2). So far, a reasonable account for this has not been found.  Results and  6.1.3  57  Discussion  Mass Deposition Measurements  T h e total amount of coke left i n the test section (heated and non-heated sections) at the end of a run, w , was measured for each run as explained i n Chapter 5. T h i s amount c  comes from any coke present i n the oil residue left on the wall of the tube, and any solid or semi-solid coke-like material formed as a result of fouling. For the first seven runs, the fluidized bed was not cooled down before shutting down the pump.  Also, for Runs 9 and 14, the pump was stopped during the run for a few  minutes because of problems w i t h the pump or the fluidized bed. F r o m R u n 8 onwards, the  fluidized  bed was cooled down to approximately 260° C before shutting down the  pump; to further help the cooling process, a sand discharge was added from R u n 22. T h e results, shown i n Table 6.3, are therefore separated according to the fluid bed cooling procedure used. Table 6.3: Coke collected i n test section and equivalent liquid thickness which would give rise to w . c  Cooling  No cooling Run no.  Run no  Wo  (mg)  (mg) 1  49  516  8  2  13  2  13  42  10  6  29  3  63  274  11  5  19  4  392  414  12  18  78  5  58  255  13  10  35  6  34  138  15  18  78  7  185  928  16  14  56  9  237  1274  17  10  51  14  684  2859  • 18  3  16  22  67  36  23  262  86  Except for the last two runs, the major difference i n the magnitude of the amounts of coke collected appears to be explained i n terms of the fluid bed cooling procedure used. The data suggest that a significant amount of coke is formed if the fluid bed is not cooled  58  Results and Discussion  down properly when the flow of o i l has stopped. F r o m the batch coking experiments (see Watkinson et al. (1998)) and from the knowledge that there is always a certain amount of residue left i n the test section once the pump is stopped, i t is concluded that most of the amounts of coke shown i n the left hand side of Table 6.3 come from batch coking reactions i n the residue left on the tube wall. Therefore, these results cannot be attributed to fouling and w i l l be discarded for the rest of the analysis. In order to evaluate the amount of coke formed as a result of fouling i n the remaining runs i t is useful to take into account the toluene insolubles i n the final sample.  If we  assume that w comes exclusively from the residue left on the tube w a l l , an equivalent c  liquid thickness which would give rise to w mg of coke may be calculated: c  X  where  p  r e s  r  e  s  =  TV „ r i- * final • presKUiL  is the density of the liquid residue which was calculated at 20° C from E q u a -  tion 3.2 and L is the test section length (=1.10 m ) . T h e values of w and x c  res  on the right  side of Table 6.3 are shown i n Figures 6.3a and 6.3b as a function of total recirculation time. It can be observed that no significant increasing trend i n w exists. For fixed T , c  b  Tfb, v, etc., it can be expected that a longer recirculation time would result i n a higher amount of coke accumulated on the surface. Runs 16 and 17 differ only by their recirculation time as shown i n Table 6.1 but show no significant difference i n their w values. c  Also, F i g u r e 6.3a indicates that, except for the last two experiments, a l l runs resulted in approximately the same low w value. A s for x , the values shown on the right hand c  res  side of Table 6.3 are reasonable when compared to the tube diameter (Z),=0.533 cm) and do not differ significantly from run to run as shown i n Figure 6.3b. If the residue layers present on the tubes at the end of the runs had such thicknesses, then the higher w values c  of Runs 22 and 23 were due to the TI content i n the final sample and not to a larger amount of fouling.  T h i s idea is consistent w i t h the correlation found between w and c  TIfi, i shown i n Figure 6.3c. One could argue that Figure 6.3c may also suggest that the m  higher concentration of coke precursor in the fluid explains the higher amount of deposit on the surface. However, this would i m p l y for Runs 22 and 23 a different (thinner) residue layer on the tube, which is not reasonable. In addition, the small values of x  res  fact that they are scattered w i t h t suggest that the assumption behind x r  res  and the  is realistic.  59  Results and Discussion  (a) Toluene insolubles in test section at the end of runs vs. recirculation time. 1 1 i i  300  1  • 23  250 200 E  . 150 100 12 10  50  : D22  •"""16'  18, 17 d 15 _i 0 3500 3000 500 1000 1500 2000 2500 t, min. r (b) Equivalent liquid thickness at the end of runs which would give rise to w vs. recirculation time 8 •  • •  c  100  i  1  1  12  80 £  i  i  :15  •23  D'  • 16  60  •  x 40 • 10  :  D  • 17 : D22  13  18  20 8°  •  : 11  500  i  i  i  i  i  1000  1500  2000 t,r min.  2500  3000  3500  (c) Toluene insolubles in test section at the end of runs vs. toluene insolubles in final sample. I  I  !  j — . .  I  |  23p_  250 200 £ 150 5  100 2  50  2  Q  8, 10-13, 15-18 i  I  TLfinal„ %wt.  i  I  10  12  14  F i g u r e 6.3: Mass deposition measurement analysis; r u n number shown besides s y m b o l .  60  Results and Discussion  Consequently, these numbers suggest very little coke formation during recirculation. A s a consequence, no substantial effect of fluid velocity, bulk fluid temperature, fluidized bed temperature and recirculation time was observed. This conclusion is consistent w i t h the thermal fouling measurements which indicated no significant fouling.  6.2  Analysis of Variations in Liquid Flowrate  6.2.1  Experiments with Pressure Drop Measurement  Ideally, the temperature difference across the test section, AT},, should remain constant as long as no fouling has been formed. However, for several runs, this parameter exhibited severe flowrate.  fluctuations  and most of these variations were caused by  fluctuations  i n mass  Evidence of this was obtained by inspecting b o t h measurements as shown i n  Figure 6.4 for R u n 9 and from the relationship between A T ; , and rn which is shown in Figure 6.5 for several runs; ATt, and rn are average values of AT}, and m which are calculated, for a given run, over the same time interval. expected since for small changes i n ra, w i t h  T h e results of Figure 6.5 are  little affected,  U  0  is constant and  mCpATb  therefore AT), oc ( 1 / m ) . Figure 6.4 reveals that the change i n both measurements occurs at the same time and according to an inverse relationship which is consistent w i t h the results of Figure 6.5. T h e concept of cross-correlation can be used to measure linear dependence between two trends (time series). T h e cross-correlation function between two t i m e series {Y } and t  {Z } t  at lag k is given by  r  k  = xcorr(Y ,Z - ) t  =  t k  var(Y )var(Z - ) t  t k  n—k  YJXt-Y){Z . -Z) t k  r n  J  >  -  Yf  £ ( Z  •t=i  (6.4)  -j 1/2  n T  -  Zf  t=i  where ??. is the number of data points and Y and Z are mean functions. Values of r  k  near ± 1 indicate strong (linear) dependence.  If r =Q, then Y and Z k  t  t  k  are said to be  Results and Discussion  (a) Bulk t e m p e r a t u r e difference a c r o s s test section v e r s u s recirculation time. 1  0  100  1 200  1  1  1  1  1  400  500  600  1  300  1  1  Run 9 |  i 700  800  900  1000  t , min r (b) M a s s flowrate v e r s u s recirculation time; n o attempt m a d e to control m a s s flowrate. I  1-  1  1-  - Run 9 |  -•  1  100  200  300  400  500  1 600  700  800  900  1000  t , min  Figure 6.4: Fluctuations i n AT), caused by variations i n mass flowrate i n R u n 9.  Figure 6.5: Relationship between AT& and ra; lines from Equations 6.6 and 6.7.  62  Results and Discussion  uncorrelated. In order to apply this concept to the data, the assumption of stationarity needs to be reasonable. A time series {Z } t  is said to be stationary i f the mean function  and the variance are constant for a l l time. A n example of a non-stationary time series is given i n Figure 6.4. A common approach used to transform a non-stationary time series into a stationary one is to use the following transformation—called differencing:  AZ = Z - Z -i for t = 2,3,--- , n t  t  (6.5)  t  T h e cross-correlation function was calculated between ATb and rh and the above transformation was used when necessary.  T h e results are given i n Table 6.4 w i t h the 95%  confidence interval and Figure 6.6 illustrates typical results for a correlated and an uncorrelated t i m e series.  For the correlated cases, the negative value and the fact that  Table 6.4: Cross-correlation between ATb and m at lag zero. Run no.  ro  95% CI  Run no.  ro  95% CI  8  -0.01  0.19  16  -0.81  0.16  9  -0.10  0.15  17  -0.01  0.08  10  -0.45  0.17  18  -0.12  0.08  11  -0.88  0.14  19  -0.12  0.19  12  -0.91  0.17  20  0.03  0.19  13  -0.26  0.14  21  -0.61  0.19  14  -0.93  0.14  22b  -0.82  0.11  15  0.01..  0.10  23  -0.56  0.14  it is only significant at lag 0 is clearly consistent w i t h Figure 6.5 which shows an inverse relationship and emphasizes the above observation that the change i n both measurements occurs at the same time. T h e large negative cross-correlation values obtained i n some runs, such as 11, 12, and 14, are attributed to larger and/or more variations i n liquid flowrate.  It was observed that when attempts were made to control the flowrate, varia-  tions i n liquid flowrate were more important and more frequent than when no attempts were made. A t t e m p t s to control the flowrate were done i n Runs 11, 12, 14, 16, and 22b. O n the other hand, when the variation i n flowrate was too small, no correlation was found. In order to see whether the changes i n ATb w i t h respect to m observed i n each run are consistent w i t h the results of Figure 6.5, the run average values of ATJ, and m were  63  Results and Discussion  (a) Cross-correlation between mass flow and AT  (b) Cross-correlation between mass flow and AT . fc  fc  1i  1  ;  CORRELATE DAT LAG ZERO  UNCORRELATED;  0.5  0.5 95°lo Confidence limit  :  \  :  V7  35% ConficJence limit  -0.5  -0.5 -1 -10  Run 8 : -5  0 5 Time lag, 5 min.  -1 -10  10  Run 16 \ -5  0 5 Time lag, 5 min.  10  Figure 6.6: Cross-correlation function between AT& and ra for Runs 8 and 16. fitted to the following equations which are shown as lines i n the same figure for the two fluidized  bed temperatures: AT(, 5oo°c ]  173.1 • ra 156.0-ra  -1.02  (6.6)  -0.77  (6.7)  The power-law equation was chosen since ra-ATft is expected to be approximately constant. The temperature difference, AT},, and ra were plotted against each other as shown i n Figure 6.7 and the slope was compared to the first derivative—with respect to Equation 6.6 or  6.7. The results are shown i n Figure 6.8.  ra—of  For both bed temperatures,  the results are quite consistent given the errors i n the fitted curves and i n the i n d i v i d u a l runs. It must be taken into account that it was not the purpose of these experiments to  1  22  Bulk temperature difference across test section versus mass flowrate. 1 1 1 r i • Run 10 Linear fit; slope=-1.9454  -  :«i7^tM^v • ' . •  7.5  i 8  i 8.5  i 9 Mass fowrate, g/s  —*—j. i 9.5  10  Figure 6.7: Linear correlation found between AT), and ra.  10.5  64  Results and Discussion  First derivative of averaged AT with respect to averaged mass flow vs. averaged mass flow. fa  i  i o :  : :  8  O T =500°C A T =600°C T\=500°C ._. T =600C FB  (B  U  )B  °5  10  15  20  Averaged mass flow, g/s  J  25  I  30  35  Figure 6.8: Slopes of Equations 6.6 and 6.7 (lines) versus corresponding slope i n i n d i v i d u a l runs (symbols). obtain such relationships and therefore the data was not taken under perfectly controlled conditions. Based on these results, it appears that the variation i n ATb observed i n these runs may have been caused by flowrate variations.  