Applied Science, Faculty of
Materials Engineering, Department of
DSpace
UBCV
Yamada, Kaiya
Master of Applied Science - MASc
University of British Columbia
Oil and natural gas are important contributors to Canada’s energy sector, and pipelines are the most prevalent means of transporting these products. Modern Canadian pipelines are produced from advanced line pipe steels that have suitable properties for their applications as they are manufactured with the thermomechanical-controlled process (TMCP) and contain an optimized steel chemistry, including a low carbon content usually below 0.1wt% and specific additions of microalloying elements. When the line pipe segments are welded, the region next to the fusion zone experiences rapid heating and subsequent rapid cooling, creating a heat-affected zone (HAZ). The microstructure and, thus, the mechanical properties of the HAZ may be different from that of the as-rolled steel and may have a detrimental effect on pipeline integrity. The area of the HAZ closest to the fusion boundary, referred to as the coarse-grain heat-affected zone (CGHAZ), is subjected to temperatures high enough to dissolve precipitates, such as niobium carbonitrides. The dissolution of these precipitates may result in significant coarsening of the austenite grains. The resulting microstructural changes can lead to inadequate properties, such as insufficient toughness and strength. The purpose of this study was to investigate austenite decomposition kinetics during continuous cooling from coarse-grained austenite in three different line pipe steels with variations in chromium and molybdenum levels. Thermal conditions were simulated with a Gleeble 3500 thermomechanical simulator. Samples were continuously cooled at rates of 3, 5, 10, 30 and 50℃/s. Resulting microstructures were examined with optical microscopy and electron backscatter diffraction (EBSD) analysis. Hardness was measured with a Vickers hardness tester. An increase in molybdenum content from 0.11wt% to 0.26wt% resulted in a decrease in transformation start temperature by approximately 15℃ for all cooling rates. Lower transformation temperatures generated an increase in the high-angle grain boundary density (HAGB) of bainite, which was found to correlate with hardness. The analysis of the role of chromium was inconclusive and will require further studies. The continuous cooling transformation kinetics were modeled for each steel using the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model with the additivity principle.
Continuous Cooling Transformation from Coarse-Grained Austenite in X80 Line Pipe Steels by KAIYA YAMADA B.A.Sc., The University of British Columbia, 2019 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Materials Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (VANCOUVER) December 2022 © Kaiya Yamada, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Continuous Cooling Transformation from Coarse-Grained Austenite in X80 Line Pipe Steels submitted by Kaiya Yamada in partial fulfillment of the requirements for the degree of Master of Applied Science in Materials Engineering Examining Committee: Matthias Militzer, Professor, Materials Engineering, UBC Supervisor Warren J. Poole, Professor, Materials Engineering, UBC Supervisory Committee Member Rizhi Wang, Professor, Materials Engineering, UBC Supervisory Committee Member iii Abstract Oil and natural gas are important contributors to Canada’s energy sector, and pipelines are the most prevalent means of transporting these products. Modern Canadian pipelines are produced from advanced line pipe steels that have suitable properties for their applications as they are manufactured with the thermomechanical-controlled process (TMCP) and contain an optimized steel chemistry, including a low carbon content usually below 0.1wt% and specific additions of microalloying elements. When the line pipe segments are welded, the region next to the fusion zone experiences rapid heating and subsequent rapid cooling, creating a heat-affected zone (HAZ). The microstructure and, thus, the mechanical properties of the HAZ may be different from that of the as-rolled steel and may have a detrimental effect on pipeline integrity. The area of the HAZ closest to the fusion boundary, referred to as the coarse-grain heat-affected zone (CGHAZ), is subjected to temperatures high enough to dissolve precipitates, such as niobium carbonitrides. The dissolution of these precipitates may result in significant coarsening of the austenite grains. The resulting microstructural changes can lead to inadequate properties, such as insufficient toughness and strength. The purpose of this study was to investigate austenite decomposition kinetics during continuous cooling from coarse-grained austenite in three different line pipe steels with variations in chromium and molybdenum levels. Thermal conditions were simulated with a Gleeble 3500 thermomechanical simulator. Samples were continuously cooled at rates of 3, 5, 10, 30 and 50℃/s. Resulting microstructures were examined with optical microscopy and electron backscatter diffraction (EBSD) analysis. Hardness was measured with a Vickers hardness tester. An increase in molybdenum content from 0.11wt% to 0.26wt% resulted in a decrease in transformation start temperature by approximately 15℃ for all cooling rates. Lower transformation temperatures generated an increase in the high-angle grain boundary density (HAGB) of bainite, which was found to correlate with hardness. The analysis of the role of chromium was inconclusive and will require further studies. The continuous cooling transformation kinetics were modeled for each steel using the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model with the additivity principle. iv Lay Summary From a climate change perspective, a transition to renewable energy sources is necessary; however, for the foreseeable future, oil and natural gas will continue to play a significant role in worldwide energy production. Pipelines are used to transport these products, and these pipelines are constructed by welding pipe segments together. Welding may affect pipeline integrity because the area next to the weld (the heat-affected zone, or HAZ) experiences rapid thermal cycles and may develop different microstructures and properties. Also, for a given pipeline construction, the same grade of steel can be sourced from different suppliers, resulting in a difference in chemistry, so the role of steel chemistry needs to be determined. In this study, the effects of cooling rate and additions of chromium/molybdenum on the microstructure and hardness property of the HAZ are investigated. Results from this study may aid the development of steels with improved weldability. v Preface The research presented in this thesis was done as part of an extensive project conducted by the Microstructure Group in the Department of Materials Engineering at The University of British Columbia in collaboration with TC Energy and EVRAZ North America. Samples used in this research were prepared in the machine shop of the Department of Materials Engineering at The University of British Columbia from steels supplied by CanmetMATERIALS in Hamilton, Ontario. I, Kaiya Yamada, am the sole author of this thesis. I conducted the research presented in this paper, including the experimental design, sample preparation, heat treatments, microstructure analysis, hardness testing, and thermodynamic calculations. I also conducted the modelling. Professor Militzer, my supervisor, provided guidance at all stages of the research, modelling, and writing of this thesis. Nicolas Romualdi and Sabyasachi Roy provided additional guidance with the heat treatments, microstructural analysis, and modelling. Professor Poole provided feedback on the structure-property relationships and oversaw the direction of the thesis as part of the larger project. Necessary results and data contributed by members of the project have been incorporated into the thesis and appropriately referenced [17, 51, 59, 60, 124]. Selected data from sections 5.5.4 and 5.6 of this thesis have been included in a published article [129]: S. Roy, N. Romualdi, K. Yamada, W. Poole, M. Militzer, and L. Collins, “The Relationship between Microstructure and Hardness in the Heat-affected Zone of Line Pipe Steels,” JOM, 74, pp. 2395 – 2401, 2022. S. Roy was the first author of this article and was responsible for coordinating the publication process. N. Romualdi contributed to EBSD measurements, statistical analysis, writing, and response to reviewers. K. Yamada provided data regarding high-angle grain boundary density, spatial distribution of misorientation, and hardness. Professors Poole and Militzer were involved in the discussion and editing of the paper. L. Collins contributed additional editorial support. vi Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ......................................................................................................................... vi List of Tables ................................................................................................................................ ix List of Figures .................................................................................................................................x List of Symbols ............................................................................................................................ xii List of Abbreviations ................................................................................................................. xiii Acknowledgements ......................................................................................................................xv Dedication ................................................................................................................................... xvi Chapter 1: Introduction ................................................................................................................1 Chapter 2: Literature Review .......................................................................................................4 2.1 Classification and development of line pipe steels ................................................................4 2.2 The role of steel chemistry in line pipe steels ........................................................................6 2.2.1 Introduction ......................................................................................................................6 2.2.2 The role of specific elements ...........................................................................................8 2.3 Welding of line pipe steels ...................................................................................................11 2.3.1 Pipe production ..............................................................................................................11 2.3.2 Girth welding infield ......................................................................................................12 2.3.3 Single and dual-torch welds and their thermal cycles ...................................................12 2.4 The HAZ ..............................................................................................................................14 2.4.1 Formation of the HAZ ...................................................................................................14 2.4.2 Measuring temperature profiles in the HAZ ..................................................................17 2.5 Continuous cooling and resulting transformation products in the CGHAZ ........................18 2.5.1 Introduction ....................................................................................................................18 2.5.2 Transformation products of the CGHAZ .......................................................................19 2.5.2.1 Polygonal ferrite and pearlite ...................................................................................19 vii 2.5.2.2 Non-equiaxed ferrite ................................................................................................19 2.5.2.3 Bainite ......................................................................................................................20 2.5.2.4 Martensite and the martensite/austenite (M/A) constituent .....................................22 2.5.3 Orientation relationships and variant selection ..............................................................23 2.6 Further study of the effects of cooling rate and chromium and molybdenum additions on the CGHAZ .....................................................................................................27 2.7 Modelling .............................................................................................................................29 Chapter 3: Scope and Objectives................................................................................................35 Chapter 4: Materials and Methodology .....................................................................................36 4.1 Materials ..............................................................................................................................36 4.2 Methodology ........................................................................................................................37 4.2.1 Continuous cooling transformation (CCT) tests ............................................................37 4.2.1.1 Gleeble simulations ..................................................................................................37 4.2.1.2 Design of thermal cycles ..........................................................................................39 4.2.1.3 Dilatometry ..............................................................................................................42 4.2.2 Microstructure characterization .....................................................................................44 4.2.2.1 Sample preparation ..................................................................................................44 4.2.2.2 Optical microscopy imaging ....................................................................................45 4.2.2.3 Electron backscatter diffraction (EBSD) imaging ...................................................45 4.2.3 Mechanical characterization: Hardness testing ..............................................................46 4.2.4 Modelling .......................................................................................................................47 Chapter 5: Experimental Results and Discussion .....................................................................48 5.1 Quality and repeatability of the CCT tests ...........................................................................48 5.2 Effect of cooling rate on the austenite decomposition kinetics ...........................................50 5.3 Effect of molybdenum on the austenite decomposition kinetics .........................................51 5.4 Characterization of microstructure with optical microscopy ...............................................52 5.5 Characterization of microstructure with EBSD ...................................................................53 5.5.1 Inverse pole figure (IPF) maps ......................................................................................53 5.5.2 Retained austenite ..........................................................................................................56 5.5.3 Orientation relationship (OR) between parent austenite and product phase ..................56 viii 5.5.4 Spatial distribution of misorientation.............................................................................59 5.6 Hardness ...............................................................................................................................63 5.7 Microstructure-property relationship ...................................................................................64 5.8 Discussion ............................................................................................................................66 Chapter 6: Modelling ...................................................................................................................70 6.1 Bainite start model ...............................................................................................................70 6.2 Bainite growth model ...........................................................................................................72 6.3 Discussion ............................................................................................................................75 Chapter 7: Summary and Future Work ...................................................................................77 7.1 Summary ..............................................................................................................................77 7.2 Future Work .........................................................................................................................78 Bibliography ................................................................................................................................79 ix List of Tables Table 2.1: Specified minimum yield strengths for API line pipe steels .........................................4 Table 2.2: The 24 variants of the KS orientation (Reprinted from [89] with permission from Elsevier) ......................................................................................................................24 Table 4.1: Steel chemistries with the amount of each element given in wt% and the Ti/N ratio ..............................................................................................................................36 Table 4.2: LUMet results for prior austenite grain size (PAGS) and required hold times [124] ...................................................................................................................40 Table 5.1: List of steel chemistries (wt%) ....................................................................................65 Table 6.1: Nucleation temperatures of the steels ..........................................................................70 Table 6.2: Fit parameters for the steels .........................................................................................71 Table 6.3: Fit parameters and their respective components in the linear function .......................73 x List of Figures Figure 2.1: Schematic diagram of a single-pass weld thermal cycle showing t8-5 ......................13 Figure 2.2: Schematic diagram of dual-torch weld thermal cycles showing a slower cooling rate (i.e., increased t8-5) for the second torch (Reprinted from [51]) ........................14 Figure 2.3: Relation between HAZ regions, peak temperatures, and the Fe-C phase diagram for a single-torch weld pass (Adapted from [7] with permission from Elsevier) .....................................................................................................................15 Figure 2.4: Schematic diagram of the HAZ with a) a single-pass weld and b) a multi-pass weld (Reprinted from [58] with permission from Springer Nature) ..........................17 Figure 2.5: Upper and lower bainite formation (Reprinted from [81] with permission from Elsevier) ....................................................................................................................22 Figure 2.6: Variant pairing within a prior austenite grain for the three different transformation products as classified by Takayama et al. (Reprinted from [89] with permission from Elsevier) ..................................................................................25 Figure 4.1: Tubular sample diagram .............................................................................................37 Figure 4.2: Gleeble 3500 thermomechanical simulator set-up .....................................................38 Figure 4.3: Single-cycle heat treatment schematic for CCT tests .................................................41 Figure 4.4: Dilation vs. temperature for a single-pass heat treatment ..........................................42 Figure 4.5: Normalized dilation vs. temperature ..........................................................................43 Figure 4.6: Fraction transformed vs. temperature .........................................................................44 Figure 5.1: Evolution of cooling rate for different initial cooling rates (Black markers indicate the transformation start temperature for each cooling rate.). .......................49 Figure 5.2: Repeat tests for L06C06NbCrMo at 10˚C/s ...............................................................49 Figure 5.3: Effect of cooling rate on the austenite decomposition kinetics for L06C06NbCr .....50 Figure 5.4: Effect of cooling rate on transformation start temperature for the three steels ..........51 Figure 5.5: Effect of molybdenum on austenite decomposition kinetics......................................52 Figure 5.6: Optical micrographs for L06C06NbCr at different cooling rates (a) 3°C/s (b) 10°C/s and (c) 30°C/s ...........................................................................53 Figure 5.7: Inverse pole figure maps for L06C03Nb at 50˚C/s (a) raw (b) cleaned .....................54 Figure 5.8: Inverse pole figure maps for L06C06NbCr at different cooling rates (a) 5°C/s (b) 10°C/s and (c) 50°C/s ...........................................................................55 xi Figure 5.9: Inverse pole figure maps at 50°C/s for (a) L06C06NbCr and (b) L06C06NbCrMo ...................................................................................................55 Figure 5.10: Retained austenite in L06C06NbCr at 5°C/s ............................................................56 Figure 5.11: (a) Theoretical (001) pole figure (Black circles indicate the 24 KS variants, and green dots indicate the orientation of the parent grain.); (b) (001) pole figure of the selected grain; and (c) Bain map for the selected grain (For L06C06NbCr for 5˚C/s) ..........................................................................57 Figure 5.12: Bain group maps and corresponding pole figures for cooling rates of (a, b) 10˚C/s and (c, d) 50˚C/s for L06C06NbCr .....................................................58 Figure 5.13: Misorientation