Applied Science, Faculty of
Materials Engineering, Department of
DSpace
UBCV
Swan, Joshua
Master of Applied Science - MASc
University of British Columbia
The oil and natural gas industry, as well as newly developing technologies such as carbon sequestration and hydrogen transport rely on pipelines for transportation of their products. As the demand for safety and efficiency of pipelines increase, the properties of the line pipe steel from which they are made must improve. To do this, line pipe steel is manufactured using a thermomechanically controlled process (TMCP) which combines specific alloying elements with processing conditions to produce an engineered microstructure. Within the TMCP, the austenite grain size and structure are important factors in determining the final microstructure and thus mechanical properties. The purpose of this work is to investigate the austenite grain growth evolution during the thermal treatment in the reheat furnace and compare austenite grain growth characteristics in as-cast slab and hot-rolled material. Two different line pipe steels with varying amounts of manganese and niobium were studied. Thermal conditions were simulated with a Gleeble 3500 thermomechanical simulator while the austenite grain size was measured in-situ with a laser ultrasonics for metallurgy (LUMet) system. The reheat furnace treatment was simulated with a slow heating rate of 5°C/min to 1200°C followed by a 2hr hold. Grain growth comparison experiments consisted of a high heating rate of 50°C/s to one of three holding temperatures of 1100°C, 1200°C and 1300°C. Results of the LUMet measurements were validated by reconstructions of prior-austenite microstructures using electron backscatter diffraction (EBSD) data. LUMet measurements and reconstructions of austenite grain structures for the as-cast slab material undergoing the reheat furnace simulation show a bimodal grain size distribution with a few extremely large grains and many small grains clustered together. A similar but less extreme version of this microstructure was found in slab material undergoing grain growth comparison experiments. This bimodal microstructure was not observed in the hot rolled material. Current hypothesis is that solute segregation of Niobium and Titanium into the inter-dendritic zones is occurring during solidification. These alloying elements promote the formation of (Ti,Nb)(C,N) precipitates that inhibit grain growth and when concentrated into specific areas, allow for a bimodal microstructure to occur.
Austenite Grain Growth Studies in Line Pipe Steels by Joshua Swan B.A.Sc., The University of British Columbia, 2021 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) July 2024 © Joshua Swan, 2024 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Austenite Grain Growth Studies in Line Pipe Steels submitted by Joshua Swan in partial fulfilment of the requirements for the degree of Master of Applied Science in Materials Engineering Examining Committee: Matthias Militzer, Professor, Department of Materials Engineering, UBC Supervisor Warren J. Poole, Professor, Department of Materials Engineering, UBC Co-supervisor Edouard Asselin, Professor, Department of Materials Engineering, UBC Supervisory Committee Member Sergey Kravchenko, Associate Professor, Department of Materials Engineering, UBC Supervisory Committee Member iii Abstract The oil and natural gas industry, as well as newly developing technologies such as carbon sequestration and hydrogen transport rely on pipelines for transportation of their products. As the demand for safety and efficiency of pipelines increase, the properties of the line pipe steel from which they are made must improve. To do this, line pipe steel is manufactured using a thermomechanically controlled process (TMCP) which combines specific alloying elements with processing conditions to produce an engineered microstructure. Within the TMCP, the austenite grain size and structure are important factors in determining the final microstructure and thus mechanical properties. The purpose of this work is to investigate the austenite grain growth evolution during the thermal treatment in the reheat furnace and compare austenite grain growth characteristics in as-cast slab and hot-rolled material. Two different line pipe steels with varying amounts of manganese and niobium were studied. Thermal conditions were simulated with a Gleeble 3500 thermomechanical simulator while the austenite grain size was measured in-situ with a laser ultrasonics for metallurgy (LUMet) system. The reheat furnace treatment was simulated with a slow heating rate of 5°C/min to 1200°C followed by a 2hr hold. Grain growth comparison experiments consisted of a high heating rate of 50°C/s to one of three holding temperatures of 1100°C, 1200°C and 1300°C. Results of the LUMet measurements were validated by reconstructions of prior-austenite microstructures using electron backscatter diffraction (EBSD) data. LUMet measurements and reconstructions of austenite grain structures for the as-cast slab material undergoing the reheat furnace simulation show a bimodal grain size distribution with a few extremely large grains and many small grains clustered together. A similar but less extreme iv version of this microstructure was found in slab material undergoing grain growth comparison experiments. This bimodal microstructure was not observed in the hot rolled material. Current hypothesis is that solute segregation of Niobium and Titanium into the inter-dendritic zones is occurring during solidification. These alloying elements promote the formation of (Ti,Nb)(C,N) precipitates that inhibit grain growth and when concentrated into specific areas, allow for a bimodal microstructure to occur. v Lay Summary Pipelines are the safest and most efficient method of transporting oil, natural gas and new products such as carbon dioxide and hydrogen. To meet increasing specifications, line pipe steel properties are improved through controlled chemistry changes and altering processing parameters during manufacturing. The properties of steels (as well as non-ferrous alloys) depend on their microcrystalline structure. During high temperature treatment in a reheat furnace of a rolling mill, coarsening of this structure occurs by what is described as grain growth. The purpose of this study is to investigate the grain structure evolution with laboratory heat treatments to represent relevant stages of the manufacturing process. A state-of-the-art laser ultrasonic system is used to in-situ monitor the grain size evolution. The knowledge gained from this study will aid in developing manufacturing schedules that produce line pipe steels with optimized properties. vi Preface The research presented in this thesis was carried out by the author, Joshua Swan, under the supervision of Prof. Matthias Militzer and Prof. Warren J. Poole. This research was conducted as part of a larger project between the Microstructure Group in the Department of Materials Engineering at The University of British Columbia, the Steel Research Center at McMaster University and EVRAZ North America Inc. The materials used in this study were provided by EVRAZ North America Inc. The material was cast and hot rolled at their facility in Regina, Sk. Experimental samples were prepared by the machine shop staff of the Materials Engineering Department at UBC. The grain growth tests were designed and conducted by the author with the assistance of Sabyasachi Roy. The analysis of grain growth tests was conducted entirely by the author with code developed by Nicolas Romualdi. EBSD scans were collected with the assistance of Sabyasachi Roy and Minyu Tseng. Reconstructions of the prior austenite grains were performed by Ruth Birch and Minyu Tseng in collaboration with the author. Microprobe analysis was performed with the assistance of Anette von der Handt. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ..................................................................................................................................x List of Figures ............................................................................................................................... xi List of Symbols .............................................................................................................................xv List of Abbreviations ............................................................................................................... xviii Acknowledgements ......................................................................................................................xx Dedication ................................................................................................................................... xxi Chapter 1: Introduction ................................................................................................................1 Chapter 2: Literature Review .......................................................................................................3 2.1.1 Line Pipe Steels........................................................................................................... 3 2.1.2 Thermomechanical Controlled Process ...................................................................... 4 2.1.3 Line Pipe Steel Chemistries ........................................................................................ 7 2.1.4 Austenite Decomposition Products ........................................................................... 11 2.2 Pipeline Fabrication and Construction .......................................................................... 15 2.3 Austenite Grain Growth ................................................................................................ 17 2.3.1 Theory of Grain Growth ........................................................................................... 17 2.3.2 Effect of Temperature on Grain Growth ................................................................... 22 2.3.3 Solute Drag ............................................................................................................... 23 2.3.4 Particle Pinning ......................................................................................................... 24 viii 2.3.5 Solute Segregation During Casting ........................................................................... 26 2.3.6 Austenite Grain Growth in Line Pipe Steels ............................................................. 28 2.3.7 Modelling Austenite Grain Growth .......................................................................... 31 2.4 Austenite Grain Size Measurements ............................................................................. 32 Chapter 3: Scope and Objectives................................................................................................37 Chapter 4: Materials and Experimental Methodology ............................................................38 4.1 Materials ....................................................................................................................... 38 4.2 Thermal Cycles ............................................................................................................. 42 4.2.1 Reheat Furnace Simulations ..................................................................................... 44 4.2.2 Austenite Grain Growth Comparison ....................................................................... 45 4.3 In-Situ Microstructural Characterization ...................................................................... 46 4.3.1 LUMet Measurement ................................................................................................ 46 4.3.2 LUMet Analysis ........................................................................................................ 48 4.4 Ex-Situ Microstructural Characterization ..................................................................... 52 4.4.1 Sample Preparation ................................................................................................... 52 4.4.2 Optical Microscopy Imaging .................................................................................... 53 4.4.3 Electron Backscatter Diffraction (EBSD) Imaging .................................................. 53 4.4.4 Prior Austenite Grain Reconstruction ....................................................................... 54 4.5 Microprobe Measurement ............................................................................................. 57 Chapter 5: Experimental Results and Discussion .....................................................................58 5.1 Characterization of As-Received Materials .................................................................. 58 5.1.1 As-Received Microstructure ..................................................................................... 58 5.1.2 Microprobe Measurements ....................................................................................... 60 ix 5.2 Austenite Grain Evolution in Hot-Rolled Material ....................................................... 63 5.2.1 LUMet Results .......................................................................................................... 63 5.2.2 EBSD Reconstruction Validation ............................................................................. 69 5.3 Austenite Grain Evolution in As-Cast Slab Material .................................................... 74 5.3.1 Comparison to Hot-Rolled Material ......................................................................... 74 5.3.1.1 LUMet Results .................................................................................................. 74 5.3.1.2 EBSD Reconstruction ....................................................................................... 77 5.3.2 Reheat Furnace Simulation ....................................................................................... 80 5.3.2.1 LUMet Results .................................................................................................. 80 5.3.2.2 EBSD Reconstruction ....................................................................................... 82 5.4 Discussion ..................................................................................................................... 88 Chapter 6: Conclusion and Future Work ..................................................................................92 6.1 Summary ....................................................................................................................... 92 6.2 Future Work .................................................................................................................. 93 Bibliography .................................................................................................................................95 x List of Tables Table 4.1 Chemical Composition of investigated steels in wt%. ................................................. 38 Table 5.1 I-05C1.2Mn09Nb microprobe analysis. ....................................................................... 62 Table 5.2 I-05C1.3Mn06Nb microprobe analysis. ....................................................................... 63 Table 5.3 Comparison of final grain size and standard deviation between I-05C1.2Mn09Nb and I-05C1.3Mn06Nb at different temperatures. ................................................................................ 69 Table 5.4 Comparison of EQAD, AWGD and LUMet grain size after 1100°C and 1300°C heat treatments on I-05C1.3Mn06Nb hot rolled material.................................................................. 72 xi List of Figures Figure 2.1 Schematic CCT diagram for a line pipe steel showing decomposition products of austenite. Cooling rate increases from I to IV [64] ....................................................................... 14 Figure 2.2 Average grain size increases due to elimination of five-sided grain. + indicate grains with greater than 6 sides, - indicate less than 6 [76] ..................................................................... 19 Figure 2.3 Six-sided grains are in equilibrium at 120°. Five sided grains curve away from the center to approach equilibrium angle. Seven-sided grains curve towards the center to approach equilibrium angle [76]................................................................................................................... 19 Figure 2.4 Drawing of a space filling tetrakaidekahedron [80] .................................................... 20 Figure 2.5 Grain boundary motion occurs to the left as atoms (C and A) move from grain 1 to grain 2 [76] .................................................................................................................................... 21 Figure 2.6 Solidification modes that can occur in directionally solidified alloys like steel [108] 27 Figure 4.1 Diagram of LUMet strip sample. ................................................................................. 39 Figure 4.2 Sampling plan for LUMet strip samples from as-cast slab material. .......................... 40 Figure 4.3 Sampling plan for LUMet strip samples from hot-rolled material. ............................. 41 Figure 4.4 Sampling plan for metallographic samples in the as-cast slab material. ..................... 42 Figure 4.5 Set up of the Gleeble machine for a LUMet grain growth experiment. ...................... 43 Figure 4.6 Thermal and quenching paths for reheat furnace simulations. .................................... 44 Figure 4.7 Thermal and quenching paths for austenite grain growth experiment. ....................... 45 Figure 4.8 Diagram of LUMet lasers interacting with strip sample. ............................................ 47 Figure 4.9 Reference waveform used during this research. .......................................................... 49 Figure 4.10 (a) Plot showing the acceptable frequency range for analysis. (b) Plot showing the determination of inflection points. ................................................................................................ 51 xii Figure 4.11 Progressive maps of a PAG reconstruction. (a) scanned EBSD data, (b) sorted initial grains, (c) PAG based on initial grains, (d) final PAG map after clustering. ............................... 56 Figure 5.1 Images of I-05C1.2Mn09Nb (a) as-cast slab microstructure at 100X magnification (b) hot-rolled microstructures at 200X magnification. ................................................................. 59 Figure 5.2 Images of I-05C1.3Mn06Nb (a) as-cast slab microstructure at 100X magnification (b) hot-rolled microstructures at 200X magnification. ................................................................. 59 Figure 5.3 Microprobe line scan on I-05C1.2Mn09Nb showing moving average Mn wt%. ....... 61 Figure 5.4 Microprobe line scan on I-05C1.3Mn06Nb showing moving average Mn wt%. ....... 61 Figure 5.5 Grain size evolution between three holding temperatures for “top” sampling location on I-05C1.2Mn09Nb material. ...................................................................................................... 64 Figure 5.6 Grain size evolution of 1300°C test on different locations for I-05C1.3Mn06Nb material. ........................................................................................................................................ 65 Figure 5.7 Grain size evolution of 1200°C test on different locations for I-05C1.3Mn06Nb material. ........................................................................................................................................ 65 Figure 5.8 Grain size evolution of 1100°C test on different locations for I-05C1.3Mn06Nb material. ........................................................................................................................................ 