6.2.2  Initial Experiments  In the early experiments (Runs 1-7), the flowrate was determined only by bourdon pressure gauges which measured A P across the orifice plate. Subsequently the D P cell was used. Because of frequent blockage i n the gauges and other problems, the flowrate was uncertain i n Runs 1-7.  T h e available pressure drop measurements i n R u n 1 revealed  that the observed drop i n ATb had been caused by an increase i n flowrate, as shown in Figure 6.9. Hence it was concluded that i n spite of the apparent increase i n the fouling resistance, Rf , c  no fouling had occurred. However, for Runs 4-7, no pressure drop  measurements could be made due to blockage of the pressure gauges. In order to recover useful data from these runs, attempts were made to correlate ATj, w i t h other parameters which could be related to the flowrate, rh. A measurement which was affected by the flowrate was the temperature difference between the temperature of the test fluid i n the tank and the bulk inlet temperature caused by heat losses, ATi . oss  Hence an attempt was made to relate A T /  o s s  to the mass  65  Results and Discussion  (a) Temperature difference across the test section versus recirculation time, t. 10  1  - T  -r  1  1  800  1000  ~r  I  -  8  O  6 |  O  Run 1  4 2  0  200  400  600  1200  1400  1600  (b) Thermal fouling resistance calculated with a constant flowrate value (RfJ versus t.. 1  1  1  1—  ;  1  1  :  :  .:  i a....:  5  o  9*-  2  | O  -  Run 1 |  DC  i 200  400  600  800  1  1  1  1000  1200  1400  1600  (c) Pressure drop across orifice plate versus t. ~> O  1600  Figure 6.9: Drop i n ATJ, i n R u n 1 caused by a flowrate increase. flow and to A T b in order to determine whether fouling or mass flow variations were the cause of the observed changes i n A T b . A T /  0 5 S  is the average value of A T /  o s s  which is  calculated, for a given run, over the same time interval as rh. A correlation was found between A T /  0 5 S  and m , as shown i n Figure 6.10a for a bulk inlet temperature of about  290°C. Figures 6.5 and 6.10a were then combined to provide a correlation between A T b and ATioss caused by the same underlying variation i n flowrate; the result is shown i n  66  Results and Discussion  Figure 6.10: Correlations found between A 7 }  o s s  , AT),, and m for Runs 4-11.  Figure 6.10b. Hence, the following equations were fitted to the data of Figure 6.10: ATi  =  oss  AT  6  142.21 - m  - 0  '  = 0.91 • AT  ATiossj =  loss  30.9-m"  (6.8)  8 4  - 2.07  (6.9) (6.10)  0 4 9  Equations 6.8 and 6.9 are valid for some of the runs performed w i t h the unit having its original insulation. T h e insulation of the unit was improved after R u n 11. E q u a t i o n 6.10 applies for some of the runs done after R u n 11. ATi  oss  was plotted versus the mass  flowrate and AT), for each i n d i v i d u a l r u n as shown i n Figure 6.11. T h e slopes obtained were compared to the first derivative of the above equations and the results are given in Figure 6.12. T h e slopes measured i n the individual runs appear consistent w i t h the  67  Results and Discussion  (a) AT,  (b) Bulk temperature difference across test section versus AT  versus mass flowrate.  26  .  25  23  Hun 10 Slope=-1.79°Cs/g ..  •  r  Jr  21  24  o  _i20  J23 5  .  Run 10 Slope=0 95  22  * «  o  |oss  22  19  21  18  20  8  8.5 9 9.5 Mass fowrate, g/s  :?.  I,.  !«•»  1:.  17 21  10  ..•*h<^  22  23 AT.  24 , °C  25  26  loss  Figure 6.11: Correlations observed between A T /  (a) First derivative of averaged A T  | O S S  0 S S  and tin and between AT  b  and A T ;  o s s  with respect to averaged mass flow vs. averaged mass flow.  0.5 0 O  of > > "D  £2  O  08  1 Derivative of Eq. 6.8 Individual runs; T =290°C, T =500°C b  (b  -0.5 -1 -1.5 -2 -2.5  5  10  15  20 Averaged mass flow, g/s  25  (b) First derivative of averaged A T with respect to averaged A T B  35  30  | Q S S  VS.  averaged  AT  | O S S  .  1.5  O  0.5  : 7 •:0  -©9  10  O  .4.  . .14  1 Derivative of Eq. 6.9 Individual runs; T =290°C, T =500°C s t  O -0.5 16  b  17  18  (b  19  21  20  22  23  24  Averaged A T  loss'  Figure 6.12: Slopes of Equations 6.8 and 6.9 vs. corresponding slopes i n individual runs.  68  Results and Discussion corresponding relationship. T h i s suggests that the drop i n AT  0  observed i n runs such  as 4 and 7 were caused by an increase i n flowrate. Figure 6.13 shows b o t h temperature differences versus time for Runs 4, 7 and 10. T h e preceding discussion revealed that i n R u n 10, the variation i n A T I was caused by a flowrate variation and Figures 6.13e and 6.13f indicate that this variation produced a similar effect on ATi . oss  T h e fact that the  change i n b o t h measurements for Runs 4 and 7 occurs at the same time and given the above comparison of slopes suggest that the variation i n AT  0  i n those experiments was  also caused by a variation i n flowrate.  6.2.3  A R M A M o d e l and Variable Flowrate Approach  In order to distinguish fouling from flowrate variations effects, a procedure was developed i n which two different techniques were applied to the data. Once pressure droj) measurements were available, the natural way to distinguish fouling from flowrate effects, which was applied to the data as a regular part of the work, was to calculate the heat flow (Equation 2.1) based on the actual flowrate. T h e effect of this approach is shown i n Figure 6.14. T h i s approach works as long as the change i n flowrate is such that rh • C ATb is approximately constant. W h e n the variation i n flowrate is too p  large, a significant change i n the heat flow occurs; an example of this is shown i n F i g ure 6.15 which is a plot of the average heat flow, Q, versus the average mass flowrate, rh. T h e increase i n heat flow w i t h mass flowrate shown for different fluid bed temperatures and two test fluids, is consistent w i t h the fact that the heat transfer coefficient (oil side) also increases w i t h the mass flowrate. T h i s phenomenon is believed to be responsible for the poor results of using a variable flowrate obtained i n R u n 10. F i g u r e 6.16 suggests that the drop i n flowrate (Figure 6.13f) was large enough to cause a significant drop in heat flow. Another technique used to distinguish fouling from flowrate variations consisted of modeling the temperature difference across the test section as a function of the pressure drop across the orifice plate, A P , and then using the model to compare the predicted AT& w i t h the true AT},. A s s u m i n g that the variations i n ATJ, were only caused by the flowrate, a significant deviation between the prediction and the data would indicate fouling. Since  Results and Discussion  b y  the model represents the process under clean conditions, the modeling step was done with the initial data where fouling had not yet occurred. A block diagram illustrating  Figure 6.13: Similarity of patterns in ATb, AT[  oss  and rh for Runs 4, 7, and 10.  70  Results and Discussion  (b) Heat flow (actual flowrate) vs. time.  (a) Heat flow (constant flowrate) vs. time.  0.38  200  400 600 t, min  800  400 600 t , min  200  1000  800  1000  Figure 6.14: Use of variable flowrate approach to reduce the effects of flowrate on Q; for Q , the flowrate value measured at the end of the run was is always assumed. c  Averaged heat flow vs. averaged mass flow for different fluid bed temperatures, 0.8  -i  1  1  1  1  1  ~  fl  14 0.6  20" A-  d 0 )  O)  V "  12 10  o_ _ e  0.4  a) > < 0.2  13  •21 •• ••  - A - T. ~126°C; T =450°C; DAO blend b  fb (1  - -O  ""••  1:1  0  - O - T =290°C; T =500 C, pitch/CHGO blend b  (b  _rj_ T =286°C; T <=600°C, pitch/CHGO blend b  (b  6  8 10 Averaged mass flow, g/s  12  14  16  Figure 6.15: Relationship between the heat flow to the test section and the mass flowrate.  71  Results and Discussion  AT(t) (true data)  AP(t)  Process Fouling Indication  v  Model Without Fouling  AT(t) (prediction)  Figure 6.17: B l o c k diagram of principle used to distinguish fouling from flowrate effects. this principle is shown i n Figure 6.17. T h e process was modeled according to an output error model structure ( A R M A ) which belongs to the category of black-box models (see e.g. B o x and Jenkins (1970) for more background):  AT (t)  = f ^ A P ^ + e(t)  b  F(q) = i + /i<r + --- + /n <r ' 1  n  /  B(q)  =  b.q-  1  + b q~ + • • • + b q- " 2  (6.11)  n  2  nb  T h i s model is a representation of linear time-invariant systems and was chosen for simplicity of identification and i n the absence of a well-founded physically parametrized model. T h e purpose of this model was to predict changes i n AT that occur over a relatively long b  period of time which are signals of low frequency.  Therefore, n and rij were taken as b  one. T h e parameters are given i n Table 6.5 and the application of the model is displayed in Figure 6.18 for three runs. T h e parameters were determined using a function called ' b j ' in M a t l a b © . T h e modeling data were taken up to 300 minutes where it was assumed that no fouling had occurred. T h e negative value of 6i indicates an inverse relationship between the flowrate and AT which is consistent w i t h Equations 6.6 and b  ures 6.18a and  6.7.  Fig-  6.18c clearly show that the variation i n AT i n Runs 9 and 13 can be b  predicted from the pressure drop data only; as a result, it can be said that no significant fouling occurred i n these experiments.  T h i s procedure gave excellent results for these  runs, but for some others such as 10, 11, and 12, the predictions were less satisfying (see  Results and Discussion  Table 6.5: Parameters regressed i n E q u a t i o n 6.11 for some experiments. Run no.  Modeling Data  Parameters  Error  (min) 9  10  11  12  13  45 - 301  35 - 301  40 - 301  100 - 300  75 - 301  Standard  bi = -5.3926  1.8  fi = -0.6307  0.15  6i =-22.1685  3.01  fi = -0.0202  0.13  6i =-11.2571  1.23  fi = 0.1601  0.11  6i = -1.2107  0.09  fi = -0.041  0.07  bi = -0.1161  0.04  fi = -0.9132  0.05  Figure 6.18e). T h e poor quality of initial data can give rise to incorrect predictions of ATJ, although no fouling is formed. If initially the data are not rich enough to cause significant changes i n A T b , the resulting model w i l l be inacurate and uncertain. T h i s is often the case i n fouling experiments since stability of variables is crucial. T h e greater uncertainty in parameter fi i n Table 6.5 for Runs 10 to 12 than for the other runs seems to explain the poor predictions obtained. A n o t h e r factor that can cause poor predictions m a y be non-linearities between ATI, and A P especially when large flowrate variations occur. T h e largest deviation between the predicted and measured ATb i n R u n 10 (see Figure 6.18e) at 400 minutes is attributed to this. T h e relationship between ATb  a  n  d A P observed i n  the modeling data does not represent the data properly outside the range of modeling data.  Results and Discussion  (a) Measured and predicted A"i" vs. time (Run 9). b  (b)Pressure drop across orifice plate vs. time (Run 9).  16 15 14 O o13 12  .  Measured Predicted Pred.± standard error  11 10  0  200  400  600  800  200  1000  (c) Measured and predicted A T (Run 13). b  22  400  600  800  1000  (d) Pressure drop across orifice plate vs. time (Run 13). 15 r  21 20 O 19 < 18 17  Measured Predicted Pred.+ standard error  16 15  0  200  400  600  800  1000  0  1200  (e) Measured and predicted AT (Run 10). fc  23  200  400  600  800  1000  1200  (f) Pressure drop across orifice plate vs. time (Run 10). 