angle maps for L06C06NbCr at different cooling rates (a) 5°C/s (b) 10°C/s and (c) 50°C/s .........................................................................59 Figure 5.14: Misorientation angle maps for (a) L06C06NbCr and (b) L06C06NbCrMo at 50˚C/s ........................................................................................................................60 Figure 5.15: Distribution of misorientation angle for the three steels at different cooling rates (a) 5°C/s (b) 10°C/s and (c) 50°C/s ........................................................................61 Figure 5.16: Effect of cooling rate on HAGB density ..................................................................62 Figure 5.17: Effect of transformation start temperature on the square root of HAGB density for Population 1 (L06C03Nb, L06C06NbMo) and Population 2 (L06C06NbCr, L06C06NbCrMo) .....................................................................................................63 Figure 5.18: Effect of cooling rate on hardness ............................................................................64 Figure 5.19: Relationship between HAGB density and hardness (Adapted from [129] with permission from Springer Nature) ...........................................................................65 Figure 5.20: Transformation start temperatures for L06C06Nb, L06C06NbMo, L06C06NbCr and L06C06NbCrMo [17].........................................................................................67 Figure 6.1: Comparison of calculated and measured transformation start temperature for the 3 to 30°C/s cooling rate thermal paths of the three steels ..............................71 Figure 6.2: Transformation start temperature based on cooling rate ............................................72 Figure 6.3: Measured and calculated transformation kinetics of L06C06NbCr ..........................74 Figure 6.4: Comparison of measured and calculated temperatures at 50 and 95% transformation ............................................................................................................75 xii List of Symbols α Ferrite 𝛽 Temperature-dependent function in the JMAK equation 𝛽ଵ and 𝛽ଶ Fit parameters based on steel chemistry in the bainite growth JMAK model γ Austenite δ Delta ferrite 𝜑 Cooling rate Ac1 Temperature at which austenite begins to form during heating Ac3 Temperature at which the transformation of ferrite to austenite is completed during heating Ae1 Equilibrium ferrite to austenite transformation start temperature Ae3 Equilibrium ferrite to austenite transformation end temperature Ar1 Temperature at which the transformation of austenite to ferrite or to ferrite plus cementite is completed during cooling Ar3 Temperature at which austenite begins to transform to ferrite during cooling. b Temperature-dependent rate parameter in JMAK equation b1 and b2 Chemistry-dependent JMAK model fit parameters d Average diagonal length of the indent for the hardness tests l Characteristic length scale n Avrami exponent in the JMAK equation HAGBD Value for the HAGB density P Load applied in hardness tests T Temperature t Time T50 50% transformation temperature T95 95% transformation temperature t8-5 Cooling time between 800 and 500℃ 𝑇ௌ஻ Bainite start temperature TN Nucleation temperature Tnr Non-recrystallization temperature X(t) Fraction of phase transformed during time t in the JMAK equation xiii List of Abbreviations ACC Accelerated cooling API American Petroleum Institute ASTM American Society for Testing and Materials BCC Body-centered cubic BCT Body-centered tetragonal BF Bainitic ferrite CA Cellular automata CCT Continuous cooling transformation CE Carbon equivalent CGHAZ Coarse-grain heat-affected zone CI Confidence index CP Close-packed plane CTE Coefficient of thermal expansion DBTT Ductile-brittle transition temperature EBSD Electron backscatter diffraction EDAX Energy dispersive X-ray analysis EQAD Equivalent area diameter ERW Electric resistance welding FCC Face-centered cubic FGHAZ Fine-grain heat-affected zone GMAW Gas metal arc welding HAGB High-angle grain boundary HAZ Heat-affected zone HSAW Helical seam submerged arc welding HSLA High-strength low alloy HV Vickers hardness ICCGHAZ Inter-critically reheated coarse-grain heat-affected zone ICHAZ Inter-critical heat-affected zone IIW International Institute of Welding IPF Inverse pole figure xiv JMAK Johnson-Mehl-Avrami-Kolmogorov KS Kurdjumov-Sachs LAGB Low-angle grain boundary LSAW Longitudinal seam submerged arc welding LUMet Laser Ultrasonics for Metallurgy M/A Martensite/Austenite MC Monte Carlo MICRESS Microstructure Evolution Simulation Software MTEX Mega Texel NSERC Natural Sciences and Engineering Research Council OIM Orientation imaging microscopy OR Orientation relationship PAGB Prior austenite grain boundary PAGS Prior austenite grain size PFM Phase field modelling RA Retained austenite SAW Submerged arc welding SCHAZ Sub-critical heat-affected zone SEM Scanning electron microscope STEM Scanning transmission electron microscope TMCP Thermomechanical-controlled process TRIP Transformation induced plasticity TSL TexSEM Laboratories xv Acknowledgements There are several people I would like to acknowledge for helping me accomplish my goal of attaining a Master of Applied Science degree. I would like to express my deepest gratitude to my supervisor, Professor Matthias Militzer, for his guidance and support during the undertaking of this degree. Special thanks also to Professor Warren Poole for his invaluable input during our group meetings and to Professor Chad Sinclair for all the support he has given me over the years. I am also grateful to the National Research Council of Canada (NSERC), TC Energy, and EVRAZ North America for their financial support. I would also like to express my gratitude to members of the Microstructure Group. A special thanks to Nicolas Romualdi for providing training on the Gleeble 3500 and with Thermo-Calc software, for giving advice on data analysis and modelling, and for being a great mentor and friend. Thanks to Sabyasachi Roy for training on the Gleeble, Vickers hardness tester, and EBSD, and for all the other ways you have helped me. I would also like to acknowledge Brian Tran for his training in metallography. Thank you also to Mariana, Rosanne, and Minghui for creating a positive environment in the lab. Nobu, Maddie, Ayush, Hari, Naveen and Freddy, I will always fondly remember our hiking trips, even though my feet may feel otherwise. I would also like to acknowledge other members of the Department of Materials Engineering and those affiliated with it. This includes Heli Eunike for her help with the EBSD and Michelle Tierney and Rebecca Abbott for all that they do to keep our department running smoothly. Thank you also to David Torok from the machine shop for preparing the steel samples. I would also like to thank my good friends who supported me throughout my degree. Without your timely distractions, I would have forgotten to have a beer every now and then. Finally, I would like to express my heartfelt thanks to my parents. Leon and I are both so incredibly lucky to have won the “oya-gacha.” xvi For my parents with genuine gratefulness and the warmest regard 1 Chapter 1: Introduction Oil and natural gas remain important contributors to Canada’s energy industry and economy, and pipelines are an efficient means of conveying these products. In Canada, there are more than 840,000 kilometers of oil and natural gas pipelines, including those used for the gathering, feeding, transmission, and distribution of these products [1]. Line pipe steels are used to manufacture these pipelines; modern line pipe steels are low carbon microalloyed steels designed to have specific properties suitable for their application. Both safety and economic concerns have led to the demand for higher performance pipelines. Pipeline integrity is paramount as accidents can cause the loss of life, endanger the environment, and precipitate severe financial repercussions for pipeline companies. Further economic considerations in the energy industry have also driven the demand for high-performance pipelines. For example, higher throughput capacity has been required, which has been achieved through larger diameter pipe and/or greater operating pressures. In addition, a reduction in pipe wall thickness has become possible as higher strength line pipe steels have been developed, and this has reduced costs [2, 3]. Particularly with the expansion into the Arctic for oil and natural gas reserves, new challenges have arisen that have influenced pipeline design and line pipe steel selection. Arctic pipelines are subjected to extremely cold temperatures as well as discontinuous permafrost with seasonal heave and thaw. Heave and thaw produce high strains in the pipes during operation [4]. Therefore, pipelines with a strain-based design have become standard, and line pipe steels with enhanced mechanical properties, including improved strength and toughness, are selected. Two main factors have facilitated the improvement of line pipe steels. First, advanced processing methods, such as thermomechanical-controlled processing (TMCP), have been of major significance for line pipe steel development. TMCP, which combines controlled rolling with accelerated cooling (ACC), is used to refine the microstructure of the steels and, thus, improve the steel properties. Second, the optimization of steel chemistry, through the reduction of carbon content and a sagacious use of microalloying elements, has also led to microstructure refinement in advanced line pipe steels and resulting properties, which include high strength, notable 2 toughness, and good weldability. Weldability refers to the ease with which metals can be fused without producing imperfections, such as cracks, in the finished product. When pipelines are constructed, pipe segments are welded end-to-end by circumferential welds called girth welds, and next to the weld pool, an area called the heat-affected zone (HAZ) develops. The microstructure and, thus, the mechanical properties of the HAZ may differ from those of the as-supplied steel. This may affect pipeline integrity. The HAZ, itself, is composed of different regions, and these regions vary in microstructure and properties, with some regions being at greater risk of failure. The region adjacent to the weld pool, referred to as the coarse-grain HAZ (CGHAZ), experiences a very high temperature, which results in austenite grain coarsening. Due to the coarse prior austenite grain size, this area of the HAZ has higher hardenability, meaning transformation products such as hard martensite form more readily upon cooling, which may result in reduced toughness and increased ductile-brittle transformation temperatures (DBTT). The CGHAZ is a region thought to be at risk for failure due to poor toughness and susceptibility to cracking [5]. Various factors determine the microstructures that form in the HAZ. One factor is the welding process. As line pipe steels have been improved, new welding technologies have also been developed to make pipeline construction more efficient and economical. For example, gas metal arc welding (GMAW) has been developed to include both tandem and dual-torch, as well as single-torch [6]. The welding processes with their different thermal cycles affect the microstructure and, thus, the properties of the HAZ. Steel chemistry is another factor that determines the microstructure and properties of the HAZ [7]. Steel chemistry can be optimized to enhance weldability and improve pipeline integrity. The aim of this research was to investigate austenite decomposition during continuous cooling for conditions of the CGHAZ in three different line pipe steels. The focus was to determine the effects of cooling rate and the addition of the alloying elements chromium and molybdenum on the austenite decomposition kinetics in these steels. Tests were carried out using a Gleeble 3500 thermomechanical simulator. Optical microscopy and electron backscatter diffraction (EBSD) analysis were employed for microstructure characterization. Hardness tests were performed with 3 the Vickers hardness test method. A microstructure model was developed for each steel, taking prior austenite grain size and cooling rate into account. This research is part of a larger project carried out by the Microstructure Group at The University of British Columbia in collaboration with EVRAZ North America, a leading producer of line pipe steel, and TC Energy, a major North American energy infrastructure company. The main objective of the project is to develop a steel chemistry-dependent microstructure/mechanical property model for the CGHAZ. The model is expected to aid the development of steels with improved weldability as well as the design of optimized welding procedures. 4 Chapter 2: Literature Review 2.1 Classification and development of line pipe steels With increased pipeline construction in harsh environments such as in the Arctic, the need for pipelines with greater operating pressure, the economic concerns of pipeline construction, and increasing concerns about pipeline safety, the demand for line pipe steels with improved properties has increased, and this has spurred the development of these steels. This section explains this development and how these steels can be classified according to their strength. The first specification for line pipe steels introduced by the American Petroleum Institute (API) in 1948 was X42, and since then, various grades of line pipe steels have been developed [8]. With this nomenclature, the number next to the X stands for the minimum yield strength requirement for this grade in thousands of pounds per square inch, or ksi. Table 2.1 also shows the specified minimum yield strengths of various grades of API line pipe steels in megapascals, or MPa [9]. Table 2.1: Specified minimum yield strengths for API line pipe steels Steel Pipe Grade X42 X46 X52 X56 X60 X65 X70 X80 X90 X100 X120 Minimum Yield Strength (MPa) 290 320 360 390 415 450 485 555 625 690 830 The early microalloyed steels, such as X52 and X60, with a pearlite-ferrite microstructure, were typically manufactured by the conventional rolling and normalizing processes [10]. The first microalloyed steels, API Grade X52 steels, were vanadium strengthened and usually normalized to develop adequate toughness [11]. With the use of various microalloying elements and the development of improved processing methods, such as TMCP, both the strength and toughness of line pipe steels have progressively increased [11]. Steel chemistry is discussed at length in Section 2.2. A brief introduction to TMCP follows. With TMCP, steel plates or coiled strips are produced, and from these plates or strips, pipes are then manufactured [10, 12]. The production of TMCP steel plates involves several steps, including heating, rough rolling, finish rolling and cooling. Heating of the as-received slabs results in austenite grain growth. Rough rolling at high temperatures refines the austenite grain size. Finish rolling then takes place below the non-recrystallization temperature, 5 or Tnr. This is the temperature below which recrystallization becomes practically impossible [12]. Deformation below the Tnr leads to the accumulation of strain hardening, resulting in pancaked austenite at the end of finish rolling; consequently, more nucleation sites are made available for the austenite to ferrite transformation, and this promotes the formation of a fine-grained ferrite microstructure [13]. Finally, during cooling, phase transformation occurs. The austenite decomposition during cooling determines the final microstructure and properties of the steel. An increased cooling rate shifts the austenite decomposition to lower temperatures, which leads to higher strength by ferrite grain refinement and/or the formation of other transformation products, such as bainite and martensite [10]. The production of coiled strips is similar to the production of plates, but finish rolling is done in a tandem mill, and the rolling time is short, so, unlike in plate rolling, little or no strain-induced precipitation occurs. The control of the coiling temperature is important for precipitation strengthening [10]. Major Canadian pipelines installed in recent decades are made from X70 and X80 grade steels, which have low carbon contents and contain primary microalloying elements such as niobium, vanadium and/or titanium [14]. With the X70 grade steels, appropriate microalloying and the use of thermomechanical-controlled rolling resulted in grain-refined microstructures, including irregular ferrite, and improved properties, such as increased strength and toughness [15, 16]. Strategic use of microalloying elements and advancements in controlled hot rolling along with accelerated cooling gave rise to the next generation of line pipe steels, X80 [15, 17]. These steels have microstructures consisting of fine-grained irregular ferrite and bainite, and they may contain martensite/austenite (M/A) constituents as well as different precipitates [15, 17]. Compared to lower strength grades, the X80 grade steels are advantageous in an economic sense as, for a given operating pressure, the wall thickness of the pipe can be reduced. With reduced wall thickness, fewer raw materials are required, and transportation and welding costs can also be decreased [18]. The large-diameter, high-pressure Arctic pipelines that use a strain-based design require high-strength line pipe steels, such as X80 [19]. The higher grades of line pipe steels from X90 to X120 are very low carbon microalloyed steels with additional alloying elements such as manganese, niobium, vanadium, titanium, molybdenum, chromium, nickel, silicon, and copper [20]. These steels are produced with 6 thermomechanical-controlled processing. With the X90 steels, there is increased cooling and grain refinement compared to the X80 steels [10]. X90 consists primarily of a bainitic microstructure. A small batch of X90 line pipe steel has been used in the West-East Gas Pipeline in China [21]. With the next generation of line pipe steels, X100, again, there is an increase in cooling and grain refinement [10]. Numerous processing routes can be used to achieve the strength required for the X100 grade. These include variations between carbon content, carbon equivalent, cooling rate, and cooling stop temperature [4]. The X100 steels have very high strength as they consist of highly dislocated bainite or acicular ferrite microstructures [15, 17]. X100 steels have been used for demonstration and test purposes by TC Energy (formerly TransCanada Pipelines Ltd.). However, commercial applications of these steels have been limited as the steels show a propensity for brittle fracture [16]. The latest generation, X120 steels, are currently being developed. With this high-strength grade, boron microalloying may be used [22, 23, 24]. The use of minute amounts of boron can promote lower temperature transformation products while maintaining alloying costs at lower levels [23]. 2.2 The role of steel chemistry in line pipe steels 2.2.1 Introduction Steel chemistry plays an important role in determining the microstructure and resulting properties of line pipe steels, such as strength, toughness, corrosion resistance, and weldability. Suitable additions of alloying elements contribute to strength by various mechanisms, including grain refinement, solid solution strengthening, work hardening, and precipitation strengthening [25]. The refinement of austenite grain size also improves toughness. Besides strength and toughness, corrosion resistance must be considered when designing steel chemistry; alloying elements such as chromium, copper, and nickel improve corrosion resistance [10]. The correct combination of alloying elements is also important for the weldability of line pipe steels; steels with poor weldability may develop cracks and other imperfections. The weldability of steels is usually expressed in terms of a carbon equivalent (CE) limit. Generally, steels with a CE below 0.4wt% are considered to have good weldability [10]. Several different CE formulae are given in the literature. For carbon contents below 0.18wt%, the Ito-Besseyo formula [7] can be used; the CE (in wt%) is given by 7 𝐶𝐸 = 𝐶 + 𝑆𝑖30 +𝑀𝑛+𝐶𝑟+𝐶𝑢20 +𝑁𝑖60 +𝑀𝑜15 +𝑉10 + 5𝐵 . (2.1) The chemical limitations for different grades of API line pipe steels are specified and can be found in [9]. An example of a typical alloy design approach for an X80 line pipe steel might include less than or equal to 0.06wt% carbon, less than 1.7wt% manganese, less than 0.40wt% silicon and less than or equal to 0.10wt% niobium. Typically, a Ti-Nb microalloying concept is employed where Ti additions, generally in the range of 0.01 to 0.02wt% [17], are below the stoichiometric level for TiN precipitation. Alloying elements such as copper, nickel and chromium may be added singly or in combination of up to ~0.6wt%, and molybdenum when added is usually up to ~0.3wt%. For higher grades, such as X100 and X120, increased additions of manganese, copper, nickel, chromium, and molybdenum are common. For X120, boron may also be added [26]. Vanadium is a microalloying addition in the range of 0 to 0.1wt% that can be found in some line pipe steels. The actual steel chemistries for line pipe steels are strategically designed so the steels have properties suitable for their specific applications. Line pipe steels designed for Arctic conditions need a combination of high strength and toughness, excellent resistance to hydrogen-induced cracking and superior field weldability. Arctic pipelines extend long distances, and there is a need to increase operating pressure, which requires greater wall thickness and/or higher strength steels such as API X80 and above. Arctic pipelines must also be capable of withstanding sub-zero temperatures and seasonal changes in temperature. These pipelines experience seasonal heave and thaw due to discontinuous permafrost, so they require a strain-based design and high strength steels. In addition, the steels must be resistant to the effects of corrosion and hydrogen embrittlement. Steels that have excellent mechanical properties at Arctic temperatures often contain minimal amounts of nitrogen, sulfur, and phosphorus. Proportions of elements such as carbon, manganese, silicon, and niobium are optimal to increase impact toughness. The content of carbon and manganese are carefully limited to reduce unwanted segregations and ensure good weldability [27]. Another example in which steel chemistry must be carefully designed is for line pipe steels used in sour service. Particularly in sour gas environments, line pipe steels must have excellent resistance to hydrogen-related damage such as hydrogen-induced cracking and sulfide stress 8 cracking. Chemistry is carefully selected for hydrogen-induced corrosion-resistant steel grades that are used in sour service, such as X65. Typically, the chemistry of these steels includes lower levels of carbon, manganese, phosphorous and sulfur. Calcium may also be added to prevent the formation of elongated MnS [28]. 