66 Figure 5.9 Comparison of I-05C1.2Mn09Nb and I-05C1.3Mn06Nb at 1100°C. ......................... 67 Figure 5.10 Comparison of I-05C1.2Mn09Nb and I-05C1.3Mn06Nb at 1200°C. ....................... 67 Figure 5.11 Comparison of I-05C1.2Mn09Nb and I-05C1.3Mn06Nb at 1300°C. ....................... 68 Figure 5.12 PAG reconstructions of I-05C1.3Mn06Nb hot-rolled material after (a) 1100°C and (b) 1300°C heat treatments. .......................................................................................................... 70 Figure 5.13 Grain size distributions obtained from the PAG reconstructions of hot-rolled I-05C1.3Mn06Nb that underwent the (a) 1100°C and (b) 1300°C heat treatments. ....................... 71 xiii Figure 5.14 Pole figures of three randomly chosen grains of the PAG reconstruction for I-0fC1.3Mn06Nb hot rolled material after 1300°C heat treatment. ................................................ 73 Figure 5.15 Grain size evolution of 1100°C experiment on I-05C1.2Mn09Nb as-cast slab material. ........................................................................................................................................ 75 Figure 5.16 Grain size evolution of 1300°C experiment on I-05C1.2Mn09Nb as-cast slab material. ........................................................................................................................................ 76 Figure 5.17 Attenuation curve fits of I-05C1.2Mn09Nb (a) hot-rolled material at 1100°C and (b) as-cast slab material at 1300°C. .................................................................................................... 77 Figure 5.18 PAG reconstructions of I-05C1.2Mn09Nb as-cast slab material after (a) 1100°C and (b) 1300°C heat treatments. .......................................................................................................... 78 Figure 5.19 Grain size distributions obtained from the PAG reconstructions of as-cast slab I-05C1.2Mn09Nb that underwent the (a) 1100°C and (b) 1300°C heat treatments. ....................... 79 Figure 5.20 Grain size evolution of reheat furnace simulation on I-05C1.2Mn09Nb as-cast slab material. ........................................................................................................................................ 80 Figure 5.21 Grain size evolution of reheat furnace simulation on I-05C1.3Mn06Nb as-cast slab material. ........................................................................................................................................ 81 Figure 5.22 PAG reconstructions of I-05C1.2Mn09Nb as-cast slab material at quenched out temperatures of (a) 950°C, (b) 1200°C 0 hours and (c) 1200°C 2 hours in the reheat simulation........................................................................................................................................................ 83 Figure 5.23 PAG reconstructions of I-05C1.3Mn06Nb as-cast slab material at quenched out temperatures of (a) 950°C, (b) 1200°C 0 hours and (c) 1200°C 2 hours in the reheat simulation........................................................................................................................................................ 85 xiv Figure 5.24 PAG reconstructions on the same sample of I-05C1.3Mn06Nb as-cast slab material quenched out at 1200°C 0 hours. In relation to the RD (a) is the left side, (b) middle and (c) right........................................................................................................................................................ 86 Figure 5.25 Austenite grain reconstructions highlighting regions of linear small grains in I-05C1.2Mn09Nb quenched at 1200°C 0 hours (a) I-05C1.3Mn06Nb quenched at 1200°C 0 hours (b) and I-05C1.3Mn06Nb quenched at 950°C (c) ........................................................................ 89 Figure 5.26 Schematic showing the elimination of low concentration areas due to the reduction in thickness.................................................................................................................................... 90 xv List of Symbols A Mean grain area Ae3 Austenite equilibrium temperature Ag Area of a given grain Atotal Area of sampling location [A]eq Equilibrium concentration of solute [A]int Interface concentration of solute [A]ppt Precipitate concentration of solute Ai(f) Current waveform amplitude Ao(f) Reference waveform amplitude a1 Grain size independent attenuation fitting parameter a2 Grain size dependent attenuation fitting parameter Dbulk Diffusivity D Austenite grain size Do Initial austenite grain size Dlim Limiting grain size DEQAD Equivalent area diameter of calculated austenite grains E Growth rate f Frequency fp Volume fraction of second phase particles ΔGZ Zener pressure ΔGGG Driving pressure for grain growth h Dimensionless constant used to calculate precipitate dissolution rates xvi J Kinetic constant used to calculate austenite grain growth k Boltzmann constant L Equilibrium distribution coefficient Leff Effective distribution coefficient M Mobility of grain boundary Mo Pre-exponential factor for mobility m Grain growth exponent P Pinning parameter Q Activation energy R Gas constant rp Radius of second phase particles ro Initial radius of second phase particles T Absolute temperature Tnr Non-recrystallization temperature t Time Vat Atomic volume WT Wall thickness xvii Greek Alphabet Symbols αus( f ) Frequency dependent attenuation component β Dimensionless constant used to calculate Zener pressure γGB Grain boundary energy γPB Interfacial energy between precipitate and matrix γGBA Austenite grain boundary energy δ Distance from interface η1 Best fit parameter 1 for attenuation response η2 Best fit parameter 2 for attenuation response η3 Best fit parameter 3 for attenuation response θ Geometric factor λ Fitting exponential for relative wavelength xviii List of Abbreviations ACC Accelerated Cooling AGG Abnormal Grain Growth API American Petroleum Institute AWGD Area Weighted Grain Diameter BCC Body Centered Cubic BCT Body Centered Tetragonal BSE Back-Scatter Electron CD Casting Direction CGHAZ Coarse Grain Heat Affected Zone EBSD Electron Backscatter Diffraction EDS Energy-Dispersive Spectroscopy 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 ICCGHAZ Intercritically reheated Coarse Grain Heat Affected Zone ICHAZ Intercritical Heat Affected Zone LAGB Low Angle Grain Boundary LUMet Laser Ultrasonics for Metallurgy xix MA Martensite/austenite MCL Markov Clustering ND Normal Direction NGG Normal Grain Growth NSERC Natural Sciences and Engineering Research Council PAGB Prior Austenite Grain Boundary RD Rolling Direction SAW Submerged Arc Welding SCCGHAZ Subcritically reheated Coarse Grain Heat Affected Zone SCGHAZ Supercritically reheated Coarse Grain Heat Affected Zone SCHAZ Subcritical Heat Affected Zone SEM Scanning Electron Microscope TD Transverse Direction TMCP Thermomechanical Controlled Process UCGHAZ Unaltered Coarse Grain Heat Affected Zone xx Acknowledgements There are many people that I would like to acknowledge and thank for their help as I pursued my goal of attaining a Master of Applied Science degree from the University of British Columbia. I would like to first and foremost thank my fiancé, Makayla Nelson, for supporting me through this journey and always being my inspiration. I would also like to sincerely thank my friends and family for their encouragement and assistance, I would not have been able to do this without all of you. I am very grateful to my supervisors, Professor Matthias Militzer and Professor Warren J. Poole, for their guidance and invaluable input during and outside our group meetings. The environment you both fostered in the microstructure group is truly something special that allowed me to learn to my full potential. I would like to say a special thank you to all my colleagues and officemates, Matthew, Smit, Nicolas, Minghui, Mariana, Ashish and Minyu for the welcoming atmosphere where I felt I could always ask for assistance or just have a discussion. I am especially grateful to Sabyasachi Roy and his patience while showing me how to operate all the testing equipment and guiding me through the different procedures. I would also like to thank the machine shop crew of David Torok, Bernhard Nimmervoll and Liam MacLellan for completing my sometimes outlandish requests for samples. Furthermore, I would like to thank Anette von der Handt for her assistance with completing mt microprobe analysis. Lasty, I would like to thank Evraz Inc North America, TC Energy and the Natural Sciences and Engineering Research Council of Canada (NSERC) for their financial support, without which, none of this research would have been possible. xxi Dedication Dedicated to my wife Makayla 1 Chapter 1: Introduction The oil and gas industry is one of the major contributors to the world’s economy and energy system with the global revenues of the industry reaching $4.3 trillion US dollars in 2023 and expecting continued growth in the future [1]. Canada follows a similar trend, where in 2023, oil and gas extraction companies reported a revenue of $188 billion Canadian dollars, with total production projected to reach an all-time high in 2024 [2]. Due to crude oil and natural gas commonly being found in remote locations, there is a need for efficient and safe transportation methods from the extraction point to storage and processing facilities. High strength steel pipelines are the safest and most economical method of achieving this need. In addition to the established oil and gas markets, in recent years, the oil and gas industry has shown interest in the use of pipelines for CO2 sequestration in an effort to reduce atmospheric CO2 to meet climate goals [3]. Furthermore, there has been interest in converting portions of the existing pipeline infrastructure for the transportation of hydrogen as an energy source [4]. One of the main goals of the oil and gas industry is to increase production throughput without risking pipeline failure or building additional transportation routes. The most efficient method of achieving this is by increasing the diameter of the pipeline. When the diameter is enlarged the thickness of the pipe wall must also increase to accommodate the increase in pressure. In addition to the increase in wall thickness, the pipeline must be designed to withstand harsh environmental conditions such as in the Canadian arctic and be constructed to stringent regulations for safety and preventing failure [5]. These requirements have cumulated into a need for an increase in wall thickness without a loss in strength, improved fracture toughness and better weldability. This demand has spurred new developments and technologies within line pipe steels. 2 Controlling the mechanical properties of line pipe steels are accomplished in two different ways. The first is through employing specific alloying elements such as niobium and titanium to increase the strength of the steel by altering the microstructure or forming strengthening precipitates [6]. The other method is to introduce a thermomechanically controlled process (TMCP) and accelerated cooling (ACC) strategy [7]. TMCP and ACC are major contributors to the microstructure of the final steel product, which is the main determinant of the mechanical properties. Control of the microstructure is of unique importance to line pipe steels with large wall thicknesses due to microstructure gradients that occur throughout the thickness. These gradients can lead to early failure and reduced strength; therefore, they must be minimized. The production of line pipe steel consists of several stages, of which the TMCP and ACC are crucial. The stages appear in the following order: continuous casting of slab, reheating of the slab, rough and finish rolling, run-out table cooling and finally coiling may be used. During these stages, the microstructure is tailored through austenite grain growth during heating, conditioning of austenite during rolling, and the transformation from austenite to ferrite during accelerated cooling [8]. In the current study, the austenite grain evolution under different conditions and in different steels will be investigated. In particular, as-cast slab material will be exposed to thermal conditions that represent the reheating stage and the austenite grain evolution of the as-cast slab material will be compared to the hot-rolled material under varying thermal conditions. This research is part of a collaborative project between the University of British Columbia, McMaster University, TC Energy and EVRAZ Inc with the purpose of developing physically based models to represent line pipe steel production. 3 Chapter 2: Literature Review 2.1.1 Line Pipe Steels Line pipe steels are classified according to the American Petroleum Institute (API) standard. This standard identifies line pipe steels based upon their yield strength. An example of the nomenclature used for classification is API X70. The number next to the X represents the minimum required yield strength of 70 ksi (kilo-pounds per square inch) for this steel grade. It is not uncommon for the yield strength to be shown in mega-pascals (MPa) instead of ksi, the nomenclature has the same structure, with the 70 being replaced by 485. The first line pipe steel specification used was for X42 in 1948 [9]. Since this first grade was introduced, there has been progressive development through various means to reach grades as high as X120 [9]. These improvements have been possible due to the gradual discovery and introduction of new techniques within microalloying and the TMCP. The first improvement in strength arose from the introduction of microalloying with vanadium, circa 1953 [10]. These vanadium microalloyed steels were classified as X52. Soon after the development of X52 line pipe steels, the benefits of austenite processing through TMCP became widely known [10]. This led to the development of X60 grade steel in the mid to late 1960’s. These early steel grades were limited in their strength due to their microstructure being dominated by polygonal ferrite and pearlite [11]. Between 1970 and 1980, the development of X70 and X80 steel grades progressed as a result of microstructure control and additional microalloying. The primary changes in microalloying were the addition of niobium and reduction in carbon content [10]. The improvements in TMCP lie mostly in controlled deformation during rolling and accelerated cooling [12]. These advancements in steel production strategies led to X70 steels having a grain refined non-polygonal irregular ferritic or bainitic microstructure [13]. 4 Further advancements led to X80 steels having a microstructure consisting of fine-grained irregular ferrite or bainite with randomly distributed martensite/austenite (MA) islands [14]. The development of X100 and X120 line pipe steels began in the early 1980’s and 1990’s respectively. A combination of grain refinement, solid solution hardening, precipitation hardening, increased dislocation density and a hard second phase were required to produce X100 and X120 steel grades [10]. X100 and X120 grade steels have not seen widespread adoption due to increased susceptibility of hydrogen embrittlement. These strengthening mechanisms are possible due to further advancements in microalloying and TMCP. It is also important to note that as yield strength improved over time, other important properties such as toughness and weldability also improved. The main contributor to an increase in toughness was the removal of Sulphur from the steel [15]. Weldability was improved as a result of the reduction in carbon content within the steel [16]. 2.1.2 Thermomechanical Controlled Process The mechanical properties of high-grade line pipe steel of X70 and above are achieved through the precise use of alloying elements and a thermomechanically controlled process. The TMCP is the combination of controlled temperature and plastic deformation pathways that result in tailored microstructures. These tailored microstructures consist of specific fine grained austenite decomposition products with further strengthening arising from precipitation hardening [17]. By adjusting the temperature and deformation pathways the resultant microstructure is changed to meet mechanical property requirements. This is particularly important to producers of line pipe steel as the most cost-effective solution can be achieved. By achieving the same mechanical properties through TMCP, the amount of costly alloying elements can be reduced [18], [19]. The 5 steel manufacturing process consists of multiple stages, each of which can be changed to alter the microstructure in known ways. The stages are as follows: 1. Continuous Casting: Continuous casting is the first stage of the process, where the liquid steel is solidified into. The liquid steel is poured into a tundish which controls the flow rate of the steel into a mould through a submerged entry nozzle. Solidification begins at the interface between the liquid metal and mould, creating a solidified shell around a liquid core [20]. The thickness of the shell increases until a fully solidified slab is obtained that can later be used as the starting material in a hot mill to be subjected to the TMCP process. Solidification control is important to the quality of the steel as defects can arise that propagate throughout the TMCP. In particular, the flow pattern of liquid steel into the mould and segregation of alloying elements during solidification need to be considered [21], [22]. 2. Slab Reheating: In preparation for deformation at later stages the slab material produced by continuous casting is conditioned in a reheat furnace. The purpose of conditioning is to control the initial austenite grain size as well as the amount and distribution of alloying elements in solid solution [23]. The reheat furnace reaches temperatures around 1200°C for line pipe steels and holds the slab at this temperature for varying lengths of time, usually over an hour. These temperatures and holding times allow for large austenite grains to grow while also facilitating the dissolution of niobium rich precipitates, such as NbC and Nb(C, N) and allowing for diffusion of hydrogen out of the slab [7], [17]. Controlling the distribution and amount of alloying elements is important for later processing steps as they influence grain growth, recrystallization austenite decomposition and precipitations [24]. 6 3. Roughing Mills: Roughing mills are the first of two stages of rolling where major plastic deformation occurs. Roughing is done at temperatures high enough to allow for dynamic and/or static recrystallization of austenite to occur [25]. This prevents work hardening of the material, while allowing for significant thickness reductions to occur [26]. Recrystallization is crucial as it contributes to the refinement of the austenite grains present [27]. 4. Finishing Mills: Finishing mills are the second stage of rolling where specific austenite grain conditioning occurs as well as plastic deformation to reach the final thickness of the steel. The temperature during finishing is higher than the austenite equilibrium temperature (𝑨𝒆𝟑) but is, at least for the final passes, lower than the non-recrystallization temperature (𝑻𝒏𝒓). Therefore, the microstructure remains completely austenitic, but recrystallization does not occur in the final rolling stands, this is the main difference between finishing and roughing. The plastic deformation applied during this stage increases the stored energy of the microstructure by increasing dislocation density and “pancaking” the austenite grains [28]. Neither of these effects are reversed due to recrystallization not occurring. The deformed austenite grains are elongated and adopt a “pancake” shape, this results in an increase in nucleation sites for decomposition products [29], [30]. Recrystallization in austenite can be slowed in particular through the addition of niobium. Niobium interacts with the austenite grain boundaries to reduce their migration rates through solute drag and/or particle pinning [31]. 