0.8 r 0.7  22  0.6  21  . 0.5 O  20  1:0.4  < 19  j  18  .  17 16 0  200  Measured Predicted Pred.± standard error 400  600  0.3 0.2 0.1  800  0  200  400  600  800  t, min  Figure 6.18: A p p l i c a t i o n of A R M A model to predict AT  b  based on A P .  Results and Discussion 6.2.4  74  Elimination of Fluctuations  F i n d i n g the source of the fluctuations i n flowrate discussed i n this section has not been straightforward. Several hypotheses were made as to what was causing them and several changes to the fouling unit were implemented to verify those hypotheses. For example, after observing a significant hysteresis problem, the orifice plate and the needle valve used to control the flowrate were replaced after R u n 11. T h e first bypass design consisted of a needle valve i n series w i t h a spring loaded pressure relief valve. D u r i n g operation of the unit, a fraction of the total flowrate delivered from the p u m p circulated i n the bypass line through the pressure relief valve. T h e fluctuations i n the flowrate were clearly related to the stability of the split fraction of the flowrate between the test section and the bypass. This split fraction depends on the resistance to flow i n both sections. After several runs w i t h this bypass configuration, it was postulated that the flowrate fluctuations may be caused by oscillations i n the spring of the pressure relief valve causing changes i n the resistance to flow i n the bypass section. Concerns about the design of the bypass circuit were also raised since liquid was not supposed to flow i n the pressure relief valve except under pressure surges (e.g. i n case of a test section blockage). In R u n 17, i n order to test this hypothesis, the needle valve and the pressure relief valve were therefore assembled i n parallel as described i n Chapter 4 so that no flow would circulate i n the relief valve under n o r m a l conditions and the excess flow would only return to the tank v i a the needle valve. In order to evaluate the change i n the stability of the flowrate after modifying the design of the bypass circuit, the standard deviation of the flowrate measurement was calculated for a l l experiments and the results are shown i n Figure 6.19. It can be seen from these results that for the first bypass design, the flowrate was more unstable in experiments w i t h lower flowrates. Also, except for the last two runs, it is clear that the new bypass configuration greatly decreased the flowrate variations and, as a result, the quality of the data was significantly improved. T h e improvement obtained supports the hypothesis formulated. For the last two runs, it is believed that the poorer stability of the flowrate was again caused by the pressure relief valve. T h e seals i n the pressure relief valve were made of viton which is rated for 204°C m a x i m u m and this was the highest  75  Results and Discussion  Standard deviation of mass flowrate vs. averaged mass flowrate for two bypass configurations. ...  !  i  !  !  r  *11  0  D  p  2 3  1918  20  D D  i  *io;  17  J  -0.2  •A- Initial bypass • Modified bypass  5  21 iI  iI  10  i 1  15 20 Averaged mass flow, g/s  L 1  1_ L  25  30  *s  Figure 6.19: Standard deviation of flowrate versus flowrate for two bypass configurations. rating available from the manufacturer.  N o w , the last two runs were done under the  highest bulk temperatures ever studied (358 and 375°C). It is therefore possible, i n those two runs, that the seals had reached a degradation state which allowed l i q u i d to flow through the valve, therefore causing the flowrate variations observed i n these runs.  6.2.5  Viscosity Effect  It has been shown i n Section 6.2.1 that a relationship exists between the  temperature  difference between the tank and the test section inlet temperature, A T j  , and rh as  o s s  shown i n Figure 6.10a. N o w , Runs 17 and 18 d i d not exhibit any correlation between and rh (see Figure 6.20). A l t h o u g h the data for these two runs indicate an increase  ATi  0SS  (a) A T,  (b) A T.  versus mass flowrate.  versus mass flowrate.  17  12 •  Run 18  Run 17  16  11.5 O  o S  15  \_r/.'v.  »14  11  i-  < 10.5  *TPi i iK 'I i T T *  • - i 10 7.5  7.55  7.6  7.65  7.7  6.2  7.75  6.6  6.8  Mass flow, g/s  Mass flow, g/s  Figure 6.20: Test for correlation between A T  6.4  .  / o s s  and m for Runs 17 and 18.  76  Results and Discussion in A T }  o s s  , which suggests a decrease i n flowrate, the flowrate measurement appeared to  be relatively constant, as shown i n Figure 6.21.  (b) A T, versus time. ' loss  (a) A T, versus time. ' loss v  v  11.5 O  " 11 n 1 1  10.5  500  (c) Heat flow versus time.  500  500  1000 1500 2000 2500 3000 3500  1000 1500 2000 2500 3000 3500 (d) Heat flow versus time.  0.58  500  1000 1500 2000 2500 3000 3500  1000 1500 2000 2500 3000 3500 (f) Mass flowrate versus time.  (e) Mass flowrate versus time.  1  i  |  1  Run 18 |  6.8  7.8  '.7.6  5  ' Si  _o  o  8  7.4 7.2  Run 17  500  1000 1500 2000 2500 3000 3500 t, min  Figure 6.21: A T /  o s s  6-4  6.2  1 500  1000 1500 2000 2500 3000 3500 t, min  , heat flow and mass flow measurements for Runs 17 and 18.  77  Results and Discussion  Now, the viscosity measurement for the i n i t i a l and final samples obtained at 80.4°C for several experiments indicates that these two runs experienced the greatest drop in viscosity as shown i n Figure 6.22.  T h i s viscosity reduction m a y be due to chemical  Dynamic viscosity ( 8 0 . 4 ° C ) of the 50:50%vol. p i t c h / C H G O blend vs. recirculation time (unsteady-state period substracted). 1  6  Q  —X  0  • 1400  9 10.... 10,12 J? 22..!.... a16 • 9 n  1200 £ =£  1000  •  13  12  D  ,  *  Contaminated  •  Final  • 15  11  : • . ; .17  *: 14  800JF 14  ,  Initial  600  .;ia.J  400  500  1500 t, min  1000  2500  2000  Figure 6.22: Viscosity drop during recirculation of test changes i n the liquid, called visbreaking (see Gray (1994)).  3000  fluid.  T h e mass flowrates were  calculated from the orifice plate equation: „  TTD*  /2pAP\  1 / 2  where C is the discharge coefficient, D h is the diameter of the orifice throat (= 1.588 x l O  - 3  t  m), p is the density of the test fluid, A P is the pressure drop, and 3 is a diameter ratio (= 0.1). T h e discharge coefficient was measured and the results are shown i n Figure 6.23. T h e data suggest a slightly decreasing trend w i t h Reynolds number and this is consistent w i t h the data reported i n Perry and Green (1984) for this range of Reynolds number. D u r i n g an experiment, a l l parameters i n E q u a t i o n 6.12 are expected to be constant such that the mass flowrate w i l l be constant too. However, if the viscosity drops during recirculation of the fluid, Figure 6.23 predicts that the discharge coefficient would decrease, thereby causing a drop i n the flowrate i f the A P was held constant. T h i s effect is i n agreement w i t h the observed increases i n A T )  o s s  i n experiments 17 and 18 (Figure 6.21) which suggest  a decrease i n flowrate. Since C is a non-linear function of Pe /,, as shown i n Perry and Green (1984), the data t  of Figure 6.23 were fitted to the following equation shown as a line i n the same figure  78  Results and Discussion  Orifice plate discharge coefficient (D =1/16", p=0.1) versus Reynolds number for the 50:50%vol. pitch/CHGO blend. 0.8  .Q..  0.7  o  O 0.6  Q18 0.5 0.4 10  10  Re.,  Figure 6.23: Discharge coefficient vs. Reynolds number for the 1/16" d i a m . orifice plate, only over the narrow range of Reynolds number that included these two experiments:  C  -0.287 • log(Reth) + 1-542 4m  Re h  (6.13)  TrpD v  t  th  Equation 6.12 can now be rearranged as:  m =  4m  - 0 . 2 8 7 • log-  TTpD U  1.542  [2pAP\  7T D th  1/2  (6.14)  th  The relative change i n m during a run can be expressed as:  rrif — mo rtif  - 0 . 2 8 7 • log  (^) (6.15)  - 0 . 2 8 7 • log (  +  1-542  where the subscripts 0 and / refer to initial and final respectively, and where p is given by Equation 3.2 and u by Equation 3.9 i n which A , B , and C are given i n Table 3.4 Q  for the 50:50%vol. blend (Dutt equation).  The corrected i n i t i a l viscosity at T , , fo.co n  was calculated by correcting the calculated initial viscosity at T,-„, fn,c> by a percentage obtained from the calculated and measured i n i t i a l viscosities at 80.4°C, Change . T h e cm  corrected final viscosity at T , , Vf , was calculated by correcting the corrected initial visn  cosity at Ti , i^o,cc, by n  a  iCC  percentage obtained from the measured i n i t i a l and final viscosities  at 80.4°C, Changeof. The results are given i n Table 6.6.  Results and Discussion  Table 6.6: Measured and calculated i n i t i a l and final viscosities for Runs 17 and 18. 80.4°C Run no.  T  VO, c  i n  Change  cm  Changeof  vo ,cc  Vf.cc  (°C)  (mm /s)  (mm /s)  (%)  (mm /s)  (%)  (mm /s )  (mm /s)  17  286  1196  1199  0.3  911  23.8  5.27  4.02  18  329  1611  1199  -34.4  345  78.6  5.08  1.09  2  2  2  2  2  'm: measured; c: calculated; cm: calculated to measured; 0: initial; / : final; 0/: initial to final; cc: corrected.  T h e value of the i n i t i a l flowrate, m , was searched by trial and error and a satisfactory 0  value was obtained by m i n i m i z i n g the absolute value of the difference between the left and the right hand sides of E q u a t i o n 6.15. T h e value of the final flowrate was measured at the end of each r u n . Table 6.7 gives the results of these calculations as well as the predicted change i n rn based on the change i n ATi , oss  * '°°°  Am  T  = {-^oJ-)  which is based on E q u a t i o n 6.10:  -{-^oJ-)  0  ( 6 f  -  1 6 )  Table 6.7: Predicted decreases i n flowrate i n Runs 17 and 18 based on two approaches. Run no.  LHS  RHS  |LHS-RHS|  17  -0.044  -0.044  4.46xlO  18  -0.251  -0.251  8.66xl0~  -10  10  m/  rh  0  Ami,  AmAT,,,,,  (g/s)  (g/s)  (g/s)  (g/s)  7.69  8.03  0.34  0.23  6.47  8.09  1.62  0.43  It can be observed that both methods predict a decrease i n flowrate. T h e deviation between these predictions may be partly due to uncertainties i n E q u a t i o n 6.10 which arise from an insufficient number of data used to derive i t . For R u n 18, the greater deviation m a y be attributed to the fact that the data i n R u n 18 are more noisy as seen on Figure 6.21. Also, E q u a t i o n 6.10 represents data obtained for a bulk temperature of around 286°C which is different from the bulk temperature i n R u n 18 (329°C). Moreover, the slope of the fitted line i n Figure 6.23 may be higher than the actual slope since, under the Reynolds number of R u n 18, the slope appears to be decreasing. T h i s is consistent w i t h the results reported i n Perry and Green (1984) which also exhibit a decreasing slope. A smaller slope would have resulted i n a smaller value of A???.„ for R u n 18.  80  Results and Discussion  Based on these results, it is possible that the drops i n viscosity i n these two experiments have caused a slight decrease i n flowrate and, as a result, the temperature difference across the test section increased. Since the flowrate is based on a pressure drop across an orifice plate, which was maintained constant, an apparent increase i n the heat flow was observed for these runs.  