2.2.2 The role of specific elements Iron is the main constituent in line pipe steels. Iron is an allotropic metal [29]. At room temperature, the stable form is called ferrite, or α-iron. It has a body-centered cubic (BCC) crystal structure. Upon heating, ferrite transforms to austenite, or γ-iron, at 912⁰C [29], which has a face-centered cubic (FCC) crystal structure [30]. Then at 1394⁰C, the FCC austenite reverts to a BCC phase known as δ-ferrite (delta ferrite), which finally melts at 1538⁰C [29]. Carbon is important for strength and hardenability in steels. Several sources in the literature explain the importance of carbon levels in microalloyed steels; in particular, Gladman [31] has done an extensive study on the microalloying of low carbon steels, as well as medium and high carbon steels. Of particular importance for modern steel is that carbon is more soluble in austenite than in ferrite, and this difference in solubility provides opportunities for strengthening by heat treatment [32]. Carbon can significantly strengthen steels through mechanisms such as interstitial solid solution strengthening; however, it can also form brittle precipitates and reduce toughness and weldability [31]. Therefore, the appropriate amount of carbon addition is essential to ensure a good combination of strength and toughness and to achieve superior weldability. For advanced line pipe steels, the carbon content is reduced to about 0.03 to 0.06wt% [13]. With carbon concentrations in this range, excellent weldability can be attained. The loss of strength due to the lower carbon content is mitigated by adding other alloying elements, such as manganese, niobium, titanium and/or vanadium [10]. Carbon, as well as several other elements, can have a thermodynamic effect on austenite decomposition. For equilibrium transformation, elements such as carbon, manganese, nitrogen, nickel, and copper decrease the austenite to ferrite transformation temperature and widen the temperature range for stable austenite. These elements are categorized as austenite stabilizers [17, 33]. Conversely, elements such as niobium, molybdenum, chromium, and vanadium 9 increase the austenite to ferrite transformation temperature, contracting the austenite field and widening the temperature range for ferrite. These elements are categorized as ferrite stabilizers [17, 33]. It is important to note that in addition to having a thermodynamic effect, some of these elements, such as niobium, molybdenum, and chromium, also have kinetic effects on transformation during continuous cooling. Niobium is a very important microalloying element for line pipe steels. In the TMCP process, during reheating, niobium precipitates can prevent austenite grain growth via the pinning effect until they dissolve [34]. Niobium also strongly retards static recrystallization and grain growth in hot rolled austenite, which enables rolling practices in the non-recrystallization area [10]. As previously explained, this results in pancaked austenite at the end of finish rolling [13, 35]. In addition, niobium in solid solution has an effect on austenite decomposition. Niobium is a ferrite stabilizer; as such, it should raise the austenite to ferrite transformation temperature. While large amounts of niobium can thermodynamically act as a ferrite stabilizer to raise the transformation temperature, the amount of niobium present in line pipe steels is usually less than 0.1wt% [36], so the effect on equilibrium transformation temperature may be considered negligible. Instead, during continuous cooling, niobium in solution is found to depress the transformation start temperature kinetically [35]. The depression of the transformation start temperature has been attributed to the solute drag effect of niobium on the austenite decomposition kinetics [37]. There has also been considerable debate about the effect of niobium on the weldability of line pipe steels. Notably, niobium is not included in the Ito-Besseyo CE equation. There have been different opinions about the effect of niobium, especially on the toughness of the HAZ, during the thermal weld cycle. Kirkwood [38] reviews the findings of different researchers who have focused on how niobium may affect the formation of M/A constituents in the HAZ and how the M/A constituents may or may not be detrimental to HAZ toughness. Kirkwood concludes by dismissing the idea that niobium levels should be restricted to avoid unacceptably low toughness in steel specifications for line pipe steels. These steels can be produced without niobium microalloying adversely affecting weldability. Titanium is another microalloying element that may be used in line pipe steels. Titanium is a strong nitride former, and one precipitate it forms in austenite (and even in the liquid steel) is 10 titanium nitride (TiN). TiN is very stable at high temperatures, and it effectively prevents austenite grain coarsening by pinning grain boundaries during slab soaking at high temperatures, thus providing a fine austenite grain structure. These particles are also effective in limiting the austenite grain growth in the coarse-grain heat-affected zone during welding, which improves weldability [23]. For effective grain refinement, an appropriate level of titanium and nitrogen concentrations in terms of their ratio is important. There has been debate about this ratio. Zhu et al. [39] have done an extensive review on the role of titanium and nitrogen in line pipe steel welds and discuss the Ti/N ratio at length. Wang [40] has shown that grain boundary pinning is most effective with TiN precipitates at the stoichiometric Ti/N ratio, i.e., 3.42. However, in another study [41], it was noted that the Ti/N ratio should be lower than the stoichiometric ratio to ensure a low coarsening rate of TiN precipitates. Very large TiN precipitates are ineffective at preventing austenite grain coarsening [23]; a loss of pinning can result if the TiN distribution density is decreased [17]. Large precipitates can also be detrimental to toughness as they can serve as initiation sites for cleavage fracture [42]. Molybdenum may also be added to line pipe steels. Molybdenum, like niobium, is a ferrite stabilizer [33], but during industrial cooling conditions, it is effective in delaying the formation of ferrite and preventing pearlite formation [10]. Mohrbacher [43] suggests that solute molybdenum can substantially delay ferrite formation by reducing carbon diffusivity and exerting a strong drag force on moving grain (phase) boundaries. A study conducted by Zhao et al. [44] shows that the addition of 0.32wt% molybdenum greatly suppresses or delays the formation of polygonal ferrite and pearlite in low carbon line pipe steels. Molybdenum in modest amounts can delay austenite decomposition and promote transformation products with greater strength, such as non-polygonal ferrite and bainite; however, some researchers have also pointed out that excessive amounts of molybdenum may be detrimental to toughness due to the increased hardenability and the formation of products such as M/A constituents [16]. Mohrbacher [43] also discusses at length the combined effects of niobium and molybdenum processing and resulting properties in TMCP steels. Mohrbacher concludes that molybdenum can reduce the rate of NbC precipitation in austenite. A significant amount of niobium in solid solution after finish rolling can delay the transformation from austenite to ferrite to a lower 11 temperature, and it can precipitate during or after the phase transformation. These precipitates can provide effective strengthening. Additions of molybdenum can also lead to complex precipitates such as (NbMo)4C3 and further strengthening [10]. Chromium may also be included in line pipe steel chemistry. Additions of chromium can improve corrosion resistance in TMCP steels [10]. Chromium is also a strong carbide former, and carbides can contribute to the strength of steels [17]. Like niobium, chromium is a ferrite stabilizer [33], but kinetically it has been shown to delay austenite decomposition [17, 45]. The amount of chromium added to line pipe steels is important; if the amount is too high, the HAZ toughness, as well as field weldability, can be deteriorated [23]. Other elements present in the line pipe steels in this study include manganese, silicon, and aluminum. Manganese is a solid solution strengthener, and it can also delay austenite decomposition. Silicon is a solid solution strengthener and a deoxidizer. Aluminum also functions as a deoxidizer and a grain refiner [10]. 2.3 Welding of line pipe steels 2.3.1 Pipe production Following the production of plate and coil, which was explained in Section 2.1, pipe is then manufactured. For welded pipe, one welding process used to manufacture the pipes is submerged arc welding (SAW). Pipes from plate can be produced in longitudinal seam submerged arc welding (LSAW) mills, and pipes from coiled strip can be made in helical seam submerged arc welding (HSAW) mills [12]. SAW is a welding process that melts and joins metals by heating them with an arc that is established between the metals and a wire electrode. This arc is not visible because it is shielded by a granular flux. With SAW, pressure is not used, and the filler metal is mostly obtained from the wire electrode, which is fed through the flux. Shielding gas is not necessary as the molten material is separated from the air. Because the arc is submerged, spatter and heat loss to the air are eliminated. SAW has a high deposition rate, but the relatively high heat input can reduce the weld quality [46]. Another welding process that can be used to manufacture pipes is electric resistance welding (ERW). It has long been used for making longitudinal seam welds. With ERW, pressure is used, 12 but filler material is not. The starting material of ERW is hot rolled steel coil. Pipe is made by cold forming a flat steel strip into a tubular shape. Then between the two edges of the steel, a current is passed, and heat is generated due to the material’s resistance to the flow of current. The steel edges are heated and then forced together to form a bond [47]. Initially, with the ERW process, low-frequency A.C. current was used to heat the steel edges. However, the welds of low-frequency ERW were prone to developing hook cracks, and they had other weaknesses, such as inadequate seam bonding and susceptibility to selective seam corrosion. Currently high-frequency processes are used, such as high-frequency induction welding and high-frequency contact welding, which produce a higher quality weld [48]. As the starting material used to form pipes with the ERW process is steel coil, the circumference of the pipe is limited to the width of the coil. Usually, for ERW, the maximum outer diameter of the pipe is 26 inches, or 660.4mm. For larger dimensions, pipe will be manufactured by SAW [47]. 2.3.2 Girth welding infield After the pipes are formed and tested, they are transported to the construction site. Construction of a pipeline infield involves joining sections of pipe with circumferential welds known as girth welds. High-caliber girth welds are important for pipeline integrity [37]. One of the main types of welding used for the girth welds of high-strength line pipe steels is gas metal arc welding (GMAW) [49]. In GMAW, an electric current is used to strike an arc between the base metal and an electrode. This electrode melts and, with some melted base metal, forms the weld metal. The arc is shielded from atmospheric contaminants by a shielding gas. In pipeline production, a large portion of the cost is due to welding and weld inspection; therefore, there has been significant research done to improve welding productivity and reduce cost. Several new methods to increase productivity, such as tandem wire, dual-torch GMAW, and laser-hybrid welding have been developed [6]. 2.3.3 Single and dual-torch welds and their thermal cycles As dual-torch welding processes, such as dual-torch GMAW, have been introduced to increase productivity, it is important to briefly explain the difference in thermal cycles between single and dual-torch welds. For a single-pass weld, the thermal cycle at a point will rapidly reach a peak 13 and cool, as shown in Figure 2.1. In this figure, t8-5 refers to the time to cool from 800°C to 500°C [4]. Steel weld properties are affected by their cooling rates in this temperature range as generally the phase transformations important for the evolution of the final microstructure of the weld take place in this range [50]. Figure 2.1: Schematic diagram of a single-pass weld thermal cycle showing t8-5 With the dual-torch welding system, the second torch follows the lead torch at an established distance (i.e., 50 to 200mm). The result is that more weld metal can be deposited than with a single-torch pass, and, thus, welding productivity can be increased. With the dual-torch system, two thermal cycles are created. Gaudet points out that the thermal cycle of the second torch may be affected by the leading torch, and, thus, the cooling rate may be slowed for the second torch (i.e., t8-5 increases for the second torch), as shown in Figure 2.2 [51]. 14 Figure 2.2: Schematic diagram of dual-torch weld thermal cycles showing a slower cooling rate (i.e., increased t8-5) for the second torch (Reprinted from [51]) 2.4 The HAZ 2.4.1 Formation of the HAZ During the construction of a pipeline, when pipe segments are welded, the ends of the pipes that are joined are heated to very high temperatures and then rapidly cooled. This intense thermal cycle introduced by the welding process may alter the original microstructure and the properties of the base metal in the area near the weld. This area is referred to as the heat-affected zone (HAZ) [7]. Different regions of the HAZ experience different peak temperatures and have different microstructures [7]. Figure 2.3 shows the relation between the HAZ regions, peak temperatures, and the Fe-C phase diagram for a single-pass weld. From closest to the fusion line, these areas are the coarse-grain heat-affected zone (CGHAZ), fine-grain heat-affected zone (FGHAZ), inter-critical heat-affected zone (ICHAZ), and sub-critical heat-affected zone (SCHAZ). While this diagram is helpful for understanding the relationship between the temperatures and the changes that occur in the HAZ regions, it must be noted that welding is a non-equilibrium process, and other phases besides those shown may form. 15 . Figure 2.3: Relation between HAZ regions, peak temperatures, and the Fe-C phase diagram for a single-torch weld pass (Adapted from [7] with permission from Elsevier) The coarse-grain HAZ (CGHAZ) is the region adjacent to the fusion boundary. Because of its coarse grain size, it is not only more hardenable but also less ductile than other areas [52]. It is thought to be at risk for failure due to poor toughness and susceptibility to cracking [5]. In this area, there is a high peak temperature (generally between 1100°C and the melting point of the steel), and the base metal is heated into the austenite () region [7, 53]. Ferrite completely transforms to austenite (α—>). Microalloying precipitates that pin the austenite grain boundaries can dissolve into the austenite, resulting in grain coarsening. For example, the dissolution of niobium carbide and niobium carbonitrides can result in significant grain growth. On the other hand, titanium nitride particles remain stable at very high temperatures and can control the grain size in the CGHAZ [17]. The degree of austenite grain coarsening is dependent upon the alloy composition and the energy input from the weld [54, 55]. Upon continuous cooling, the austenite decomposition products that form in the CGHAZ are the result of a combination of factors such as prior austenite grain size, cooling rate, and the presence and state of alloying elements such as niobium, molybdenum, etc. In X80 line pipe steels, the CGHAZ in general consists of irregular ferrite and bainite. M/A constituents may also be present [17, 56]. 16 Next to the CGHAZ, at a greater distance from the fusion boundary, is the fine-grain HAZ (FGHAZ). In this region, the metal is heated into the austenite region but to a lower temperature than in the CGHAZ. While complete austenite formation occurs, the grain size remains small [7]. In addition, carbonitride precipitates may not fully dissolve, and they may continue to slow grain boundary motion. On cooling, austenite tends to transform into fine-grained ferrite/pearlite microstructures. The microstructures that form depend, of course, on factors such as alloy composition, welding energy input, etc. [4, 7]. The next region further from the fusion boundary is the inter-critical heat-affected zone (ICHAZ). This is an area that is heated above the Ac1 but below the Ac3 temperature. During heating, Ac1 represents the temperature at which austenite starts to form, and Ac3 represents the temperature at which the ferrite to austenite transformation is finished [51]. In this area, there is some austenite transformation, but only to a limited degree. Peak temperatures do not allow the microstructure to become fully austenitized. Upon cooling, a wide range of microstructures may form, depending on the cooling rate, including pearlite, bainite, or martensite [7]. Lastly, in the sub-critical heat-affected zone (SCHAZ), the temperature never exceeds the Ac1, so no austenite is formed. In this region, the base metal is tempered [17]. With multi-pass welds, subsequent passes also produce a HAZ, and each HAZ overlaps the HAZ of the preceding weld run and reheats it [5]. HAZ regions from each pass may interact and produce different microstructures. The inter-critically reheated coarse-grain HAZ (ICCGHAZ), labelled “C” in Figure 2.4b, is a major concern because when steel is reheated by a subsequent weld pass into the inter-critical temperature range where both austenite and ferrite exist, hardenability can increase due to carbon segregation in austenite, and then during cooling, the austenite may transform into martensite and M/A constituents, which may cause embrittlement and reduction of toughness [57]. 17 Figure 2.4: Schematic diagram of the HAZ with a) a single-pass weld and b) a multi-pass weld (Reprinted from [58] with permission from Springer Nature) 2.4.2 Measuring temperature profiles in the HAZ One method that has been used for temperature measurements during thermal weld cycles is embedded thermocouples. Gaudet [51] used this method to measure temperature profiles during GMAW in both single and dual-torch configurations for the heat-affected zone of an X80 line pipe steel. The single-torch configuration had the shortest t8-5 time with an average of 3 18 seconds, meaning the average cooling rate was 100℃/s. With the dual-torch configuration, the average t8-5 for the lead torch was 5.6 seconds, meaning the average cooling rate was 54℃/s. The average t8-5 for the trailing torch was 17 seconds, which gives an average cooling rate of 18℃/s. Kulakov [59] conducted experiments with submerged arc welding (SAW), similar to Gaudet’s experiments with GMAW, in order to compare welding scenarios and their influence on microstructure. With SAW, the average cooling rate was around 5°C/s in the temperature range of 800°C to 500°C. The t8-5 is important when comparing welding scenarios. An increase in the t8-5 means a decrease in cooling rate, and this leads to an increase in transformation start temperatures [60]. SAW has a rather high heat input. It has a longer t8-5, which means it has a slower cooling rate, and higher transformation temperature products are favored. GMAW has a relatively low heat input. It has a short t8-5, which means it has a relatively fast cooling rate, and lower transformation temperature products are favored. Shifting the austenite decomposition to lower temperatures results in higher strength as ferrite grains are refined and/or non-equilibrium transformation products such as bainite and martensite are formed [10]. In general, martensite formation is a concern in the HAZ as it may increase the risk of hydrogen cracking and lower the weld toughness [7, 46, 61]. 2.5 Continuous cooling and resulting transformation products in the CGHAZ 2.5.1 Introduction The transformation products that form in the HAZ of low carbon microalloyed line pipe steels depend on factors such as prior austenite grain size and steel chemistry, but it is the austenite decomposition during cooling that determines the final microstructure and properties of the steels. Changing the cooling conditions can refine the microstructure that results from the phase transformation, and it can also lead to different transformation products. Under continuous cooling conditions, fully austenitized steel, such as that in the CGHAZ, can transform into various products, such as ferrite, pearlite, bainite and martensite, depending on the cooling rate and transformation temperature [62]. For the CGHAZ of X80 line pipe steels, the microstructure is generally composed of non-equiaxed ferrite with the M/A constituent and bainite [17]. This 19 section describes the transformation products that may form in the CGHAZ of line pipe steels under continuous cooling conditions. 2.5.2 Transformation products of the CGHAZ 2.5.2.1 Polygonal ferrite and pearlite At sufficiently slow cooling below the Ae3 (the upper equilibrium temperature between ferrite and austenite), polygonal ferrite forms. Polygonal ferrite has nearly equiaxed grains with smooth boundaries, mainly containing a low dislocation density and no substructure [63]. This microstructure is nucleated as grain-boundary allotriomorphs. Growth is controlled by fast substitutional atom transfer and the diffusion of carbon atoms. These carbon atoms are rejected from the growing ferrite [64]. The carbon concentration in austenite increases with the rejection of carbon from ferrite, and when the eutectoid composition is reached, pearlite formation can take place. Pearlite exists as grains often referred to as colonies, and it contains alternating layers of ferrite and cementite. Its growth is controlled by carbon diffusion [29]. 