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CONTENTS

Preface

Acknowledgments

Conference Editors/Organizers

IMPORTANCE OF CONTROLLING MICROSTRUCTURE HETEROGENEITY WHEN DESIGNING STEEL

Introduction
Heterogeneous deformation structure and recrystallization
B segregation to the γ grain boundary and its effect on the γ/α phase transformation
Resistance to hydrogen embrittlement by means of hydrogen trap
Future outlook
References

ICME FOR PROCESS SCALE-UP: IMPORTANCE OF VERTICAL AND HORIZONTAL INTEGRATION OF MODELS

Introduction
Mathematical Models of Ladle Refining and Continuous Casting Operations
Problem Statement
Illustrations of Vertical-Horizontal Integration
Closing Remarks
Acknowledgments
References

FINITE ELEMENT MODEL FOR PLYMOUTH TUBE PROCESSING USING INTERNAL STATE VARIABLES

Introduction
Model Description
Conclusions
References

AB-INITIO CALCULATION OF SOLUTE EFFECTS ON AUSTENITE GRAIN BOUNDARY PROPERTIES IN STEEL

1. Introduction
2. Procedure
3. Results
4. Discussion
5. Acknowledgements
6. References

ICME TOWARDS IMPROVED UNDERSTANDING OF BAINITE IN 100CR6

Introduction
Experimental
Simulation methods
Results and discussion
Conclusions
Acknowledgements
References

STEEL – AB INITIO: QUANTUM MECHANICS GUIDED DESIGN OF NEW FE-BASED MATERIALS

Introduction
Deformation Mechanism Maps
TRIP/TWIP Effect in Fe-Mn-Al-C Alloys
Kappa Phase Formation in Fe-Mn-Al-C Alloys
Conclusions
Acknowledgement
References

EXPERIMENTS AND MODELING OF THREE-DIMENSIONAL DENDRITIC MORPHOLOGY OF MAGNESIUM ALLOY

Introduction
Experimental
Model Description
Results and Discussion
Conclusions
Acknowledgments
References

PHASE FIELD SIMULATION OF OROWAN STRENGTHENING BY COHERENT PRECIPITATE PLATES IN A MG-ND ALLOY

Introduction
Methodologies
Total Energy and Kinetics of Dislocations
Microstructure Construction and Initial Conditions
Results and Discussion
Summary
Acknowledgements
References

APPLICATION OF MULTI-SCALE FATIGUE MODELS IN LIGHTWEIGHT METAL CASTINGS

Introduction
Multi-Scale Fatigue (MSF) Life Models
Application of MSF Life Models
Summary
Acknowledgments
References

EXPERIMENTAL VERIFICATION FOR SOLID FRACTION MEASUREMENT IN SEMI-SOLID SILVER METAL PROCESSING IN COMPARISON WITH THEORETICAL THERMODYNAMICS MODEL

1.Introduction
2. Experimental procedures
3. Results and Discussion
4. Summary
Acknowledgements
References

EXPERIMENTAL AND NUMERICAL DETERMINATION OF THE FRACTURE ENERGY OF PAN/PHENOLIC-BASED CARBON/CARBON COMPOSITES

1. Introduction
2. Analysis
3. Experimental
4. Results and discussion
5. Conclusions
References

FROM INTEGRATED COMPUTATIONAL MATERIALS ENGINEERING TO INTEGRATED COMPUTATIONAL STRUCTURAL ENGINEERING

Introduction
The Integrated Computational Structural Engineering (ICSE) Paradigm
Forming the Team
ICSE Validation Approach
ICSE Implementation Plan
Summary and Conclusions
Acknowledgements
References

PREDICTIVE SIMULATION OF DIFFUSION IN NI-BASED ALLOYS USING PAIR INTERACTION BASED KINETIC MONTE CARLO METHOD

Introduction
Computational approach
Results and discussion
Conclusions
Acknowledgements
References

YIELD STRENGTH MODEL FOR UNDERCOOLED ALUMINIUM ALLOYS BASED ON CALORIMETRIC IN-SITU QUENCHING EXPERIMENTS

Introduction
Experimental work
Derivation of yield strength model based on DSC-curves
Conclusion
References

LOAD PARTITIONING MECHANISMS IN STAINLESS STEEL 440C BY CRYSTAL PLASTICITY BASED MICROMECHANICAL MODELING APPROACH

Introduction
CPFEM and Lattice Strain Simulation
Results and discussion
Summary
References

A MOLECULAR DYNAMICS SIMULATION MECHANISM WITH IMPRECISE INTERATOMIC POTENTIALS

Introduction
Kaucher Interval Arithmetic
Reliable Molecular Dynamics
Discussions and Future Work
Acknowledgement
References