Consequently, it appears that monitoring and controlling the viscosity  during recirculation of these heavy hydrocarbon streams may be crucial for the correct interpretation of the fouling data.  6.3  Heat Transfer in a Bubbling Fluidized B e d  As discussed i n Chapter 2, i n order to estimate the relative importance of the different resistances between the fluidized bed and the flow of liquid inside the test section, three tests were performed i n which wall temperature measurements were made, as described i n Chapter 4. In Runs 16 and 20, measurements were obtained for a series of gas  flowrates,  but for R u n 23, only one gas flowrate was used. In this section, the experimental values of fluidized bed heat transfer coefficients obtained i n these tests w i l l be compared to the predictions of calculation methods introduced i n Chapter 2. A l s o , the characterization of the test fluids of Chapter 3 allowed the use of different correlations available to estimate the clean heat transfer coefficient inside the test section.  6.3.1  Heat Transfer Coefficient Around an Immersed Tube  T h e measured heat transfer coefficients for the three tests are compared w i t h the predictions of some of the correlations given i n Chapter 2 i n Figures 6.24 and  6.25. For Runs  16 and 23, only the correlation by Molerus et al. (1995) was tested. It is well known that in the intermediate range of 10 < Ar < 10 , h goes through a m a x i m u m at some inter2  5  0  mediate gas velocity, which is consistent w i t h our results (see e.g. K u n i i and Levenspiel (1991) and Molerus et al. (1995)). T h e decreasing h at higher superficial gas velocities Q  was attributed by K u n i i and Levenspiel (1991) to more contact time w i t h bubbles w i t h their low h values. T h e percentage deviation of the experimental h  0  from the predicted values is given  Results and Discussion  81  in Table 6.8 for the three experiments. The correlation by Vreedenburg (1960) deviates  Predicted (line) and experimental (symbol) heat transfer coefficient between surface and bed vs. excess gas velocity.  0.35  0.15 600  0.25  0.35  0.3  Calculated based on average bed and tube wall temperature.  Molerus etal. (1995) Molerus etal. (1995)  500  0.2  400  Calculated based on average tube wall temperature.  :  ^.300 o  O  :  :  O  ^ 200 100  0.05  0  0.15 0.2 U - Umf„ m/s  0.1  0.25  0.35  0.3  Figure 6.24: Measured and predicted h according to different methods for R u n 20. 0  Experimental and predicted (Molerus et al.(1995)) heat transfer coefficient versus excess gas velocity. 1200  —  1000  o  o  ^ 800 rature. | 600 _Bas.ed .on average, be d and.tube wall tern pe  •  *-^cf~v  • ° 400 c  —"  200 0  0  0.05  0.1  O  #16, h  V •  #23, ho.exp; Based on T..fb, ,topand T„fb,, bot , #16, h ; Based on T,. . and T..  ; Based on T. ,„„ and T..  o.exp  fb, top  o.exp  fb, mid  m i  Run 16; Predicted * Run 23; Predicted 0.2 0.25 0.3 0.35 U - Umf, m/s  0.15  fb. bot  0.4  fb, bot  0.45  (  Figure 6.25: Measured and predicted h according to E q u a t i o n 2.19 for Runs 16 and 23. 0  Results and Discussion  Table 6.8: E x p e r i m e n t a l and predicted h from various methods. 0  Molerus et al. (1995)  Measured Run  h  0  0  'Dev.  ho  Dev.  Vreedenburg (1960) h  Dev.  0  no.  (m/s)  (W/m K)  (W/m -K)  (%)  (W/m -K)  (%)  (W/m K)  (%)  20  0.0722  155  339  54  309  50  92  67  0.1274  233  435  46  280  17  179  30  0.2260  273  514  47  236  16  406  33  0.2453  278  519  46  227  22  459  39  0.3231  236  530  55  203  16  706  67  0.0248  309  266  16  0.0644  354  387  8  0.1152  438  489  10  0.1299  449  510  12  0.2282  430  589  27  0.2931  776  606  28  16  23 t T  h  Kunii and Levenspiel (1991)  J /: m  2  2  2  2  minimum fluidization velocity (see Appendix D.3); U - U / is excess gas velocity. 'Dev. is deviation. m  significantly from the data and does not predict a m a x i m u m as found i n their experimental data. Saxena (1989) attributed this deficiency of the correlation to an absence of a particle concentration term (1 — e). T h e correlations of Vreedenburg (1960) underestimated the data of V e r m a a n d Saxena (1983), the experimental values being about three times the calculated values. T h i s is not the case for the data of R u n 20. Note that the correlation by Wender a n d Cooper (1958), which was found by V e r m a and Saxena (1983) to reproduce their data best, could not be tested here because of a lack of information for the bed voidage, e. T h e deviations of experimental data from the model proposed by K u n i i and Levenspiel (1991) were smaller, although a m a x i m u m could not be predicted. T h i s may be attributed to the lack of data for the bubble frequency at various gas flowrates, n . w  The correlation by Molerus et a l . (1995) reproduced best the qualitative trend of the experimental data, although the values were significantly lower for R u n 20. T h e agreement for R u n 23 is much better. For R u n 16, the experimental coefficient, h „ , was obtained using two different sets of wall temperatures. Usually, the log mean temperature difference, L M T D , involved i n the calculation of h was based on the bulk inlet and 0  outlet temperatures and on the wall and the sand temperatures at the top and bottom  83  Results and Discussion  axial positions described i n Chapter 4. T h i s was the case for Runs 20, 23, and 16 (circle symbol). However, the temperature difference between the sand and the tube wall of the top axial position i n R u n 16 appeared to be too small compared to the other temperature drops observed. This is shown i n Table 6.9.  For that reason, the heat transfer  Table 6.9: Bed-to-wall temperature difference at three axial positions (Runs 16, 20, 23). #16  #20  #23  top  15  175  70  middle  180  210  40  bottom  100  220  84  Axial position  coefficient i n R u n 16 was recalculated using the middle and b o t t o m bed temperatures measurements.  T h e results, shown as squares on Figure 6.25, are more consistent w i t h  the predicted coefficient, h . T h e deviations now range from -6% to +27% which is quite 0  resonable given the accuracy of the available correlations. T h i s suggests that the wall temperature measurement at the top of the bed i n R u n 16 was not correct. T h e h values Q  for R u n 16 marked w i t h a circle are clearly too high. F r o m these results, it is suspected that the wall temperature measurement may not necessarily give the actual wall temperature. Three new thermocouple wires were silver-soldered for each test, resulting i n three welding "lumps" on the test section. It is likely that the variability i n the position of the thermocouple tip i n this spot w i l l cause some error i n the measurement. In some cases, the thermocouple tip was just on the top of the l u m p while sometimes it was deeper i n the test section. Also, i n each test, the spot was covered w i t h sintered quartz sand. This may have increased the thermal resistance between the fluidized bed and the wall. The significantly higher temperature gradients measured i n R u n 20 may have been caused by this phenomenon, therefore causing the measured h to be lower than the pre0  diction. Usually, h is calculated under the conditions of an average fluid bed temperature 0  between the wall and the bed temperatures. For R u n 20, h was also calculated assuming 0  the bed to be under the conditions of the average wall temperature only. T h e results are shown as a dashed line i n Figure 6.24. T h i s clearly does not account for the discrepancy  84  Results and Discussion  between the experimental and the predicted values. T h e accuracy of the correlations by Molerus and M a t t m a n n (1992) and Molerus et a l . (1995) was also tested w i t h a set of independent data obtained by M a k h o r i n and Kharchenko (1964) w i t h a spherical probe immersed i n 80-cm deep and 22-cm diameter air fluidized bed of quartz sand (d = 0.34 p  m m ) . T h e results are shown i n Figure 6.26 and illustrate the accuracy of b o t h correlations. Note that the diameter of particles was between 0.25 and 0.50 m m , which is considered a narrow size distribution. Based on these results, it seems reasonable to expect our data  r  800  ^  Prediction of maximum heat transfer coefficient vs. bed temperature (O. Molerus et al. 1995). 1 1 1 r1 i i i O Data Prediction  7001  ^ — c  £ 5  600 \  d  500  400 100 1  200  300  400  500  600  700  800  900  1000  Bed Temperature, C Prediction of heat transfer coefficient vs. superficial gas velocity (O. Molerus et al. 1995). 700 r  O  Data; Bed Temp^SOtfC Prediction  600 h-  500  400  300  1  0.5  1.5  U [m/s]  Figure 6.26: F i t by Equations 2.19 and 2.24; data from M a k h o r i n and Kharchenko (1964). for R u n 20 to be lying somewhere between the data for 300°C and 500°C. Molerus and W i r t h (1997) have used data from Janssen (1973) obtained with quartz sand (d  p  = 0.58mm) i n air (horizontal tube) to illustrate the accuracy of their correla-  tion 2.19. T h e results are shown i n Figure 6.27 for various bed temperatures.  A s can be  seen, at a 400 °C bed temperature and a particle size of d = 0.58 m m , a m a x i m u m heat p  Results and  85  Discussion  transfer coefficient close to /J =400 W / m - K has been measured.  N o w , it is well known  2  O  that the heat transfer coefficient decreases w i t h particle size i n the regime of d « 100 p  08  r  I  i  12  u-u [m/s] raf  Figure 6.27: E x p e r i m e n t a l (symbols) w i t h air at varying bed temperatures and predicted h  0  (Equation 2.19); reproduced from Molerus and W i r t h (1997) w i t h permission.  Figure 6.28:  E x p e r i m e n t a l and predicted h  0>max  (Equation 2.24) at different levels of  temperature; reproduced from Molerus and W i r t h (1997) w i t h permission.  86  Results and Discussion  up to 1 m m . Figure 6.28 shows measured m a x i m u m heat transfer coefficients at 400°C for a particle size of d =0.34 m m i n the order of h p  « 5 0 0 W / m - K . T h i s suggests that 2  0tmax  our results for R u n 20 may be too low. Moreover, as seen i n Figures 6.24 and 6.25, the predicted m a x i m u m coefficient does not occur at the same gas velocity as for the experimental data. T h e prediction is still increasing while the data is decreasing. Now, i n both tests a loss of sand from the bed was observed for the highest gas flowrate. T h e premature decrease i n h may be attributed 0  to a reduction i n the heat flow caused by this loss of sand. T h i s behavior may not occur when using a more narrow particle size range as is generally the case for the data used to derive such correlations. W i t h a wide particle distribution such as used here (Figure C . l ) , the fine particles may be entrained while this is not the case w i t h a narrow size range. Table 6.10 contains the measured and predicted m a x i m u m heat transfer coefficient, h ,max and h 0  0%max  respectively, using the correlations given i n Chapter 2. It can be seen  that a l l correlations point to the fact that a higher value for h  0}Tnax  would have been  expected for both runs. T h i s may be partly attributed to some error i n the temperature measurement as explained above. A l s o , according to Figures 6.24 and that h ^ 0  nax  occurs at a higher gas velocity than i n the measurements.  6.25 it is clear  T h i s may be due  to the loss of sand during the measurement which may not occur when a narrow size distribution is used. Table 6.10: Measured, and predicted h , 0t  Run no.  Measured  Zabrodsky  16  449  641  20  336  518  nax  from various correlations for Runs 16 and 20. Grewal and Saxena  Molerus  572  698  651  464  568  531  Varygin et al.  Finally, it is interesting to consider the instantaneous heat transfer coefficient,  h, . nst  M i c k l e y et al. (1961) reported values at a point on a 6.35-mm tube located along the axis of a 0.1-m fluidized bed of 43-320 /.an particles and found sharply varying values, as shown i n Figure 6.29. Baskakov et al. (1973) also obtained similar data. K u n i i and Levenspiel (1991) saw this behavior as evidence for the fact that the exchanger surface is  87  Results and Discussion bathed alternately by gas bubbles (very low h  inst  h  values) and by emulsion packets (high  values). T h e relatively high magnitude of the noise i n our thermal fouling data may  inst  be attributed to this phenomenon.  