2.5.2.2 Non-equiaxed ferrite With faster cooling rates, the transformation temperature is lowered, and non-equiaxed ferrite forms. The types of non-equiaxed ferritic microstructures that form in low carbon steel weld metals and heat-affected zones have been introduced by the International Institute of Welding (IIW) [65]. Cizek et al. [63] point out that while non-equiaxed ferritic microstructures form at similar temperatures to what bainite forms at in medium carbon steels, they do not contain cementite, and they have unique morphological features. These non-equiaxed ferritic morphologies improve strength through small effective grain sizes and increased dislocation density, and they provide a good level of toughness. Roy [17] describes the microstructure in the CGHAZ of X70 and X80 line pipe steels as consisting predominantly of bainite and what is termed “irregular ferrite.” This “irregular ferrite” is described as having higher dislocation density compared to polygonal ferrite and intergranular substructure. The higher dislocation density leads to increased hardness. Factors such as the partitioning of solute atoms at the 20 interfaces, the anisotropy of interface energy, and the anisotropy of elastic energy result in the irregular appearance of the ferrite. The presence of M/A constituents is also noted in this ferrite. 2.5.2.3 Bainite In low carbon steels, at higher cooling rates and lower transformation temperatures than those for ferrite, bainite forms. In the CGHAZ of X80 line pipe steels, bainite is commonly found. Bainite is a non-lamellar aggregate of carbides and ferrite [66]. Bainite morphology is complicated and influenced by factors such as the chemical composition of the steel, prior austenite grain size, processing time and temperature, cooling rate, etc. The formation mechanism of bainite has been debated for many years. The two main theories that have emerged to explain the mechanism of bainite transformation are the diffusive (reconstructive) theory and the displacive theory [67]. Proponents of the two theories have debated a myriad of issues about bainite transformation, such as the incomplete reaction phenomenon, the surface relief effect, the role of carbon diffusion, the method of nucleation, growth rate, etc. The diffusive (reconstructive) theory of the bainite transformation mechanism is based on short-range diffusion at the transformation front. There is a reconstructive transformation, and thermally activated atoms move from the parent lattice to the product lattice by random diffusional jumps after neighbour bonds are broken [68]. Growth is due to the migration of growth ledges [69]. With the displacive theory, bainite formation is thought to occur by a shear transformation [70]. This kind of deformation involves a disciplined motion of atoms rather than the random transfer that is associated with diffusion. Bainitic ferrite sheaves grow by successive nucleation of the subunits either on the parent austenite grain boundary or on the tips of the initial ferrite plate. This is often referred to as autocatalytic growth [71]. The growth of bainite is accompanied by an invariant-plane strain shape deformation [72]. The strain energy of the shape deformation is about 400Jmol-1 [66, 73]. The product phase takes the shape of plates to minimize the strain energy of shape deformation [72]. 21 The morphologies of bainite have also been classified in several ways. Classification systems include those introduced by Mehl [74], Ohmori et al. [75], and Bramfitt and Speer [76]. One of the newest and most advanced classification systems is by Zajac et al. [77, 78]. Disagreement about the transformation mechanism has made it difficult to classify and agree upon the various bainite morphologies, but, in general, researchers do concur in the classification of bainite into upper and lower bainite. Mehl [74] originally classified bainite into upper and lower bainite. The difference between the two can be explained by the competition between the rate of carbon rejection into austenite and precipitation [79]. Upper bainite forms at a higher temperature at which carbon diffuses more rapidly. The carbon is rejected into austenite before carbide precipitation can take place in the ferrite. In time, cementite may precipitate out of the austenite. Conversely, lower bainite forms at a lower temperature, so carbon diffusion is slower. Some of the carbon precipitates inside the ferrite plates. The remaining carbon escapes and may precipitate as carbides between the plates [80]. Figure 2.5 shows the difference between upper and lower bainite formation. In terms of properties, lower bainite has been shown to have higher strength and fracture toughness. Lower bainite contains more high-angle grain boundaries, which are important for crack deflection [16, 17]. It is difficult to see the difference between the two microstructures with optical microscopy, but EBSD and Bain group analysis have been used to discriminate between upper and lower bainite. This is discussed in Section 2.5.3. 22 Figure 2.5: Upper and lower bainite formation (Reprinted from [81] with permission from Elsevier) 2.5.2.4 Martensite and the martensite/austenite (M/A) constituent Martensite is basically a supersaturated solid solution of carbon in iron. This supersaturation is generally produced by rapid cooling, or quenching, from the austenite phase region to a relatively low temperature. There is a very high amount of carbon in martensite compared to that found in solid solution in ferrite. The normal body-centered cubic (BCC) lattice is distorted to accommodate the carbon atoms, and it becomes body-centered tetragonal (BCT) [82]. Martensite forms by a displacive mechanism. When transformations such as the bainite transformation happen at higher temperatures than the martensite transformation temperature, residual austenite can be enriched in carbon and the martensite start temperature reduced. Some of this residual austenite may transform into martensite if the reduced martensite transformation temperature is above ambient temperature. 23 This mixture of martensite and carbon-enriched austenite is referred to as the M/A constituent [83]. Regarding the effects of M/A constituents on the HAZ, there has been some debate in the literature. Li and Baker [84] state that M/A plays a significant role in governing the fracture toughness of the HAZ. They point out that several investigations by other researchers [58, 85-87] have suggested that M/A particles, due to their high hardness and crack susceptibility, are the main cause of a deterioration in the HAZ toughness of welded microalloyed steels. Li and Baker, however, clarify that toughness is in detail related to the morphology and distribution of the M/A constituents. For example, a small amount of finely dispersed M/A constituents can impede secondary cracks and, thus, increase rather than decrease toughness. While several researchers propose that cleavage fracture may be initiated by the M/A constituents in the HAZ, and, therefore, cause a deterioration in HAZ toughness, others such as Ohya et al. [88] suggest that fracture sites are mostly associated with bainitic ferrite plates possessing different crystallographic orientations and that M/A constituents are not likely to embrittle HAZ microstructures. 2.5.3 Orientation relationships and variant selection An orientation relationship (OR) is a relationship between specific planes and directions of two crystal lattices. With the bainite transformation, the transformation products have been found to have specific orientation relationships with the parent austenite [89, 90]. Similar parent/product orientation relationships have also been found with martensite and Widmanstätten ferrite [91]. Several crystallographic relationships have been observed for the transformations in steels, including the Bain, Pitsch, Nishiyama-Wasserman, Kurdjumov-Sachs, and Greninger-Troiano orientations [92-94]. The Kurdjumov-Sachs (KS) relationship is a commonly observed relationship [92, 93]. With this relationship, there are four different {111} planes (austenite planes) that are parallel to a {110}α plane (ferrite plane). Each {111} plane also has three different <110> directions. Each direction can be parallel to two different <111> α directions. This means the KS relationship has 24 variants [94]. Variants of a given OR are specific alignments of planes and directions. Table 2.2 shows the 24 variants of the KS orientation with 24 the corresponding close-packed plane (CP) groups, the Bain groups, and the misorientations (from Variant 1). There are four CP groups, and each CP group has six variants, which share the same parallel relationship of close-packed planes with austenite. The 24 variants can also be divided into three Bain groups. Low misorientation angles separate variants in the same Bain group, while high misorientation angles separate regions belonging to different Bain groups [17]. Different selections of the 24 KS variants may occur during austenite decomposition. This variant selection can be used to discriminate different transformation products [16]. Table 2.2: The 24 variants of the KS orientation (Reprinted from [89] with permission from Elsevier) In a recent study, Takayama et al. [89] looked at the effects of transformation temperature on the OR between bainitic ferrite (BF) and austenite and on the variant pairing of bainitic ferrite in low carbon steels. They noted that BF holds a near KS OR with respect to the austenite matrix. Regarding the effect of transformation temperature on variant pairing, Takayama et al. found three types of microstructures formed in the temperature range between 580 and 450°C and called them Type I, II and III. Type I is bainite formed at high temperature. Type II is bainite 25 formed at intermediate temperature, and Type III is lath martensite formed at low temperature. The schematic in Figure 2.6 shows the variant pairing within a prior austenite grain of each type. Frequently occurring variant pairs are indicated. The three different Bain groups with their variants are represented by different colors - red, yellow, and blue. Low-angle grain boundaries (LAGBs) are shown by white lines, and high-angle grain boundaries (HAGBs) are shown by black lines. Figure 2.6: Variant pairing within a prior austenite grain for the three different transformation products as classified by Takayama et al. (Reprinted from [89] with permission from Elsevier) . Type 1 is bainite formed at higher temperatures (580°C in the study) and consists of regions or packets belonging to the same Bain group. In the red Bain group, low misorientation variants such as V1/V8 or V4 are favored within that Bain group, and they form adjacently. Only low-angle boundaries are formed in each group. However, high-angle boundaries exist between Bain groups. As the temperature lowers (450°C in the study) and the driving force for austenite decomposition increases, the microstructure changes from Type I to Type II. In the bainite structure shown in Type 2, variant packets sharing the same parallel relation for close-packed planes are formed. In particular, the V1/V2 pair is dominant. However, they belong to different Bain groups. To summarize, at higher transformation temperatures, BF variants with small misorientations are formed side by side by sharing the same Bain correspondence, but at lower transformation 26 temperatures, BF variants are formed adjacently by sharing the same parallel relations for close-packed planes [89]. The reasons considered for the change in the variant selection are related to the driving force for the transformation and the transformation temperature. One explanation given for the change in the variant pairing with the change in transformation temperature is that the austenite matrix strengthens at lower temperatures, so there is a need for the pairing of specific variants for self-accommodation of the transformation strain. To clarify, compared to Type I bainite, Type II bainite tends to be formed at lower transformation temperatures. At these lower transformation temperatures, accommodation of the transformation strain by plastic deformation in austenite is more difficult. Therefore, variant pairs that favor self-accommodation are mostly formed [89, 95]. Variant selection takes place so that the high misorientation between the variants accommodates the strain. With this variant selection, there is an increase in high-angle grain boundary density at the lower transformation temperature. For Type I bainite, which forms at higher transformation temperatures, plastic deformation in austenite due to the formation of BF becomes easier; therefore, there is less of a need for the pairing of specific variants for self-accommodation [89]. Lastly, on lowering the transformation temperature below the martensite start temperature, Type III martensitic microstructure is obtained. In the martensite shown in Type III, variants in the same CP group are formed side by side, but the V1/V4 pairing with a low misorientation angle is preferred, resulting in the development of sub-blocks. Sub-blocks of different variants belonging to the same Bain group form in a single CP group. In studies of line pipe steels, the relationship between transformation temperature and variant selection has also been observed. Reichert [16] used EBSD and Bain group analysis to discriminate between upper and lower bainite in a low carbon low alloy X80 line pipe steel. A KS orientation was found between austenite and upper and lower bainite. There was a clear difference in variant selection for upper and lower bainite. The variant selection is related to the driving force for the bainite reaction, and, therefore, it depends on the transformation temperature [96]. Lower bainite forms at a lower temperature than upper bainite. Within a prior austenite grain, upper bainite showed a dominance of one of the three Bain groups. However, a 27 higher density of high-angle grain boundaries existed in lower bainite due to the arrangement of grain packets of variants belonging to the three different Bain groups. . In another study, Wang et al. [97] investigated the effect of the carbon content of the base material on the variant selection in the CGHAZ of an X80 line pipe steel. It was observed that an increase in carbon content from 0.03wt% to 0.06wt% influenced the variant selection. At the lower carbon content of 0.03wt%, the V1/V4 variant pair was dominant. These variants belong to the same Bain group. With the 0.06wt% carbon content, the variant pair V1/V2 was dominant. The V1/V2 pair belong to different Bain groups neighbouring in the CGHAZ, increasing the density of high-angle grain boundaries. The increase in carbon content lowered the transformation temperature and altered the crystallographic arrangement of bainite formed in a prior austenite grain. 2.6 Further study of the effects of cooling rate and chromium and molybdenum additions on the CGHAZ Further research on the effects of cooling rate and chromium and molybdenum additions on the CGHAZ is necessary to gain insights into the factors that affect the microstructures and properties of this region. Some studies have shown the effect of cooling rate specifically on the CGHAZ. Huda et al. [98] investigated the continuous cooling transformation behaviour and toughness of the heat-affected zone in an X80 line pipe steel. They determined the role of cooling rate during a single heating thermal cycle on the CGHAZ. Samples were heated to 1350ºC and had a hold time of one second. Cooling rates from 7.6 to 356°C/s were used. The CGHAZ microstructure changed from martensite to granular bainite with decreasing cooling rate. Granular bainite is a term used to describe irregular ferrite with M/A islands. In another study, Naik et al. [99] investigated the effect of cooling rate on the weld coarse-grain heat-affected zone of an API X70 steel. Twelve different cooling rates between 1.25 and 62.5°C/s were chosen. They observed that phase transformation temperatures (Ar3 and Ar1) and impact toughness decreased while hardness and the amount of bainite increased with increased cooling rate. During cooling, Ar3 is the temperature at which austenite begins to transform to ferrite, and Ar1 is the temperature at which 28 the transformation is complete. Singh et al. [100] studied the effects of continuous cooling on the CGHAZ of X80 grade steel. Cooling rates ranged from 3 to 100℃/s. The dominant microstructure for all cooling rates was bainite with the M/A constituent. At low cooling rates (below 5℃/s), some ferrite and pearlite were observed in addition to the bainite and M/A constituent. The transformation start temperature was lowered from 660 to 545℃ as the cooling rate increased from 3 to 100℃/s. There is little in the literature regarding the effects of chromium specifically on the CGHAZ. Roy [17] investigated the effect of chromium content, carbon content, and cooling rate on austenite decomposition kinetics for an austenite grain size representative of the CGHAZ in three different line pipe steels. Results showed that an increase in chromium content from 0.023wt% to 0.24wt% shifted transformation curves to a lower temperature. The transformation start temperature decreased by approximately 10°C irrespective of the cooling rate. One reason suggested for the lowering of transformation temperature with an increase of chromium content is the solute drag effect. Chromium was also shown to have little to no effect on the microstructure and a marginal increase of 5 HV on the hardness. In another study, Huang et al. [101] investigated the effect of different chromium contents (0.33, 0.65 and 1.02wt%) and heat input (20, 100, and 200kJ/cm) on the microstructure and impact toughness in the simulated CGHAZ of high-strength low-alloy steels. For microstructure, both increased heat input and increased chromium content decreased the fraction of acicular ferrite, which is described as a fine-grained ferrite that nucleates intragranularly on inclusions and has high-angle grain boundaries and an interlocked microstructure. Huang et al. also point out that the density and area fraction of M/A constituents increased with both heat input and chromium content. For toughness, higher heat input and chromium content led to lower impact toughness. Specifically, chromium content had a significant effect on decreasing the impact toughness at lower heat inputs, but it had little to no effect at high heat inputs, indicating regions of heat input with higher sensitivity to the chromium content. The effects of molybdenum with regard to the CGHAZ have also been shown in some studies. Chen et al. [45] looked at the continuous cooling transformation (CCT) diagrams of the CGHAZ for an Mn-Cr-Nb X80 line pipe steel and the effect of replacing chromium with molybdenum. 29 When molybdenum replaced chromium in the Mn-Cr-Nb steel, the temperature of the undercooled austenite deformation decreased by about 20⁰C, indicating molybdenum is much more effective at lowering the transformation temperature than chromium. When both chromium and molybdenum were used in a third steel, this further increased the effectiveness of decreasing the austenite transformation temperature. In addition, Chen et al. found that the addition of molybdenum in the X80 grade line pipe steels was more effective at improving the toughness and strength of the HAZ than chromium. The combined addition of chromium and molybdenum was strongly effective in increasing the toughness and strength of the HAZ. In another study, Wu et al. [102] investigated the effect of molybdenum on the impact toughness of the HAZ in high-strength low-alloy steels, and they found that the microstructure of the CGHAZ was refined, and the toughness enhanced with the addition of low levels of molybdenum such as 0.07%. As the CGHAZ is an area prone to failure, further investigation into the factors that may help improve the microstructure and properties of this area, such as cooling rate and steel chemistry, is necessary. This investigation seeks to further elucidate the effects of chromium and molybdenum additions over a range of cooling rates on the austenite decomposition kinetics of the CGHAZ and, thus, on the microstructure and properties of this area. 2.7 Modelling Several types of models have been developed for austenite decomposition in steels. Particularly relevant to this study are models for austenite decomposition under continuous cooling conditions, especially those related to the HAZ of line pipe steels. The JMAK model is a traditional model that was developed independently by Johnson and Mehl [103], Avrami [104], and Kolmogorov [105]. The JMAK model has been used to describe the kinetics of isothermal phase transformations. The model can be best described using 𝑋(𝑡) = 1 − 𝑒ି(௕௧)೙ , (2.2) where X(t) is the fraction of the phase transformed during time t, b is a temperature-dependent rate parameter, and n is the Avrami exponent [106]. The values n and b are empirically found. If 30 n stays constant (i.e., isokinetic), non-isothermal decomposition kinetics can be described using the JMAK model with the additivity principle [103], as shown in ௗ௑ௗ௧= 𝑛(𝑏)భ೙(1 − 𝑋)( ଵ୪୬(ଵି௑))೙షభ೙ . (2.3) Austenite decomposition is complex, and several different transformation products may form. Models have been used to describe the austenite decomposition products as forming either simultaneously or sequentially. The JMAK analysis has been used to describe both. Jones and Bhadeshia [107] used an extended JMAK analysis to describe the simultaneous decomposition of austenite into several transformation products under isothermal and continuous cooling conditions. These products include pearlite, Widmanstätten ferrite, and allotriomorphic ferrite. In a model developed by Azghandi et al. [108] for the continuous cooling decomposition of a vanadium microalloyed steel, JMAK is used to describe the sequential transformation of the decomposition products. This model consists of several sub-models. The fraction transformed of ferrite, pearlite and bainite is described using the JMAK analysis with the additivity principle. For bainite, the JMAK rate parameter is formulated using a diffusion-controlled