A CURVE SWARM ALGORITHM FOR GLOBAL SEARCH OF STATE TRANSITION PATHS

Introduction
Curve Swarm Search Algorithm
Demonstration
Conclusion and Future Work
References

MODELLING THE MICROSTRUCTURE OF POLYCRYSTALLINE AUSTENITE-MARTENSITE STEELS

Introduction
Polycrystalline austenite
Crystallography
Effect of austenite grain size on the M_s temperature
3D Martensitic microstructure
Plastic deformation after transformation
Conclusion
Acknowledgement
References

AN INTERFACE TO QUANTUM ESPRESSO

Introduction
Methodology
Computational Details
Results and Discussion
Summary
Acknowledgement
References

MICROSTRUCTURE MODELING IN ICME SETTINGS

Introduction
Experimental Microstructure Characterization
Microstructure Models
Modeling of Microstructures in ICME Settings
Towards a Future Digital Description of Microstructures
Summary
Acknowledgement
References

DEVELOPMENT OF AN ICME APPROACH FOR ALUMINUM ALLOY CORROSION

Introduction
Approach
Simplified Demonstration System
Future Directions
Conclusions
References

ICME SUPPORT FOR JUMBO VERTICAL BLOOM CONTINUOUS CASTER

Introduction
Tundish Design
Soft Reduction
Bloom Thermal Profile
Conclusions
References

ICME APPLICATIONS IN OPTIMIZING WELDING AND THERMAL-FORMING PROCESSES

Introduction
ICME Applications in Welding
ICME Applications in Plate Thermal Forming
Summary
Acknowledgements
Reference

DESIGN OF CO-FREE CEMENTED CARBIDES

Introduction
Cemented Carbides
Materials Design
Creator – Multiscale Treatment of Gradient Formation
Translator – Hardness and Fracture Toughness
Conclusion
Acknowledgments
References

MODELING AND SIMULATION OF DIRECTIONAL SOLIDIFICATION OF NI-BASED SUPERALLOY TURBINE BLADES CASTING BY LIQUID METAL COOLING

Introduction
Model description
Experiment and validation
Process Optimization of a Real Blade Casting
Conclusions
Acknowledgements
References

FROM MELT POOL TO STRENGTH - APPLICATION OF ICME METHODS FOR THE DEVELOPMENT OF RAPID MANUFACTURING TECHNOLOGIES

Introduction
Selective Laser Melting Process Simulation
Precipitation Kinetic Simulation
Local Strength Simulation
Results
Outlook
Acknowledgment
References

CALIBRATED LOCALIZATION RELATIONSHIPS FOR POLYCRYSTALLINE AGGREGATES BY USING MATERIALS KNOWLEDGE SYSTEM

Introduction
Extension of MKS Framework to Polycrystalline Aggregates
Calibration of Influence Coefficients
Validation of MKS
Conclusion
Acknowledgements
References

COMPUTATIONAL MODELING AND EXPERIMENTAL CHARACTERIZATION OF MARTENSITIC TRANSFORMATIONS IN NICOAL FOR SELF-SENSING MATERIALS

Introduction
Experimental Procedure
Experimental Results
Multiscale Simulation Model
Simulation Results
Conclusion
Acknowledgements
References:

MESOSCALE MODELING OF 3-D VOIDS EVOLUTION IN LARGE INGOT DURING MULTI-HIT DEFORMATION

1. Introduction
2. The 3-D void evolution model for multi-hit forming process of the large ingot
3. Verification
4. Application
5. Conclusions
Acknowledgements
Reference

Data Infrastructure Developed for PW-8: Nickel Base Superalloy Residual Stress Foundational Engineering Problem

Introduction
FEP On Nickel Base Superalloy Residual Stress
Possible Applications for the ICME/MGI Community
Conclusion
Acknowledgement
References

APPLICATION OF MACHINE LEARNING TECHNIQUES FOR INVERSE PREDICTION IN MANUFACTURING PROCESS CHAINS

Data Science Techniques in ICME
Our Approach
Use Case - The Carburization-Quenching-Tempering (CQT) Process
Bayesian Network Model for CQT
Optimization-based Model for CQT
Results and Analysis
Conclusion and Future Work
Acknowledgements
References

NANOHUB AS A PLATFORM FOR IMPLEMENTING ICME SIMULATIONS IN RESEARCH AND EDUCATION

Introduction
Materials Science Simulations Available on nanoHUB
nanoHUB Educational Resources and Features for Instructors
nanoHUB Simulation Tools in Research
Publishing Simulations on nanoHUB
Conclusions
Acknowledgements
References

A REVIEW OF MATERIALS DATA INFRASTRUCTURE PROJECTS: ASM International CMD Network