Glass beads, U =0.186 m/s o  Microspheres, U =0.086 m/s 1500  600  cV 1000 » 500  Figure 6.29: Instantaneous h on a vertical tube; adapted from M i c k l e y et al.(1961).  6.3.2  Clean Coefficient For The O i l  T h e heat transfer between a pipe and the fluid flowing w i t h i n it is determined either singly or i n combination by two mechanisms, namely, forced convection and natural convection. In most process plant heat exchangers where the fluid is p u m p e d through the system at relatively high velocity, the effects of natural convection are, therefore, insignificant. In laminar flow, the distances required to attain the fully developed thermal boundary layer (thermal entry length, L ) and hydrodynamic boundary layer (hydrodynamic entry eT  length, L ) are given by: e  fd,T  v  =L  'fd,H  D  t  0.05RePr  (6.17)  O.ObRe  (6.18)  lam  For our test section w i t h a non-heated entry length of about 40 c m , it was possible to treat the velocity profile as fully developed throughout the thermally developing region. Moreover, the Graetz number, defined as  Gz = — RePr x  (6.19)  88  Results and Discussion  is an important parameter i n the analysis of developing boundary layer phenomena. T h e thermal boundary layer is fully developed when Gz~  x  has a value of about 0.05, which  is the origin of E q u a t i o n 6.17. Correlations w i t h a fully established velocity profile for a developing temperature boundary layer (Gz~  x  < 0.05) were compared w i t h our ex-  perimental results obtained i n Runs 16, 20, and 23.  These correlations have usually  been derived on the basis of constant fluid properties and the mean fluid temperature, Tb = (Tb,i + Tfc n  i0ut  )/2, was used i n calculating the nondimensional parameters.  Gnielinski (1983) proposed the following Nusselt number  (Nu = hi • Di/ki) based on  the average heat transfer coefficient over the length 0 to x for a uniform wall temperature  Nu = lMGz  Gz > 10  1/3  3  (6.20)  For the constant surface temperature condition, K a y s (1955) presents a correlation which presumes a thermal entry length and is of the form  TT-  n  „  0.066S(Di/L)RePr  ,„ ^ n  where L is the heated length of the test section. T h e best results were obtained from a correlation proposed by Obot et al. (1997) who reported heat transfer data i n laminar flow for the 0.7 to 126 P r a n d t l number range: ?Vu = 0.0086#e / 3  2  i^-j^ Pr  0A  (6.22)  F r o m the knowledge of the measured heat transfer coefficient i n the fluidized bed, h , Q  of the wall resistance, and of the overall coefficient, U , the inside heat transfer coefficient, 0  hi, was calculated. E q u a t i o n 6.22 was used to predict the average heat transfer coefficient inside the tube, hi, and the results are given i n Tables 6.11 and 6.12. T h e values of heat capacity and thermal conductivity required i n the calculation of the P r a n d t l number were obtained from Cassis et al. (1985) and Perry and Green (1984) respectively.  It is shown  that the flow is laminar and there is a fully developed hydrodynamic boundary layer w i t h a developing temperature boundary layer over the whole length of the 46-cm heated section. Table 6.12 indicates that there is a significant deviation between experimental and predicted hi, especially for R u n 20.  N o w , i f we use the correlation 2.19 proposed by  Molerus et al. (1995) to calculate h , we can deduce the heat transfer inside the tube, 0  Results and  89  Discussion  Table 6.11: Parameters involved i n the calculation of hi. Run no.  T  Xfd.H  Xfd,T  b  (°C)  (cm)  (cm)  Re  Pr  Gz~ x 10 l  16  303  934  12  465  78  2.43  20  132  326  7  266  47  6.96  23  376  1073  22  824  49  2.26  3  Table 6.12: Measured (hi), and predicted (hi) coefficient from E q u a t i o n 6.22. Run no.  Dev.  Dev.  hi M  hi  hi  (W/mM<)  (W/m -K)  (%)  (W/m -K)  (%)  16  498  408  22  451  11  20  530  252  110  293  16  23  407  444  -8  460  3  2  t  2  knowing the overall heat transfer coefficient U . T h e results, given i n Table 6.12, become Q  much more consistent w i t h the predicted h{. T h i s reinforces the validity of Molerus's correlation a n d the possibility of an error i n the wall temperature measurement. Finally, Table 6.13 gives the inverse overall heat transfer coefficient based on the external surface area of the test section, l/U , and the relative importance of each of the Q  individual resistances w i t h respect to the total resistance. T h e relatively high resistance from the fluidized bed (average=38% of the total) m a y reduce the sensitivity of the fouling unit to detect a change i n the overall heat transfer coefficient that would result from fouling. Table 6.13: Total, and fractional tube side and shell side resistances . 1  Tube/Total  Total Run no.  W~  L  x 10  3  Aol{Aih VZ ) x  iM  Shell/Total  I/CIOMUO 1)  16  4.703  0.56  0.43  20  6.024  0.67  0.32  23  4.258  0.61  0.39  (W/m -K); 'Tube wall resistance is less than 1% in these runs. 2  90  Results and Discussion 6.4  Analysis of Variations in Fluidized B e d  6.4.1  Power Spectral Density  In order to identify undesirable oscillations i n process variables, their frequency, their relative importance, and their effects on the fouling data, the measurements were decomposed by using a Fourier method called Fourier transform ( F T ) . For a signal that is both discrete and periodic, the appropriate transform is the discrete Fourier transform ( D F T ) . The D F T of the sequence {x }, t  t = 0 , 1 , . . . , N — 1 is given by N-1  X(n)  =  J2 t N i t=o  W  =  exp^j^j  N  x W  nt  n = 0,1,..., N - 1  (6.23) (6.24)  This material is covered i n many textbooks on digital signal processing such as Roberts and M u l l i s (1987).  T h e D F T was computed using a fast algorithm implemented i n  M a t l a b © called fast Fourier transform ( F F T ) . T h e frequency content of a signal y can t  be estimated from a periodogram S (6) which is an estimate of the power spectral density p  S (8). In practice, only a sample of the entire periodogram is computed. A set of equally p  spaced samples of S (6) can be obtained from the F F T algorithm for the D F T . Let N > L p  be a power of two, and let 6 = 2ir/N. 0  Then  S (ne ) P  0  = \\Y,y^-  = j\T,*tW^\*  \  3tn6a 2  t=o  = ^j^-  (6.25)  t=o  where x  t  w  t  =  yw,  =  0,  L <t < N - 1  =  1,  0 < t < L - l  =  0,  otherwise  t  t  0 < t < L -1  (6.26)  (6.27)  This tool was applied to all experiments and the results for R u n 5 are given i n F i g ure 6.30 as an example, plotted up to the Nyquist frequency.  In Runs 3 to 7, a periodic  Results and Discussion  91  variation i n the air flowrate fluidizing the bed was observed, although its origin had not yet been identified. T h i s resulted i n oscillations of several process variables such as the temperature of the air entering the fluidized bed, T  a t r  , the fluid bed temperatures, and  the heat flow. T h i s is shown i n Figure 6.30 by the major peaks at around 0.1 and 0.2 r a d / m i n . T h e period (p = 2ir/6 min.) corresponding to the first and second peaks was calculated and the results are given i n Table 6.14. It can be noticed that, for a given run, the major  fluctuations  all have the same period, whose origin was the air building  compressor as w i l l be shown later.  Also, the air flowrate had at least two important  oscillations whose frequency varied from run to run. T h e variation i n the air flowrate caused a corresponding variation i n the heat transfer coefficient i n the fluidized bed as discussed i n the last section and as a result, the heat flow fluctuated. T h e temperature measurements at the top and b o t t o m of the fluid bed were usually more affected than  (b)  (a)  0.08  15  T,  lop  E 2 10  •a  o> % 0.04 o  •: . L...  11.1  5  <D  0-  0.2  a> •a CL  b  0.4 (c)  . ..i  0 )  i  a. 0.02  7\A  0.6  0.2  0.8  0.4 (d)  0.6  0.8  200  15 E 2 10 o o <5 5  AT  co  D) O  p  —  £ 0.06  mid  "'"air  E 150 CO  1j  •8 1 0 0  k WM w  0.2  0.4 (e)  o  •c  CD  D_  50  ,J  ; \  0.6  D  0.8  X10"  100 T  E 2  0.2 3  0.4  0.6  0  (0 Heat Flow  bot  E CO  % 0.5 o  % 50 o <u CL  CD CL  0.2 0.4 0.6 Frequency, rad/min  0.8  0.2 0.4 0.6 Frequency, rad/min  0.8  Figure 6.30: Samples of the periodogram obtained from the F F T ( D a t a from R u n 5).  Results and Discussion  Table 6.14: Magnitude and period of the peaks identified i n Runs 3 to 7. Q  Tair  Mag.  T  Mag.  (min )  (°c )  (min)  (°c )  (min)  (°C )  1.05  37  31  26  3  36  22  72  4.56  71  5  22  4  73  319  102  36  1.87  32  2  31  1  36  80  67  195  67  8.60  67  13  144  6  67  86  32  26  32  2.83  32  3  33  8  31  15  66  212  66  9.90  66  8  65  6  65  45  32  35  32  1.99  32  5  30  8  32  14  61  42  62  1.67  24  1  34  3  53  1  53  74  53  1.26  -  -  -  -  -  -  Mag.  T  Mag. x 10"  no.  (min)  (°c )  (min)  (kW 2 )  3  37  92  38  4  73  352  36  7  ot  T  T  6  b  Mag.  Run  5  T  Ttop  2  T  2  2  2  the middle temperature as shown i n Figure 6.30 and Table 6.14. A l s o , the second peak was not significant for all the runs. It is interesting to note that the fluctuation i n heat flow m a y not be detected from the fluid bed temperature measurements as shown by R u n 7 and others. F i n a l l y , after R u n 8 the fluctuations i n air flowrate were reduced and no other significant oscillations were detected.  6.4.2  Elimination of Fluctuations  To reduce the effect of air flow oscillations on fouling data, two approaches were taken. In the first one, a band-stop filter was designed specifically to remove the major oscillations from the data and i n the other approach, the effect of the fluctuations was m i n i m i z e d . In the discussion of filters, signals are viewed as a collection of signal components with different frequencies. A filter is designed to accept certain frequencies and reduce other frequencies. T h e Bode diagram indicates which frequency components the filter reduces and how much each component is reduced. In this section, the design and application of a band-stop filter to eliminate the fluctuations discussed previously are demonstrated. A band-stop filter has two frequency values, called the half-power frequencies, that are separated by a frequency range called the bandwidth of the filter. T h e band-stop filter  93  Results and Discussion  reduces a l l components of the signal between the two half-power frequencies and does not affect the components on either side. T h e m a x i m u m reduction of the signal occurs at the midpoint between the two half-power frequencies.  A second order digital B u t t e r w o r t h  filter is of the form  n  H  1+ a~  J  l  iq  where q~  x  + a q~  2  V  2  '  is the backward-shift operator and the parameters determine the frequency  band to be attenuated and the attenuation. T h e function ' B u t t e r ' i n M a t l a b © was used to design the filter; the inputs of the function were the order of the filter (=2) and the two half-power frequencies, whereas the outputs were the parameters a and b. To reduce the two significant components identified i n last section, two band-stop filters were designed. T h e Bode diagram for the digital filter used to m i n i m i z e the component occurring at around 0.1 r a d / m i n i n R u n 5 (see Figure 6.30) is shown i n Figure 6.31. T h e filter produces -50.9 d B of attenuation at the desired frequency of 0.0939 r a d / m i n . Table 6.15 contains  fx  (T  U J1  ! ;  ;  ;  10" Frequency, rad/min 1  1001  :  :  . — ; —  10°  1  Frequency, rad/min  Figure 6.31: Bode diagram of the band-stop filter used to reduce oscillations i n R u n 5. the parameters a and b for the two filters used i n Runs 5 and 6.  