model. Transformation products are also assumed to form sequentially in an integrated model proposed by Garcin et al. [60] for the HAZ of girth welds of an X80 line pipe steel. Two separate models are used to predict transformation start temperature as, depending on the cooling conditions in the HAZ, austenite decomposition may start from ferrite or bainite. The model used to predict the onset of ferrite formation was originally developed for plain carbon steels by Militzer et al. [109]. The model proposed by Militzer et al. to describe the transformation start is based on carbon diffusion-controlled early ferrite growth with nucleation at austenite grain corners. Ferrite nucleation was assumed to cease upon reaching a critical carbon concentration in the grain boundary area. The point at which this critical carbon concentration is reached represents the transformation start temperature and is concurrent with reaching a measurable fraction of ferrite (i.e., 5% transformed). Ferrite growth was modelled using the JMAK model with additivity. The transformation start model was later extended to include the solute drag effect of niobium [110] and later again extended to include austenite decomposition into bainite and M/A constituents 31 [111]. In the approach by Garcin et al., austenite grain growth, the solute-drag effect of niobium, austenite decomposition into ferrite and bainite, and M/A fraction are considered so that microstructure evolution in the weld HAZ can be predicted. A temperature model is also introduced with the microstructure evolution model so that maps of microstructures in the HAZ for different welding scenarios could be made. In a later study, Roy [17] developed a model partly based on the model by Garcin et al. [60] to describe the effects of chromium and carbon content on the bainite start temperature and growth kinetics at different cooling rates for the HAZ of X80 line pipe steels. A Hall-Petch type relation is proposed by Roy to describe hardness as a function of the microstructure (HAGB density). The JMAK model has been extensively used for describing austenite decomposition kinetics. However, this model has its drawbacks. For example, while the JMAK model can be used to describe bainite formation, with the additivity rule there is a general requirement of constant n (the Avrami exponent), and for bainite the values of n tend to vary quite widely, meaning the additivity principle is of less use for the bainite reaction [112]. Another drawback of the JMAK analysis is that in the JMAK-based growth models, the rate parameter and the JMAK exponent are fit parameters that lack physical meaning [17]. Advances in computer technology have now made it feasible to model microstructure on the meso scale, i.e., on the length scale of the microstructure features, thereby predicting actual microstructures. Examples of meso-scale models include cellular automata (CA) models, Monte Carlo (MC) models, and phase field models. CA and MC models have been useful in simulating grain growth and recrystallization, and some have been used to model the microstructure evolution that takes place during austenite decomposition. Monshat and Serajdzadeh [113] simulated the transformation of austenite to ferrite under continuous cooling conditions in low carbon steels using cellular automata-finite element modelling. The finite element method was used for the heat conduction equations, and 2D CA modelling was used to predict the progress of the austenite decomposition. Continuous cooling experiments on low carbon steels were made, and the ferrite microstructure was determined and compared with the simulation data. A good agreement was found between the experimental results and the simulation. In another study, 32 Tong et al. [114] used an MC model to simulate the austenite to ferrite diffusive transformation during continuous cooling. The simulation results agree well with the experimental results. While CA and MC models can be used to simulate austenite decomposition under continuous cooling conditions, it is phase field modelling (PFM) that is the most useful for modelling the complex morphologies that form during austenite decomposition in the HAZ. PFM shows promise for the modelling of bainite formation in the HAZ of welds [115]. PFM, indeed, has several advantages. One of the problems with other meso-scale models, such as MC and CA, is the difficulty of converting the numerical time step to the physical time step. There is no need to do this with phase field models as PFM is based on diffusional time steps [116]. Another advantage of PFM is that it does not require tracking of interfaces as other models do, and this makes it a good choice for the simulation of complex microstructures [16, 116]. With PFM, field variables are used to describe the microstructure, and the evolution of these variables represents microstructure evolution. These field variables are continuous across the interfacial regions and, hence, the interfaces are diffuse [117]. While PFM has many advantages, one of the main disadvantages is that material-specific properties must be introduced into the model through parameters that are determined based on experimental and theoretical information. These parameters are related to the thermodynamic properties and elastic properties of co-existing phases, interfacial energy, diffusion properties of solute elements, etc. Due to the large number of parameters and because some of them are related to properties that are difficult to measure, it is complicated to determine all the parameters in a phase field model [118]. PFM is extremely complex, but there are different approaches used for simulations. For example, much of the simulation work in steels has been done with a multi-phase field approach using MICRESS (Microstructure Evolution Simulation Software). In this approach, each grain and/or microstructure constituent has its own phase field parameter and can be tracked during the simulation to predict the evolution of grains and phases [115]. Phase field models have been developed to simulate the microstructure evolution of the HAZ. 33 For example, Thiessen et al. [119] used PFM to simulate the microstructure evolution in the HAZ of a low-carbon (AISI1005) steel. They looked at phase transformation kinetics and the microstructures that resulted at various positions in the HAZ. In this model, both the nucleation and growth of austenite during heating and ferrite formation upon cooling are included. The phase transformation simulations of ferrite to austenite upon heating and the reversion to ferrite upon cooling show good agreement with real-time in-situ synchrotron measurements in the literature. Toloui and Militzer [120] conducted phase field simulations of austenite grain growth in the HAZ of an Nb-Ti microalloyed X80 line pipe steel. The model implicitly accounts for the dissolution effects of NbC by introducing an effective grain boundary mobility. The effective mobility is a function of temperature because the pinning pressure decreases as temperature increases due to the dissolution of NbC. Therefore, two Arrhenius relationships are proposed for the mobility - one for the strong pinning at lower temperatures and one for the weak pinning at higher temperatures. At intermediate temperatures, there is a gradual transition where the NbC is dissolving. A phase field model for austenite decomposition was later developed and applied to the HAZ of the X80 line pipe steel [121]. Austenite decomposition into polygonal ferrite and bainite is considered in the model, and the phase field model is coupled with a diffusion- controlled model. In this model, bainite is considered thermodynamically as ferrite but with different nucleation and growth scenarios. At sufficiently high undercooling, bainite nucleation takes place at available interface sites. For austenite-bainite interface mobility, a suitable anisotropy approach is proposed. A faceted growth model is used for interface anisotropy. Anisotropy parameters were benchmarked for a TRIP steel to obtain a reasonable bainite sheaf morphology. Elastic anisotropy is not accounted for and there are no explicit considerations of crystallographic aspects. Phase field simulations have been developed for austenite decomposition into various products, including polygonal ferrite, pearlite, and Widmanstätten ferrite. Phase field models have also been developed for the displacive martensitic transformation. Artemev et al. [122] developed a phase field simulation for the displacive martensitic transformation, and an Fe-Ni alloy was considered in 3D simulations of the martensitic formation. However, models for bainite are 34 perhaps the most important for advanced line pipe steels. Bainite is extremely challenging to model, especially because its underlying mechanism is still being debated. To determine weld integrity in advanced line pipe steels, appropriate models for bainite microstructure evolution in the HAZ, which show the relationship between this evolution and resulting mechanical properties, are essential. 35 Chapter 3: Scope and Objectives When welding pipe segments during pipeline construction, a weld heat-affected zone (HAZ) is created. The mechanical properties of the HAZ may differ from those of the as-supplied steel and could affect pipeline integrity. The CGHAZ is particularly prone to failure, and it is necessary to decrease the negative effects of this area by improving its mechanical properties. Steel chemistry and welding parameters can be optimized to produce microstructures with improved properties. In this research, three X80 line pipe laboratory steels were investigated to determine the effects of chromium and molybdenum additions on the austenite decomposition kinetics of the CGHAZ under continuous cooling conditions. Austenite decomposition results were analyzed to develop a bainite transformation model for these steels. The objectives of this study were as follows: 1. To quantify the effects of two levels of chromium (i.e., 0.023 and 0.230wt%) and molybdenum (i.e., 0.11 and 0.26wt%) on austenite decomposition kinetics for CGHAZ conditions through continuous cooling transformation (CCT) tests conducted in the range of 3 to 50⁰C/s 2. To quantify the transformation products and HAGB densities observed in the microstructure following austenite decomposition using optical microscopy and EBSD 3. To measure the hardness of the as-transformed microstructures to establish a structure-property relationship 4. To expand on a pre-existing phenomenological model to describe bainite start and transformation kinetics for the investigated steels 36 Chapter 4: Materials and Methodology 4.1 Materials Three steels were investigated in this study. These steels were laboratory cast and hot rolled by CanmetMATERIALS in Hamilton, Ontario. The initial materials received from CanmetMATERIALS were in the form of steel plates with a thickness of 12.5mm. The chemistries of the steels are shown in Table 4.1. In the specimen names, the “L” indicates laboratory-cast steel, and each set of numbers represents the weight percentage (wt%) of the key alloying elements. For example, the L-06C03Nb steel is a laboratory-cast steel with approximately 0.06wt% carbon and 0.03wt% niobium. For the second steel, the Cr indicates the presence of chromium, and for the third steel, the CrMo indicates the presence of chromium and molybdenum. Table 4.1: Steel chemistries with the amount of each element given in wt% and the Ti/N ratio Steel Name C Cr Nb Mo Ti N Mn Si Al Ti/N L-06C03Nb 0.059 0 0.037 0.10 0.016 0.0061 1.59 0.27 0.031 2.62 L-06C06NbCr 0.057 0.230 0.057 0.11 0.017 0.0066 1.65 0.27 0.057 2.58 L-06C06NbCrMo 0.058 0.230 0.057 0.26 0.017 0.0064 1.66 0.27 0.061 2.66 The aim of studying these three steels was to observe the effects of chromium and molybdenum on austenite decomposition kinetics in the CGHAZ during continuous cooling. The key difference between the first two steels is the presence of chromium, and the key difference between the second and third steels is the level of molybdenum, 0.11wt% and 0.26wt%, respectively. Niobium levels vary between 0.03 and 0.06wt% for the first steel and the other two steels. In a study by Isasti et al. [123] on phase transformations of Nb and Nb-Mo microalloyed steels, an increase in Nb from 0.03 to 0.06wt% had little effect on austenite decomposition kinetics for undeformed austenite, but it has to be appreciated that the role of these different Nb levels may not be completely negligible. Manganese and silicon are targeted to be at 1.65wt% and 0.25wt%, respectively. The titanium to nitrogen ratio is below 3.42 to ensure the titanium nitrides are understabilized to limit the precipitate size. 37 Tubular steel samples were prepared for the CCT tests. The dimensions of the samples are 8mm for the outer diameter, 6mm for the inner diameter, and 20mm for the sample length, as shown in Figure 4.1. The sample length is parallel to the rolling direction. Figure 4.1: Tubular sample diagram 4.2 Methodology 4.2.1. Continuous cooling transformation (CCT) tests 4.2.1.1. Gleeble simulations CCT tests were conducted on samples of the three steels to investigate the effect of cooling rate and the effects of chromium and molybdenum content on the austenite decomposition kinetics of the CGHAZ. The Gleeble 3500 thermomechanical simulator was used for the CCT tests to simulate CGHAZ microstructures. As minimal loads were required to hold and stabilize the sample, low-force jaws were used for the heat treatments. The sample holders are made from copper. This is important, especially for samples cooled at ambient temperature, as the copper facilitates the removal of heat from the sample through conduction. Two K-type thermocouples were welded at the center of the tubular samples on the same plane, perpendicular to the tube’s length, to monitor and control the temperature. These were connected to the TC1 sensors, which provide accurate feedback control 38 of the sample’s temperature. On the same plane as the thermocouples, a contact mechanical dilatometer was placed to grasp the sample securely so that the dilatometer would neither indent nor slip off the sample during cooling. The set-up is shown in Figure 4.2. Figure 4.2: Gleeble 3500 thermomechanical simulator set-up The vacuum level and temperature of the sample had to be controlled carefully during the heat treatments. All tests were conducted under high vacuum (~1.2 x 10-5 Torr, or 1.59 x 10-3Pa) up to the point of helium quenching. For temperature control, resistive heating was used to increase the temperature by adjusting current levels, and ambient cooling (for the cooling rate of 3°C/s) or helium quenching (for all other cooling rates) was used to achieve the desired cooling rate for each test. The helium quenching was applied by the nozzle shown in Figure 4.2. The nozzle is connected to the left holder, and the helium flows through the interior of the tubular sample. The tubular geometry with a 1mm wall thickness was designed to reduce temperature differentials that were found in the through thickness of sheet samples. To further minimize the temperature gradient within the sample, the Heat Power, or Power Angle, measured by the Gleeble simulator, was used to run the thermal treatments with the least amount of gas possible. As Heat Power had Movable jaw Copper sample holder Helium supply tube Sample with thermocouples attached Dilatometer 39 a strong correlation with the amount of gas used during the test, this was an effective method to monitor and minimize the gas usage in the tests. The original method for austenite decomposition tests co-developed by Romualdi [124], Roy [17], and the author minimized the gas flow while strictly maintaining the cooling rate within ±0.5˚C of the designed thermal path. For the lower cooling rates of 3 and 5˚C/s, the temperature gradient in the through thickness was minimal. However, for the higher cooling rates between 10 and 50˚C/s, there was a significant temperature gradient in the through thickness of the sample. This caused the sample at each point in the through thickness to experience the same heat treatment, but at different points in time. Thus, the microstructure was homogenous and representative of the intended thermal path. However, the nonconcurrent nature of the through thickness thermal path resulted in a significant error for the dilation data in terms of transformation temperatures. Thus, a method was designed to improve the accuracy of the dilation transformation temperature measurements as explained in 4.2.1.2. This minimized the temperature gradient, but it did not maintain a constant cooling rate throughout the test. 4.2.1.2 Design of thermal cycles The thermal cycles for each steel were designed to study the effect of chromium and molybdenum levels with different cooling rates on the austenite decomposition observed in the CGHAZ. The cycles were designed to produce microstructures representative of the CGHAZ in gas metal arc welding (GMAW) scenarios and submerged arc welding (SAW) scenarios. Previous studies by Gaudet [51] and Kulakov [59] show that the cooling rate can vary widely depending on the welding procedure, and it is necessary to include a range of cooling rates so various welding scenarios are represented. Relevant cooling rates for GMAW and SAW procedures were between 5 and 100˚C/s. As it was not feasible to achieve an average cooling rate of 100˚C/s, cooling rates of 3, 5, 10, 30, and 50˚C/s were used. The CGHAZ experiences very high temperatures, which result in the dissolution of most precipitates, including Nb-rich precipitates, leading to substantial grain growth. This condition was simulated. A thermal path consisting of a constant heating rate of 50⁰C/s up to a peak 40 temperature of 1300˚C, followed by isothermal holding, was used to achieve full austenitization, dissolution of niobium, chromium, and molybdenum-rich precipitates, and a target grain size. LUMet (Laser ultrasonics for metallurgy) tests by Romualdi [124] involving heating sheet samples at 50˚C/s to 1300 ˚C for 90 seconds and measuring grain growth were used to determine the target grain size and associated holding time for each steel. For the hold time, a minimum of 10 seconds was needed to ensure that all Nb-rich precipitates were brought into solution. LUMet results showed an initial rapid growth with decreasing rates as the austenite grain size approached its limiting value. The measured grain sizes and associated hold times to achieve these grain sizes for each steel are shown in Table 4.2. Table 4.2: LUMet results for prior austenite grain size (PAGS) and required hold times [124] As shown in Figure 4.3, the thermal cycles were all a single-pass cycle with a heating rate of 50˚C/s, a hold temperature of 1300˚C, followed by an initial cooling rate of 20˚C/s to 900˚C, and finally, a range of cooling rates (3, 5, 10, 30, 50˚C/s) to 200˚C. To avoid decarburization, high vacuum was held during cooling at a rate of 20˚C/s until 900˚C. Following this, for the 3˚C/s cooling rate, the vacuum was maintained as helium gas quenching was not needed. For all other cooling rates, the vacuum was interrupted, and helium gas was used to quench the sample at the desired cooling rate. Steel Name LUMet (µm) Hold Times (s) L06C03Nb 78±15 10 L06C06NbCr 59±12 12 L06C06NbCrMo 55±11 12 41 Figure 4.3: Single-cycle heat treatment schematic for CCT tests Two separate methods had to be utilized for quenching. The first method prioritized maintaining the cooling rate by using higher outputs of helium gas. This method kept the cooling rate within ±0.5˚C of the programmed thermal path, producing relevant microstructure corresponding to the heat treatment. Thus, microstructure analysis and hardness testing were conducted on the samples (3-50˚C/s) from this method. One drawback of this method, however, was the temperature gradient across the through thickness of the sample. A second method which minimized gas flow to reduce the temperature gradient and achieve more accurate dilatometric measurements was employed. This method no longer maintained the cooling rate for the entirety of the 10, 30, and 50˚C/s thermal paths. However, the transformation start temperatures up to the 30˚C/s cooling rate could be measured to an acceptable degree of accuracy with this method. Thus, for 50˚C/s, the data for microstructure analysis and hardness are included as the cooling rate could be maintained and the results were reliable, but dilation results and modelling for the decomposition at this cooling rate are excluded as they are unreliable. Temperature (℃) 42 4.2.1.3 Dilatometry Dilatometry was used to observe the phase transformation in situ. As the molar volumes of the parent phase (austenite) and decomposition products (i.e., ferrite, bainite, etc.) are different, the volume change of the sample can be used to measure austenite decomposition. The contact dilatometer was placed on the same plane as the thermocouples to closely match the desired thermal path with the corresponding volume change in the diameter. A typical dilatometric result is shown in Figure 4.4, where dilation is plotted against temperature. Figure 4.4: Dilation vs. temperature for a single-pass heat treatment In an ideal dilatometry graph, such as the one shown in Figure 4.4, the dilation curves through the experiment are stable; the heating path and cooling path for dilation in section A are overlapped, indicating identical thermal expansion and shrinkage; and the sections B and C are linear with normalized slope values that correspond to the coefficient of thermal expansion (CTE) values of austenite and ferrite, respectively. The relative diameter change is divided by the initial diameter of the sample (8mm) to normalize the dilation results. The slopes of the curves corresponding to the contraction of austenite and its products are shown in Figure 4.5. The 0204060801001201401601800 200 400 600 800 1000 1200 1400Dilation (µm)Temperature (°C)BCATemperature (℃) 43 validity of the test can be evaluated by checking if the slopes match well with the actual CTE of austenite (22.5 x 10-6˚C-1) and ferrite (14.8 x 10-6˚C-1). These CTE values given for austenite and ferrite in low carbon steels were measured by Zhao et al. [125]. For this study, the CTE values for each test were required to be within ±5% of the values given by Zhao et al. Figure 4.5: Normalized dilation vs. temperature The cooling portion of the dilatometry curve shown in