Introduction
CMD Network projects
Finding ways to work faster
Summary of Materials Data Infrastructure Activities
References

AN INTEGRATED COLLABORATIVE ENVIRONMENT FOR MATERIALS RESEARCH

Introduction
Requirements Approach
Challenges
Architectural Solution
Progress
Conclusions
Note
References

ANALYSIS OF PUBLISHED CAST IRON EXPERIMENTAL DATA

Introduction
Analysis
Results
Conclusion
Acknowledgement
References

A GENERAL SIMULATION TECHNOLOGY FOR FORGING WITH CONSIDERING THE EVOLUTION OF VOIDS, GRAINS AND CRACKS

Introduction
Models for integration
Verifications by results comparison
Applications in engineering
Conclusions
Acknowledgements
References

A METHOD FOR DETERMINING THE SET POINTS OF THE LADLE, TUNDISH AND CASTER FOR MANUFACTURING A HIGH STRENGTH STEEL SLAB

Frame of Reference
Problem Statement and Solution Strategy
Results and Discussions
Closing Remarks
Acknowledgments
References

ICME FOR THE INTEGRATED DESIGN OF AN AUTOMOTIVE GEAR CONSIDERING UNCERTAINTY

Frame of Reference
Design of Heat Treatment Processes for a Gear
IDEM based Robust Design of Heat treatment Processes Chain
Results and Discussion
Closure
Acknowledgments
References

AN INTEGRATED SURROGATE MODELING APPROACH FOR MATERIALS AND PROCESS DESIGN

Introduction
Integrated Surrogate Modeling Approach
Draw Bending Simulation
Results
Extension of the Integrated Approach
Conclusion
References

UNCERTAINTY MANAGEMENT IN THE INTEGRATED REALIZATION OF MATERIALS AND COMPONENTS

1. Frame of Reference
2. Managing Uncertainty in a Decision Model
3. The Robust Concept Exploration Method
4. The Inductive Design Exploration Method (IDEM)
5. Closure
Acknowledgments
References

Exploring the Performance-Property-Structure Solution Space in Friction Stir Welding

1. Frame of Reference
2. Friction Stir Welding
3. Design Problem
4. Results and Discussion
5. Concluding Remarks
Acknowledgments
References

FORCE MODELLING FOR TEMPERATURE FIELD DETERMINATION DURING HIGH SPEED END- MILLING OF SUPER ALLOYS

Introduction
The Model Development
Results and Discussion
Conclusion
REFERENCES

Author Index

Subject Index

EULA

List of Tables

Chapter 1

Table 1

Chapter 4

Table 1

Chapter 5

Table 1

Chapter 6

Table 1

Chapter 8

Table 1
Table 2

Chapter 10

Table 1
Table 2
Table 3

Chapter 11

Table 1

Chapter 13

Table 1

Chapter 14

Table 1

Chapter 15

Table 1

Chapter 16

Table 1
Table 2

Chapter 18

Table 1
Table 2
Table 3

Chapter 19

Table 1

Chapter 21

Table 1
Table 2

Chapter 25

Table 1
Table 2
Table 3

Chapter 29

Table 1

Chapter 30

Table 1
Table 2

Chapter 35

Table I
Table II
Table III

Chapter 36

Table 1

Chapter 37

Table 1
Table 2
Table 3
Table 4
Table 5
Table 6

Chapter 38

Table 1
Table 2

Chapter 39

Table I
Table II
Table III

Chapter 41

Table 1
Table 2
Table 3
Table 4
Table 5

List of Illustrations

Chapter 1

Figure 1 Spectrum of steel strengths together with the strength levels of practically used steels [1].
Figure 2 Schematic illustration of the heterogeneity of a cold-rolled structure [2].
Figure 3 Heterogeneous cold-rolled microstructure in the vicinity of a grain boundary [3].
Figure 4 TEM bright field image showing shear band, and diffraction pattern together with dark field images. 3D schematic illustration of shear band is also presented. [3, 4]
Figure 5 Deformation zone around a hard second phase in Fe-0.07C-16Cr. (a) quenched α' and (b) tempered α' [5].
Figure 6 a) STEM image and B concentration profiles measured by CS-STEM with several tilt angles around the prior γ grain boundary of Fe-0.05C-1.5Mn-3Ni-0.001 1B (mass %) annealed at 950°C for 60s, then cooled to 650°C with a cooling rate of 30°C/s followed by He quenching [9], and b) schematic view of B segregation into Σ9 grain boundary and structure units after first principle calculation [10].
Figure 7 Calculated activation energy for α nucleation as a function of γ grain boundary energy γ^γγ at 705°C for two γ/α interfacial energies γ^γα [11].
Figure 8 3D AP elemental mapping showing deuterium trapped by TiC in α-Fe [12].
Figure 9 a) Calculated interface energies of the coherent and semi-coherent NbC/ α-Fe interface as a function of the length of C₀, b) atomic configuration of the semi-coherent interface in the (110) plane [13]. The region of the dislocation core is positioned in the center of interface.