5. Accelerated Cooling: Once the steel has completed the final rolling pass, the steel is rapidly cooled at controlled rates to develop the desired microstructure. Accelerated cooling promotes the development of a fine grained ferritic-bainitic microstructure over 7 the coarser ferritic-pearlitic microstructure found in non-accelerated cooled steels [32]. Accelerated cooling is commonly achieved in a run-out table equipped with water jets on both the top and bottom. As the steel plate travels through the run-out table, a controlled flow rate of water is sprayed onto the steel surface resulting in controlled cooling rates of the steel plate [33]. Different cooling rates result in changes of microstructure with a higher cooling rate predominantly leading to a finer microstructure with less polygonal ferrite and more irregular ferrite and bainite [34]. 6. Coiling: The coiling step is only relevant for coiled steel products as the final microstructure is achieved post accelerated cooling. The purpose of coiling is to promote the formation of a fine microstructure and precipitates that further contribute to yield strength [35]. The desired precipitates that form during coiling in line pipe steels are titanium and niobium carbo-nitrides [36]. 2.1.3 Line Pipe Steel Chemistries The mechanical properties of line pipe steel such as strength and toughness can be improved by advancements in processing, as shown in thermomechanically controlled processing or by the addition of alloying elements. Alloying elements in union with TMCP can increase strength through grain refinement, precipitation strengthening and solid solution strengthening [37]. In addition to increasing strength and toughness, alloying elements can improve weldability, which is of special importance for line pipe steels. Iron is the main component in line pipe steels. Pure iron, at room temperature exists in a stable form called ferrite, or α-iron and has a Body Centered Cubic (BCC) crystal structure. Upon heating, iron experiences a phase transformation from BCC ferrite to Face Centered Cubic (FCC) 8 austenite, or γ-iron, at 912°C [38]. Austenite remains as the main phase up to 1394°C, where the FCC austenite reverts back to a BCC phase called δ-ferrite, which eventually melts at 1538°C [38]. The addition of carbon to the iron system is what allows for alternative transformation products such as bainite, martensite, pearlite and cementite to form. Carbon is present within the iron matrix in solid solution or as precipitates. When existing in solid solution, carbon occupies the octahedral interstitial sites, providing notable interstitial solid solution strengthening [39]. Carbon may co-precipitate with other alloying elements to form brittle carbide precipitates which decrease toughness [40]. These competing effects force producers of line pipe steel to identify the optimal carbon content to satisfy both strength and toughness. The carbon content in line pipe steels has decreased over time due to a push towards improved weldability and low temperature fracture toughness [37]. The transformation from austenite to its daughter products such as ferrite, pearlite, bainite and martensite is crucial to the final microstructure. Controlling which of these transformation products form and in which mixtures is essential for steel producers to obtain the required mechanical properties. The presence of certain alloying elements can greatly influence the resulting transformations through both thermodynamic and kinetic means [41]. Alloying elements such as carbon, manganese, nitrogen, nickel, copper and others that reduce the austenite to ferrite transformation temperature are referred to as austenite stabilizers. In opposition to these elements, ferrite stabilizers exist which increase the austenite to ferrite transformation temperature. Examples of ferrite stabilizers in line pipe steels are niobium, molybdenum, vanadium and silicon. Both austenite and ferrite stabilizing elements influence the transformation temperature through kinetic aspects that are primarily related to the mobility of interfaces [42]. 9 Niobium is an important alloying element added to line pipe steels for the purpose of slowing recrystallization of austenite during the thermomechanical process. In essence, niobium widens the operational window for optimal austenite processing [28]. The mechanism by which niobium slows recrystallization is the reduction of grain boundary migration rates due to solute drag and Zener pinning [43]. Reduced recrystallization retains the “pancaking” of austenite grains, which in turn provides additional ferrite nucleation sites. These pancaked grains with additional nucleation sites promote the formation of a fine ferritic microstructure upon cooling [44]. Niobium is also known to form precipitates such as NbC and Nb(C,N) in ferrite, providing additional precipitation strengthening [45]. Titanium is an alloying element added to line pipe steels that forms a very stable titanium nitride precipitate. This precipitate is stable up to extremely high temperatures including the melting point of steel. As this precipitate is stable at high temperatures it is primarily used to influence the austenite phase. It does this by limiting austenite grain growth through pinning austenite grain boundaries [46]. This mechanism is primarily related to controlling the austenite grain size in the weld heat affected zone (HAZ), therefore, improving the weldability. To obtain the most effective grain refinement, an appropriate ratio of titanium and nitrogen must be used. This is done to prevent the formation of large TiN precipitates, approximately 500nm, as these larger precipitates are less effective at pinning the grain boundaries and can act as crack initiation sites [47]. The ratio of titanium to nitrogen should be kept at the stoichiometric ratio of 3.42 or lower for optimal results [48], [49]. Vanadium is added to line pipe steels to further increase the strength due to precipitation strengthening. Vanadium forms almost no precipitates in the austenite region but does form precipitates during and after the austenite to ferrite transformation. Vanadium primarily forms 10 V(C,N) precipitates in the ferrite phase which increase strength [50]. Carbonitride precipitates can form without the addition of vanadium, however, it was found that the addition of vanadium improves the strengthening qualities of the carbonitrides [51]. The addition of vanadium resulted in a larger volume density, a more uniform distribution and a smaller average size of precipitates [51]. Molybdenum is added to line pipe steels to suppress the austenite to ferrite transformation temperature. This causes the addition of molybdenum to promote the formation of an irregular ferritic or bainitic microstructure while also preventing pearlite formation [52]. Molybdenum in solute delays the ferrite transformation by reducing carbon diffusivity and exerting a solute drag force on grain boundaries and the BCC-FCC interfaces [52]. The addition of molybdenum also promotes finer Nb(C,N) precipitate to form, further increasing strength [53]. Manganese is an alloying element added to line pipe steels that has a dual purpose of increasing strength and removing impurities. Manganese is an austenite stabilizer and provides solid solution strengthening [54]. Manganese also has the purpose of forming manganese sulphide precipitates, thereby preventing the formation of iron sulphide inclusions [54]. Iron sulphide inclusions are detrimental to line pipe steels as they can cause hot shortness and decrease toughness [55]. Manganese sulphide precipitates have been shown to be hydrogen trapping sites, decreasing the susceptibility of the steel to hydrogen cracking [56]. Manganese concentrations cannot be increased too much for their benefits as higher concentrations leads to an increase of banding in the microstructure as a result of segregation during solidification. 11 2.1.4 Austenite Decomposition Products During cooling the austenite phase can transform into a multitude of daughter products that are the primary determinants of the final microstructure’s mechanical properties. The common daughter products of austenite in line pipe steels are polygonal ferrite, irregular ferrite, pearlite, bainite and martensite. The deciding factors for which transformation product exists are the cooling rate, alloying elements, prior austenite grain size and the state of stress in the grains [57]. Ferrite is formed when austenite is cooled at a relatively slow cooling rate. There are two primary forms of ferrite, polygonal and irregular ferrite [57]. Polygonal ferrite forms at slower cooling rates than irregular ferrite. Ferrite nucleates at the austenite grain corners and boundaries. Polygonal ferrite grows as equiaxed grains with very little misorientation within the grain crystal structure [58]. Irregular ferrite grows in a non-equiaxed manner with a high dislocation density found within the crystal structure. The formation of irregular ferrite is also influenced by anisotropy in elastic and interfacial energy, and the morphological instability of the austenite-ferrite interface due to partitioning of the carbon atoms at the interfaces [58]. In addition to the increased dislocation density, martensite/austenite constituents can be found in irregular ferrite and their origins are attributed to carbon rich triple junctions where the ferrite interfaces converge [59]. The increase in dislocation density and martensite/austenite constituents lead to irregular ferrite having increased strength and toughness when compared to polygonal ferrite. The formation and growth of ferrite is agreed to be a diffusion-controlled process [60]. The solubility of carbon in ferrite is less than in austenite resulting in long range diffusion of carbon atoms from newly formed ferrite into the austenite. It is thought that the diffusion of carbon atoms and the transfer of substitutional atoms across the austenite-ferrite interface control the growth rate of ferrite [60]. 12 Pearlite can be formed as a secondary product during the transformation from austenite to ferrite. As austenite transforms into ferrite, the carbon concentration in the remaining austenite increases as carbon atoms are rejected from ferrite [8]. As carbon concentration increases, the austenite eventually reaches the eutectoid composition and pearlite is able form. The resulting pearlite consists of an alternating lamella of ferrite and cementite. Pearlite formation is also a diffusion-controlled process, therefore, as temperature decreases, the driving force for austenite increases but diffusivity of carbon decreases [8]. This results in a pearlite with finer lamella. Coarser pearlite lamella can be caused by an increase in the interfacial energy due to larger lamella reducing the interfacial surface area [61]. As the cooling rate increases and transformation temperature from austenite to ferrite decreases, a unique form of ferrite called bainite can be formed. Bainite consists of a lath or plate like morphology containing aggregates of carbides and ferrite [62]. The morphology of bainite is very complex with a high dislocation density and many grain boundaries resulting in increased strength and toughness [63]. The formation mechanism of bainite has been under debate with two main theories of diffusive and displacive prevailing. The diffusive theory proposes that bainite transformation is controlled by short-range diffusion of carbon atoms at the transformation interface and simultaneous carbide formation [64]. The displacive theory proposes that bainite formation occurs through a shear transformation [64]. This mechanism implies that the carbon atoms move in an organized way rather than randomly through diffusion. This results in the bainitic ferrite laths growing by successive nucleation of subunits at either the austenite grain boundary or tips of the initial ferrite lath [65]. Independent of which formation mechanism is agreed upon, bainite is commonly classified into two sub-categories, upper and lower bainite. Upper bainite forms at higher temperatures and 13 contains a larger proportion of low angle grain boundaries. Lower bainite forms at lower temperatures and contains a larger proportion of high angle grain boundaries [66]. The proportion of high to low angle grain boundaries and Bain groups are used as the classification criteria. Bain groups are derived from the specific orientation relationships between bainitic transformation products and the parent austenite. Depending on which Bain groups form and in which pattern, it can be determined if upper or lower bainite is present. Due to the larger amount of high angle grain boundaries, lower bainite is seen to have improved mechanical properties such as strength and toughness when compared to upper bainite [66]. Martensite is the final transformation product commonly found in line pipe steels and is produced at the highest cooling rates and lowest transformation temperatures. Martensite is a carbon supersaturated solid solution form of ferrite [67]. Due to the very high amount of carbon atoms, the normally BCC crystal lattice is distorted to a Body Centered Tetragonal (BCT) crystal lattice to accommodate the carbon atoms [67]. The distortion of the crystal lattice results in increased strength and toughness of the steel. It is agreed that the mechanism that controls martensite formation is displacive [68].[69] 14 In summary, the daughter product of austenite upon cooling is heavily controlled by the cooling rate and transformation temperature. Other factors such as alloying elements, prior austenite grain size and stress-state also contribute. As the cooling rate increases and transformation temperature decreases, a transition from polygonal ferrite with pearlite to irregular ferrite with pearlite to bainite to martensite can be observed. This is accompanied by a simultaneous increase in strength and a switch from diffusion to displacive controlled transformations. Figure 2.1 Schematic CCT diagram for a line pipe steel showing decomposition products of austenite. Cooling rate increases from I to IV [64] 15 2.2 Pipeline Fabrication and Construction Once production of line pipe steel in plate or coiled form is completed, the pipe is then manufactured. The process begins with forming the plate or coil into a tubular shape by consecutive mechanical deformation steps. Once the steel has been formed into the final geometry, the seams are welded to produce the finished pipe. Welding is typically done in a longitudinal or spiral method with longitudinal welding performed by electric resistance welding (ERW), or submerged arc welding (SAW) and spiral welding performed mainly by submerged arc welding [70]. In ERW, a current is passed between the two edges of the line pipe steel, heat is generated due to the material’s resistance to the flow of current. The edges of the steel are heated until an external force closes the gap and combines the edges into one seamless bond [71]. The weld temperature and frequency of the current are closely monitored to ensure the final weld quality. Low welding temperatures can lead to an insufficient metallic bond, and high temperatures may result in the formation and trapping of oxides known as penetrators [72]. Initially, low frequency alternating current was used, however, this led to hook cracks, inadequate bonding and susceptibility to seam corrosion. Currently, modern ERW employs high frequency induction or contact welding to produce higher quality welds [73]. The resulting microstructure is often unsuitable for in-service uses and a subsequent heat treatment is necessary. ERW is advantageous as it does not require a filler material for the weld but is limited to the size of the pipe, typically a maximum outer diameter is 26 inches [71]. For larger diameters, production with submerged arc welding is preferred. In the SAW process an electric arc is struck between a filler metal and the base metal, in this case the pipe. The arc melts both the filler and the base metal, joining the two metals into one 16 seam [74]. This process results in a large amount of heat input and is highly susceptible to inclusions from oxides. To prevent this, a solid flux is placed around the filler material and is also melted during the process. As the flux material melts, a shielding layer is produced that aids in isolating the weld area from contaminants [75]. The properties of the resultant weld can be controlled by the choice of which filler metal to use, but heavily depend on the quality of the weld [75]. The SAW process is advantageous as it has a high deposition rate and therefore high production rate, but the weld quality may suffer [74]. Once the pipes are formed and tested for quality, they are transported to the construction site. Construction of a pipeline in the field is carried out by joining individual sections of pipe end to end with circumferential welds known as girth welds. In modern construction practices the infield joining of pipes is performed by gas metal arc welding (GMAW) [76]. GMAW is very similar to SAW in that an arc is struck between a filler material and base material. The difference arises in the use of flux as a shielding agent. In GMAW, the filler metal and flux are joined together as one electrode, as the electrode melts the filler material is deposited and the flux creates a shielding gas to protect the weld pool [77]. To decrease the cost of construction, new methods such as tandem wire, laser-hybrid and dual torch GMAW have been developed [76]. Dual torch GMAW is the most widely adopted and is a method using two torches, one moving behind the first at a fixed distance, to increase the deposition rate of the weld [76]. The welding process during both production and construction results in a change of microstructure at and near the weld area. This changed microstructure is known as the heat affected zone. Different regions within the HAZ experience different peak temperatures and cooling rates resulting in regions with different microstructures [78]. In single pass welds, four subregions of the HAZ can be identified. Moving from the exact weld area towards the surrounding base metal, 17 the sub-regions are coarse grain heat affected zone (CGHAZ), fine grain heat affected zone (FGHAZ), intercritical heat affected zone (ICHAZ) and subcritical heat affected zone (SCHAZ) [79]. In multipass welding procedures the subregions of the HAZ are more complicated as a new pass interacts with the HAZ of the previous pass. These new subregions can also be classified and are divided into the unaltered coarse grain heat affected zone (UCGHAZ), supercritically reheated coarse grain heat affected zone (SCGHAZ), intercritically reheated coarse grain heat affected zone (ICCGHAZ), and subcritically reheated coarse grain heat affected zone (SCCGHAZ) [79]. The HAZ is crucial to understand and control as the changed microstructure has different mechanical properties and may lead to failure. 