Figure 4.5 can then be used to find the fraction transformed of the parent phase (austenite) to daughter products (ferrite/bainite). By applying the lever rule, as described in the American Society for Testing and Materials (ASTM) A1033 standard [126], the linear extrapolations of the austenite CTE and ferrite CTE can be used to find the fraction transformed over the complete range of temperatures during which phase transformation occurs. Fraction transformed at a given temperature can be found using Fraction Transformed = D1/D2, (4.1) 0.0010.0020.0030.0040.0050.0060.0070.0080.0090.01200 300 400 500 600 700 800 900Normalized dilation Temperature (°C)D1D2Decomposition productsCTE= 15x10-6 C-1 AusteniteCTE= 23.2x10-6 C-1 Temperature (℃) 44 where D1 and D2 are determined as shown in Figure 4.5. For the purposes of this study, transformation start temperature and end temperature are taken at 5% and 95% transformation, respectively. The fraction transformed can then be plotted against the temperature to find the transformation curves for each heat treatment. An example of the resultant transformation curve is shown in Figure 4.6. Figure 4.6: Fraction transformed vs. temperature 4.2.2 Microstructure characterization 4.2.2.1 Sample preparation Microstructure characterization was carried out on the same plane where the thermocouples and the contact dilatometer had been located. Each sample was sectioned using an abrasive cutter on the plane to which the thermocouples were attached. Standard grinding, polishing, and etching methods were used. A Buhler polishing machine was used to grind and polish the samples. Increasingly finer silicon carbide papers (320, 600, 800, 1200) were used with continuous water lubrication to grind the samples. Samples were then polished using cloths with 6µm and 1µm diamond suspension and lubricants. Between each grinding or polishing step, the samples were 00.10.20.30.40.50.60.70.80.91400 450 500 550 600 650 700 750Fraction TransformedTemperature (˚C)45 carefully washed with soapy water, denatured with ethyl alcohol, and dried using a high-pressure air nozzle. For each sample, there were two surfaces that could be inspected as the samples were sectioned in half. After both sections of the samples were polished using the 1µm polishing cloth, one section was prepared for optical microscopy, and the other section was prepared for EBSD analysis. For the preparation of the optical microscopy section, the sample was etched using 2% Nital solution. The Nital solution was prepared using 2mL of concentrated nitric solution (70% HNO3) and 98mL of ethyl alcohol. Each sample was dipped in the etching solution for an average of 10 seconds and then rinsed immediately with water, cleaned with soapy water, and dried using ethyl alcohol and a high-pressure air nozzle. Nital etching reveals the grain boundaries of ferrite, pearlite, and bainite. Optical microscopy was used following etching to make qualitative observations about the transformation products that were present. For EBSD studies, the samples were electropolished following the 1µm polishing to remove the strained layer caused by mechanical polishing. Electropolishing is important for obtaining clear diffraction patterns of the unstrained material. Electropolishing was done by dipping the polished surface in a solution with 95% acetic acid and 5% perchloric acid for 15 seconds with a 15V potential difference applied. The samples were then immediately washed with water and denatured with ethyl alcohol and dried with the high-pressure air nozzle. 4.2.2.2 Optical microscopy imaging For optical microscopy imaging, the Nikon EPIPHOT 300 series inverted optical microscope with a digital camera was used to take images at 50, 100, 200, and 500X magnification. The manual multi-layer capture feature was used to take clear, focused images. These images were analyzed for qualitative determination of the microstructure. 4.2.2.3 Electron backscatter diffraction (EBSD) imaging Quantitative microstructure determination was done through EBSD measurements on the electropolished samples. A Zeiss-Sigma field emission scanning electron microscope (SEM) was used in conjunction with a Nikon high-speed camera and EDAX (TSL) OIM 6.2 data collection 46 software to scan the surface of the sample. Standard procedures were followed using a 70˚ tilt angle, 10mm working distance, 60µm aperture size, and 20kV accelerating voltage. Diffraction patterns were captured using a binning size of 8x8 with a capture speed of around 40 frames per second. BCC (i.e., ferrite) and FCC (i.e., austenite) were selected as possible phases for automatic indexing in the OIM software. A step size of 150nm was used to obtain maps with an area of 175 x 175µm on average. EDAX (TSL) OIM 6.2 data analysis software was used for post-processing. A single-step cleaning process entailing grain dilation was used with a grain tolerance angle of 5° and a minimum grain size of two pixels for grain boundary orientation distribution. HAGB density was measured using a cleaned scan of the ferrite phase. Quantification of retained austenite (RA) was carried out prior to cleaning. As the scan was set to find BCC and FCC phases, RA could be determined by any area with a cluster of 2 pixels or more assigned the FCC phase. The total area produced the fraction of RA. 4.2.3 Mechanical characterization: Hardness testing Hardness tests were conducted for each cooling rate for each steel. The section that was used for optical imagery was reground using 1200 silicon carbide paper. The samples were then tested using a Vickers microhardness indenter. The load was set to 1kgf (kilogram-force), and the load time was 10 seconds. The diagonals of the indent made by the pyramid indenter were measured, and the hardness value was found using [127] Hardness 𝐻𝑉 = ଵ.଼ହସସ௉ௗమ , (4.2) where P is the load applied in kgf, and d is the average diagonal length in millimeters. Seven indents were made, and an average hardness value from these seven indents was reported for each sample along with the standard deviation. Each indent was placed at the center of the sample’s tubular thickness. Indents were made at least 2.5 diagonal lengths from the edges and from each other to avoid edge effects and prevent inaccuracy due to the hardness value of an indent being affected by work hardening from previous indents. 47 4.2.4 Modelling A semi-empirical model was developed for each steel individually with two sub-models: i) a bainite start model and ii) a bainite growth model. For the bainite start model, the temperature at which ferrite and austenite have the same free energy, was found using Thermo-Calc 2021a. Then, using the 400Jmol-1 value for bainite nucleation given in the literature [66, 128], the bainite nucleation temperature was calculated for each steel. This temperature was then used in the empirical model developed by Garcin et al. [60], and two fit parameters for each steel were calculated based on root-mean-square error minimization. For the bainite growth model, the JMAK with the additivity principle was used. The rate parameter was expressed as an exponential function of temperature with two fit parameters for each steel. The fit parameters for each steel were calculated based on the least root-mean-square error for 50% transformation temperature. A Hall-Petch type relation proposed by Roy [17] was used to describe the microstructure (HAGB density) and hardness of the steel. 48 Chapter 5: Experimental Results and Discussion 5.1 Quality and repeatability of the CCT tests The heat treatments introduced in the methodology were set as the programmed thermal paths for all tests. During heating and isothermal holding, the temperature was controlled within a range of ±0.5˚C with a temporary overshoot of up to 3˚C at the start of isothermal holding at 1300˚C. During cooling, the tests with cooling rates of 3 and 5˚C/s were in agreement with the programmed path within ±0.5˚C. However, for tests at 10 and 30˚C/s a greater deviation was measured as a result of the release of transformation heat, i.e., recalescence, within a relatively shorter time compared to slower cooling rates. Thus, up to 30˚C/s, the cooling rate was mostly maintained up to the transformation start temperature. For 50˚C/s the combination of a large release rate of the heat of transformation and a significant through thickness gradient did not allow for a reasonable measure of transformation temperature. It can be observed in Figure 5.1 that the 30˚C/s test and, to a certain extent, the 10˚C/s test, experience a cooling rate that is notably lower than the intended cooling rate for a portion of the transformation. This is due to a combination of the suppressed cooling rate at lower temperatures and recalescence from the transformation. Thus, the resultant microstructure and properties may reflect that of a higher t8-5 (lower cooling rate). 49 Figure 5.1: Evolution of cooling rate for different initial cooling rates (Black markers indicate the transformation start temperature for each cooling rate). For the CCT tests, four repeat tests were conducted for the L06C06NbCrMo steel at 10˚C/s. This is presented in Figure 5.2 as fraction transformed vs. temperature. The tests have good repeatability with a maximum difference of 11˚C for the transformation start temperature. Figure 5.2: Repeat tests for L06C06NbCrMo at 10˚C/s 00.10.20.30.40.50.60.70.80.91450 500 550 600 650Fraction TransformedTemperature (˚C)-40-35-30-25-20-15-10-50500 550 600 650 700 750 800Cooling Rate (˚C/s)Temperature (˚C)3°C/s5°C/s10°C/s30°C/s50 5.2 Effect of cooling rate on the austenite decomposition kinetics Cooling rates of 3, 5, 10 and 30˚C/s were used and were successfully maintained between 650 and 800˚C. Figure 5.3 shows the effect of cooling rate on the austenite decomposition kinetics of the L06C06NbCr steel. An increase in the cooling rate consistently decreased the transformation start temperature. With the current methodology of minimizing gas flow, the cooling rate was maintained for the 3 and 5˚C/s, resulting in a more accurate determination of the transformation start temperature and growth behaviour. For 10 and 30˚C/s, the cooling rate was maintained to low enough temperatures to accurately determine the transformation start temperature, but it was not maintained throughout the entire transformation temperature range. Figure 5.3: Effect of cooling rate on the austenite decomposition kinetics for L06C06NbCr Transformation curves were found for each of the steels, and the transformation start temperatures are shown in Figure 5.4. All three steels follow a similar trend for the start temperatures. The comparison between L06C06NbCr and L06C06NbCrMo shows that molybdenum depresses the transformation temperatures by approximately 15˚C. Comparing L06C03Nb to the other two steels, however, reveals an inconsistency. L06C03Nb has negligible amounts of chromium and molybdenum compared to the other two steels; however, the other two steels have higher transformation start temperatures. Previous results found in the literature show chromium and molybdenum lower transformation start temperature when added in similar amounts to the amounts in this study [17, 45]. This inconsistency and the steps taken to find the possible causes are explained in Section 5.8. 0.000.200.400.600.801.00450 500 550 600 650 700Fraction TransformedTemperature (°C)3°C/s5°C/s10°C/s30°C/s51 Figure 5.4: Effect of cooling rate on transformation start temperature for the three steels 5.3 Effect of molybdenum on the austenite decomposition kinetics The effect of molybdenum addition with the different cooling rates on the austenite decomposition kinetics was observed. By comparing L06C06NbCr and L06C06NbCrMo, the effect of molybdenum on transformation temperatures can be found for these steel chemistries when increasing the molybdenum content from 0.11wt% to 0.26wt%. As shown in Figure 5.5, this increase in molybdenum shifts the transformation curves to lower temperatures by about 15˚C consistently. 5205405605806006206406606800 5 10 15 20 25 30 35Temperature (˚C)Cooling Rate (˚C/s)L-06C03Nb (V8030) L-06C06NbCr (V9030) L-06C06NbCrMo (V9031) 52 Figure 5.5: Effect of molybdenum on austenite decomposition kinetics 5.4 Characterization of microstructure with optical microscopy Micrographs for each steel and cooling rate were taken. Figure 5.6 presents the microstructure for L06C06NbCr, showing a predominantly bainitic microstructure with progressive refinement as a result of increasing the cooling rate. For the lower cooling rate of 3°C/s, minor quantities of grain boundary ferrite nucleated in prior austenite grain boundaries are observed; however, the microstructure remains predominantly bainitic. These micrographs provide qualitative data about the microstructure. 00.10.20.30.40.50.60.70.80.91450 500 550 600 650 700Fraction TransformedTemperature (°C)L06C06NbCr 3°C/sL06C06NbCrMo 3°C/sL06C06NbCr 10°C/sL06C06NbCrMo 10°C/s53 Figure 5.6: Optical micrographs for L06C06NbCr at different cooling rates (a) 3°C/s (b) 10°C/s and (c) 30°C/s 5.5 Characterization of microstructure with EBSD 5.5.1 Inverse pole figure (IPF) maps As optical microscopy could not provide reliable quantitative data for these steels, EBSD was used to analyze the microstructure quantitatively. All EBSD scans were taken with the rolling direction oriented normal to the map and the orientations are all with respect to the (100) plane. EBSD scans were required to have CI values greater than 90% to be used. Variations in CI values were random and were attributed to sample preparation and equipment condition. The scans were cleaned with a single-step cleaning process entailing grain dilation using a grain tolerance angle of 5˚ and minimum grain size of two pixels for grain boundary orientation distribution. The raw and cleaned scans (for L06C03Nb at 50⁰C/s) are shown in Figure 5.7. The comparison of the scans shows that the cleaning process does not heavily affect the results. a b d a a b c c 54 Figure 5.7: Inverse pole figure maps for L06C03Nb at 50˚C/s (a) raw (b) cleaned Figure 5.8 shows IPF maps for the L06C06NbCr steel with the rolling direction oriented normal to the plane of the map. The figures show increased refinement of bainitic structures with cooling rate. At 5°C/s, the structures have a bulky appearance with a generally uniform color scheme, indicating similar orientations within a block. At 50°C/s, the bainitic laths are much finer and more needle-like. The prior austenite grain boundaries can be clearly seen in the maps, regardless of cooling rate. a b 55 Figure 5.8: Inverse pole figure maps for L06C06NbCr at different cooling rates (a) 5°C/s (b) 10°C/s and (c) 50°C/s Comparing the maps in Figure 5.9 of L06C06NbCr and L06C06NbCrMo, the microstructure and refinement are quite similar. Thus, molybdenum has little to no impact on the microstructure. Figure 5.9: Inverse pole figure maps at 50°C/s for (a) L06C06NbCr and (b) L06C06NbCrMo a b b c a 56 5.5.2 Retained austenite During decomposition, the austenite does not fully transform, but instead some is retained. Figure 5.10 shows the retained austenite in the L06C06NbCr steel at 5˚C/s. The amount of retained austenite decreases with increased cooling rate for all three steels starting at 1 to 1.9% for 5°C/s down to 0.2 to 0.7% at 50°C/s. This can be expected as higher cooling rates provide less time for carbon diffusion to take place, leading to less enrichment of the austenite grains, which prevents the stabilization of this phase. The colour of the pixels indicates orientation, and similar groupings of coloured pixels can be seen belonging to the same prior austenite grains. The orientations found from these pixels are useful in conducting the Bain analysis. Figure 5.10: Retained austenite in L06C06NbCr at 5°C/s 5.5.3 Orientation relationship (OR) between parent phase and product phase The orientation relationship between prior austenite and bainite can be described using the Kurdjumov-Sachs orientation relationship (KS OR). By identifying the retained austenite orientation, the orientation of the product phase can be analyzed. Using an IPF map, a single grain can be identified, which can then be used to find a single prior austenite orientation. This orientation can result in 24 possible variants in the product phase, which is calculated theoretically fulfilling the {111}γ||{011}α<101>γ||<111>α orientation relationship. Figure 5.11a gives the pole figure of this grain with the austenite orientation represented by the three red dots and the possible transformation variants shown as open circles. The yellow triangles and green diamonds are artifacts of the pole figure program and have no significant meaning. Figure 5.11b shows the orientation obtained from the experiment, which indicates three Bain groups in a b c 57 different primary colours, each with eight variants. As the theoretical and experimental orientation maps show good agreement, KS orientation describes the bainite to austenite orientation relationship well. Figure 5.11c shows the Bain map for the selected grain. Figure 5.11: (a) Theoretical (001) pole figure (Black circles indicate the 24 KS variants, and green dots indicate the orientation of the parent grain.); (b) (001) pole figure of the selected grain; and (c) Bain map for the selected grain (For L06C06NbCr for 5˚C/s) a b c 58 Bain group analysis was conducted on 5, 10, and 50˚C/s cooling rate tests for the three steels. Figure 5.11 shows the Bain maps and pole figures at 5˚C/s for L06C06NbCr, and Figure 5.12 shows the Bain maps and pole figures for L06C06NbCr at 10 and 50˚C/s. All three Bain groups are present in each map, although not with the same proportion of each Bain group. Higher cooling rates tended to favour formation of different Bain groups adjacent to each other. At lower cooling rates, the Bain groups are present in a blockier structure, whereas for 50˚C/s, the Bain groups show a lath-like structure. a) Bain map for 10˚C/s b) Pole figures for 10˚C/s c) Bain map for 50˚C/s d) Pole figures for 50˚C/s Figure 5.12: Bain group maps and corresponding pole figures for cooling rates of (a, b) 10˚C/s and (c, d) 50˚C/s for L06C06NbCr 59 5.5.4 Spatial distribution of misorientation Figure 5.13 shows the low and high angle grain boundary maps for the L06C06NbCr steel for cooling rates of 5, 10 and 50°C/s. The green lines delineate the low angle grain boundaries (LAGBs), which are below 15°, and the black lines delineate the high angle grain boundaries (HAGBs), which are greater than 15°. As the cooling rate increases and the microstructure becomes more refined, the HAGB density increases, as seen by the more detailed black lines in the 50°C/s scan compared to the 5°C/s scan. HAGB density, or 𝐻𝐴𝐺𝐵𝐷, can be described by 𝐻𝐴𝐺𝐵𝐷 = ு஺ீ஻ ௟௜௡௘ ௟௘௡௚஺௥௘௔ ௢௙ ௠௜௖௥௢௦௧௥௨௖௧௨௥௘ . (5.1) Figure 5.13: Misorientation angle maps for L06C06NbCr at different cooling rates (a) 5°C/s (b) 10°C/s and (c) 50°C/s a b c 60 Figure 5.14 shows the addition of molybdenum does not affect the microstructure to any significant extent. Figure 5.14: Misorientation angle maps for (a) L06C06NbCr and (b) L06C06NbCrMo at 50˚C/s Figures 5.15 a, b, and c show the quantitative distribution of misorientation angles for 5, 10, and 50°C/s, respectively, for each of the steels. For 5°C/s, shown in Figure 5.15a, the curves indicate the presence of LAGBs and no other misorientation up to about 50°. There are two peaks at 54° and 59°, which are seen consistently for the three steels. These are consistent with bainitic peaks [95]. For 10°C/s, shown in Figure 5.15b, similar peaks are seen as for 5°C/s, except there is an additional peak at 30° for the L06C06NbCr steel. For 50°C/s, shown in Figure 5.15c, the same peaks are seen as at 10°C/s, but there are additional peaks for L06C06NbCrMo at 30, 35, and 45°. A general trend can be seen for all the steels, which is that as the cooling rate increases, there is a greater fraction of higher misorientation angles, which suggests a finer microstructure. This is more pronounced in the L06C06NbCr and L06C06NbCrMo steels, which have additional niobium and chromium. Similar exaggerated peaks are seen close to 60° for these two steels. a b 61 Figure 5.15: Distribution of misorientation angle for the three steels at different cooling rates (a) 5°C/s (b) 10°C/s and (c) 50°C/s 0.000.050.100.150.200.250.300.350 10 20 30 40 50 60 70FractionMisorientation Angle (˚)L06C03Nb L06C06NbCr L06C06NbCrMoa)0.000.050.100.150.200 10 20 30 40 50 60 70FractionMisorientation Angle (˚)L06C03Nb L06C06NbCr L06C06NbCrMob)0.000.050.100.150.200 10 20 30 40 50 60 70FractionMisorientation Angle (˚)L06C03Nb L06C06NbCr L06C06NbCrMoc)62 As can be seen from Figures 5.13, 5.14, and 5.15, the fraction of high angle grain boundaries is greater with increased cooling rate. HAGB density can be found by dividing the total length of HAGBs by the scan area. By plotting the inverse of this against the cooling rate, a relationship can be observed between cooling rate and HAGB density. L06C06NbCr and L06C06NbCrMo have similar HAGB densities, which are noticeably higher than for the L06C03Nb steel. As can be seen from Figure 5.16, HAGB density increases with cooling rate. However, the HAGB density for the 5°C/s scenario for L06C06NbCr and L06C06NbCrMo are higher than the HAGB density for the 10°C/s scenario. This can be explained by the fact that the 10˚C/s nominal cooling rate had an actual cooling rate closer to 5˚C/s throughout the transformation as can be seen in Figure 5.1. Figure 5.16: Effect of cooling rate on HAGB density With increased cooling rate, transformation start temperature decreases and HAGB density increases. Thus, a relationship can be drawn between transformation start temperature and HAGB density. In Figure 5.17, HAGBD0.5 is graphed against transformation start temperature. Two trends are observed that suggest that there are two populations of steels, shown in blue and orange. To illustrate the point, L06C06NbMo from Roy’s work [17] is added to draw a comparison. L06C03Nb, along with L06C06NbMo, display a linear relationship between transformation start temperature and HAGBD0.5. This is Population 1 and is shown in blue. 00.20.40.60.811.20 20 40 60HAGBD(µm-1)Cooling Rate (˚C/s)L06C03NbL06C06NbCrL06C06NbCrMo63 L06C06NbCr and L06C06NbCrMo, in turn, also display a linear relationship between transformation start temperature and HAGBD0.5. This is Population 2 and is shown in orange. Trendlines were drawn, and the R2 values give a good indication that there may be two populations of steels. The two trend lines have a similar slope with values of 0.0076 and 0.0069, which suggests that the general trend of the steel behavior has not changed, but there is some factor causing the transformation start temperature to be shifted upwards for Population 2. Possible causes for this shift are introduced in section 5.8. Figure 5.17: Effect of transformation start temperature on the square root of HAGB density for Population 1 (L06C03Nb, L06C06NbMo) and Population 2 (L06C06NbCr, L06C06NbCrMo) 5.6 Hardness Figure 5.18 shows the hardness for each steel at each cooling rate. Hardness increases with increased cooling rate. L06C06NbCr and L06C06NbCrMo have similar hardness values across the cooling rates, and these values are noticeably higher than the hardness values for L06C03Nb. There is a drop in hardness value at 10°C/s for L06C06NbCr and L06C06NbCrMo, which is within the error. This is consistent with the drop in HAGB density seen in Figure 5.16. L06C06NbCrMo steel seems to have a general trend of plateauing in hardness faster than y = -0.0076x + 5.0237R² = 0.9648y = -0.0069x + 4.7894R² = 0.89490.400.500.600.700.800.901.001.10500 550 600 650HAGBD0.5 (µm-0.5)Transformation Start Temperature (˚C)Population 1Population 264 L06C06NbCr, but it is difficult to come to this conclusion as the values are very similar at higher cooling rates. The increase in molybdenum, thus, has little effect on the hardness. The difference in hardness observed between L06C03Nb and L06C06NbCr can not be attributed solely to chromium as the difference in niobium content could have an effect as well. L06C03Nb does not have a drop in the hardness at 10°C/s, unlike the other two steels. Figure 5.18: Effect of cooling rate on hardness 5.7 Microstructure-property relationship A relationship can be shown between the microstructure that is observed (i.e., HAGB density) and the mechanical properties (i.e., hardness) for the three steels. HAGBD is the reciprocal of the characteristic length scale as defined by Mandal [56], which is a measure of the grain size. The square root of the HAGBD can be correlated with hardness. For better statistics, the steels studied by other members of The University of British Columbia Microstructure Group [17, 124] as part of the overall project have been included in Figure 5.19. This figure delineates the relationship between hardness (HV) and HAGB density. The relationship can be described as 𝐻𝑉 = 129 + 181(𝐻𝐴𝐺𝐵𝐷)଴.