T h e data for the  temperature difference across the test section were filtered u n t i l sufficient attenuation of the desired components was obtained. T h e resulting power spectral density estimate for ATb i n R u n 5 is shown i n Figure 6.32 which clearly shows the attenuation of the two components. T h e heat flow was recalculated using the filtered data and the results are  94  Results and Discussion  Table 6.15: Parameters for the bandstop filters for R u n s 5 and 6. Filter 1 Run no.  6l  &2  63  CJl  02  5  0.9629  -1.7177  0.9629  -1.7177  0.9258  6  0.9651  -1.7149  0.9651  -1.7149  0.9302  Filter 2 5  0.8616  -0.9239  0.8616  -0.9239  0.7232  6  0.8632  -0.9351  0.8632  -0.9351  0.7263  (b) Filtered data.  (a) Raw data. 0.08  £  1  1  0.08  11  0.06  E CO  2  D) O TJ .O CD CL  D) O T3 .O  0.04  1  1  1  0.06 0.04  CD  Q_ 0.02  0.02 0  I * ... 0.2 0.4 0.6 Frequency, rad/min  0.8  0.2 0.4 0.6 Frequency, rad/min  0.8  Figure 6.32: Samples of the periodogram for the raw and filtered AT), for R u n 5. illustrated i n Figure 6.33 for Runs 5 and 6. T h e attenuation of the two major oscillations has clearly improved the quality of the fouling data. T h e air flowrate variations were caused by the periodic pressure increase and decrease of the air building compressor occurring at each cycle of the compressor. T h e variability in the frequency of this cycle observed i n Table 6.14 depended on the demand of air at the time of the experiment and was sometimes decreasing during the night time w i t h i n the same r u n . To m i n i m i z e the effect of this cycle on the air flowrate, the pressure of the air regulator was reduced from 60 to 40 psig. A test revealed that when the pressure was set at 60 psig, the pressure varied between 50 to 60 psig w i t h i n one cycle of the compressor. Because the compressor could not provide a constant pressure of 60 psig, the pressure of the air regulator was reduced to 40 psig. T h e effect of this change on the  95  Results and Discussion air  temperature entering the fluidized bed, which is directly related to the air  is shown i n Figure 6.34.  flowrate,  No significant oscillation i n air flowrate was observed after  implementing this change.  (b) Run 6 (raw data).  (a) Run 5 (raw data). 0.55  r  0.5 0.45  d 0.4  500 Recirculation time, min  0.35  1000  0  500 Recirculation time, min  1000  (d) Run 6 (filtered data).  (c) Run 5 (filtered data). 0.55  0.55  0.5  0.5  0.45  0.45  d  d  0.4  0.4 0.35  0  500 Recirculation time, min  1000  500 Recirculation time, min  0.35  1000  Figure 6.33: Raw and filtered heat flow for Runs 5 and 6.  Air temperature versus time. 300  i  i  !  !  !  Air pressure= 40 psig i  o v250  200  Air pressure= 50 - 6 0 psig  200  400  i 600  800  -  1  'I-  1000  i  i  1200  1400  1600  1800  Time, min  Figure 6.34:  Test revealing the effect of air pressure on air temperature, T . air  96  Results and Discussion 6.4.3  Sensitivity of U to A i r Flow Variations 0  According to Equations 2.2 and 2.4, the heat flow and the overall heat transfer coefficient, /7 , share a similar dependency w i t h the air flowrate as the heat transfer coefficient between 0  the bed and the test section, h . T h e semi-empirical knowledge of h as a function of the 0  0  superficial gas velocity described i n Section 6.3.1 could be used to estimate changes i n U  0  resulting from air flowrate variations using E q u a t i o n 2.4.  Unfortunately, i n none of the  runs was a continuous measurement of the air flowrate recorded. A l s o , the correlations used i n Section 6.3.1 could not predict the m a x i m u m i n the curve h vs. excess gas velocity Q  as observed experimentally. Concerning the experimental data for h  0  obtained i n Runs  16 and 20, they are valid only for the conditions under which they were obtained. T h e heat flow generated i n each run depends on several factors as seen previously. Because the purpose of this work was not to study heat transfer i n a fluidized bed, many of these parameters were not controlled from run to run. Nevertheless, i n order to have an idea of the sensitivity of U to air flow variations, other empirical relationships between the 0  experimental data were sought. A s seen previously, a relationship was observed between the air flowrate and the temperature of the air entering the fluidized bed, T i . One approach considered was to a  r  estimate air flowrate variations based on this relationship and on the knowledge of T >. at  Runs such as 5 and 6 would have provided a relationship between U and T a  a i r  and R u n  20 would have given the link between T > and air flowrate. However, this approach was ai  not valid since it was found i n R u n 18 that T , was also affected by variations i n line a  r  voltage. Another approach for evaluating the sensitivity U to air flowrate variations was to a  relate the fluid bed temperatures to U by using the data obtained i n R u n 20 as a result 0  of step changes i n air flowrate. T h e correlations found between U and the three fluid 0  bed temperatures obtained i n R u n 20 are shown i n Figure 6.35.  T h e data indicate that  an increase i n air flowrate causes an increase i n the temperature of the bed at the bottom and a decrease of the bed temperature at the top, but does not affect the temperature of the bed i n the middle.  97  Results and Discussion  Overal heat transfer coefficient vs. fluid bed temperatures during step changes in air flowrate.  — i  1  180 O  * 160  1  1  "—  !  0 :0  Air rotameter = 5 . 5 a  O  0  OC© :  Q  JS 140  Air rotameter = 8.0  3°120 100 h 440  420  1  180 h * 160 O J  E  5= 140  o <§po° o : cp O  o C  425  r  1  D  i  430  §SP'O OO  °o:  :  OfO:  OP  ° ''[6Q>0  !  !  O c  fP  0  Co .  1I  !  1  540  520  500  480 T.  460  0  Qj  O  O  o  o  •  • •  -  o"  i  i  i  i  i  1  1  1  1  435  440  445  450 T mid  455  460  465  470  475  O  OfJoO  180  0:Q§^30@6o  * 160  O  O  0  0 0  0  O  00#.  O  0  ^  0  CP  0  :  Air rotameter = 8.0  450  460  g 140 3°120  P  100 390  400  CD ^SE©' o Air rotameter = 5.5  410  420  430 T  440  470  bot  Figure 6.35: Correlation between U and the fluid bed temperatures i n R u n 20. 0  6.5  Tests W i t h a K n o w n Fouling F l u i d  In order to evaluate the ability of the fouling unit to detect fouling, Runs 19 to 21 were performed using a m i x t u r e of fuel o i l (75%wt.), heavy o i l (10%wt.), and deasphalted o i l — DAO—(15%wt.).  T h i s blend was selected because of the high fouling rates measured  when used i n another fouling unit ( A l - A t a r (2000)). T h e results obtained are discussed by taking into account all the fouling runs performed i n the present work. For each run, the i n i t i a l and final values of the process variables believed to affect the heat flow to the test section were calculated by taking an average of twenty-one points. T h e initial value was calculated after a steady-state regime was achieved i n a l l measured variables. In order to estimate the uncertainty i n the measured and calculated variables, a linear regression (LS) was performed through these twenty-one points. A s s u m i n g the  98  Results and Discussion  prediction errors to be 7V(0, <7 ), a 95% confidence interval was obtained as follows 2  ) where a  (6.29)  is the standard error of the prediction errors and (t i )  pe  va  ue  is obtained from a  Student's t-distribution table. The results are given in Table 6.16 where the subscripts 0 and / refer to initial and final respectively and where N is the number of data points used to obtain the values. Table 6.16: Initial and final values of measured and calculated variables for all runs with 95% confidence interval (CI). Qo  Qf  (kW)  (kW)  0.6  0.64  0.45  5.4  0.3  0.40  0.39  0.6  6.3  0.6  0.36  0.36  4.1  0.2  4.9  0.2  0.40  0.33  21  4.2  0.3  4.3  0.4  0.46  0.44  957-1057  21  4.4  0.3  4.5  0.4  0.45  0.43  110-210  787-887  21  4.3  0.2  5.0  0.3  0.48  0.41  8  100-200  546-646  21  5.7  0.3  5.8  0.4  0.34  0.33  9  100-201  817-917  21  4.7  0.3  4.7  0.2  0.42  0.42  10  75-176  662-762  21  4.6  0.1  4.6  0.1  0.43  0.43  11  90-191  865-956  21  4.7  0.2  5.1  0.2  0.42  0.39  12  100-200  661-762  21  4.8  0.3  5.2  0.2  0.39  0.37  13  115-216  1023-1123  21  3.7  0.1  3.8  0.2  0.75  0.73  14  231-331  1048-1148  21  4.4  0.1  4.2  0.1  0.63  0.65  15  200-301  1909-2009  21  4.9  0.3  4.7  0.3  0.56  0.59  16  355-455  1022-1122  21  4.7  0.2  5.2  1.1  0.62  0.59  17  301-401  3186-3287  21  4.6  0.1  4.5  0.1  0.59  0.61  18  501-602  3253-3353  21  4.5  0.2  4.2  0.2  0.51  0.54  19  166-266  1203-1304  21  6.8  0.2  7.5  0.4  0.19  0.17  20  200-301  1788-1889  21  5.9  0.2  5.9  0.1  0.50  0.49  21  200-301  1919-2019  21  4.5  0.1  4.6  0.1  0.66  0.64  22  201-301  1654-1754  21  4.4  0.2  4.0  0.1  0.50  0.58  23  201-301  1153-1254  21  4.3  0.1  4.2  0.2  0.51  0.53  Run  datao  data;  no.  (min)  (min)  1  240-400  1390-1560  18  4.4  0.3  6.8  2  200-300  630-730  12  5.3  0.7  3  270-370  671-770  21  6.3  4  216-316  1185-1305  21  5  101-201  862-962  6  125-225  7  CI  N  l/Uo,/  CI  (m -K/kW)  (m -K/kW)  2  2  99  Results and Discussion  According to these results, the change in (1/U ) is significant for Runs 1, 4, 7, and 0  19. Section 6.2.3 has shown that for Runs 1, 4 and 7, the change in heat flow was mostly due to a variation in liquid flowrate. Runs 19, 20, and 21 were performed with the DAO mixture. For Run 19, there was no significant change in all the measured variables. This is the only run where both the increase in (1/U ) was significant and where there is no 0  indication of significant changes in process variables. Figure 6.36e indicates that the mass flowrate during Run 19 was constant while the heat flow was slightly decreasing (see Figure 6.36a). The results of this run therefore suggest fouling formation. For Run 20,  Table 6.15: Continued. CI  CI  Tbot,o  CI  CC)  (°C)  CC)  (°C)  2  490  0  -  -  496  7  497  3  -  -  8  496  6  498  4  477  10  480  9  509  5  504  8  506  7  435  16  429  20  10  510  9  501  7  502  9  490  15  484  15  507  5  509  6  501  7  503  8  500  13  499  12  7  511  3  511  4  502  7  501  7  510  7  509  6  8  505  3  507  4  498  7  502  7  486  8  488  11  9  506  5  506  4  499  6  501  5  505  8  503  12  10  503  4  502  3  500  5  499  6  502  5  501  8  11  504  3  505  4  498  4  500  5  503  6  502  8  12  505  2  505  4  500  6  500  4  501  5  499  5  13  601  7  605  5  594  7  596  6  603  13  601  14  14  601  5  603  4  596  6  597  4  596  12  593  9  15  528  11  537  6  503  8  504  5  483  13  489  12  16  622  7  669  83  602  8  605  5  611  11  602  17  17  617  9  627  10  599  10  592  10  587  9  581  7  18  594  8  593  5  597  10  598  14  598  9  594  8  19  246  6  246  6  248  5  249  13  222  5  219  9  20  450  5  447  5  448  8  448  9  453  12  447  14  21  445  5  447  6  445  12  444  13  441  8  436  6  22  610  5  613  6  614  9  610  7  616  13  612  6  23  613  4  618  3  610  4  610  5  615  3  620  4  CI  CI  Run  Ttop,o  CI  no.  (°C)  (°C)  CC)  (°C)  CC)  (°C)  1  534  16  569  12  491  2  533  25  528  18  3  510  9  509  4  508  4  5  507  6  Ttopj  Tmid,0  Tmid,f  Tbotj  CC)  (°C)  100  Results and Discussion  there is no significant change between the initial and final heat flow—this is also true for the flowrate as shown in Figure 6.36e—although some variations occurred during the run (see Figure 6.36a). The observed change in Q at around 700 min (Fig. 6.36a) is believed to have been caused by a decrease in bulk temperature which occurred at the same time; the bulk temperature came back to its original value at around 1000 min. Hence it was concluded that no fouling was detected in Run 20. For Run 21, the heat flow had an decreasing trend (Fig. 6.36b) although it was less pronounced than for Run 19. More fluctuations in flowrate were observed in Run 21 than in Runs 19 and 20 (Fig. 6.36f).  