2.3 Austenite Grain Growth 2.3.1 Theory of Grain Growth In a polycrystalline material, grain boundaries will migrate to reduce the overall free energy of the system. This process called grain growth results in an increase of the average grain size within the material. When considering the TMCP, austenite grain growth is the dominant process in the reheat furnace and between rolling stands after recrystallization is complete [80]. When designing for line pipe steels the austenite grain size is crucial to control as it is a major contributor to the final ferrite grain size and thus the mechanical properties [80]. To achieve the desired austenite grain sizes within the TMCP, the kinetics of grain growth are altered through multiple means such as temperature or alloying elements. The thermodynamic driving pressure for grain growth is a result of the need for space filling and the reduction of grain boundary energy, 𝜸𝑮𝑩 per unit volume. When considering 2D for simplicity, a grain’s structure consists of vertices joined together by the grain boundaries. To 18 maintain the minimum energy in the system, there must be three grain boundaries constructing a vertex with an equilibrium angle between the grain boundaries of 120° [81]. This means that for an equilibrium 2D grain structure where all the grain boundaries have equivalent 𝜸𝑮𝑩, all grains will consist of six grain boundaries. A perfect equilibrium is almost impossible to achieve in a polycrystalline material, there will be many grains with more or less than six sides. Grain growth occurs due to the drive of eliminating grains with more or less than six sides and replacing them with an equilibrium structure [81]. When looking at a five-sided grain, its internal angles at the vertices are 108° when all its sides are of equal length. The edges of the grain will therefore curve away from the center to achieve an internal angle closer to 120°. In a seven-sided grain the internal angles at the vertices are 128.57°, therefore the edges will curve towards the center of the grain to achieve an internal angle closer to 120° [81]. Once the grain boundaries have become curved, grain boundary motion will occur. The direction of grain boundary motion is towards their center of curvature; therefore, the five-sided grain will shrink, and the seven-sided grains will grow [82]. In addition to the regular shrinking and growing of grains, when a grain is shrinking the grain boundaries may migrate in a way to reduce the total number of boundaries on that grain. This is done as the elimination of a grain boundary may cause a grain with a higher number of grain boundaries than six to now have a number closer to equilibrium [82]. The end result of both modes is an increase in the average grain size, or rather, grain growth. 19 In 3D, the angles at the vertex are 109.5° to achieve equilibrium between the grain boundaries. No regular polyhedron with planar faces possesses an internal angle of exactly 109.5°. The closest approximation is a Kelvin tetrakaidekahedron composed of six four-sided faces and eight six-sided faces [83]. This grain shape is space filling and attains an internal angle of 109.5° at the vertices when curvatures are forced upon the hexagonal faces, thus achieving the requirements for an equilibrium structure [84]. The existence of a curved grain boundary as a prerequisite for this grain shape to exist suggests that grain growth will always occur in 3D. [85] Figure 2.3 Six-sided grains are in equilibrium at 120°. Five sided grains curve away from the center to approach equilibrium angle. Seven-sided grains curve towards the center to approach equilibrium angle [76] Figure 2.2 Average grain size increases due to elimination of five-sided grain. + indicate grains with greater than 6 sides, - indicate less than 6 [76] 20 Grain growth is fundamentally the result of the motion of grain boundaries. Grain boundary motion is caused by the difference in free energy on either side of the boundary as a result of the curvature present. Atoms on the higher energy side of the boundary will detach from the lattice and jump across the boundary to join the lattice on the lower energy side [81]. The jumping of an atom across the boundary results in a local change of the grain boundary position, when multiplied over many atoms, grain boundary motion occurs. The jumping of atoms from higher to lower energy positions determines the direction of the grain boundary motion as the higher energy side will always be towards the center of curvature [81]. Figure 2.4 Drawing of a space filling tetrakaidekahedron [80] 21 Two types of grain growth modes can be identified and may be present in austenite grain growth during the TMCP. They are denominated as normal grain growth (NGG) and abnormal grain growth (AGG). NGG is defined as the uniform increase of average grain size adhering to a log-normal distribution as a result of grain boundary motion. Conversely, AGG is defined as the increase of average grain size characterized by the presence of a bimodal grain size distribution as the result of rapid growth of a small number of large grains [86], [87]. NGG is the expected grain growth mode based upon the assumptions that the only forces that act on the grain boundaries are due to curvature, the radius of curvature is proportional to the diameter of the grain, grain boundary Figure 2.5 Grain boundary motion occurs to the left as atoms (C and A) move from grain 1 to grain 2 [76] 22 mobility is independent of diameter and 𝜸𝑮𝑩 is equal for all grain boundaries [88], [89]. AGG occurs when these assumptions are no longer valid for every grain within the structure. These assumptions begin to break down due to inhomogeneities within the polycrystalline material caused by alloying elements or defects [90]. Both NGG and AGG adhere to the same thermodynamic principles for grain growth, their differences are a result of grain growth kinetics and inhomogeneous distribution of alloying elements. Factors that affect grain growth kinetics include temperature, solute drag and particle pinning [91]. 2.3.2 Effect of Temperature on Grain Growth Temperature influences grain growth kinetics by impacting temperature dependent parameters in grain boundary mobility, alloying element solubility and second phase particles. As grain boundary mobility is a diffusion-controlled process, by increasing the temperature, the rate of grain boundary movement increases [92]. Higher temperatures also increase the diffusion of soluble alloying elements within the matrix. These solute elements will either migrate towards or away from the grain boundary which affects the boundary’s mobility in a process called solute drag [93]. The third way temperature can alter kinetics is through the coarsening and dissolution of second phase particles. Second phase particles act as obstacles for grain boundary movement in a process called particle pinning. As temperature increases the growth of these particles also increases until they reach a critical size where they are not as effective in pinning moving boundaries. If the temperatures become high enough the particles will begin to dissolve leading to the complete loss of particle pinning [94]. Within the TMCP for line pipe steels, temperature gradients occur throughout the sample thickness, these lead to grain size gradients and finally a 23 resultant gradient of mechanical properties. Ignoring the property gradients may lead to unexpected structural failure or early pipe failure [95]. 2.3.3 Solute Drag Solute drag is a phenomenon where grain boundary motion is impeded due to the presence of a concentration gradient of solute atoms at grain boundaries. The concentration gradient is driven by the difference in the free energy of the system between a solute atom within the grain boundary and within the bulk material [96]. This concentration gradient is termed solute segregation. When a grain boundary undergoes movement, there is a loss of symmetry in the concentration profile ahead and behind the grain boundary [97]. This loss of symmetry results in an increase of free energy within the system, which opposes grain boundary motion, thus slowing grain growth [98], [99]. As a concentration gradient is the determining factor in solute drag it is important to note that the magnitude of the effect is independent of whether the boundary is enriched or depleted of solute atoms [99]. Only a difference in the concentration of solute atoms between the grain boundary and matrix is needed. The magnitude of the solute drag effect is also a function of the velocity of the grain boundary motion. As the grain boundary velocity is slow with a small driving force, the solute atoms are capable of diffusing at a similar rate and therefore keep up with the boundary. Maintaining the solute drag effect at a low magnitude. As the velocity continues to increase with higher driving pressures, the solute atoms become a larger burden on the boundary and the magnitude of the effect increases [100]. This trend changes once a critical driving pressure and velocity is reached, at this moment, the grain boundary migrates at rate high enough to leave the diffusing solute atoms behind and effectively break away from the solutes thereby eliminating 24 the solute drag effect [100]. Once the grain boundary breaks away from the solute effect there is a distinct increase in the grain boundary velocity as it is no longer impeded. This results in two distinct regimes of grain boundary velocity. Since the ability of a grain boundary to break away depends on the diffusion rates of solute atoms, it was found that fast diffusing elements had a larger impact on high velocity grain boundary motion while the opposite is true for low velocity motion [99]. 2.3.4 Particle Pinning Alloying elements present within the steel can form precipitates; these second-phase particles can obstruct grain boundary movement through a mechanism called particle pinning. Particle pinning occurs when the pressure exerted on the grain boundary by the precipitates, termed Zener pressure, ∆𝑮𝒁, competes against the driving force for grain growth ∆𝑮𝑮𝑮 [101]. Zener pressure resists grain boundary movement as the grain boundary area is reduced when a grain boundary intersects a particle [85]. The Zener pressure can be expressed with the equation [102]. ∆𝑮𝒁 =𝜷𝜸𝑮𝑩𝒇𝒑𝒓𝒑 where 𝒇𝒑 is the total volume fraction of second-phase particles, 𝒓𝒑 is the average particle radius and 𝜷 is a dimensionless constant that depends on characteristics such as particle distribution, morphology and grain geometry [103]. Particle pinning is important for grain size control and therefore mechanical properties as particle pinning can lead to an effective maximum grain size, termed the limiting grain size. A limiting grain size occurs when the Zener pressure is larger than or equal to the driving pressure for grain growth [101]. (2.1) 25 Given that the Zener pressure is a function of both the volume fraction and average radius of precipitates, precipitate coarsening greatly reduces the Zener pressure. Coarsening is a process driven by the reduction of total interfacial energy where atoms of smaller precipitates are consumed by larger precipitates [104]. Coarsening of precipitates is a diffusion-controlled process that can be expressed with the equation [105]. 𝒓𝒑𝟑 − 𝒓𝟎𝟑 =𝟖[𝑨]𝒆𝒒𝜸𝑷𝑩𝑽𝒂𝒕𝑫𝒃𝒖𝒍𝒌𝟐𝟕(𝟏 − [𝑨]𝒆𝒒)𝒌𝑻 where 𝒓𝟎 is the initial precipitate radius, [𝑨]𝒆𝒒 is the equilibrium concentration of the precipitate element, 𝜸𝑷𝑩 is the interfacial energy between the precipitate and grain, 𝑽𝒂𝒕 is the atomic volume, 𝑫𝒃𝒖𝒍𝒌 is the bulk diffusivity of the particle’s rate limiting species, 𝒌 is the Boltzmann constant and 𝑻 is the absolute temperature. Similar to how coarsening reduces the Zener pressure, particle dissolution results in the elimination of Zener pressure. At sufficiently high temperatures, the precipitates dissolve into the bulk matrix and therefore cannot pin the grain boundaries [106]. For spherical particles uniformly distributed in a finite matrix, the rate of dissolution can be described with the equation [107]. 𝒅𝒓𝒑𝒅𝒕=−𝒉𝑫𝒃𝒖𝒍𝒌𝒓𝒑− 𝒉√𝑫𝒃𝒖𝒍𝒌𝝅𝒕⁄ where 𝒉 is a dimensionless variable indicating the constituent concentration gradient near the precipitate/grain interface, calculated with [107]. 𝒉 =[𝑨]𝒊𝒏𝒕 − [𝑨]𝒆𝒒[𝑨]𝒑𝒑𝒕 − [𝑨]𝒊𝒏𝒕 where [𝑨]𝒊𝒏𝒕 is the solute concentration at the interface of the precipitate and matrix, and [𝑨]𝒑𝒑𝒕 is the solute concentration in the precipitate. (2.2) (2.3) (2.4) 26 In line pipe steels, titanium nitrides (TiN) and niobium carbides (NbC) form precipitates that are very stable at high temperatures and therefore have long been used to pin austenite grains during rolling procedures [48]. Titanium nitrides are of special interest as they coarsen extremely slowly once a critical size has been reached and they do not dissolve into the steel matrix at the temperatures seen during processing [108], [109]. Niobium carbides usually dissolve into the steel matrix during the reheating process, however, niobium carbides can co-precipitate with titanium nitrides to create complex precipitates that survive at elevated temperatures [110]. Due to this titanium and potentially niobium precipitates contribute to pinning austenite grain growth during the TMCP. 2.3.5 Solute Segregation During Casting During the solidification process of continuous casting, solutes can be redistributed between the solid and liquid phases leading to inhomogeneous concentrations. The solubility of solutes is generally lower in the solid phase than the liquid phase at temperatures during casting. Therefore, the solid phase will reject solute atoms into the liquid phase at the solid-liquid interface. This leads to a gradual buildup of solutes at the interface which moves during solidification. The end result is that the final regions of the material to solidify have a much higher concentration of solute than the bulk of the material [111]. 27 During the solidification process multiple solidification modes can be present such as equiaxed dendritic, equiaxed non-dendritic, columnar dendritic, cellular and plane front [112]. This is important for segregation as the different modes of solidification have different solid-liquid interface patterns and thus the distribution of solute atoms is affected. The modes of solidification help determine whether microsegregation or macrosegregation are present. Microsegregation occurs at a much smaller scale, commonly within the inter-dendritic spaces. Macrosegregation occurs the entire length of the material and is most commonly associated with centerline segregation during steel production [111]. Figure 2.6 Solidification modes that can occur in directionally solidified alloys like steel [108] 28 As segregation during continuous casting has a large impact upon the distribution of alloying elements it therefore has a large impact on the solute drag effect and particle pinning of austenite grain growth. Certain austenite grains may exist in a region with very little solute elements or particles leading to fast grain growth, while other grains exist in regions with such high concentration of solute elements, they barely grow, which in turn leads to abnormal grain growth [100]. Another consequence of segregation in alloying elements is the “banding” of the resultant steel microstructure. Banding occurs when alternating layers of different microstructures are present, this causes anisotropy and therefore, a reduction in strength of the line pipe steel [113]. While all alloying elements are subject to segregation, the severity of segregation varies. The tendency for a specific alloying element to segregate can be quantified by a parameter called the effective distribution coefficient, 𝑳𝒆𝒇𝒇. The most extensively used equation for 𝑳𝒆𝒇𝒇 is as follows. 𝑳𝒆𝒇𝒇 =𝑳𝟏 − 𝑳𝒆𝑬𝜹𝑫𝒃𝒖𝒍𝒌⁄ where 𝑳 is the equilibrium distribution coefficient, 𝑬 is the growth rate and 𝜹 is the distance from the interface [114]. In line pipe steels, elements such as Manganese and Nitrogen are known to have large equilibrium distribution coefficients and therefore heavily segregate during solidification [115]. 2.3.6 Austenite Grain Growth in Line Pipe Steels Austenite grain growth for line pipe steels is of primary importance in three areas; the reheat furnace to obtain an initial austenite grain size before rolling, austenite grain growth after recrystallization during rolling and austenite grain growth during welding in the HAZ. Extensive (2.5) 29 research has been conducted over the years to investigate what parameters effect austenite grain growth rates, abnormal vs normal growth and the limiting grain size. The parameters consistently investigated are the heating rate, peak temperature, residence time at or near the peak temperature and chemistry. Banerjee et al. [96] conducted experiments on a microalloyed X80 line pipe steel with 0.06 wt% carbon, 1.65 wt% manganese and 0.034wt% niobium to investigate the effects of heating rate and peak temperature on the austenite grain size. This study was motivated by austenite grain growth in the HAZ explaining the different heating rates. Using heating rates of 10°C/s, 100°C/s, 1000°C/s and peak temperatures of 950°C, 1150°C, 1350°C, they found that increasing the peak temperature and decreasing the heating rate leads to larger grain sizes. They determined that peak temperature has a more dominant role than heating rate to the point that for heating rates larger than 100°C/s, the austenite grain size is a function of peak temperature and independent of heating rate. They conclude that this is primarily due to the dissolution of Nb-rich precipitates. A higher peak temperature allows for more Nb-rich precipitates to dissolve resulting in larger grain size. In conjunction with this, a lower heating rate allows for more time for complete dissolution of Nb-rich precipitates when compared to a higher heating rate that may not provide sufficient time for complete dissolution. Hossain Seikh et al. [116] investigated the reheating process on two steels of X65 with 0.08 wt% carbon, 1.5 wt% manganese and 0.12 wt% Nb and X70 with 0.05 wt% carbon, 1.5 wt% manganese and 0.09 wt% Nb which were supplied as hot rolled plate. They specifically looked into holding temperatures of 1150°C, 1200°C, 1250°C and holding times from 10 to 60 minutes. They found that with increasing temperature and time the austenite grain size increased as expected. The final grain size at 60 minutes for holding temperature of 1200°C and 1250°C were 30 approximately 95μm and approximately 80μm for a holding temperature of 1150°C after 60 minutes. The gap in grain size between the temperatures was theorized to be a result of the Nb-rich precipitates dissolving at or above 1200°C but not completely at 1150°C. These results are in agreement with the work of Banerjee et al [96] even though the heating rates and holding times were very different. Duan et al. [117] researched the impact of holding temperature and time related to the reheating process of a X80 line pipe steel with 0.032 wt% carbon, 1.82 wt% manganese and 0.10 wt% niobium. Holding temperatures from 1100°C to 1250°C and holding times up to 5 hours were investigated on samples from the center of a cast slab. As expected, they found that an increase in time and temperature resulted in an increase in austenite grain size. In respect to the impact of temperature, they found that abnormal grain growth appears at 1200°C. When the holding temperature was below 1180°C, the grain size was less than 55μm, above 1200°C, they observed a sudden jump in grain size with a final grain size of 120μm at a holding temperature of 1250°C. They attribute the increase in grain size above 1200°C to the dissolution of Nb-rich precipitates which is in agreement with other studies aforementioned. When considering the holding time, they found that the austenite grain size increases rapidly at the beginning of the experiment, but the growth rate begins to slow down after approximately 1 hour. These investigations show the general trends expected for austenite grain growth in line pipe steels. As peak or holding temperatures increase, holding times increase and the heating rates decrease, the resultant grain size will increase. The effect of temperature is expected as grain boundary mobility is a function of temperature. In respect to the effect of chemistry or rather the precipitates present, Nb-rich precipitates slow growth by pinning boundaries up to their dissolution temperature commonly between 1150°C and 1200°C. Once dissolved the Nb-rich precipitates no 31 longer slow growth, resulting in a jump in grain growth rates, however, grain growth rates decrease over time as the average grain size approaches the limiting grain size which is most likely controlled by Ti-rich precipitates. It should be noted that most research conducted on austenite grain growth in line pipe steels is carried out on steel obtained post accelerated cooling or post coiling. Research conducted on as-cast slab material or post reheat material is lacking in the literature. 