ହ. (5.2) This relationship has an R2 value of 0.94, indicating it has a very good fit. 2002202402602803003203400 20 40 60Hardness (HV)Cooling Rate (˚C/s)L06C03NbL06C06NbCrL06C06NbCrMo65 Table 5.1 summarizes the chemistry of the steels presented in Figure 5.19. Table 5.1: List of steel chemistries (wt%) C Nb Cr Mo Mn Ti N Si Al Ti/N L06C03Nb 0.059 0.037 0 0.1 1.59 0.016 0.0061 0.27 0.031 2.62 L06C06NbCr 0.057 0.057 0.23 0.11 1.65 0.017 0.0066 0.27 0.057 2.58 L06C06NbCrMo 0.058 0.057 0.23 0.26 1.66 0.017 0.0064 0.27 0.061 2.66 L04C03Nb 0.041 0.032 0.031 0.11 1.65 0.015 0.0055 0.25 0.031 2.73 L03C05Nb 0.033 0.051 0.017 0.1 1.74 0.017 0.0074 0.26 0.06 2.3 L04C07Nb 0.039 0.07 0.031 0.11 1.67 0.014 0.0054 0.26 0.018 2.59 L04C1Nb 0.043 0.1 0.009 0.1 1.54 0.014 0.006 0.29 0.032 2.33 L04C08NbMo 0.035 0.08 0.023 0.25 1.72 0.015 0.0055 0.25 0.024 2.73 L04C08NbCrMo 0.035 0.083 0.24 0.25 1.76 0.014 0.0058 0.26 0.016 2.41 L06C06NbMo 0.061 0.063 0 0.25 1.63 0.018 0.0055 0.26 0.044 3.27 L07C09Nb 0.074 0.089 0.021 0.1 1.67 0.017 0.0076 0.25 0.048 2.24 L07C09NbCr 0.065 0.093 0.24 0.1 1.63 0.015 0.0075 0.26 0.046 2 Figure 5.19: Relationship between HAGB density and hardness (Adapted from [129] with permission from Springer Nature) 1752252753250.25 0.5 0.75 1 1.25Hardness (Hv)HAGB density0.5(µm-0.5)L06C03Nb(8030)L06C06NbCr(9030)L06C06NbMoCr(9031)L04C03Nb(7011)L03C05Nb(9028)L04C07Nb(7012)L04C1Nb(6008)L04C08NbMo(7013)L04C08NbMoCr(7014)CrMo4 8 CrMo66 From Figure 5.19, it can be observed that HAGB density, a microstructural feature, is related to hardness. Further work needs to be done to explore the relationship between transformation start temperature and HAGB density to draw a better conclusion between transformation start temperature and hardness. 5.8 Discussion CCT tests show that with increased cooling rate, transformation start temperature decreases for all steels. By increasing the cooling rate from 3˚C/s to 30˚C/s, the transformation start temperatures for L06C03Nb, L06C06NbCr, and L06C06NbCrMo drop by 65, 67, and 57˚C, respectively. The drop of the transformation start temperature with increased cooling rates has been shown in several studies in the literature [16, 56, 99]. With the decomposition of austenite, the formation of the new product phase, which involves kinetic processes such as nucleation and growth, takes time. When the cooling rate is increased, the time spent at any given temperature is reduced and the transformation temperature is lowered [17, 130]. The effect of chromium on the transformation temperature cannot be determined at this time. If a comparison were made between L06C03Nb and L06C06NbCr with the addition of 0.23wt% chromium, the transformation temperatures increase by approximately 25˚C across the cooling rates for L06C03Nb and L06C06NbCr. This is contradictory to the results found by Roy [17] and Chen et al. [45]. In Roy’s study, with a similar addition of chromium, a 10˚C drop in transformation temperatures was observed. Similarly, Chen et al. observed a drop of 5 to 15˚C in transformation temperatures with the addition of 0.269wt% chromium. As previously explained, there is an inconsistency in the behaviour of the steels as the L06C06NbCr and L06C06NbCrMo steels have higher transformation temperatures compared to the L06C03Nb steel. Therefore, determining the effect of chromium is not possible by comparing the L06C03Nb and L06C06NbCr steels. Different hypotheses were raised to identify the inconsistent behavior of these steels. One, in particular, was explored and is discussed in this section. However, it is critical to list the observations and considerations in a logical order before introducing the hypothesis. Figure 5.20 67 shows the transformation start temperatures for L06C03Nb, L06C06NbMo, L06C06NbCr, and L06C06NbCrMo. Figure 5.20: Transformation start temperatures for L06C03Nb, L06C06NbMo, L06C06NbCr and L06C06NbCrMo [17] By comparing L06C03Nb with L06C06NbMo as well as L06C06NbCr and L06C06NbCrMo, it can be seen that molybdenum has a consistent effect of depressing transformation start temperatures by 15˚C, which is similar to observations made by Chen et al. [45]. Thus, the two sets of steels have transformation start temperatures that are internally consistent when it comes to the effect of molybdenum. 5205405605806006206406606800 5 10 15 20 25 30Temperature (˚C)Cooling Rate (˚C/s)L06C06NbMo L06C06NbCrMoL06C03Nb L06C06NbCr68 However, when the transformation start temperatures of L06C03Nb and L06C06NbCr are compared, an addition of chromium appears to have increased transformation start temperatures by 25˚C. Upon further analysis, it was found that L06C03Nb behaved consistently with steels that had been investigated previously, but for some unknown reason, L06C06NbCr and L06C06NbCrMo seemed to have transformation start temperatures that were much higher than would be expected based on steel chemistry. One hypothesis that was raised to explain this observation was the difference in prior austenite grain size. Different sources in the literature show that austenite grain size may or may not affect transformation start temperature. For example, Reichert [16] found that an increase in austenite grain size from 26µm to 80µm led to a decrease in transformation temperature and a change in bainite morphology. However, Yamamoto et al. [131] reported that the austenite grain size had no appreciable effect on the bainitic transformation temperature under continuous cooling conditions. The limiting prior austenite grain size among the three steels in this study is different. L06C03Nb had a limiting grain size of 80µm. L06C06NbCr and L06C06NbCrMo, on the other hand, were found to have a limiting grain size close to 60µm. To check if the difference in austenite grain size could explain the observation regarding transformation temperatures, a representative steel (i.e., L04C08NbCrMo) was heat treated with the thermal cycle for the 50˚C/s cooling rate, but with different hold times to achieve different PAGS (40, 60, 80µm). For the 40µm PAGS, a two-pass thermal cycle was used with a first-pass quench followed by a second pass without an isothermal hold to ensure that most niobium was in solution while attaining the desired PAGS. The dilation data from the tests showed that there was less than ±2˚C variation in the transformation start temperature for these three different PAGS. This is within the error of the experiment. Thus, the hypothesis of a difference in PAGS being the cause of the difference in transformation start temperature was rejected. Another possible explanation for the shift in transformation start temperatures is the role of precipitates. The formation of chromium carbides could deplete the carbon in solution and, thus, raise the transformation start temperature. The difference in nature of titanium nitrides between the two sets of steels could also be a factor as titanium nitride precipitates may affect nucleation 69 and growth of bainite. However, the evaluation of these aspects goes beyond the scope of this study, and, thus, will be left to future work. In conclusion, with increased cooling rate, transformation start temperature decreases, the microstructure becomes finer, HAGB density increases, and thus hardness increases. A Hall-Petch relationship was observed between the characteristic length scale in terms of the reciprocal of the HAGB density and hardness [129]. Two populations of steels were observed that had an offset in transformation start temperature for which potential causes were raised and one investigated. The role of precipitates should be further investigated as chromium carbides could decrease the carbon content in solution and titanium nitride precipitate distribution may affect bainite transformation as well, but this will have to be investigated as future work through Scanning Transmission Electron Microscopy (STEM), grain growth and transformation studies. Thus, a relationship between transformation start temperature and hardness is yet to be developed as the two populations pose an issue. 70 Chapter 6: Modelling 6.1 Bainite start model Based on the bainite start model used by Garcin et al. [60], bainite start temperatures were modelled for each steel. The bainite start temperature was found using a simplified form of Garcin’s equation 0.05 = ∫ ቂ௕భା௕మ்ఝ ቃ 𝑑𝑇்ಿೄ்ಳ , (6.1) where 𝑇ௌ஻ is the bainite start temperature, TN is the nucleation temperature, b1 and b2 are chemistry-dependent fit parameters, and 𝜑 is the cooling rate in ˚C/s. Bainite nucleation temperature was found using Thermo-Calc. According to Bhadeshia [66], the critical driving pressure for bainite nucleation is 400J/mol, based on the strain energy associated with shear in bainite formation. Table 6.1 lists the bainite nucleation temperature for each steel. The effect of chemistry on bainite nucleation temperature is marginal. Table 6.1: Nucleation temperatures of the steels Steel Name Bainite Nucleation Temperature (˚C) L06C03Nb 649 L06C06NbCr 646 L06C06NbCrMo 648 The fit parameters are found for the three steels based on minimizing root-mean-square error as shown in Table 6.2. 71 Table 6.2: Fit parameters for the steels Steel name b1 (s-1) b2 (˚C-1s-1) L06C03Nb 479 -0.53 L06C06NbCr 683 -0.73 L06C06NbCrMo 902 -0.99 Based on these fit parameters, the bainite start temperatures are calculated and compared against the data, as shown in Figure 6.1. The calculated and experimental data have very good agreement with a deviation of ±5˚C, i.e., within the error of measurement. Figure 6.1: Comparison of calculated and measured transformation start temperature for the 3 to 30˚C/s cooling rate thermal paths of the three steels By comparing the calculated and measured transformation temperatures against cooling rate, a transformation start temperature for any cooling rate can be predicted, as shown in Figure 6.2. 72 Figure 6.2: Transformation start temperature based on cooling rate 6.2 Bainite growth model Bainite growth is modelled using the JMAK model with the additivity principle, i.e., 𝑋 = 1 − exp (− ∫ ఉఝ 𝑑𝑇)௡ೄ்ಳ் , (6.2) where X is fraction transformed, 𝑇ௌ஻ is the bainite start temperature, and n is the JMAK exponent. Calculated values of bainite start temperatures were used for the bainite growth model. A value of 1.1 is adopted from literature [16] for the JMAK exponent, which is found to provide a 73 satisfactory fit to the CCT data for the three investigated steels. 𝛽, with units of s-1, is a temperature-dependent function described by 𝛽 = exp(𝛽ଵ𝑇 + 𝛽ଶ), (6.3) where 𝛽ଵ and 𝛽ଶ are fit parameters that depend on steel chemistry. The values for 𝛽ଵ and 𝛽ଶ for each of the steels is given in Table 6.3. Table 6.3: Fit parameters and their respective components in the linear function Steel name 𝜷𝟏 (K-1s-1) 𝜷𝟐 (s-1) L06C03Nb -3.5 10-2 27.9 L06C06NbCr -2.9 10-2 23.6 L06C06NbCrMo -2.5 10-2 19.6 The fit parameters and their linear functions were calculated minimizing the total error between the model and the experimental data for 3, 5 and 10⁰C/s. Figure 6.3 compares the model to the data for L06C06NbCr. The model matches the experimental result well with a maximum difference in temperature of 15˚C around T50. L06C03Nb and L06C06NbCrMo both show a similar level of agreement between the calculated and measured temperatures. 74 Figure 6.3: Measured and calculated transformation kinetics of L06C06NbCr Figure 6.4 gives the comparison of the temperatures at 50 and 95% transformation. Error bars of ±15˚C have been drawn. There is reasonable agreement between the calculated and measured temperatures with a ±15˚C deviation. This is within the error of measurement for temperature. Thus, the models sufficiently describe the growth kinetics of the three steels. 75 Figure 6.4: Comparison of measured and calculated temperatures at 50 and 95% transformation 6.3 Discussion This chapter dealt with modelling the austenite decomposition kinetics of the three steels accounting for the effect of cooling rate for austenite grain sizes relevant to the CGHAZ. For bainite start, the calculated and measured values had good agreement with a ±5˚C deviation. This is comparable to what Roy [17] found in his research on the effect of carbon content, 76 chromium content, and cooling on austenite decomposition kinetics. Fit parameters were found by minimizing the root-mean-square error, and the resultant transformation start temperatures were used to model bainite growth. For bainite growth, the JMAK exponent was found to be 1.1 upon analyzing the CCT data for the three steels, which is the value Reichert [16] used and comparable to the value Roy [17] used to describe the growth kinetics of the steels in their respective studies. Fit parameters were calculated based on conditions where the cooling rate was maintained (i.e., 3, 5, 10˚C/s). For the growth model, the calculated and measured values had a deviation of ±5˚C for the majority of the T50 and T95 values. This is, again, similar to what was found by Reichert and Roy. In order to develop a function that predicts the fit parameters as a function of steel chemistry, it is necessary to identify all the relevant microstructural parameters. The results indicate a dependence on the studied elements. However, the inconsistencies between the observations and established literature indicate that there is likely a parameter which has not been considered and cannot be identified through this study. 77 Chapter 7: Summary and Future Work 7.1 Summary The objective of this study was to quantify the effects of cooling rate and chromium and molybdenum contents on austenite decomposition of X80 line pipe steels by analyzing the resultant microstructure and properties of the CGHAZ. Three steels in tubular form were heat treated mimicking the thermal path of relevant welding processes to replicate CGHAZ microstructure produced by welding. Dilatometric values were analyzed to study the austenite decomposition kinetics. Optical microscopy and EBSD scans of the cross section where the thermocouple was attached provided the microstructural characteristics. Vickers hardness testing was done to measure the mechanical properties. Based on the model by Garcin et al. [60], bainite start and growth kinetics were reproduced and compared to the experimental data. The relevant findings from this study are: 1. An increase in molybdenum content from 0.11wt% to 0.26wt% resulted in a decrease in the transformation start temperature of 15˚C on average across all cooling rates. 2. The effect of the addition of chromium content (0.23wt%) could not be quantified as there is a factor causing the transformation start temperature to shift that could not be identified. Prior austenite grain size affecting transformation start temperature was raised as a possible hypothesis but was eliminated upon further testing. 3. Hardness for the three steels all increased by about 80HV with a change in cooling rate from 3˚C/s to 50˚C/s. 4. HAGB density for all steels increased with increased cooling rate. L06C06NbCr and L06C06NbCrMo had comparable HAGB density values for all cooling rates starting from 0.34µm-1 at 3˚C/s to ~0.85µm-1 at 50˚C/s, indicating a similar microstructure for the two chromium steels. L06C03Nb had much lower HAGB densities at 0.18µm-1 at 3˚C/s up to 0.67µm-1 at 50˚C/s. 5. A steel chemistry independent Hall-Petch type relationship was established between HAGB density0.5 and hardness. The relationship between HAGB density0.5 and hardness is consistent with other steels investigated as part of the overall project, as summarized by Roy et al. [129]. 78 6. Transformation start models were developed for each steel that were within ±5˚C variation of the experimental data. A bainite growth model based on the JMAK model with the additivity principle was applied to capture the growth kinetics within ±15˚C variation. 7. The experimental values of the HAGB density0.5 were used to predict hardness values which were within ±5% of the experimental values. 7.2 Future Work In this study, the effect of molybdenum (0.11wt% to 0.26wt%) was successfully quantified, but the effect of chromium could not be identified. Thus, based on the results of the individual steels, the effect of cooling rate on transformation temperatures, microstructure, and hardness was described separately. In order to create a comprehensive chemistry-sensitive model, suggestions for future work would focus on finding the cause of the shift in transformation start temperatures which created two populations of steels. In particular, the role of precipitates should be investigated by conducting systematic studies on the following phenomena. 1. The formation of chromium carbide precipitates could remove carbon from solution and raise the transformation start temperatures. 2. TiN precipitates can act to promote austenite decomposition into bainite by affecting nucleation and growth rates. Thus, a difference in the nature of the titanium nitrides could cause a change in the transformation start temperature. In addition, different specimen designs could be used for the Gleeble CCT tests to minimize the temperature gradients (i.e., using deformation-CCT specimen designs). 79 Bibliography [1] “Pipelines Across Canada,” Sept. 2020. [Online]. Available: https://www.nrcan.gc.ca/our-natural-resources/energy-sources-distribution/clean-fossil- fuels/pipelines/pipelines-across-canada/18856. [2] A. J. DeArdo, “The metallurgy of high strength line pipe steels,” In Proceedings of the International Symposium on Pipelines for the 21st Century,” as held at the 44th Annual Conference of Metallurgists of CIM (COM 2005), Calgary, Alberta, Canada. [3] M. M. Salama, “Qualification of fiber wrapped steel pipe for high pressure arctic pipeline,” Paper presented at OTC Arctic Technology Conference, Houston, Texas, Feb. 2011. Paper number OTC-22082-MS. [4] G. R. Goodall, “Welding high strength modern line pipe steel,” PhD dissertation, McGill University, Montreal, Canada, 2011. [5] N. Bailey, Weldability of Ferritic Steels, 1st ed., Cambridge, UK: Woodhead Publishing, 1994, p. 15. [6] D. Yapp and S. A. Blackman, “Recent developments in high productivity pipeline welding,” J. Braz. Soc. Mech. Sci. & Eng. 26, 1, pp. 89-97, 2004. [7] K. E. Easterling, Introduction to the Physical Metallurgy of Welding, 2nd ed., Oxford, UK: Butterworth-Heinemann, 1992. [8] A. K. Das, “The present and the future of line pipe steels for [the] petroleum industry,” Mater. Manuf. Processes, 25, pp.14-19, 2010. [9] “Specification for Line Pipe,” ANSI/API Specification 5L, 44th ed., pp. 25-26, 2007. [10] M. Militzer, “Thermomechanical processed steels,” in Comprehensive Materials Processing: Volume 1- Assessing Properties of Conventional and Specialized Materials, C. J. Van Tyne, Ed., Amsterdam: Elsevier, pp. 191-216, 2014. [11] J. M. Gray, “Niobium bearing steels in pipeline projects.” In Niobium, Science and Technology: Proceedings of the International Symposium Niobium 2001, Orlando, Florida, pp. 889-906. [12] P. R. Kirkwood, “Technical briefing: Thermomechanical controlled processing (TMCP): Delivering the advantages of niobium technology,” CBMM Niobium Nb, Editorial support by Beta Technology, May 2020. [Online]. Available: https://niobium.tech/en/thermomechanical-controlled-processing-tmcp. 80 [13] S. Vervynckt, K. Verbeken, B. Lopez, and J. J. Jonas, “Modern HSLA steels and role of non-recrystallization temperature,” Int. Mater. Rev., 57, 4, pp. 187-201, 2012. [14] M. Mohammadijoo, L. Collins, H. Henein, and D. G. Ivey, “Canadian HSLA steel pipelines: History and technology developments,” Contributed paper from Materials Science and Technology 2018 (MS&T18), Columbus, Ohio, pp. 1174-1181. [15] D. Belato Rosada, W. De Waele, D. Vanderschueren, and S. Hertelé, “Latest developments in mechanical properties and metallurgical features of high strength line pipe steels,” Int. J. Sustain. Constr. Des., 4, 1, 2013. [16] J. M. Reichert, “Structure and properties of complex transformation products in Nb/Mo micro-alloyed steels,” PhD dissertation, The University of British Columbia, Vancouver, Canada, 2016. [17] S. Roy, “Austenite decomposition in the coarse grain heat affected zone of X80 linepipe steel,” MASc. thesis, The University of British Columbia, Vancouver, Canada, 2020. [18] C. Stallybrass, H. Meusser, F. Gerdemann, C. Kalwa, and H. G. Hillenbrand, “High strength, large diameter UOE pipes optimised for application in remote areas and low-temperature service,” In Proceedings of the 8th Pipeline Technology Conference, Hannover, Germany, Mar. 18-20, 2013. [19] J. A. Gianetto, J. T. Bowker, and D. V. Dorling, “Assessment of properties and microstructure of X100 pipeline girth welds,” Welding in the World, 49, pp.77-89, 2005. [20] J. M. Gray and F. Siciliano, “High strength microalloyed line pipe: Half a century of evolution,” In Proceedings of the Pipeline Technology Meeting, Houston Texas, Apr. 22-23, 2009. [21] G. Zhang, X. Bai, D. G. Stalheim, S. Li, and W. Ding, “Development and production of heavy gauge X80 and X90 pipeline steels utilizing TMCP/Optimized cooling process,” In Proceedings of the 2014 10th International Pipeline Conference Volume 3: Materials and Joining; Risk and Reliability, Calgary, Alberta, Canada, Sept. 29 - Oct. 3, 2014. . [22] H. Asahi, T. Hara, E. Tsure, H. Morimoto, S. Ohkita, M. Sugiyama, N. Maruyama, K. Shinada, K. Koyama, Y. Terada, H. Akasaki, N. Ayukawa, M. Murata, N. Doi, H. Miyazaki, and T. Yoshida, “Development of ultra-high-strength linepipe, X120,” Nippon Steel Tech. Rep., No. 90, pp. 82-87, Jul. 2004. 