Table 6.15: Continued. CI  Tin,/  CI  CO  (°C)  CO  cc)  -  196.9  0.6  195.4  1.8  -  -  277.4  0.6  275.8  0.5  3  -  -  244.9  0.5  245.1  0.6  4  -  -  284.7  0.4  286.4  0.6  5  -  -  288.5  0.8  288.9  0.9  6  -  -  289.4  1.0  289.5  0.8  7  -  -  276.5  0.5  278.3  0.7  8  31.1  0.6  30.8  0.5  290.5  0.3  291.3  0.3  9  13.7  0.1  13.1  0.1  283.9  0.4  284.6  0.2  10  9.3  0.5  9.1  0.1  277.7  0.4  277.9  0.2  11  10.4  1.0  10.1  0.7  280.9  0.6  282.5  1.0  12  8.4  1.9  7.8  1.1  286.0  0.8  285.7  0.6  13  15.1  0.1  15.8  0.2  288.5  0.7  289.1  0.5  14  7.5  0.5  7.7  0.3  282.8  0.4  282.5  0.3  15  16.3  0.4  16.3  0.1  198.8  0.4  198.9  0.2  16  7.3  0.7  7.6  0.1  286.4  0.6  285.7  1.4  17  7.6  0.0  7.7  0.0  286.7  0.5  286.3  0.5  18  6.6  0.1  6.5  0.0  330.3  1.4  330.8  0.9  19  5.8  0.0  5.8  0.0  86.5  0.2  86.5  0.2  20  3.2  0.0  3.2  0.0  95.0  0.3  93.8  0.2  21  12.8  0.5  12.7  0.2  106.7  0.3  106.8  0.2  22  8.4  0.1  8.3  0.4  361.4  0.5  343.2  0.6  23  7.8  0.3  8.0  0.3  363.8  0.5  361.9  0.6  Run  mo  CI  m/  CI  Ti„,  no.  (g/s)  (g/s)  (g/s)  (g/s)  1  -  2  0  101  Results and Discussion  The test section used in Run 19 was cut axially in order to examine the inner surface of the tube by visual inspection. Only a layer of oil was observed; the layer was thin  (b) Heat flow calculated with actual flowrate vs. t.  (a) Heat flow calculated with actual flowrate vs. t. 1  •—1  1  "  0.8  1  0.5  0.75  0.45  0.7  0.4  Run 19 Run 20  § 0.35 Q  0.65 O  0.3  >  r  > 0.6 0.55 \  0.25  Run 21  0.5  0.2  0.45  0.15  0  500  1000  1500  1000  500  2000  1500  2000  (d) 1/U calculated with actual flowrate vs. t.  (c) 1/U calculated with actual flowrate vs. t.  Run 21  5.5 §  5 34.5 4  0  500  1000  1500  3.5  2000  (  1000  1500  2000  (f) Mass flow vs. t.  (e) Mass flow vs. t.  -S  500  6  14  5.5  13.5 13  5 Dl  Run 19 Run 20  £ 4.5  w in  ( 0  m  to  ( 0  S  5 §: 12.5  4 2  12  Run 21  3.5 11.5 3  500  1000 t, min r  1500  2000  Figure 6.36: Heat flow, (l/U ), 0  11  500  1000 t, min  1500  2000  and mass flowrate in Runs 19 to 21.  102  Results and Discussion  enough such that the surface of the tube could still be seen. N o black and thick deposit such as that obtained w i t h the probe of the other unit when used w i t h the same m i x t u r e was found. For Runs 20 and 21, the test section was washed w i t h varsol according to the procedure described i n Chapter 5 i n order to measure w , the amount of coke i n the test c  section at the end of a run. T h e results are given i n Table 6.17.  Note that w  c  could  Table 6.17: Coke collected i n test section at the end of Runs 20 and 21. Run no.  (mg) 19  -  20  41  21  18  not be measured i n R u n 19 because of the tube opening performed. Since the amount of insolubles i n the D A O blend is probably negligible, the mass of coke for Runs 20 and 21 is therefore the result of fouling. However, based on the thermal measurements obtained in Runs 20 and 21, these deposits were apparently too small to be detected by the fouling unit.  Note that the higher amount collected i n R u n 20 might have been caused by a  lower liquid velocity, given that the other process variables and the total recirculation times were very similar (see Table 6.1), since fouling is often expected to increase when the velocity decreases. T h e thermal measurements of R u n 19 indicate fouling formation. N o w , for the runs w i t h pitch and C H G O , the mass deposition measurements have shown the absence of significant fouling under the conditions covered. However, i n some of these runs, variations i n 1/U  0  were observed, although they could not be explained i n terms of flowrate  variations. Because of that, and since no mass deposition measurements were made i n R u n 19, which was the only run where fouling seems to have been detected, the evidence is judged insufficient to say whether fouling was actually formed i n R u n 19. For Runs 20 and 21, some fouling has occurred as shown by the measured deposits, but detection by thermal measurement may have been prevented by the small amounts measured, and by the noise level and variability of the fouling unit present i n all the other experiments.  Chapter 7 Conclusions &: Recommendations  7.1  Conclusions  T h e m a i n objective of this study was to evaluate the tendency of the pitch-coker heavy gas oil stream to form coke as well as to assess the ability to detect it under the appropriate bulk and surface temperature conditions. To meet this objective, several fouling experiments were done by recirculating a 50:50%vol. pitch-heavy gas o i l blend over 11-56 hour periods w i t h bulk fluid temperatures of 2 0 0 - 3 7 5 ° C , tube side velocities of 0.3-2.2 m / s , and fluid bed temperatures i n the range 5 0 0 - 6 1 5 ° C . F l o w was generally laminar. B o t h the mass deposition and thermal measurements showed no significant fouling by coke formation. Interpretation of the thermal fouling data was sometimes made difficult by their sensitivity to variations i n process variables. B y the use of different data analysis techniques and of empirical correlations found between process variables, fouling was distinguished from other effects. In order to see whether the absence of fouling observed was due to the fouling unit or could be attributed to the nature of the test fluid used, a series of fouling experiments were performed w i t h a blend of de-asphalted o i l known to give measurable fouling rates i n turbulent flow and i n similar periods of time as for the coking experiments. Moreover, viscosity and density measurements were done to determine the flow regime in the fouling runs and to account for possible viscosity changes during the fouling experiments. A d d i t i o n a l experiments were performed to monitor the viscosity change during recirculation of the test fluid and also the change i n the amount of toluene insolubles in the 50:50%vol. pitch-heavy gas o i l blend. Finally, measurements of heat transfer coefficients were also made to estimate the relative importance of the thermal resistances between the fluidized bed and the bulk liquid.  103  104  Conclusions & Recommendations Based on these studies, the following conclusions can be drawn:  • A n improved insulation of the fouling unit and the use of heating tapes increased the capability of the unit to handle viscous fluids and to reach the higher bulk temperatures required (see Sections 4.7.1 and 4.7.3). • A s described i n Sections 4.2 to  4.4, the design and implementation of a pressure  drop measuring system combined w i t h a digital balance setup provided an accurate mass flowrate measurement of viscous fluids using a small amount of test  fluid.  • A n adjustment of the air pressure regulator reduced undesirable oscillations i n air flowrate as shown i n Section 6.4.2, thereby i m p r o v i n g both the fluid bed temperature profile and the thermal fouling data.  T h e data obtained prior to this  adjustment  were improved by filtering through a digital band-stop filter as demonstrated i n Section 6.4.2. Oscillations i n the voltage to the air preheater were also reduced by use of a voltage regulator. • F r o m the viscosity measurements reported i n Chapter 3, viscosity-temperature correlations were developed over a wide range of temperatures for the viscosity prediction of any blend of pitch and C H G O . Density-temperature equations were also derived from the density data presented i n the same chapter. Hence a laminar flow regime i n a l l the fouling experiments performed could be determined. • In some fouling runs a drop i n viscosity was observed and a possible bias effect on the mass flowrate measurement was demonstrated i n Section 6.2.5. • For the runs w i t h the 50:50%vol. p i t c h - C H G O blend, the TI  measurements are  consistent w i t h the previous work of Watkinson et al. (1998) as discussed i n Section 6.1.2; i.e. as long as a certain amount of volatiles has not been released, no significant change i n the TI of the test fluid w i l l occur. • In Sections 6.2.1 and  6.2.2, the use of cross correlation analysis and empirical  correlations found between process variables confirmed the effect of l i q u i d flowrate variations on thermal measurements.  A n A R M A model and a variable  flowrate  approach were applied to the measurements which essentially eliminated the effect  Conclusions & Recommendations  105  of l i q u i d flow variations as discussed i n Section 6.2.3. A l s o , the configuration of the bypass circuit was modified thereby eliminating the variations i n l i q u i d flowrate (see Section 6.2.4). • T h e tests for determining the heat transfer coefficient revealed the complexity of heat transfer i n fluidized beds. Comparison of the data w i t h predictions from correlations in Section 6.3.1 indicated that the wall temperature measurements m a y not always provide the actual wall temperature. Moreover, the loss of sand from the bed may explain the fact that the measured m a x i m u m heat transfer coefficent occurs at a lower gas velocity than for the predicted coefficient. T h e premature decrease i n h  0  may be attributed to the relatively large particle size range of the sand used. • In Section 6.3.2 the measured and predicted heat transfer coefficients inside the test section have shown the relative importance of each of the i n d i v i d u a l resistances between the bed and the bulk fluid w i t h respect to the total resistance. T h e resistance i n the bed was as high as around 38% of the total resistance; this m a y reduce the sensitivity of the fouling unit to detect a change i n the overall heat transfer coefficient that would result from coke deposition. • Over the range of bulk fluid temperatures ( 2 0 0 - 3 7 5 ° C ) , fluid bed temperatures ( 5 0 0 - 6 1 5 ° C ) , and liquid velocities (0.3-2.2 m / s ) , no fouling was observed over recirculation periods of 11-56 hours. A statistical analysis of the t h e r m a l measurements on the 50:50% v o l . p i t c h - C H G O blend presented i n Section 6.5 showed that a l l the significant variations observed i n the inverse overall heat transfer coefficient could be explained by variations i n process variables. T h e analysis of the mass deposition measurements given i n Section 6.1.3 also suggested evidence of very small coke formation over the range of conditions covered. Calculations of an equivalent liquid thickness of a residue layer presented i n Section 6.1.3 revealed that the amounts of coke i n the test section measured i n the runs performed w i t h adequate fluid bed cooling may have come exclusively from this residue layer. A s for the other experiments, it was concluded that the coke collected was formed as a result of batch coking reactions i n the residue left on the tube wall due to inadequate cooling of the fluid bed.  Conclusions & Recommendations  106  • For the tests w i t h the DAO blend, the mass deposition measurements indicated that some fouling has taken place i n Runs 20 and 21, although it was not detected from the thermal measurements. In R u n 19 the thermal data indicated significant fouling. However, no mass deposition measurement were made, hence the evidence is judged insufficient to say whether fouling actually occurred. Nevertheless, based on the observed noise level and the variability i n process variables, and the magnitude of the thermal resistance of the fluid bed, it is clear that the ability of the fouling unit to detect deposit formation must be improved.  