2.3.7 Modelling Austenite Grain Growth Mean field models are commonly used to describe austenite grain growth due to their relative simplicity. Mean field models are typically empirical or semi-empirical and are comprised of equations with parameters that require fitting to experimental data [118]. The classical parabolic grain growth law as developed by Burke and Turnbull assumes an idealized case where the driving pressure for grain growth arises solely from the curvature of the grain boundary [119]. Using this approach the kinetics of isothermal austenite grain growth can be expressed with the following empirical equation [120]. 𝑫𝒎 − 𝑫𝟎𝒎 = 𝑱𝒕 where 𝑫 is the austenite grain size, 𝑫𝟎 is the initial austenite grain size, 𝑱 is a kinetic constant, 𝒎 is the grain growth exponent and 𝒕 is time. For the idealized case analyzed by Burke and Turnbull, the grain growth exponent is a constant of 𝒎 = 𝟐 [119]. This model can be further expanded upon to represent austenite grain growth rate in a line pipe steel while considering the effect of particle pinning [96]. (2.6) 32 𝒅𝑫𝒅𝒕= 𝑴𝜸𝑮𝑩𝑨 (𝜽𝑫− 𝑷) where 𝒅𝑫 𝒅𝒕⁄ is the austenite grain growth rate, 𝑴 is the austenite grain boundary mobility, 𝜸𝑮𝑩𝑨 is the austenite grain boundary energy, 𝜽 is a geometric factor equal to 4 and 𝑷 is the pinning parameter. The grain boundary mobility is known to follow an Arrhenius type relationship with temperature and can be expressed with [96]. 𝑴 = 𝑴𝟎𝒆(−𝑸 𝑹𝑻⁄ ) where 𝑴𝟎 is the pre-exponential factor, 𝑸 is the activation energy, typically 350 kJ/mol for line pipe steels [121], 𝑹 is the gas constant and 𝑻 is the absolute temperature. The pre-exponential factor 𝑴𝟎 is a fit parameter that accounts for the solute drag effect of alloying elements and must be determined experimentally as it changes with chemistry [121]. The pinning parameter 𝑷 is a variable depending on contributions from both Nb-rich precipitates which dissolve at high temperatures and Ti-rich precipitates that are treated as a constant as they do not dissolve and have a critical size at which they no longer coarsen [108], [121]. 2.4 Austenite Grain Size Measurements Measuring austenite grain size faces the challenge that austenite transforms into multiple possible decomposition products at room temperature. Therefore, the austenite grain size must either be measured at temperatures where the austenite is present or by revealing the prior austenite grain boundaries (PAGB) at room temperature. There are varying techniques employed that each have their own strengths and weaknesses such as reliability, cost and the types of steel it is possible to work on. (2.7) (2.8) 33 Chemical etching is a technique carried out at room temperature that employs an etching agent, commonly aqueous picric acid, that preferentially etches the grain boundaries over the matrix [122]. The difficulty with this technique is that it is only effective on microstructures that contain martensite, tempered martensite or lower bainite [123]. This technique can be aided through the tempering of the steel to promote the segregation of phosphorous to the PAGB which further highlights the PAGB upon etching [123]. The exact composition of the etching agent as well as the time and temperature for etching change depending on the steel, but studies have shown that the addition of a wetting agent and hydrochloric acid are beneficial to the process [123]. This technique is very time consuming as the sample must be prepared beforehand by grinding and polishing the surface adequately enough to not hamper the etching process. Thermal etching is a technique performed in situ that captures the austenite grain boundaries at different moments in time at the actual temperatures. For this technique, the sample must be polished first and then heated to the temperatures of interest in a furnace under vacuum or inert atmosphere. At these temperatures, atoms diffuse and vaporize into the atmosphere at much higher rates from the grain boundaries when compared to the rest of the sample [124], [125]. This preferential depletion of the sample at the grain boundaries causes grooves to appear that can be detected and measured by a microscope [124]. This technique is useful as the grain size evolution throughout time can be measured as multiple images can be taken of the same area. However, there are multiple challenges involved, such as creating a system that can house the microscope within the furnace, focusing the microscope during the experiment and obtaining a large enough area for statistical analysis [124]. Additionally, old thermal grooves may interfere with the formation of new thermal grooves, thus not accurately representing the current austenite grain boundaries. 34 High-temperature laser scanning confocal microscopy (HT-LSCM) is a technique that enables the observation of surfaces and interfaces at elevated temperatures. HT-LSCM employs a low wavelength laser light source to scan the surface of the sample and record topological features [126]. This is used to measure austenite grains as the thermal grooves produced by the thermal etching effect can be recorded. HT-LSCM is an advancement and refinement of the thermal etching technique as it allows for more rapid and higher resolution measurement of thermal grooves. However, it still has some of the same drawbacks of thermal etching where the total area for statistical accuracy may be lacking and the experimental setup is challenging [126]. The oxidation etching technique is similar to thermal etching in that it is an in-situ method and depends on the atmosphere within the furnace. In oxidation etching the sample is polished beforehand and heated up to the temperatures of interest where the sample is then exposed to an oxidizing atmosphere [127]. Under the oxidizing atmosphere the austenite grain boundaries preferentially accumulate oxides or experience decarburization, both of which are observable upon room temperature inspection [127]. To aid in identifying the PAGB at room temperature, the sample may be immersed in molten glass to increase ionic transport which enhances the oxidative contrast created at the PAGB [128]. This technique is advantageous as it is reliable, relatively easy to conduct and multiple areas can be examined, however, it is not suitable for rapid grain growth and cannot show the grain growth evolution through time. A common weakness of the thermal etching, HT-CLSM and oxidation etching methods is that they are surface techniques. The grain growth kinetics on the surface of the sample may not be the exact same as in the interior due to effects such as decarburization and grain growth being affected by surface energy variation as a function of crystallographic orientation. Therefore, these 35 surface techniques, while still being in-situ, may not accurately describe the microstructure in the bulk of the sample. More recently, techniques to create maps of the prior austenite grains using electron backscatter diffraction (EBSD) have been developed. In this technique the decomposition products of austenite are analyzed ex-situ using EBSD to determine their crystallographic orientations. The crystallographic orientations of martensite and bainite share a relationship with the parent austenite phase [129]. The crystallographic orientations can be inputted into software such as PAG_GUI or AZtecCrystal to reconstruct the prior austenite grains, resulting in a map [130]. This technique is useful as the austenite grain analysis is independent of the experimental procedure and multiple areas of the sample may be analyzed. This technique is limited in that the reconstruction of the austenite grains is sensitive to the settings used for reconstructions Laser Ultrasonics for Metallurgy (LUMet) is an expansion of ultrasound technology that generates and detects ultrasound waves within a sample, which enables non-contact in-situ evaluation of austenite grain size evolution. As an ultrasound wave travels through a material, its amplitude decays and this attenuation can be correlated to grain size [131]. The attenuation is caused by absorption, diffraction and scattering. Absorption is the conversion of sound energy to other forms of energy [132]. Diffraction is the spreading of an ultrasound wave throughout a sample depending on its geometry [133]. Scattering is the change in the wave direction due to internal inhomogeneities such as voids, inclusions and grains [134]. Absorption and diffraction can be accounted for through standards and if a sample is without voids and inclusions, then the scattering contribution can be isolated to the grain size. The resulting attenuation of the measured waveform can be used to directly measure the grain size. LUMet is very advantageous as it is able to record hundreds of measurements within a single test, thus showing the entire grain growth 36 evolution of the bulk sample. LUMet is also very useful as a flexible technique as it has been successful in measuring not only austenite grain size evolution in steels but other kinetic phenomena such as grain growth in INCONEL superalloys, recrystallization, and phase transformations in titanium [135], [136], [137]. Once prior austenite grain boundaries have been revealed through various methods, the grain size can be determined. There are multiple techniques for obtaining the grain size such as linear intercept, grain count per unit area correlation and image analysis [138], [139]. The grain size obtained through these techniques is commonly expressed as an equivalent area diameter (EQAD) of the mean grain area 𝑨 through the equation [136], [140]. 𝑬𝑸𝑨𝑫 = √𝟒𝑨 𝝅⁄ There is an alternative to this equation that better incorporates the relative area of each grain to the bulk when determining grain size. This method called area weighted grain diameter (AWGD) is calculated with the following equation [141]. 𝑨𝑾𝑮𝑫 = 𝚺𝒊 (√𝟒𝑨𝒈𝝅⁄ ∗𝑨𝒈𝑨𝒕𝒐𝒕𝒂𝒍⁄ ) where 𝑨𝒈 is the area of a given grain and 𝑨𝒕𝒐𝒕𝒂𝒍 is the area of the entire sampling location. This method is better suited to describe wide grain distributions where a few large grains occupy the majority of the sampling area, as is seen in abnormal grain growth [141], [142]. (2.9) (2.10) 37 Chapter 3: Scope and Objectives The objective of this research is to use laboratory simulations to quantify austenite grain growth in selected line pipe steels during industrially relevant thermal cycles in the reheat furnace of a hot rolling mill. Austenite grain size measurements are to be conducted using LUMet analysis in-situ and EBSD reconstructions ex-situ to attain a more complete quantification of the grain growth evolution. The overall goal of the project is divided into the following sub-objectives. 1. Simulate the conditions of an industrial reheat furnace to measure the austenite grain growth evolution on as-cast slab material. 2. Compare austenite grain growth between as-cast slab and hot-rolled material at different temperatures and holding times. 3. Investigate the effect of sampling location on austenite grain growth, i.e., determine if there are differences between the top, middle and bottom of the as-received material. 4. Analyze and compare grain size measurements obtained from LUMet analysis with measurements obtained with EBSD reconstructions. 38 Chapter 4: Materials and Experimental Methodology 4.1 Materials In this research two industrial steels were investigated as provided by EVRAZ Inc North America. The steels were cast and hot rolled at their facility in Regina, Saskatchewan. For each of the steels, both as-cast slab and hot-rolled material were provided. The chemistries of the two steels are shown in Table 4.1. For the steel names, the “I” indicates industrial cast steel, and each number followed by an elemental symbol represents the approximate weight percentage (wt%) of that element. The elements shown in the steel name are considered crucial alloying elements in the context of this research. The materials received were sectioned from the tail end of full sized industrial as-cast slabs and hot-rolled skelp. The final hot-rolled thickness was different for the two steel chemistries. Steel I-05C1.2Mn09Nb had a final thickness of 25 mm and I-05C1.3Mn06Nb had a thickness of 20 mm. For both steels chemistries the as-cast slab material had a provided thickness of approximately 25 cm. Table 4.1 Chemical Composition of investigated steels in wt%. Steel Identification C Mn Nb Ti N Cr Mo Al Si I-05C1.2Mn09Nb 0.053 1.16 0.088 0.017 0.007 0.24 0.226 0.037 0.27 I-05C1.3Mn06Nb 0.055 1.31 0.059 0.015 0.007 0.25 0.234 0.036 0.28 39 LUMet “strip samples” were prepared for the LUMet grain size measurements. The dimensions of the samples are 60mm in length, 10mm in height and 3mm in thickness. Additionally, two holes are drilled near the ends of the sample to allow for attachment to the Gleeble thermomechanical simulator. A drawing of the strip sample is shown in figure 4.1. Figure 4.1 Diagram of LUMet strip sample. To investigate how different positions within the as-cast slab and hot-rolled material affect grain growth, the strip samples were obtained from the “top, middle and bottom” of the as-recieved steels. Top, middle and bottom are referencing the normal direction (ND), i.e. through-thickness as shown in not to scale schematics in figures 4.2 and 4.3. 40 The strip samples were taken at minimum one inch away from the edges parallel to the normal direction and transverse direction (TD) of the as-cast material to minimize edge effects that may be present. The strip samples were machined with the testing face perpendicular to the casting direction (CD). The thickness of the slab in the casting direction allowed for only three samples to be obtained in series. This allowed for a total of 6 samples to be taken out at each of the “top, middle and bottom” locations. For the as-cast slab, top and bottom samples were taken out as close to the exposed edge as allowable and the middle samples were taken out at the geometric middle of the parent material. This resulted in approximately 75mm between the top, middle and bottom locations. Figure 4.2 Sampling plan for LUMet strip samples from as-cast slab material. 41 The strip samples were obtained from the hot-rolled material in a slightly different manner than from the as-cast slab due to the shape of the as-received material. For the hot-rolled material the top, middle and bottom refer to one-quarter, one-half and three-quarters of the through thickness parallel to the normal direction. The testing face of these strip samples had to be rotated to be perpendicular to the normal direction due to geometric constraints. The sampling pattern was repeated in the rolling direction (RD) for a total of fifteen samples from each location. The top, middle and bottom locations were separated by approximately 7mm in I-05C1.2Mn09Nb as its final thickness was 25mm. For I-05C1.3Mn06Nb with a final thickness of 20mm the samples were separated by approximately 4.5mm. For both steels the top and bottom samples were taken out 1mm away from the exposed surfaces. In addition to the LUMet strip samples, different samples from the as-cast slab material from both steel 1 and steel 2 were prepared for optical imaging, SEM imaging and microprobe analysis. This type of sample was termed as “metallographic” samples in this research. The samples were taken out at 5 specific locations with approximately cubic dimensions of 15mm. The sampling locations included the same “top, middle and bottom” as the LUMet samples with the Figure 4.3 Sampling plan for LUMet strip samples from hot-rolled material. 42 4th and 5th locations at ¼ and ¾ of the way through the thickness of the slab in the Normal Direction (ND). This resulted in the samples being approximately 8.5cm apart from each other. Before these samples were extracted, the edges of the slab material were removed so no edge effects would be present in the samples. Figure 4.4 Sampling plan for metallographic samples in the as-cast slab material. 4.2 Thermal Cycles Grain growth experiments were conducted using a Gleeble 3500 thermomechanical simulator equipped with a Laser Ultrasonics for Metallurgy (LUMet) sensor. The Gleeble machine was used to impose controlled thermal cycles on the steel samples. The LUMet system measures austenite grain size of the steel sample in-situ. The QuickSim program was used to write scripts that control the thermal cycle and LUMet acquisition frequency. All tests were performed in the 43 “low force jaw” configuration as high stresses were not imposed on the sample. Thermocouples are welded at the middle of the sample on the surface. The thermocouples are connected to the TC1 sensors for K-type thermocouples and TC3 sensors for S-type thermocouples. Resistive heating is used to supply heat to the sample. The relationship between thermocouple output, heat supply and the QuickSim script control the thermal cycle. All experiments were carried out under a high vacuum between 0.0013 to 0.0004 Pa to minimize oxidation and decarburization of the sample surface. All experiments were quenched at the end of the thermal cycle using pressurized Helium gas. Figure 4.5 Set up of the Gleeble machine for a LUMet grain growth experiment. LUMet strip sample Helium quench nozzle Thermocouple connection LUMet laser window 44 4.2.1 Reheat Furnace Simulations A thermal cycle simulating the reheating furnace conditions was developed to study the austenite grain evolution. The parameters of the thermal cycle were based off the conditions present in the reheating furnace at the EVRAZ steel mill in Regina. The foundational parameters for the reheat furnace consisted of a heating rate between 3°C/min and 7°C/min to a holding temperature of 1200°C for multiple hours. This was simplified for experimentation to a heating rate of 5°C/min up to an isothermal holding temperature of 1200°C for 2 hours. Additionally, the initial heating rate from room temperature until 650°C was increased to 50°C/s as this reduced the total experimental time. 650°C was chosen as the transition temperature for 50°C/s to 5°C/min as no relevant changes to the microstructure would occur below 650°C. At the end of the thermal cycle the sample was He quenched with an approximate cooling rate of 60°C/s. The total time of the thermal cycle was 3 hours and 41 minutes. 02004006008001000120014000 0.5 1 1.5 2 2.5 3 3.5 4Temperature (°C)Time (hours)Reheat Furnace SimulationThermal Path950C Quench1200C 0h Quench1200C 2h QuenchFigure 4.6 Thermal and quenching paths for reheat furnace simulations. 50°C/s to 650°C 300°C/h 650°C to 1200°C 1200°C 2h hold 45 Due to holding the sample at 1200°C for 2 hours the vacuum level had to be increased and S-type thermocouples were required. Prior to beginning the thermal cycle, the chamber was vacuumed to 0.0004 Pa or lower. This process would take approximately 1 hour. S-type thermocouples which consist of one pure platinum wire and one 90% platinum-10% rhodium alloy wire are required as they are more resistant to high temperatures. 4.2.2 Austenite Grain Growth Comparison Three thermal cycles were created to investigate and compare austenite grain growth in the as-cast slab and hot-rolled material. Three isothermal holding temperatures of 1100°C, 1200°C and 1300°C were chosen to be investigated. Due to the different holding temperatures, corresponding different holding times were necessary to allow the austenite grains to reach their limiting size. 1300°C was held for 90s, 1200°C for 10min and 1100°C for 20 min. A heating rate of 50°C/s was used to reach the three different holding temperatures. The length and temperature of these experiments allowed for a lower vacuum of 0.0013 Pa and K-type thermocouples to be employed. Figure 4.7 Thermal and quenching paths for austenite grain growth experiment. 