81 [23] P. Suikkanen, “Development and processing of low carbon bainitic steels,” PhD dissertation, Oulu University, Oulu, Finland, 2009. [24] R. H. Petrov, J. J. Jonas, L. A. I. Kestens, and J. M. Gray, “Microstructure and texture development in pipeline steels,” Oil and Gas Pipelines: Integrity and Safety Handbook, R.W. Revie, Ed., Hoboken: John Wiley and Sons, pp. 159 -185, 2015. [25] A. G. Kostryzhev, O. O. Marenych, C. R. Killmore, and E. V. Pereloma, “Strengthening mechanisms in thermomechanically processed NbTi-microalloyed steel,” Metall. Mater. Trans. A, 46, 8, pp. 3470-3480, 2015. [26] D. G. Stalheim, K. R. Barnes, and D. B. McCutcheon, “Alloy designs for high strength oil and gas transmission linepipe steels,” in International Symposium on Microalloyed Steels for the Oil and Gas Industry, TMS (The Minerals, Metals, and Materials Society), pp. 73-108, 2007. [27] E. G. Ohaeri and J. A. Szpunar, “An overview in pipeline steel development for cold climate application,” Journal of Pipeline Science and Engineering, 2, 1, pp. 1-17, 2022. [28] J. D. S. Martinez, D. H. Ladino, J. W. C. Hernández, N. A. Falleiros, H. Gomes de Melo, “Corrosion characterization of new low manganese microalloyed X65 steels in sour and non-sour synthetic seawater,” J. Mater. Res Technol., 18, pp. 3198-3214, 2022. [29] W. D. Callister and D. G. Rethwisch, Materials Science and Engineering, SI Version, 8th ed., Asia: John Wiley and Sons, 2011. [30] S. K. Sarnia, “The iron-carbon phase diagram,” IspatGuru, 2013. [Online]. Available: https://www.ispatguru.com/the-iron-carbon-phase-diagram. [31] T. Gladman, The Physical Metallurgy of Microalloyed Steels, London: Institute of Materials, 1997. [32] M. P. Groover, Fundamentals of Modern Manufacturing: Materials, Processes, and Systems, 4th ed., Hoboken: John Wiley and Sons, p. 105, 2010. [33] M. Maalekian, “The effects of alloying elements on steels (I),” Technische Universität Graz, Institut für Werkstoffkunde, Schweißtechnik und Spanlose Formgebungsverfahren, Christian Doppler Laboratory for Early Stages of Precipitation, pp. 3-6, 2007. [34] K. Nishioka and K. Ichikawa, “Topical Review: Progress in thermomechanical control of steel plates and their commercialization,” Sci. Tech. Adv. Mat., 13, 2, 2012. Article 023001. 82 [35] T. Jia and M. Militzer, “The effect of solute Nb on the austenite-to-ferrite transformation,” Metall. Mater. Trans. A, 46, 2, pp. 614-621, 2015. [36] K. Hulka and J. M. Gray, “High temperature processing of linepipe steels,” In Proceedings of the International Symposium Niobium 2001, Orlando, Florida, TMS, pp. 587-612. [37] W. J. Poole, M. Militzer, and T. Garcin, “An integrated model to predict microstructure and mechanical properties in the heat affected zone for X80 linepipe,” in Proceedings of the 2012 9th International Pipeline Conference, Calgary Alberta, Canada, Sept. 24-28, 2012. [38] P. R. Kirkwood, “Niobium and heat-affected zone mythology,” In Proceedings of the International Seminar on Welding of High Strength Pipeline Steels, CBMM and TMS, pp. 23-64, 2013. [39] Z. X. Zhu, L. Kuzmikova, M. Marimuthu, H. S. Li, and F. Barbaro, “Role of Ti and N in line pipe steel welds,” Sci. Technol. Weld. Joining, 18, 1, pp. 1-10, 2013. [40] S. -C. Wang, “The effect of titanium and nitrogen contents on the microstructure and mechanical properties of plain carbon steels,” Mat. Sci. Eng. A, 145, 1, pp. 87- 94, 1991. [41] W. Yan, Y. Y. Shan and K. Yang, “Effect of TiN inclusions on the impact toughness of low carbon microalloyed steels,” Metall. Mater. Trans. A, 37, pp. 2147-2158, 2006. [42] L. P. Zhang, C. L. Davis, and M. Strangwood, “Effect of TiN particles and microstructure on fracture toughness in simulated heat-affected zones of a structural steel,” Metall. Mater. Trans. A, 30, 8, pp. 2089-2096, 1999. [43] H. Mohrbacher, “Mo and Nb alloying in plate steels for high-performance applications,” In The International Symposium on the Recent Developments in Plate Steels, AIST, Warrendale, Pennsylvania, pp. 169–179, 2011. [44] M.-C. Zhao, K. Yang, F.-R. Xiao, and Y.-Y. Shan, “Continuous cooling transformation of undeformed and deformed low carbon pipeline steels,” Mat. Sci. Eng. A, 355, pp. 126-136, 2003. [45] X. W. Chen, G. Y. Qiao, X. L. Han, X. Wang, F. Xiao, and B. Liao, “Effects of Mo, Cr and Nb on microstructure and mechanical properties of heat-affected zone for Nb-bearing X80 pipeline steels,” Mater. Des., 53, pp. 888-901, 2014. 83 [46] S. Kou, Welding Metallurgy, 2nd ed., Hoboken: John Wiley and Sons, Inc., pp. 23- 24, 2003. [47] S. Zardynezhad, “Evaluate ERW and SAW pipes for onshore buried gas pipelines,” Gas Processing and LNG: Technology and Business Information for the Global Gas Processing Industry, Gulf Publishing Holdings LLC, June 2021. [Online]. Available: http://www.gasprocessingnews.com/features/202106/evaluate-erw-and-saw-pipes-for- onshore-buried-gas-pipelines.aspx. [48] The Process Piping, “Introduction to welded pipe manufacturing,” Jul. 2018. [Online]. Available: https://www.theprocesspiping.com/introduction-to-welded-pipe- manufacturing/. [49] S. Fiore, M. Boring, P. Patel, and S. Vaze, “Review of X80 and X100 pipeline welding: Task I report - Optimizing weld integrity for X80 and X100 line pipe,” Edison Welding Institute, Tech. Rep. 47960GTH. Prepared for submission to the U.S. Department of Transportation, Washington, D. C., Feb. 4, 2006. [50] H. K. D. H. Bhadeshia, L. -E. Svensson, and B. Gretoft, “A model for the development of microstructure in low-alloy steel (Fe-Mn-Si-C) weld deposits,” Acta Metall., 33, 7, pp. 1271 – 1283, 1985. [51] M. J. Gaudet, “The tensile properties and toughness of microstructures relevant to the HAZ of X80 line pipe steel girth welds,” PhD dissertation, The University of British Columbia, Vancouver, Canada, 2015. [52] V. K. Pal, L. P. Singh, and C. Pandey, “Control of hydrogen assisted cracking in high strength steel welds,” Int. J. Eng. Sci. Res. Technol., 6, 4, pp. 556-567, 2017. [53] J. C. Ion, K. E. Easterling, and M. F. Ashby, "A 2nd report on diagrams of microstructure and hardness for heat-affected zones in welds," Acta Metall., 32, 11, pp. 1949-1955, 1957-1962, 1984. [54] M. Shome, "Effect of heat-input on austenite grain size in the heat-affected zone of HSLA-100 steel," Mater. Sci. Eng. A, 445, pp. 454-460, 2007. [55] I. Andersen and Ø. Grong, "Analytical modelling of grain growth in metals and alloys in the presence of growing and dissolving precipitates--I. normal grain growth," Acta Metall. Mater., 43, 7, pp. 2673-2688, 1995. [56] M. Mandal, “Microstructure and mechanical properties of simulated weld heat-affected zones in X80 linepipe steel,” PhD dissertation, The University of British Columbia, Vancouver, Canada, 2020. 84 [57] B. de Meester. “The weldability of modern structural TMCP steels,” ISIJ Int., 37, 6, pp. 537–551, 1997. [58] C. L. Davis and J. E. King, “Cleavage initiation in the inter-critically reheated coarse- grained heat-affected zone: Part I Fractographic evidence,” Metall. Mater. Trans. A, 25, pp. 563-573, 1994. [59] M. Kulakov, Unpublished work, 2014. [60] T. Garcin, M. Militzer, W. J. Poole, and L. Collins, “Microstructure model for the heat- affected zone of X80 line pipe steel,” Mat. Sci. Technol., 32, 7, pp. 708-721, 2016. [61] R. W. Messler, Jr., A Practical Guide to Welding Solutions: Overcoming Technical and Material-Specific Issues, Weinheim, Germany: Wiley-VCH, pp. 179-183, 2019. [62] M. P. Singh, K. S. Arora, N. Shajan, and S. R. Pandu, “Comparative analysis of continuous cooling transformation behaviour in CGHAZ of API-X80 and X65 line pipe steels,” J. Therm. Anal. Calorim., 137, 7, pp. 1155-1167, 2019. [63] P. Cizek, B. P. Wynn, C. H. J. Davies, B. C. Muddle & P. D. Hodgson, “Effect of composition and austenite deformation on the transformation characteristics of low- carbon and ultra low-carbon steels,” Metall. Mater. Trans. A, 33, 5, pp. 1331– 1349, 2002. [64] G. Krauss and S. W. Thompson, “Ferritic microstructures in continuously cooled low- and ultra low carbon steels,” ISIJ Int., 35, 8, pp. 937 - 945, 1995. [65] International Institute of Welding, Guide to the Light Microstructure Examination of Ferritic Steel Weld Metals, IIW Doc. No. IX-1533-88, IXJ-123-87 Revision 2, IIW, 1988. [66] H. K. D. H. Bhadeshia, Bainite in Steels: Transformations, Microstructures, and Properties, London: The Institute of Materials, pp. 245-82, 1992. [67] L. Fielding, “The bainite controversy,” Mater. Sci. Technol., 29, 4, pp. 383-399, 2013. [68] S. Banerjee and P. Mukhopadhyay, Eds. “Chapter 2: Classification of phase transformations,” in Phase Transformation: Examples from Titanium and Zirconium Alloys, Pergamon Materials Series, 12, pp. 87, 89-123, 2007. [69] F. G. Caballero, M. K. Miller, C. Garcia-Mateo, J. Cornide, and M. J. Santofimia, “Temperature dependence of carbon supersaturation of ferrite in bainitic steels,” Scr. Mater., 67, 10, pp. 846-849, 2012. 85 [70] E. Swallow and H. K. D. H. Bhadeshia, “High resolution observations of displacements caused by bainitic transformation,” Mater. Sci. Technol., 12, 2, pp. 121-125, 1996. [71] J. G. Zhu, “Bainite transformation kinetics - Microstructure characterization of austempered 4140/4150 steel,” D.Phil., Oakland University, Rochester, Michigan, 2019. [72] H. K. D. H. Bhadeshia and J. W. Christian, “Bainite in steels,” Metall. Mat. Trans. A, 21, pp. 767-797, 1990. [73] H. K. D. H. Bhadeshia and D. V. Edmonds, “The mechanism of the bainite transformation in steels,” Acta Metall., 28, 9, pp. 1265-1273, 1980. [74] R. F. Mehl, “The physics of hardenability – The mechanism and the rate of decomposition of austenite,” in Hardenability of Alloy Steels (Medium and Low Alloy Steels – Up to 5% Alloys), Cleveland, Ohio: ASM, pp. 1-65, 1939. [75] Y. Ohmori, H. Ohtani, S. Okaguchi, and Y. Fujishiro, “Morphology and properties of low-carbon bainite,” Metall. Trans. A, 21, pp. 877-888, 1990. [76] B. L. Bramfitt and J. G. Speer, “A perspective on the morphology of bainite,” Metall. Mater. Trans. A, 21, 4, pp. 817-829, 1990. [77] S. Zajac, V. Schwinn, and K. H. Tacke, “Characterization and quantification of complex bainitic microstructures in high and ultra-high strength linepipe steels,” Mater. Sci. Forum, 500-501, pp. 387-394, 2005. [78] European Commission, Directorate-General for Research and Innovation, S. Zajac, J. Komenda, P. Morris, P. Dierickx, S. Matera, and F. Penalba Diaz, “Quantitative structure-property relationship for complex bainitic microstructures: Final report,” Publications Office, 2005. [79] S. J. Matas and R. F. Hehemann, “The structure of bainite in hypoeutectoid steels,” TMS-AIME, 221, pp. 179-85, 1961. [80] S. B. Singh, “Mechanisms of bainite transformation in steels” in Phase Transformations in Steels, Vol. 1: Fundamentals and Diffusion-Controlled Transformations, E. Pereloma and D. Edmonds, Eds., Oxford: Woodhead Publishing Limited, pp. 385- 416, 2012. [81] H. K. D. H. Bhadeshia and R. Honeycombe, Steels: Microstructures and Properties, 4th ed., Oxford, UK: Butterworth-Heinemann, p. 193, 2017. 86 [82] B. L. Bramfitt, “Structure/Property relationships in irons and steels,” in Metals Handbook Desk Ed., 2nd ed., J. R. Davis, Ed., pp. 153-173, 1998. [83] H. K. D. H. Bhadeshia, “About calculating the characteristics of the martensite- austenite constituent,” In Proceedings of the International Seminar on Welding of High Strength Pipeline Steels, CBMM and TMS, pp. 99-106, 2013. [84] Y. Li and T. N. Baker, “Effect of morphology of martensite-austenite phase on fracture of weld heat affected zone in vanadium and niobium microalloyed steels,” Mater. Sci. Technol., 26, 9, pp. 1029–1040, 2014. [85] Ø. M. Akselsen, Ø. Grong and J. K. Solberg, “Structure-property relationships in intercritical heat-affected zone of low-carbon microalloyed steels,” Mater. Sci Technol., 3, 8, pp. 649- 655, 1987. [86] C. L. Davis and J. E. King, “Effect of cooling rate on inter-critically reheated microstructure and toughness in high strength low alloy steel,” Mater. Sci. Technol., 9, pp. 8-15, 1993. [87] A. Guillal, N. A. Ddelbaki, M. Gacels, and M. Betlayeb, “Effects of martensite- austenite constituents on mechanical properties of heat affected zone in high strength pipeline steels - Review,” Chem. Eng. Trans., 70, pp. 583-588, 2018. [88] K. Ohya, J. Kim, K. Yokohama and M. Nagumo, “Microstructures relevant to brittle fracture initiation at the heat-affected zone of weldment of a low carbon steel,” Metall. Mater. Trans. A, 27, pp. 2574-2582, 1996. [89] N. Takayama, G. Miyamoto, and T. Furuhara, “Effects of transformation temperature on variant pairing of bainitic ferrite in low carbon steel,” Acta Mater., 60, pp. 2387– 2396, 2012. [90] A. Lambert-Perlade, A. F. Gourgues, and A. Pineau, “Austenite to bainite phase transformation in the heat-affected zone of a high-strength low-alloy steel,” Acta Mater., 52, pp. 2337– 2348, 2004. [91] V. A. Yardley and E. J. Payton, “Austenite-martensite/bainite orientation relationship: Characterization parameters and their application,” Mater. Sci. Technol., 30, 9, pp. 1125-1130, 2014. [92] H. K. D. H. Bhadeshia, Worked Examples in the Geometry of Crystals, 2nd ed. London: Institute of Metals, pp. 12-24, 2006. 87 [93] J. W. Christian, The Theory of Transformations in Metals and Alloys. Amsterdam: Elsevier, pp. 992-1059, 2002. [94] K. Verbeken, L. Barbé, and D. Raabe, “Evaluation of the crystallographic orientation relationships between FCC and BCC phases in TRIP steels,” ISIJ Int., 49, 10, pp. 1601-1609, 2009. [95] T. Furuhara, H. Kawata, S. Morito, and T. Maki, “Crystallography of upper bainite in Fe–Ni–C alloys,” Mater. Sci. Eng. A, 431, 1-2, pp. 228-236, 2006. [96] J. M. Reichert, W. J. Poole, M. Militzer, and L. Collins, “A new approach using EBSD to quantitatively distinguish complex transformation products along the HAZ in X80 line pipe steels,” In Proceedings of the 2014 10th International Pipeline Conference, Volume 3: Materials and Joining; Risk and Reliability, Calgary, Alberta, Canada, Sept. 29-Oct. 3, 2014. V003T07A055. [97] X. L. Wang, X. P. Ma, Z. Q. Wang, S. V. Subramanian, Z. J. Xie, C. J. Shang, and X. C. Li, “Carbon microalloying effect of base material on variant selection in coarse grained heat affected zone of X80 pipeline steel,” Mater. Charact., 149, pp. 26-33, 2019. [98] N. Huda, A. R. H. Midawi, J. A. Gianetto, and A. P. Gerlich, “Continuous cooling transformation behaviour and toughness of heat-affected zones in an X80 line pipe steel,” J. Mater. Res. Technol., 12, 1, pp. 613-628, 2021. [99] A. K. Naik, R. Roshani, K. S. Aroraz, N. Shajan, and S. C. Mishra, “Continuous cooling transformation diagram and mechanical properties in weld coarse-grain heat-affected zone of API X70 steel,” Sādhanā 46, 88, 2021. [100] M. P. Singh, K. S. Arora, N. Shajan, S. R. Pandu, M. Shome, R. Kumar, and D. Shukla, “Comparative analysis of continuous cooling transformation behaviour in CGHAZ of API X-80 and X65 line pipe steels,” J. Therm. Anal. Calorim.,137, pp. 1155–1167, 2019. [101] G. Huang, X. L. Wan, and K. M. Wu, “Effect of Cr content on microstructure and impact toughness in the simulated coarse-grained heat-affected zone of high-strength low-alloy steels,” Steel Res. Int., 87, pp. 1426-1434, 2016. [102] X. Wu, P. Xiao, S. Wu, C. Yan, X. Ma, Z. Liu, W. Chen, L. Zhu, and Q. Zhang, “Effect of molybdenum on the impact toughness of heat-affected zone in high-strength low-alloy steel,” Materials (Basel), 14, 6, 2021. [103] W. A. Johnson and R. F. Mehl, “Reaction kinetics in processes of nucleation and growth,” Trans. Am. Inst. Min., Metall. Pet. Eng., 135, pp. 416-458, 1939. 88 [104] M. Avrami. “Kinetics of phase change. I General theory,” J. Chem. Phys., 7, 12, pp. 1103–1112, 1939. [105] A. N. Kolmogorov, “On the statistical theory of metal crystallization (1937) in Selected Works of A. N. Kolmogorov, Volume II: Probability Theory and Mathematical Statistics, A. N. Shiryayev, Ed., Translated from Russian by G. Lindquist, Dordrecht: Springer Science + Business Media, pp. 188-192, 1992. [106] S. Serajzadeh, “Prediction of temperature distribution and phase transformation on the run-out table in the process of hot strip rolling,” Appl. Math. Modell., 27, 11, pp. 861-875, 2003. [107] S. J. Jones and H. K. D. H. Bhadeshia, “Kinetics of the simultaneous decomposition of austenite into several transformation products,” Acta Mater., 45, pp. 2911-2920, 1997. [108] S. H. M. Azghandi, V. G. Ahmadabadi, I. Raoofian, F. Fazeli, M. Zare, A. Zabett, and H. Reihani, “Investigation on decomposition behavior of austenite under continuous cooling in a vanadium microalloyed steel (30MSV6),” Mater. Des., 88, pp. 751–758, 2015. [109] M. Militzer, R. Pandi and E. B. Hawbolt: ‘Ferrite nucleation and growth during continuous cooling’, Metall. Mater. Trans. A, 27, pp. 1547–1556, 1996. [110] M. Militzer, F. Fazeli and H. Azizi-Alizamini, “Modelling of microstructure evolution in advanced high strength steels,” La Metall. Ital., 4, pp. 35-41, 2011. [111] M. Militzer, M. Maalekian, T. Garcin and W. J. Poole, “Microstructure evolution model for the HAZ of girth welds in X80 linepipe steel,” In Proceedings of the International Seminar on Welding of High Strength Pipeline Steels, CBMM and TMS, pp. 261-279, 2013. [112] M. Militzer, “Computer simulation of microstructure evolution in low carbon sheet steels,” ISIJ Int., 47, 1, pp. 1-15, 2007. [113] H. Monshat and S. Serajzadeh, “Simulation of austenite decomposition in continuous cooling conditions: a cellular automata-finite element modelling,” Ironmak &. Steelmak., 46, 6, pp. 513-521, 2017. [114] M. Tong, D. Li, and Y. Li, “Modeling the austenite-ferrite diffusive transformation during continuous cooling on a mesoscale using Monte Carlo method," Acta Mater., 52, 5, pp. 1155-1162, 2004. [115] M. Militzer, “Phase field modeling of microstructure evolution in steels,” Current Opinion in Solid State and Materials Science, 15, 3, pp. 106-115, 2011. 89 [116] M. Toloui, “Microstructural evolution in The HAZ of X80: Phase field modeling,” PhD dissertation, The University of British Columbia, Vancouver, Canada, 2015. [117] L. -Q. Chen, “Phase-field models for microstructure evolution,” Annu. Rev. Mater. Res., 32, pp. 113-140, 2002. [118] N. Moelans, P. Wollants, and B. Blanpain, “An introduction to phase-field modeling of microstructure evolution,” CALPHAD (Computer Coupling of Phase Diagrams and Thermochemistry), 32, pp. 268-294, 2008. [119] R. G. Thiessen, I. M. Richardson, and J. Sietsma, “Physically based modelling of phase transformations during welding of low-carbon steel,” Mat. Sci. Eng. A, 427, 1-2, pp. 223-231, 2006. [120] M. Toloui and M. Militzer, “Phase field simulation of austenite grain growth in the HAZ of microalloyed linepipe steel,” Int. J. Mater. Res., 101, pp. 542–548, 2010. [121] M. Toloui and M. Militzer, “Phase field modelling of microstructure evolution in the HAZ of X80 line pipe steel,” In Proceedings of the 2012 9th International Pipeline Conference Volume 3: Materials and Joining, Calgary, Alberta, Canada, Sept. 24-28, 2012, pp. 323-328. [122] A. Artemev, Y. Jin, and A. G. Khachaturyan, “Three-dimensional phase field model of proper martensitic transformation,” Acta Mater., 49, pp. 1165-1177, 2001. [123] N. Isasti, D. Jorge-Badiola, M. L. Taheri, and P. Uranga, “Phase transformation study in Nb-Mo microalloyed steels using dilatometry and EBSD quantification,” Metall. Mater. Trans. A, vol. 44, pp. 3552– 3563, 2013. [124] N. Romualdi, Unpublished Work, 2022. [125] L. Zhao, T. A. Kop, V. Rolin, J. Sietsma, A. Mertens, P. J. Jacques, and S. van der Zwaag, “Quantitative dilatometric analysis of intercritical annealing in a low-silicon TRIP steel,” J. Mater. Sci., 37, pp. 1585–1591, 2002. [126] ASTM A1033-18, Standard Practice for Qualitative Measurement and Reporting of Hypo-eutectoid Carbon and Low-alloy Steel Phase Transformation, ASTM International, 2018. [127] ASTM E384-17, Standard Test Method for Microindentation Hardness of Materials, ASTM International, 2017. [128] H. K. D. H. Bhadeshia, “A rationalisation of shear transactions in steels,” Acta Metall., 29, pp. 1117-1130, 1981. 90 [129] S. Roy, N. Romualdi, K. Yamada, W. Poole, M. Militzer, and L. Collins, “The relationship between microstructure and hardness in the heat-affected zone of line pipe steels, JOM, 74, pp. 2395-2401, 2022. [130] K. K. Lottey, “Austenite decomposition of a HSLA-Nb/Ti Steel and an Al-Trip steel during continuous cooling,” MASc. thesis, The University of British Columbia, Vancouver, Canada, 2004. [131] S. Yamamoto, H. Yokoyama, K. Yamada, and M. Niikura, “Effects of the austenite grain size and deformation in the unrecrystallized austenite region on bainite transformation behaviour and microstructure,” ISIJ International, 35, 8, pp. 1020-1026, 1995.
Thesis/Dissertation
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Materials Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Militzer, Matthias
Continuous cooling transformation from coarse-grained austenite in X80 line pipe steels
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