7.2  Future Work  Based on the results obtained, the following recommendations are suggested to verify and ensure that the fouling unit is able to form and detect fouling and to provide more insights into the precipitation of carbon-rich material from heating heavy petroleum streams: • A s discussed i n Section 6.3.2, the high thermal resistance due to the fluidized bed m a y be detrimental to the sensitivity of the fouling unit to detect coke formation. Also, the high level of noise observed i n the thermal measurements deteriorates the quality of the data and appears to be due to the intrinsic nature of the fluid bed as suggested i n Section 6.3.1. Moreover, the heat transfer between a fluidized bed and a vertical tube is extremely complex and the experiments revealed the difficulty of maintaining a constant heat flow to the test section, which is essential for a correct interpretation of the fouling data. Hence it seems appropriate to consider another heating method. • It is recommended to use a 'Portable Fouling Research U n i t ( P F R U ) ' probe capable of reaching the desired surface temperatures and which is supplied b y 'Heat Transfer Research Incorporated ( H T R I ) ' because of the successful results obtained w i t h this type of probe i n an apparatus originally constructed by Fetissoff (1982).  It has  several advantages over the fluidized bed. T h e thermal resistance between the probe surface and the bulk liquid is usually the dominant resistance as opposed to the fluidized  bed. Also, it is experimentally much simpler to use because of the fewer  Conclusions & Recommendations  107  operations required to replace the probe and because the heat flow is self-controlled. Due to its design the surface temperature is readily obtained and is likely to be more accurate than the more difficult measurements i n a fluid bed. Furthermore, the evidence of coke formation is more obvious since fouling occurs on the outer surface of the probe. • A s explained i n Section 6.1.2, the amount of toluene insolubles i n the test  fluid  remains approximately constant as long as a critical yield of about 30% has not been reached. It is important to operate under this value to keep the properties of the test fluid constant.  A water condenser has already been installed i n the vent  line of the feeder to return the condensates i n the system. • Because of the change i n viscosity observed i n the experiments and its possible bias effect on the flowrate, it is recommended to monitor the viscosity and to ensure it remains constant during recirculation. • Due to the voltage variations observed, it is recommended to m a i n t a i n the power to the unit constant by using voltage regulators when necessary. • Due to the flammable and toxic nature of the fluids studied and the long periods of time required by the fouling experiments, it is recommended to implement a l l the necessary security devices. A n alarm system relating the pressure drop across the orifice plate to the total power to the unit has been designed and is now being used. T h i s system shuts off the power i n case the pressure signal becomes outside a specified pressure band.  The above suggestions w i l l help ensure that whatever change observed i n the overall heat transfer coefficient is due to fouling not to variations i n process variables, in fluid properties, or to a problem i n the design of the fouling unit. Once the ability of the fouling unit has been confirmed—for example by repeating the tests w i t h the D A O mixture—the coke forming tendency of various blends can be studied systematically by varying the fluid velocity, the bulk and surface temperatures, and the recirculation time.  Bibliography Al-Atar, E. (2000). Effect of oil compatibility and resins/asphaltenes ratio on heat exchanger fouling of mixtures containing heavy oil. M.A.Sc. Thesis. University of British Columbia. Albright, L. F., B. L. Crynes, and W. H. Corcoran (1983). Pyrolysis:  Theory and  industrial practice. New-York: Academic Press Inc. Allan, J. M . and A. S. Teja (1991). Correlation and prediction of the viscosity of defined and undefined hydrocarbon liquids. Can. J. 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Drinkenburg (Ed.), Proceedings of The International Symposium of Fluidization, pp. 739. Amsterdam: Netherlands University Press.  Appendix A Calibrations  The calibration curves for the orifice plates are shown i n Figures A . 2 and A . 3 for different operating temperatures. The numbers in parentheses i n the upper figures refer to the run number while the numbers i n the lower figures corresponds to the discharge coefficient values. T h e calibration curve for the fluidized bed air rotameter is given i n Figure A . l .  Fluidized B e d Air Flowmeter Calibration Curve, T u b e n o . : B - 2 5 0 - 6 / G l a s s Ball  Rotameter S c a l e (cm)  Figure A . l : A i r rotameter calibration curve.  117  118  Calibrations  Orifice Plate 1/8" Discharge Coefficient Versus Reynolds Number (same blend). !  !  '—r~ X X  >  X  •  -"*-^  _o -  <  O 0.5^  0.590  . J  10  i 3  i  I  i  i—1—'•—I- J  10  4  Re  Figure A . 2 : Orifice 1/8" calibration and discharge coefficient; symbols i n lower graph represent same data as i n upper graph; bulk inlet temperature indicated i n legend of upper graph and R u n 8 indicated i n parentheses.  119  Calibrations  Orifice Plate 1/16" Calibration with a 50:50 %vol. Pitch/Coker HGO Blend. 1 1 1 1 1— 1 i i  *  *  o  o  X  X  •  •  0  0  V  V  -  286 °C (12) 289 °C (13) 283 °C (14) 199 °C (15) 286 °C (16) 331 °C (18) m  m^a AP  i  2  , a=0.52319E-04 + 0.17186E-05 (95% CL)  -  • m =b AP , b=0.59136E-04 + 0.17409E-05 (95% CL) 1/2  2  50  _i_  150  100  200  250 AP  1/2  300 (Pa)  350  400  450  500  550  Orifice Plate 1/16" Discharge Coefficient Versus Reynolds Number (same blend). i  1  !  [  j:  -  n  6* o  b  V O  0.5  v  10 Re 3  v  0.636 0.697 0.550  10  4  Figure A . 3 : Orifice 1/16" calibration and discharge coefficient; symbols i n lower graph represent same data as in upper graph; bulk inlet temperature indicated i n legend of upper graph and run number indicated i n parentheses.  Appendix B Properties of Fluids and Distillation T B P curves  Table B . l : Properties of pitch and C H G O Parameter  Pitch  CHGO  Carbon, wt.%  81.6  84.0  Hydrogen, wt.%  9.1  10.5  Sulfur, wt.%  5.3  4.3  Nitrogen, ppm  6557  3810  Aromatic Carbon  34.2  -  M C R , wt.%  27.1  2.8  Ash, wt.%  1.5  -  Density (25°C), g/mL  1.071  0.960  Ni, ppm  159  0.0  V, ppm  422  2.3  ( C i NMR), % 3  Table B.2: Some properties of Fuel O i l , C o l d Lake Heavy O i l and De-Asphalted O i l Parameter  Cold Lake Heavy Oil  Fuel Oil  De-Asphalted Oil  Saturates, wt.%  23.14  69.62  20.72  Aromatics, wt.%  49.84  27.71  68.45  Resins, wt.%  10.4  2.72  10.08  Asphaltenes, wt.%  16.63  Trace  0.76  Polars, wt.%  27.03  2.72  10.84  Carbon, wt.%  80.27  86.41  86.71  Hydrogen, wt.%  10.52  12.76  11.15  Nitrogen, wt.%  0.41  0.21  0.28  Sulphur, wt.%  4.51  0.56  3.54  H / C atomic ratio  1.57  1.77  1.58  120  121  SIMDIST  Figure B . l : SIMDIST for Virgin and Coker HGOs.  Appendix C Size Distribution of Quartz Sand Used in Fluid Bed  Figure C . l : Size distribution of quartz sand used i n fluidized bed; mean particle diameter=0.34 m m . 122  Appendix D Sample Calculations  D.l  Tube Side Velocity, and Reynolds Number.  For rh = 9.2 x I O c  - 3  k g / s , D , = 5.33 x I O  m , and p calculated at ¥  - 3  b  = 287°C from  E q u a t i o n 3.2 (conditions of R u n 10): =  = 0.48 [m/s]  p • irDf  (D.l)  For the same R u n , w i t h v calculated at T from E q u a t i o n 3.9 where A , B , and C are given b  in Table 3.4 (51.7%wt. pitch and D u t t ) , the Reynolds number is:  Re = c  D.2  = 487  v  (D.2)  Heat Flow, Overall Heat Transfer Coefficient, and Thermal Fouling Resistance rT fT (t) out  Q (t) = m(t) /  C (T) • dT (t) [kW]  v  P  b  (D.3)  JT {t) in  where C = (0.055 + 6.818 x 1 0 " • T(t) - 4.464 x 10~ • T ) [ l d / k g - K ] (see L u (1989)) 3  6  2  p  and m is given by E q . 6.12. W i t h D = 6.35 X 1 0 " m and L = 0.46 m , the overall heat 3  Q  transfer coefficient at time t based on the actual mass flowrate is:  Uo, = v  Q  v { t )  irD L • All {Ttop T t) — (T t — Ti ) n  r  A T  0  i  A  where AT/,,,  [m'-K/kW]  —  T  =  (D.4)  m  —r— ln[(l  top  ou  - l t)/(Ibot ou  bo  -  n  ——-  / ,,\ n  (D.5)  lin)\  The thermal fouling resistance is calculated as the difference between the reciprocals of overall heat transfer coefficients under clean conditions a n d at time t:  123  Sample Calculations  124  where U (0) is an average of twenty-one points calculated from the S.S. value reported OiV  i n Table 6.1.  D.3  Superficial Gas Velocity, U, and M i n i m u m Fluidization Velocity, U f. m  4• V  n  u  = 7nf  <'> D 7  where Db=0.05 m and V , the volumetric flowrate of air, is obtained by correcting the g  value read from Figure A . l for the appropriate conditions of pressure and temperature of the fluid bed. T h e m i n i m u m fluidization velocity is given by:  1.75  D.4  (d  p  •p  g  - U m f Y  , 150 • (1 - e ) mf  -dp-pg-  U  d • 3  m  f  =  p  P g  • (p. - p ) • 9  (  g  .  Experimental Bed-to-Wall and Oil Side Heat Transfer Coefficients.  T h e bed-to-tube wall heat transfer coefficient measured i n Runs 16, 20, and 23 was calculated from:  1 \ U  0  nDc-L-ATI^-  1  , J  Q  (D.9)  v  (D.10) AT/  = m  (Tt p,w  T t)  0  ln[{Ttop,w  (Tf)ot,w  ou  ~  Tout)  —  {Tbot,w  where the subscript w refers to outer wall temperature.  ~~ —  Tin) Ti )] n  T h e tube side heat transfer  coefficient measured was calculated according to:  A  • hi = 0  'TXDO • L • A T /  m  A  0  •  ln{D /D,)' 0  2vr • L • k  (D.ll)  125  Sample Calculations D.5  Effect of h on Sensitivity of Unit to detect Coke Formation. 0  A l - A t a r (2000) obtained a fouling resistance of 0.3 m - K / k W — f i n a l value—after recircu2  lating a 75% F O / 1 0 % H O / 1 5 % D A O blend for 380 m i n . at an average bulk temperature of 85.5 ° C , average surface temperature of 222 ° C , and liquid velocity of 0.75 m / s . W h a t change i n 1/U  would result i n our unit given this final value?  0  T h e change i n 1/U  0  is calculated from  \Uo,c J  \Ai-hi + ^  + ho)  and can be expected to be at least 10% i f evident detection is to be made. T h e subscripts C and F refer to clean and fouled conditions respectively. Table D . l gives the results for three values of h , the heat transfer coefficient i n the fluid bed. T h e value of 489 and 451 0  W / m - K for h 2  Q  and /i, respectively are the predicted values for R u n 16. Table D . l : Effect of h on the change i n l / ( 7 . 0  0  hi  Change in 1/Uo  (W/m -K)  (W/m -K)  (%)  489  451  8  1500  451  11  3000  451  12  h  0 2  2  F r o m these results it may be inferred that the sensitivity of the unit is rather low. Also, it is shown that as h  0  increases, the change i n l / ( 7 becomes more significant. 0  Al-Atar  (2000) reported a value of (1/(7 )=0.317 m - K / k W for this r u n , and hence the change i n 2  C  (1/U) was 95% given a final R  of 0.3 m - K / k W . 2  f  126  Sample Calculations D.6  Calculation of parameters presented in Table 6.1  — - — E ( Ttop^ + Tmid^ + Tbot^\ ^ t=s.s. ^  T  tn  T  6  =  1  =  —  JT T (t) t=s.s.  (D.14)  tn  E  f ^ Tin  ^ t=5.5. V  Q =^E  (D.13)  ^  + °«t(*A r  2  (D.15)  y  (- ) D 16  t=S.S.  ^™ = IT E " « W at  "  ,=S.S.  (D  -  17)  (D.18) where t is the total recirculation time, N is the number of data points from S.S. to t , r  and AT (t) lm  r  is given by Equation D . 5 .  

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