02004006008001000120014000 200 400 600 800 1000 1200Temperature (°C)Time (seconds)Grain Growth Comparison Thermal Paths1100C 20min hold1200C 10min hold1300C 90s holdHeating at 50C/s46 4.3 In-Situ Microstructural Characterization 4.3.1 LUMet Measurement The LUMet system allows for a high volume of measurements taken during the thermal cycle of the experiment. It is a non-destructive and non-contact technique that can be used to determine grain size, recrystallization and phase transformations [136], [141]. The LUMet system operates in accordance with the Gleeble machine and is controlled by the same QuickSim script as the thermal cycle. The LUMet system gathers information with two lasers, a generation laser and a detection laser. The generation laser is fired through a window of the Gleeble main chamber located at the center of the rear access door and impacts the surface of the experimental sample. When the generation laser impacts the sample surface, a small portion of the material expands, generating an ultrasonic pressure wave that travels through the sample thickness. This wave repeatedly travels through the sample as it echoes at each of the sample surfaces. As the wave reaches the surface and echoes, displacement occurs that is measured by the detection laser. The resulting change in reflection of the detection laser is measured by a photo-refractive crystal which produces a signal that travels via a fiber optic cable to an optical interferometry system. This system converts the optical signal into a voltage signal which is then filtered by a third order Butterworth passband filter. The resultant filtered voltage signal is stored and used for further processing [143]. 47 Figure 4.8 Diagram of LUMet lasers interacting with strip sample. The generation laser is a frequency-doubled Q-switched Nd:Yag laser, with a 6 ns, 72 mJ green light pulse of wavelength 532 nm. The frequency of generation laser pulses can be controlled through the QuickSim script with an upper limit of 50 Hz and a lower limit of ½ Hz. The detection laser is a frequency stabilized infrared light, with a 90 us pulse and wavelength 1064 nm. The spot size is 2 mm in diameter, resulting in an interaction volume of 9.3 mm3. During the various thermal cycles, LUMet measurements must be taken over the whole temperature range of interest, however, there is a limitation for the total amount of measurements per test. As the laser pulse impacts the sample, the sample surface is slightly damaged, as the total number of laser impacts increases, the quality of the measurement decreases. It was found that for the conditions used in this research, measurement quality reduced after approximately 300 pulses. Therefore, for each test the total number of measurements was kept to a minimum while still maintaining enough measurements for statistical accuracy. Another constraint is the minimum measurement frequency of ½ Hz. Due to this, the measurements must be taken in batches 48 throughout the test. For the reheat furnace simulation the measurements were divided into 4 batches of approximately 24 laser pulses. These batches occurred when the sample reached 950°C, reached 1200°C, after 1 hour of holding at 1200°C and finally after 2 hours of holding at 1200°C, immediately before quenching. The measurement frequency used within the batched measurements was 1 Hz. Measuring in batches has the added benefit where the first few laser impacts clean the sample surface, increasing the quality of the following measurements. For the three austenite grain growth experimental conditions of 1100°C, 1200°C and 1300°C, different LUMet measurement schedules were used. Due to the short total time of the test at 1300°C, LUMet measurements could be taken continuously. Once reaching 850°C LUMet measurements were taken at a frequency of 20 Hz until 1300°C was reached, where the frequency dropped to 5 Hz until the end of the test. This resulted in an approximate total number of pulses of 360. For the experiments at 1200°C and 1100°C, the same pulse frequency of 20 Hz during heating was used. Once the holding temperature was achieved, the pulses had to be divided into batches. Each batch was taken with a frequency of 10 Hz. For the 1200°C test, there were 5 batches, resulting in a total of approximately 290 pulses. For the 1100°C test, there were 9 batches, resulting in a total of approximately 320 pulses. For both conditions, the batches occurred every 2.5 minutes. 4.3.2 LUMet Analysis In each waveform generated, captured and filtered by the LUMet system specific characteristics are unique. These characteristics include the amplitude, echo spacing and the attenuation. The attenuation is used to calculate the resulting grain size. There are three major contributions to attenuation in a polycrystalline material. The first and primary contribution is the scattering of the ultrasonic pressure wave due to the elastic mismatch between neighbouring grains 49 of differing crystallographic orientations. The second contribution comes from the dispersion of the wavefront as the wave travels throughout the sample geometry. The third contribution arises from internal friction caused by precipitates, inclusions, dislocations and the vibration of magnetic domains. The first two contributions depend heavily on the frequency while the third contribution does not. To analyze the frequency response of the attenuation, the filtered waveform is put through a fast Fourier transform and each component is compared to a reference waveform by. 𝛼𝑈𝑆(𝑓) =202𝑊𝑇𝑙𝑜𝑔10 (𝐴𝑖(𝑓)𝐴𝑜(𝑓)) where 𝛼𝑈𝑆 is the frequency dependent attenuation component, 𝑓 is frequency, 𝑊𝑇 is the sample wall thickness, and 𝐴𝑖(𝑓) and 𝐴𝑜(𝑓) are the amplitude for the current and reference waveform respectively. To determine the grain size, the diffraction contribution from grain mismatch must be removed from the total attenuation response which results in a frequency response that is entirely dependent on grain size. To do this, the total frequency response of the first echo in the filtered waveform is compared to a reference waveform, shown in figure 4.9, of negligible grain size with the same sample geometry. Figure 4.9 Reference waveform used during this research. (4.1) 50 The isolated scattering contribution from the crystallographic mismatch can be fit to an exponential expression. This expression is simplified using logarithms to a linear fit. Then, the frequency dependence of attenuation can be fit to the equation. 𝛼𝑈𝑆(𝑓) = 𝑎1 + 𝑎2𝑓𝜆 with 𝑎1 and 𝑎2 being frequency independent fitting parameters where 𝑎1 is independent as the frequency dependence of internal friction can be neglected and 𝑎2 is independent while being correlated to grain size [144], 𝜆 is an exponential that depends on the relative wavelength to the grain size, this is considered constant and equal to 3 [145]. The analysis of a single waveform can lead to different values of the 𝑎2 parameter and thus grain size depending on the frequency window selected during analysis. To account for this the frequency range used for each analysis is determined beforehand. This is done by assessing the quality of the exponential fit within different frequency ranges. To do this the attenuation response 𝛼𝑈𝑆 in the frequency range of 3 to 61 Hz of a waveform near the end of the experiment is collected. The frequency vs attenuation response is run through an in-house code to determine the inflection point. The location of the inflection point, shown in figure 4.10 (b) determines the valid frequency range, shown in figure 4.10 (a) that can be used for this experiment. The inflection point used for the analysis is the first inflection point to appear, as highlighted in figure 4.10 (b). (4.2) 51 Figure 4.10 (a) Plot showing the acceptable frequency range for analysis. (b) Plot showing the determination of inflection points. The 𝑎2 parameter can then be correlated to the austenite grain size using the following equation. √1000𝑎2 = 𝜂1𝐷𝐸𝑄𝐴𝐷𝜂2 − 𝜂3(𝑇 − 𝑇0) where 𝐷𝐸𝑄𝐴𝐷 is the equivalent area diameter of the mean austenite grain, 𝜂1 is 0.0461, 𝜂2 is 0.6913, and 𝜂3 is − 0.0005. The parameters 𝜂1, 𝜂2 and 𝜂3 are the best fit parameters for the attenuation response in the calibration developed by Levesque et al. [146]. These best fit parameters were determined on a broad chemistry range of steels of which the steels used in this study fall within. For this chemistry range it was determined the best fit parameters were independent of the steel chemistry. (a) (b) (4.3) Inflection Point 52 4.4 Ex-Situ Microstructural Characterization 4.4.1 Sample Preparation Selected LUMet samples were prepared for ex-situ microstructural characterization for the purpose of validating LUMet grain size results. The samples were sectioned perpendicular to the laser impact face along the plane where the laser impact was located. The sample was cut using a Struers Accutom-2 cut off saw. The excess length was also removed to result in a sample of roughly 1.5cm in length. The sample was then ground and polished using a Buehler MetaServ 250 polishing machine. Grinding of the sample was carried out using successively finer silicon carbide paper with grit sizes of 400, 600, 800 and 1200 with continuous water flow for lubrication and cooling. The samples were then polished using a 6μm then 1μm diamond suspension on cloth polishing discs. Lubrication during polishing was provided with propylene glycol “RedLube”. Once polishing was completed the samples were electropolished to remove remaining features caused by mechanical polishing. Electropolishing was carried out by dipping the sample in a solution of 95% acetic acid and 5% perchloric acid while applying a 15V potential difference on the sample for 15 seconds. Between each grinding, polishing and electropolishing step, the samples were carefully rinsed under water, cleaned with ethanol then dried using a high-pressure air nozzle. The metallographic samples were initially mounted in conductive filled phenolic mounting compound for easier handling during imaging and polishing. The exposed face used for analysis was the ND/TD face. Once mounted these samples were ground and polished in an identical manner as the LUMet samples with the exception of the final electropolishing step. Instead of electropolishing, the samples were etched using a 2% Nital solution for 10-15 seconds to better reveal the existing microstructure. The Nital solution was prepared using 2 mL of concentrated nitric acid and 98 mL of ethanol. 53 4.4.2 Optical Microscopy Imaging For optical microscopy imaging, a Nikon EPIPHOT 300 series inverted microscope attached with a digital camera was used to capture optical images. Images were taken at magnifications of 100X and 200X. The manual multi-layer capture feature included in the imaging software, Clemex, was used to take higher focused images. Additionally, the manual stitching feature included in Clemex was used to combine multiple images at the same magnification. These images were taken for a qualitative analysis of the microstructure. 4.4.3 Electron Backscatter Diffraction (EBSD) Imaging EBSD scans were performed on specific LUMet samples that had undergone heat treatments for the purpose of reconstructing the prior austenite grains. A Tescan AmberX equipped with Oxford instruments EBSD detector was used to complete the scans. Diffraction patterns were captured by tilting the sample 70°, using a voltage of 20 kV, a current of 3 nA or 10 nA depending on the set-up and a working distance of 14 mm. The Aztec software was used to create the mapping conditions for the EBSD scans. Map sizes of 2000 μm x 2000 μm with a step size of 1 μm were chosen as the default settings. Phases with BCC (ferrite) and FCC (austenite) crystal structures were selected for indexing. An exposure time of 0.8 ms resulting in a scan rate of 1200-1250 Hz was used. The optimized beam deceleration settings used were 11 band and 60 Hough resolution to obtain patterns which are used to index between the phases. After the EBSD scan was completed, the map used for PAG reconstruction may be cropped to smaller dimensions. This was done as the edges of the scan were commonly less indexed than the center and would thus not produce a reliable reconstruction. 54 4.4.4 Prior Austenite Grain Reconstruction Once EBSD scans were completed the collected data was used to reconstruct the prior austenite grains. This process can be broken down into 5 steps. 1. From the completed EBSD scan data, an orientation map can be produced which contain the crystallographic orientations and crystal structure of each point measured during the scan. An example of the raw EBSD scan data is shown in figure 4.11 (a). 2. Once in MATLAB, the imported data is run through an altered form of the PAG_GUI code for delineating grains. This code compares the orientations of one measured point to the orientations of its neighbours, after which, it groups regions of similar orientations into grains. An example of this is shown in figure 4.11 (b). The two primary settings used to control how the code produces grains are the grain boundary threshold and small grains. All reconstructions used the same settings of 2° for the grain boundary threshold and 20 for the small grains for the ferrite grains. 3. Once the grains have been processed, the orientation relationship between the parent (prior austenite) and daughter (existing microstructure) can be determined. This is done through an iterative process developed by Nyyssonen et al. [147] where the experimental orientation relationship approaches the true orientation relationship. This method requires a starting point for the iterative process, in this case, the Kurdjumov-Sachs orientation relationship for the 24 orientation variants is used. An example of this map is shown in figure 4.11 (c). 4. Using the experimental orientation relationships and grain boundary misorientations obtained in earlier steps, a Markov Clustering (MCL) algorithm is used to process the data. The controlling parameter for this algorithm is the inflation power. All reconstructions used 55 the same inflation power of 1.4. Once clustering is complete the data is processed again using the PAG_GUI code to produce a map of the prior austenite grains. This step also relies on the grain boundary threshold and small grains parameters. All reconstructions used the same grain boundary threshold of 5° and small grains of 50 for the austenite grains. An example of this map is shown in figure 4.11 (d). 5. The final step is used to refine the produced prior austenite grain map. This is done by repeating steps 2-4 on the processed data obtained in step 4. This results in a higher quality map as the original orientation relationships obtained from the EBSD scans are based on a BCC microstructure while the orientation relationships produced from the reconstruction process data are based on an FCC microstructure. 56 Figure 4.11 Progressive maps of a PAG reconstruction. (a) scanned EBSD data, (b) sorted initial grains, (c) PAG based on initial grains, (d) final PAG map after clustering. (a) (b) (c) (d) [1 11] [011] [001] 𝐍𝐃 𝐓𝐃 𝐑𝐃 57 4.5 Microprobe Measurement Microprobe measurements were conducted on the as-cast slab metallography samples for both chemistries using a JEOL JXA-iHP200F field emission electron microprobe. Line scans were performed on the samples with a total line length of 5mm employing a 2μm step size. The conditions for the line scans included an accelerating voltage of 20kV, beam current of 300nA, beam diameter of 1μm and count times of 100ms for each step. The elements of interest included manganese, copper, chromium, molybdenum and silicon. The element concentrations were acquired using analyzing crystals LIFL for manganese and copper, PETJ for chromium, PETL for molybdenum and TAPL for silicon. 58 Chapter 5: Experimental Results and Discussion 5.1 Characterization of As-Received Materials 5.1.1 As-Received Microstructure For the as-cast slab of steel I-05C1.2Mn09Nb shown in figure 5.1 (a), the microstructure is comprised of primarily large polygonal ferrite grains. The polygonal ferrite grains are intermixed with smaller irregular ferrite grains. The polygonal ferrite grains have an approximate average grain size of 130 μm with the irregular ferrite having an approximate average grain size of 80 μm. This type of microstructure is expected in as-cast steels as the slow cooling rate post-casting is expected to produce a mainly ferritic microstructure. Similar to the as-cast slab material, the microstructure of the hot-rolled material for steel I-05C1.2Mn09Nb shown in figure 5.1 (b) is also comprised of primarily ferrite grains, but at a much smaller size. The approximate average ferrite grain size for the hot-rolled material is 7 μm. The grains also show elongation in the rolling direction. The fine grain size in conjunction with the elongated shape are expected in steels that have undergone a rolling treatment and accelerated cooling as this steel has. 59 Figure 5.1 Images of I-05C1.2Mn09Nb (a) as-cast slab microstructure at 100X magnification (b) hot-rolled microstructures at 200X magnification. Figure 5.2 Images of I-05C1.3Mn06Nb (a) as-cast slab microstructure at 100X magnification (b) hot-rolled microstructures at 200X magnification. (a) (b) (a) (b) 60 The microstructures found within both the as-cast slab and hot-rolled material for steel I-05C1.3Mn06Nb are of the same type as the microstructures for I-05C1.2Mn09Nb shown in figure 5.2 (a) and (b). The as-cast slab material consists of large polygonal ferrite and smaller, less common irregular ferrite while the hot-rolled material is comprised of fine ferrite grains, elongated in the rolling direction. While both steel chemistries have identical microstructure morphologies, their respective average grain size are slightly different. For I-05C1.2Mn09Nb, the approximate average grain size of the polygonal ferrite is 150 μm and the irregular ferrite is 90 μm. The hot-rolled material has an approximate ferrite grain size of 5 μm. For both steel chemistries to contain the same type of microstructure with the difference between their respective average grain sizes being comparatively minor reflects that both steels underwent similar processing steps. Due to their similar characteristics, it is assumed that the initial ferrite microstructure will not impact comparisons between the steels in other experiments. 5.1.2 Microprobe Measurements Microprobe measurements were performed on the as-received as-cast slab material for both steel chemistries to determine the elemental distribution within the as-cast steel. By investigating the elemental distribution, it could be determined to what extent segregation of elements occurred during casting. The elements measured include manganese, copper, chromium, molybdenum and silicon. 61 Figure 5.3 Microprobe line scan on I-05C1.2Mn09Nb showing moving average Mn wt%. Figure 5.4 Microprobe line scan on I-05C1.3Mn06Nb showing moving average Mn wt%. Figure 5.3 shows the manganese content in weight percent (wt%) acquired during a line scan performed on a sample from I-05C1.2Mn09Nb. Figure 5.4 shows the same measurements performed on I-05C1.3Mn06Nb. The presented results are representative of line scans taken on all five samples from each steel chemistry. Manganese is the only element shown of those measured as the other elements did not have any variation in their concentration. This is not unexpected as 1.11.151.21.251.31.351.40 500 1000 1500 2000 2500 3000 3500 4000 4500 5000Mn wt%Distance (μm)1.21.251.31.351.41.451.50 500 1000 1500 2000 2500 3000 3500 4000 4500 5000Mn wt%Distance (μm)62 manganese has a higher total weight percent in the steel, therefore, it is easier to measure accurately. The line scans were 5000 μm in length using a 2 μm step size, therefore, a total of 2500 measurements were taken on each sample. A moving average of 30 was used to filter the data. All scans performed show a similar trend where manganese had peaks and valleys in concentration. The peaks and valleys show an approximately repeating distance between them which can be termed as a wavelength. By determining the number of peaks present in a line scan the wavelength can be expressed as a distance in microns. The microprobe measurements also allow for the determination of the maximum and minimum manganese weight percent as well as the average weight percent. Tables 5.1 and 5.2 show the number of peaks, spacing, and the minimum and maximum weight percent of manganese of every sample for both steel chemistries. Table 5.1 I-05C1.2Mn09Nb microprobe analysis. I-05C1.2Mn09Nb Peaks Spacing (μm) Maximum (wt%) Minimum (wt%) S01 18 278 1.33 1.14 S02 22 227 1.28 1.17 S03 18 277 1.40 1.15 S04 21 238 1.32 1.17 S05 21 238 1.32 1.14 Average 20 252 1.34 1.15 63 Table 5.2 I-05C1.3Mn06Nb microprobe analysis. I-05C1.3Mn06Nb Peaks Spacing (μm) Maximum (wt%) Minimum (wt%) S01 20 250 1.46 1.28 S02 19 263 1.42 1.32 S03 17 294 1.46 1.28 S04 20 250 1.45 1.26 S05 17 294 1.45 1.31 Average 18.6 270 1.45 1.29 The microprobe line scans on I-05C1.2Mn09Nb show an average of 20 peaks which correspond to a wavelength spacing of 252 μm. The average maximum weight percent is 1.34 wt%, the minimum is 1.15 wt% and the total average is 1.24 wt%. I-05C1.3Mn06Nb showed a slightly lower average number of peaks of 18.6 which correspond to a larger wavelength spacing of 270 μm. The average maximum weight percent is 1.45 wt%, the minimum is 1.29 wt% and the total average is 1.36 wt%. 5.2 Austenite Grain Evolution in Hot-Rolled Material 5.2.1 LUMet Results Figure 5.5 shows LUMet results for austenite grain growth in experiments with different holding temperatures of 1100°C, 1200°C and 1300°C on I-05C1.2Mn09Nb. As expected, with increasing temperature, the limiting grain size also increases. At 1100°C the limiting grain size is approximately 22 μm, it is approximately 35 μm at 1200°C and approximately 90 μm at 1300°C. Within the grain growth curves, different regimes can be identified which include initial rapid 64 growth, slow growth and maintaining at the limiting grain size. It may be hard to identify in this graph but the 1300°C test does approach a limiting grain size; this can be more easily seen when the time axis is reduced to 140 s as shown in figure 5.6. For all LUMet results shown, time zero begins when the LUMet system is activated as the sample reaches 900°C. 1100°C is reached at 27 seconds, 1200°C at 29 seconds and 1300°C at 31 seconds. Figure 5.5 Grain size evolution between three holding temperatures for “top” sampling location on I-05C1.2Mn09Nb material. For the 1100°C experiment the transition from initial rapid grain growth to slow grain growth when approaching the limiting grain size occurred between 80 and 110 seconds after 900°C was reached. The limiting grain size was reached at approximately 200 seconds. For the 1200°C experiment the transition occurred after 30 to 60 seconds and the limiting grain size was reached at approximately 130 seconds. Finally, for the 1300°C experiment the transition occurred after 10 to 20 seconds and the limiting grain size was reached at approximately 60 seconds. 0204060801000 200 400 600 800 1000 1200 1400Grain Size (μm)Time (seconds)1100C1200C1300C65 Figure 5.6 Grain size evolution of 1300°C test on different locations for I-05C1.3Mn06Nb material. Figure 5.7 Grain size evolution of 1200°C test on different locations for I-05C1.3Mn06Nb material. 0204060800 20 40 60 80 100 120 140Grain Size (μm)Time (seconds)TopMiddleBottom010203040500 100 200 300 400 500 600 700Grain Size (μm)Time (seconds)TopMiddleBottom66 Figure 5.8 Grain size evolution of 1100°C test on different locations for I-05C1.3Mn06Nb material. Figures 5.6-8 compare the effect of sampling location at the different holding temperatures for the same steel chemistry. At all three holding temperatures there is within the accuracy of measurement of 18% [120] no difference between the three sampling locations of "top, middle and bottom". At 1100°C the limiting grain size for all three positions varies by approximately 5 μm, the variation is slightly larger at 1200°C and 1300°C with 7 and 10 μm respectively. However, as the variation in the positions increases with increasing temperature, the limiting grain size also increases meaning the relative error stays consistent. In addition to no discernible difference in average limiting grain size the transition from rapid to slow growth and time to reach the limiting grain size occurs at approximately the same time between all positions. The LUMet results shown in figures 5.6-8 are for I-05C1.3Mn06Nb, the results of experiments performed on I-05C1.2Mn09Nb show identical trends. 0510152025300 200 400 600 800 1000 1200 1400Grain Size (μm)Time (seconds)TopMiddleBottom67 Figure 5.9 Comparison of I-05C1.2Mn09Nb and I-05C1.3Mn06Nb at 1100°C. Figure 5.10 Comparison of I-05C1.2Mn09Nb and I-05C1.3Mn06Nb at 1200°C. 0510152025300 200 400 600 800 1000 1200 1400Grain Size (μm)Time (seconds)I-05C1.2Mn09NbI-05C1.3Mn06Nb010203040500 100 200 300 400 500 600 700Grain Size (μm)Time (seconds)I-05C1.2Mn09NbI-05C1.3Mn06Nb68 Figure 5.11 Comparison of I-05C1.2Mn09Nb and I-05C1.3Mn06Nb at 1300°C. Figures 5.9-11 compare the effect of steel chemistry on austenite grain growth at the three different holding temperatures. As there was a negligible effect of sampling location, the LUMet results closest to the average grain size for all three positions are shown as examples. Table 5.3 shows the average limiting grain size and standard deviation between both chemistries for the three holding temperatures. The averages and standard deviations were calculated from the results of all positions and repeat experiments for each chemistry. It can be seen from all tests that I-05C1.2Mn09Nb has a larger limiting grain size than I-05C1.3Mn06Nb. This trend is least noticeable at 1100°C as the limiting grain size is almost the same and within the error of measurement of 18% for both chemistries. However, I-05C1.2Mn09Nb showed a minor but consistent larger limiting grain size of approximately 22 μm compared to 21 μm for I-05C1.3Mn06Nb. The trend becomes more noticeable at 1200°C with a difference of approximately 6 μm between the limiting grain sizes. Where I-05C1.2Mn09Nb had a limiting grain 0204060801000 30 60 90 120 150Grain Size (μm)Time (seconds)I-05C1.2Mn09NbI-05C1.3Mn06Nb69 size of approximately 37 μm and I-05C1.3Mn06Nb had 31 μm. Finally, at 1300°C a distinct difference of approximately 22 μm in limiting grain size is observed. Here, I-05C1.2Mn09Nb has a limiting grain size of approximately 82 μm and I-05C1.3Mn06Nb of 60 μm. Table 5.3 shows the average limiting grain size for all tests as well as the standard deviation. Standard deviation is calculated by finding the square root of the variance between the limiting grain sizes. It is also important to note that the transition from rapid to slow grain growth and time to reach the limiting grain size is almost identical between the two chemistries the only discernible difference is the limiting grain size. Table 5.3 Comparison of final grain size and standard deviation between I-05C1.2Mn09Nb and I-05C1.3Mn06Nb at different temperatures. 1100°C 1200°C 1300°C I-05C1.2Mn09Nb 22 ± 1.7 μm 37 ± 4.0 μm 82 ± 6.5 μm I-05C1.3Mn06Nb 21 ± 2.3 μm 31 ± 4.1 μm 60 ± 5.0 μm 5.2.2 EBSD Reconstruction Validation Reconstructions of the prior austenite grain boundaries using data acquired through EBSD scans was performed to validate the grain size results obtained with LUMet. The reconstruction process is very time intensive, therefore, only two reconstructions were performed. The reconstructions were done on samples from the "top" position of I-05C1.3Mn06Nb that experienced the 1100°C and 1300°C heat treatments. The reconstructed maps are 1000 X 1000 μm in size and were obtained using a step size of 0.25 μm. 70 Figure 5.12 PAG reconstructions of I-05C1.3Mn06Nb hot-rolled material after (a) 1100°C and (b) 1300°C heat treatments. Figure 5.12 (a) shows the PAG reconstruction for the 1100°C experiment. The reconstructed austenite microstructure has the expected characteristics for this heat treatment. The grains are randomly distributed in both size, shape and crystallographic orientation with no unique features identified. For instance, the largest grain is approximately 70 μm, which is not an outlier when looking at the other grains, the majority of the austenite grains have an equiaxed shape and no one region of the map is biased towards a specific crystallographic orientation. Figure 5.12 (b) shows the PAG reconstruction for the 1300°C experiment which shares the same characteristics as the 1100°C reconstruction with the exception that the average grain size is larger due to the increase in holding temperature. For example, the largest austenite grain is (a) (b) [1 11] [011] [001] 𝐑𝐃 𝐍𝐃 𝐓𝐃 71 approximately 100 μm, with the overall average also increasing. Additionally, the grains in the 1300°C reconstruction are more clearly equiaxed with no specific crystallographic orientation being preferred. Figure 5.13 shows the grain size distributions of the reconstructed austenite grain maps as area fraction versus the EQAD. Both figure 5.13 (a) and (b) show a normal distribution in the grain sizes measured. The tail of the distribution at 1300°C is longer than the tail at 1100°C due to a number of grains larger than 60 μm, especially a few grains that exceed 100 μm. Figure 5.13 Grain size distributions obtained from the PAG reconstructions of hot-rolled I-05C1.3Mn06Nb that underwent the (a) 1100°C and (b) 1300°C heat treatments. (a) (b) 72 An average diameter for the prior austenite grains produced from the reconstructions must be obtained to compare to the average diameter obtained from the LUMet analysis. This is done using two methods of EQAD, equation 2.9 and AWGD, equation 2.10. A comparison of the three different methods to obtain austenite grain sizes for the specific experiment is shown in table 5.4. For the test at 1100°C, LUMet suggests an average grain size of 16.5 μm, the EQAD method is in very good agreement with an average size of 19.0 μm, AWGD shows a much larger average grain size of 30.7 μm. For the test at 1300°C, LUMet suggests an average grain size of 57.0 μm, opposite to the 1100°C test, the EQAD method shows a smaller average grain size of 34.6 μm and the AWGD method is in very good agreement with the LUMet data with an average grain size of 52.4 μm. Table 5.4 Comparison of EQAD, AWGD and LUMet grain size after 1100°C and 1300°C heat treatments on I-05C1.3Mn06Nb hot rolled material. I-05C1.3Mn06Nb 1100°C I-05C1.3Mn06Nb 1300°C Number of grains 3225 921 EQAD (μm) 19.0 34.6 AWGD (μm) 30.7 52.4 LUMet results (μm) 16.5 57.0 73 The AWGD method is more sensitive to larger grains within the map than the EQAD method which is why AWGD suggests a larger average grain size for both experiments. The LUMet analysis is also more sensitive to larger grains as it is representative of the microstructural volume rather than a 2D map. Due to LUMet being more sensitive to lager grains, this explains why the LUMet results are closer to the AWGD at larger average grain sizes and closer to EQAD at lower average grain sizes. As the average grain size increases a higher proportion of the volume is taken up by the larger grains and at the lower grain sizes the large grains do not take up by high proportion of the volume. Figure 5.14 Pole figures of three randomly chosen grains of the PAG reconstruction for I-0fC1.3Mn06Nb hot rolled material after 1300°C heat treatment. {001}𝐹𝐶𝐶 ∥ {001}𝐵𝐶𝐶 {111}𝐹𝐶𝐶 ∥ {011}𝐵𝐶𝐶 ⟨1 01⟩𝐹𝐶𝐶 ∥ ⟨111⟩𝐵𝐶𝐶 Ferrite orientations in selected PAG grain Variants for selected PAG grain (using experimental OR) 74 The quality of fit for the PAG reconstructions is determined by comparing the crystallographic orientations of three randomly selected grains in the reconstructed austenite grain map to the orientations of their corresponding ferrite grains in the initial grain map. An example of this comparison is shown in figure 5.14, where pole figures are used to compare the potential variants of the randomly selected austenite grain to the known ferrite orientations of the same grain. If there is consistent and good overlap between the two orientations, the PAG reconstruction is considered to be of good quality. If there is not good overlap of the orientations, it suggests that the reconstructed austenite grain has been allocated to the wrong ferrite grain and the reconstruction is of lower quality. All reconstructions shown in this work are considered to be of good quality, reconstructions that were rejected have been re-scanned. 5.3 Austenite Grain Evolution in As-Cast Slab Material 5.3.1 Comparison to Hot-Rolled Material 5.3.1.1 LUMet Results Figures 5.15-16 show two of the common LUMet grain growth trends observed during these experiments. The LUMet results in figure 5.15 show an austenite grain evolution where the initial size is approximately 40 μm followed by a region of minor growth up to 55 μm after which the average grain size decreases to then reach a limiting grain size of approximately 45 μm. A number of additional tests varying in holding temperature, sampling position and chemistry show the same pattern of a large initial grain size followed by slow growth which then begins to decrease before a limiting grain size below the peak size is reached. A test at 1200°C on I-05C1.3Mn06Nb showed an extreme case where the peak grain size is double the final limiting size with the transition occurring in less than 100 seconds. 75 The LUMet results in figure 5.16 show the other common trend where the shape of the curve is relatively normal but there is a huge amount of scatter in the grain size results at any given moment. The scatter of the results increases throughout the test where it was common to observe a scatter approaching the assumed average limiting grain size. For example, in figure 5.16 the scatter at the end of the test is approximately 50 μm while the limiting grain size is assumed to be near 80 μm. For this research the scatter is considered to be the difference between the maximum and minimum reported grain size for measurements taken at approximately the same time. Figure 5.15 Grain size evolution of 1100°C experiment on I-05C1.2Mn09Nb as-cast slab material. 0102030405060700 200 400 600 800 1000 1200 1400Grain Size (μm)Time (seconds)76 Figure 5.16 Grain size evolution of 1300°C experiment on I-05C1.2Mn09Nb as-cast slab material. One of the major determinates used by the LUMet system to produce an austenite grain size is the attenuation spectrum fit. An example of a good fit is shown in figure 5.17 (a). This attenuation spectrum fit was obtained for an experiment on the hot-rolled material of I-05C1.2Mn09Nb at 1100°C. Figure 5.17 (b) shows an example of a poor fit which was obtained for an experiment on the as-cast slab material of I-05C1.2Mn09Nb at 1300°C, the same test shown in figure 5.16. The fit quality of the as-cast slab experiments varies greatly while the hot-rolled experiments are consistent. This is an indication that the grain structure in these tests with the as-cast slab material may deviate from a normal grain size distribution for which the LUMet grain size had been calibrated with. 0204060801001200 30 60 90 120 150Grain Size (μm)Time (seconds)77 Figure 5.17 Attenuation curve fits of I-05C1.2Mn09Nb (a) hot-rolled material at 1100°C and (b) as-cast slab material at 1300°C. 5.3.1.2 EBSD Reconstruction EBSD reconstructions were needed to determine what was occurring during the heat treatments as the LUMet analysis could not produce a clear picture. A total of six reconstructions were completed, one for each holding temperature of 1100°C, 1200°C, 1300°C and repeated for both chemistries. Two of the reconstructions with the highest quality of fit are shown in figure 5.18. The map in figure 5.18 (a) is 2000 μm wide and 1250 μm tall, the map in figure 5.18 (b) is 1250 μm wide and 2000 μm tall. Both maps were originally 2000 x 2000 μm in size but were cropped to eliminate unindexed regions. The maps were scanned using a step size of 0.25 μm. (a) (b) 78 Figure 5.18 PAG reconstructions of I-05C1.2Mn09Nb as-cast slab material after (a) 1100°C and (b) 1300°C heat treatments. From the PAG reconstructions it can be seen that a unique microstructure has formed. Individual extremely large grains are separated by regions of many small grains. This dual grain size microstructure was found on all six reconstructions. However, the size of the large grains and distribution of regions of smaller grains show significant variability. For example in figure 5.18 (a), the 1100°C reconstruction, 5 extremely large grains of 500 μm in diameter or potentially larger are separated by almost linear regions of the smaller grains with sizes ranging from approximately 10 to 100 μm. Additionally, the extremely large grains have islands of these small grains within them. In contrast, with the test at 1300°C, figure 5.18 (b), the reconstruction shows 4 grains that are approximately 350 to 550 μm in size which are still much larger than the surrounding small grains of approximately 10 to 150 μm in size. These regions of smaller grains are also not aligned (a) (b) [1 11] [011] [001] 𝐍𝐃 𝐓𝐃 𝐑𝐃 79 in linear patterns. Such microstructures were not seen in the hot-rolled material and have not been reported in the literature. Figure 5.19 shows the grain size distributions of the reconstructed austenite grain maps as area fraction versus the EQAD. From the distributions it can be seen that a normal distribution is not present and rather the bimodal distribution is observed. The reconstruction of the experiment at 1100°C, shown in figure 5.19 (a) shows two groupings of grain sizes. One grouping is between 10 and 100 μm which represent the small grains and another grouping between 100 and 700 μm which represents the large grains. The experiment at 1300°C, figure 5.19 (b), shows a similar trend where the small grains are grouped between 10 and approximately 150 μm while the large grains are grouped between 150 and 530 μm. Figure 5.19 Grain size distributions obtained from the PAG reconstructions of as-cast slab I-05C1.2Mn09Nb that underwent the (a) 1100°C and (b) 1300°C heat treatments. (a) (b) 80 5.3.2 Reheat Furnace Simulation 5.3.2.1 LUMet Results Due to the length of the reheat furnace simulation experiments the LUMet measurements were grouped into four regions spaced throughout the test. The measurements occurred at 950°C, when the ferrite to austenite transformation finished, the start of the 1200°C hold, one hour after the 1200°C hold started and finally 2 hours after the 1200°C hold began, immediately before quenching. Figure 5.20 Grain size evolution of reheat furnace simulation on I-05C1.2Mn09Nb as-cast slab material. 0204060801001200 1 2 3 4Grain Size (μm)Time (hours)81 Figure 5.21 Grain size evolution of reheat furnace simulation on I-05C1.3Mn06Nb as-cast slab material. As shown in figures 5.20-21 the results of these LUMet tests are similar to some of the LUMet results obtained from the 1100°C, 1200°C and 1300°C experiments where the overall shape of the grain size curve is normal but the scatter of the average grain size increases throughout the test to an unacceptable amount. Initially, the scatter of the measurement taken at 950°C is within an acceptable limit of approximately 10 μm, additionally the reported grain size between approximately 30 and 40 μm is not unusual at this time and temperature within the test. For both chemistries the LUMet results at the beginning of the 1200°C hold show the sudden increase in the scatter suggesting a similar dual microstructure as identified in the other grain growth tests on the as-cast slab material. For I-05C1.2Mn09Nb the initial average grain size is 34 μm with a very minor scatter of 4 μm. The scatter starts to increase at the beginning of the 1200°C hold where the average grain size is 57 μm and the scatter is 19 μm. The trend of increasing scatter continues where the average 0204060801001200 1 2 3 4Grain Size (μm)Time (hours)82 grain size is 60 μm with a scatter of 31 μm after holding for 1 hour and the average grain size is 67 μm with a scatter of 42 μm after holding for 2 hours at 1200°C. I-05C1.3Mn06Nb shows the same pattern where the initial grain size is 34 μm with a slightly higher scatter of 7 μm. At the beginning of the 1200°C hold the average grain size is 90 μm with a scatter of 24 μm. After 1 hour of holding the average grain size has dropped to 83 μm with a scatter of 36 μm. After 2 hours of holding the average grain size has slightly increased to 85 μm with the largest scatter of 45 μm. The drop in average grain size is not very concerning as due to the large scatter, the apparent average grain sizes of 83, 85 and 90 μm are the same. These experiments were repeated on all sampling positions from both steel chemistries. The same pattern of increasing scatter over time was observed in all experiments with differences in average grain size and total scatter, therefore, no repeatable limiting grain size was identified. 5.3.2.2 EBSD Reconstruction EBSD reconstructions were performed on samples quenched out at 950°C, when the sample first reached 1200°C and 2 hours after reaching 1200°C to match when LUMet measurements were taken. These reconstructions were performed on samples from the "top" position of both steel chemistries. These reconstructed maps are 2000 x 2000 μm and used a step size of 0.25 μm. 83 Figure 5.22 PAG reconstructions of I-05C1.2Mn09Nb as-cast slab material at quenched out temperatures of (a) 950°C, (b) 1200°C 0 hours and (c) 1200°C 2 hours in the reheat simulation. The EBSD reconstructions of I-05C1.2Mn09Nb are shown in figure 5.22 and confirm the presence of an austenite grain structure consisting of a few extremely large grains alongside regions of many small grains. Similar to the reconstructions of the as-cast slab material that underwent the more conventional heat treatments at different temperatures there is not a unifying trend for the distribution of small and large grains. Some reconstructions show the large grains being separated by small grains aligned in linear lines while other reconstructions showed regions of large grains next to regions of small grains or one extremely large grain containing islands of small grains. Figure 5.22 (a) shows the PAG reconstruction when the sample was quenched at 950°C. At first glance the characteristics of the reconstructed grains are almost normal but there are areas of concern. For example, there are groupings of grains that share a similar crystallographic (a) (b) (c) [1 11] [011] [001] 𝐍𝐃 𝐓𝐃 𝐑𝐃 84 orientation, this can be seen in the light green grains dominating the upper half of the map. Additionally, there is a large variation in grain sizes and groupings of grains with similar sizes are present. For instance, grain of approximately 100 μm in size are concentrated in the middle right of the map and grains of approximately less than 10 μm are concentrated on the bottom edge of the map. Figure 5.22 (b) shows the reconstructed austenite grains of the sample quenched at the start of the 1200°C hold. This reconstructed map shows a microstructure more similar to those found in the previous as-cast slab reconstructions where a few extremely large grains are surrounded by regions of smaller grains. In this map there are two dominant grains, shown in green and purple that exceed the map boundaries and therefore can be assumed to be larger than 2000 μm. These two grains are separated by a linear region of smaller grains that are approximately 100 μm in size. Furthermore, the two dominant grains contain islands of smaller grains primarily less than 50 μm in size. Figure 5.22 (c) shows the reconstructed austenite grains of the sample quenched after holding for 2 hours at 1200°C. This map is almost entirely composed of a single grain shown in the dark blue colour that is easily larger than 2000 μm. Evidence of a second grain can be seen in the top right edge of the map where a region of smaller grains may be separating the two grains. Additionally, the massive blue grain contains islands of smaller grains less than 50 μm in size. 85 Figure 5.23 PAG reconstructions of I-05C1.3Mn06Nb as-cast slab material at quenched out temperatures of (a) 950°C, (b) 1200°C 0 hours and (c) 1200°C 2 hours in the reheat simulation. Figure 5.23 shows the PAG reconstructions of samples of I-05C1.3Mn06Nb when quenched at 950°C (a), the start of the 1200°C hold (b) and the end of the 1200°C hold after 2 hours (c). In figure 5.23 (a), the austenite microstructure is one of the clearest examples of the bimodal grain structure where a few extremely large grains are separated by linear regions of smaller grains. In this map, 5 large grains of approximately 1000 μm in size and most likely larger, are partitioned by linear regions of small grains commonly between 20 and 100 μm. Furthermore, there are islands of small grains within the 5 dominant large grains. The austenite microstructure present in figure 5.23 (b) is different from the as-cast slab microstructures shown previously as there is a mixture of the common trends observed. For example, in the top left side of the map a few large grains approximately 250 μm in size are coexisting with concentrations of small grains between 30 and 100 μm in size. The other (a) (b) (c) [1 11] [011] [001] 𝐍𝐃 𝐓𝐃 𝐑𝐃 86 microstructure trend observed in the bottom right of the same map was one massive grain potentially exceeding 2000 μm that is constrained by linear regions of small grains. Additionally, this single massive grain contains the same islands of small grains observed in other reconstructions. Figure 5.23 (c) shows an austenite microstructure that varies from the previously discussed reconstructions as it appears to be near a normal distribution. In this map, no one large grain can be seen to dominate, no obviously distinct high concentration areas of small grains are present and no one preferred crystallographic orientation is identifiable. Even though this map appears close to a more normal distribution it is not as the range of grain sizes is very large. For instance, it is easy to identify multiple grains approximately 300 μm in size and many more above 200 μm while there are also many grains between 10 and 30 μm. Figure 5.24 PAG reconstructions on the same sample of I-05C1.3Mn06Nb as-cast slab material quenched out at 1200°C 0 hours. In relation to the RD (a) is the left side, (b) middle and (c) right. (a) (b) (c) [1 11] [011] [001] 𝐍𝐃 𝐓𝐃 𝐑𝐃 87 Due to the high variably between the as-cast slab reconstruction it was unknown if one reconstruction was an accurate representation of the microstructure for the entire sample. To investigate this, three reconstructions were completed on the same sample of I-05C1.3Mn06Nb quenched at 1200°C at different locations on the scanning surface. It was found that the austenite microstructure varied greatly within the same sample. Figure 5.24 (a) shows an austenite microstructure that consists of a few large grains approximately 300 μm in size primarily co-existing with regions of smaller grains but sometimes separated by linear regions of the small grains. The smaller grain regions are primarily comprised of austenite grains with a size between 10 and 80 μm. Figure 5.24 (b) is the same reconstruction map as in figure 5.23 (b). As explained earlier, the microstructure of this map contains both regions of relatively large grains next to regions of small grains and one massive grain that contains islands of small grains and is defined by linear regions of small grains. Figure 5.24 (c) is very similar to the bottom right region of map (b) where a few extremely large grains are separated by linear regions of small grains and also contain islands of small grains. The few large grains in this reconstruction are approximately 1000 μm in size but some may exceed this. The size of the small grains is consistent with other reconstructions as they are between 20 and 80 μm. When comparing all three reconstructions of the same sample it can be seen that there is a high degree of heterogeneity within the sample. However, the heterogeneity is not completely random as it can be seen that the microstructure transitions when moving from map (a) to (c). Map (a) contains no extremely large grains separated by linear regions of small grains while map (c) is entirely composed of this type of microstructure, furthermore, map (b) is an almost perfect transition between the two types of microstructures. It can be expected that this heterogeneous microstructure can be found within all positions of the as-cast slab material. 88 5.4 Discussion From the experiments conducted in this study it can be seen that there is a fundamental difference in how the as-cast slab and hot-rolled material experience austenite grain growth. No matter what holding temperature and time is used, the as-cast slab material exhibits a bimodal austenite grain size distribution with few large grains and many small grains. The hot-rolled material does not show a similar microstructure, rather, it shows a normal distribution of grain sizes. It is theorized that this unexpected bimodal microstructure in the as-cast slab material is due to the segregation of alloying elements that inhibit austenite grain growth. It is believed that this segregation occurs during the solidification process after casting when the solid is growing in the columnar dendritic manner. As most alloying elements are less soluble in the solid steel than liquid, the alloying elements are concentrated in the inter-dendritic spaces during solidification. It is believed that these areas with high concentrations of alloying elements correspond to the regions of small austenite grains observed in the reconstructions, the spaces between these regions correspond with the extremely large grains as there is nothing to inhibit their growth. Two alloying elements of note for this steel chemistry are titanium and nitrogen. These elements will most likely segregate as well promoting TiN precipitates which limit grain growth through pinning. Evidence of this alloying element segregation is provided through the microprobe measurements. Manganese is known to be a strong segregating element and assuming the theory of segregation into the inter-dendritic spaces, the wavelength spacing of manganese concentration observed in the microprobe measurements corresponds to the inter-dendritic spacing. For I-05C1.2Mn09Nb the average spacing is 252 μm with a maximum spacing of 278 μm, for I-05C1.3Mn06Nb the average spacing is 270 μm with a maximum spacing of 294 μm. 89 Further evidence of the inter-dendritic spaces corresponding to the regions of small grains is found in the reconstructed maps. In figure 5.25 (a,b,c) the dashed black lines correspond to relatively parallel and linear regions of small grains. The spacing between these regions is between approximately 250 and 300 μm which agrees with the spacing shown in the microprobe measurements. In samples that exhibit the linear regions of small grains this spacing of 250 to 300 μm is common but not the rule, there are regions spaced greater than 600 μm and regions of small grains do not exclusively appear in these linear forms. These deviations can be explained by the inherit randomness within solidification where different modes of solidification still result in regions with high concentrations of alloying elements. This also can explain why there is high levels of heterogeneity within the same sample. Figure 5.25 Austenite grain reconstructions highlighting regions of linear small grains in I-05C1.2Mn09Nb quenched at 1200°C 0 hours (a) I-05C1.3Mn06Nb quenched at 1200°C 0 hours (b) and I-05C1.3Mn06Nb quenched at 950°C (c) (b) (c) (a) 𝐍𝐃 𝐓𝐃 [1 11] [011] [001] 𝐑𝐃 90 The segregation of alloying elements into the inter-dendritic spaces can also explain the differences observed between the as-cast slab and hot-rolled material. The starting thickness of the as-cast slab is approximately 25 cm, during the rolling process this thickness is reduced to 25 mm for I-05C1.2Mn09Nb and 20 mm for I-05C1.3Mn06Nb, a reduction of 90% and 92% respectively. Assuming a linear correlation between the reduction in thickness and the reduction in average inter-dendritic spacing the hot-rolled material would see the regions of high alloying element concentrations reduce from 252 μm to 25 μm for I-05C1.2Mn09Nb and a reduction of 270 μm to 21 μm for I-05C1.3Mn06Nb. This is illustrated in figure 5.26 where the regions of low alloying element concentration are eliminated. The spacing of 25 and 21 μm or lower respectively would not highly impact the average grain size as this spacing is similar to the limiting grain size at 1100°C and well below the limiting grain size for 1200°C and 1300°C. Figure 5.26 Schematic showing the elimination of low concentration areas due to the reduction in thickness. The bimodal microstructure observed in the as-cast slab material also explains why the LUMet analysis produced inconsistent austenite grain size measurements. The LUMet analysis operates on multiple foundational assumptions and calibrations to a normal grain structure with a 91 clearly defined mean grain size. For the LUMet analysis a space filling polycrystalline structure is assumed to be present and is calibrated for a normal distribution of austenite grains with an upper limit of approximately 150 to 200 μm. For the as-cast slab samples of both chemistries the LUMet system sees the small grains as being embedded in a matrix. This matrix is comprised of the large grains which are too large to be seen by the analysis, therefore they appear as a transparent matrix in which the smaller grains are immersed. This begins to break down the analysis as the LUMet system cannot properly rationalize the large grains and the measured grain structure is no longer space filling. However, the CTOME software still forces a solution to be produced based on the small grains that are influenced by the large grains. To compound on this issue, the calibration to determine the austenite grain size from the ultrasonic waveform is optimized for a normal distribution of grains less than 200 μm. As many of the grains produced by the PAG reconstructions are above this size, another source of error is introduced into the result. The sensitivity of the LUMet system on the existing austenite structure at that exact moment in time also explains why there is very little repeatability between experiments on the as-cast slab material. Due to the heterogeneity of microstructures observed in the PAG reconstructions of the same sample it is thought that the LUMet results would be heavily impacted by the location of the laser impact. This introduces another large source of error that makes the repeatability of experiments very low. These sources for error in the as-cast slab also explains why the LUMet analysis for the hot-rolled material is reliable and accurate. The hot-rolled material does not share the bimodal grain structure but rather consists of a uniform distribution of grains smaller than the upper limit of the LUMet system. 92 Chapter 6: Conclusion and Future Work 6.1 Summary The objective of this study was to investigate austenite grain growth evolution under varying conditions. These conditions included two steel chemistries, as-cast slab versus hot-rolled material, sampling location and multiple thermal paths. There was a total of four thermal paths implemented. Three thermal paths employed a heating rate of 50°C/s up to three different holding temperatures of 1100°C, 1200°C and 1300°C. These thermal paths were tested on samples from the “top, middle and bottom” of both the as-cast slab and hot-rolled material to determine the effect of sampling location. The fourth thermal path was used to simulate a reheat furnace using a heating rate of 300°C/h up to 1200°C then holding for 2 hours before quenching. This thermal path was only conducted on the as-cast slab material. The thermal paths were carried out on the samples with the use of a Gleeble 3500 thermomechanical simulator. In-situ evaluation of the austenite grain evolution was obtained using a LUMet system. Ex-situ evaluation was obtained through EBSD reconstructions of the prior austenite grains. The key findings presented in this work are summarized below. 1. For experiments on the hot-rolled material, as the holding temperature increased from 1100°C to 1200°C to 1300°C the austenite grain size increased as expected. This trend was observed for all positions and both chemistries. 2. Within the accuracy of measurement there is no difference in the austenite grain growth between the top, middle and bottom sampling positions for the hot-rolled material. 93 3. I-05C1.2Mn09Nb had a consistent larger limiting austenite grain size at all holding temperatures and positions when compared to I-05C1.3Mn06Nb. This is most likely due to pinning of the grain boundaries caused by titanium rich precipitates. Steel I-05C1.3Mn06Nb therefore must contain a finer distribution of these precipitates resulting in the smaller limiting austenite grain size. 4. The hot-rolled material contained a normal distribution of austenite grain sizes while the as-cast slab material experienced a bimodal austenite grain size structure. This bimodal grain size structure consisted of many small austenite grains and few very large austenite grains. 5. Within the same sample of as-cast slab material there is a high degree of heterogeneity in grain size and morphology. 6. It is theorized that this bimodal austenite grain structure in the as-cast slab material is due to segregation of alloying elements into the inter-dendritic spaces during casting. The high concentration regions of alloying elements inhibit grain growth due to increased solute drag or particle pinning. The high concentration regions are associated with the regions of small austenite grains while the low concentration regions are associated with the large austenite grains. 6.2 Future Work The present work showed the expected trends of austenite grain growth on hot-rolled material but this was not observed in the as-cast slab material. The as-cast slab material was comprised of a bimodal austenite grain size structure that was highly variable both within the same sample and between separate samples. Additionally, this complex microstructure was unable to be 94 properly analyzed using the LUMet system. Due to this phenomenon not being sufficiently researched there are many avenues for future work. Some suggestions for future work in this area are shown below. 1. Further investigation into segregation of alloying elements in both as-cast slab and hot-rolled material. A focus area for this would be analyzing the regions of small austenite grains in the as-cast slab material for TiN precipitates. A higher concentration of TiN precipitates in these regions would contribute to the small grain size and further support the segregation theory. 2. It would be useful to determine if this bimodal structure is found in the as-cast slab material of additional chemistries. This can be used to determine if the bimodal structure is caused by the processing steps, chemistry or other variables. 3. Expanding on the current LUMet system and analysis procedure to allow for accurate determination of the in-situ austenite grain evolution for the bimodal microstructures observed. 4. Further work on refining the EBSD reconstruction method to allow for larger maps without extending the time for processing to unfeasible amounts in needed. 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Thesis/Dissertation
eng
Materials Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Militzer, Matthias
Poole, W. J. (Warren J.)
Austenite grain growth studies in line pipe steels
Text