Chapter 2

Figure 1 Schematic of operations in steel processing
Figure 2 Flow of information across process chain
Figure 3 Variation in the inclusion number density as a function of its size
Figure 4 Size distribution along caster length for (a) NbC precipitates and (b) MnS precipitates respectively
Figure 5 Variation of yield strength (YS) as a function of carbon equivalent and along distance of the cast. All values are normalized.

Chapter 3

Figure 1 Material constants calibration using DMG fit routine. The dotted line is from tension tests, and the red line is model plot for data at room temperature while the blue line is for high temperature (623 K).
Figure 2 Tube forming simulation showing the von Mises stress (in psi) progression from sheet to tube.
Figure 3 Stress-strain behavior comparison between simulation and experimental result (tension) after each step

Chapter 4

Figure 1 Structures used in simulating prior austenite grain boundaries in VASP. Symmetric (a) and asymmetric (b) Σ5 grain boundaries, an asymmetric Σ7 grain boundary (c), and symmetric (d) and asymmetric (e) Σ13 boundaries. Projections of (0 0 1) planes are shown in the figure.
Figure 2 The topology of the adjacent PSS and US. There are two potential US and two potential binding sites (PSS) in this structure because each US is bound to two PSS and vice versa (color image; refer to PDF version).
Figure 3 The topology of atomic sites that display high binding energies. The central atom is the PSS (color image; refer to PDF version).
Figure 4 The topology of atomic sites that display instability when occupied by certain solutes. The central atom is the US (color image; refer to PDF version).
Figure 5 The topology of an US containing Mo (a) and pure Fe (b). The bond lines can be seen to curve towards the Mo solute where they remain straight with the Fe, indicating that the Mo is not able to supply enough valence electrons to meet the needs of the local bonding environment (color image; refer to PDF version).
Figure 6 The relationship between the average of solute binding energies for seven preferential solute sites from DFT simulations and the empirically determined activation energies from Lee and Lee [14]. The error bars represent standard error for each solute.

Chapter 5

Figure 1 Heat treatment cycle of the investigated steel 100Cr6. (ITT stands for Isothermal Transformation Temperature)
Figure 2 TEM micrographs of 100Cr6 steel (a) lower bainite at 260 °C for 2500 s, (b) upper bainite at 500 °C for 1200 s; α_B: ferrite, θ: cementite and GB: grain boundary [3].
Figure 3 (a) Carbon atomic map and 13 at.% iso-concentration surface in lower bainite in 100Cr6 isothermally heat-treated at 260 °C for 2500 s; 1D concentration profile in ROI1 (b) and ROI2 (c) in Figure 3 (a); α_B: bainitic ferrite, θ: cementite and ϵ: ϵ carbide Fe₂.₄C [3].
Figure 4 (a) Carbon atomic map and 12.5 at.% iso-concentration surface in upper bainite in 100Cr6 isothermally heat-treated at 500 °C for 1200 s; (b) Proxigram showing carbon and alloy concentrations across bainitic ferrite and cementite (θ) interface; α_B represents bainitic ferrite, θ represents cementite [3].
Figure 5 Gibbs free reactions energies between ϵ-Fe₂₄C and cementite (Fe₃C, θ) as a function of temperature in a ferritic (left) and an austenitic matrix (right). Both experimental isothermal transformation temperatures (ITT) are indicated [3].
Figure 6 (a) phase field simulated microstructure in 100Cr6 at 260 °C for 1500 s; (b) carbon concentration along a-b line in Figure 6(a) showing the migrating bainitic ferrite/austenite interface and carbon redistribution behavior during bainitic ferrite thickening in bainite formation at 260 °C in 100Cr6; (c) carbon concentration along c-d line in Figure 6(a) showing the migrating bainitic ferrite/cementite interface and carbon redistribution behavior during cementite precipitation in bainite formation at 260 °C in 100Cr6.

Chapter 6

Figure 1 2D composition-dependent map of stacking fault energy (unit, mJ/m²) at 300 K (a) Fe-Mn-C alloy system (b) Fe-Mn-Al-C alloy system, Al 1.5 wt.% [7].
Figure 2 3D composition-dependent SFE map of Fe-Mn-Al-C steel at 300 K [7].
Figure 3 (a) True strain-stress curve, strain rate 0.001 s⁻¹; SEM of fractured sample after tensile test; (b) In situ synchrotron X-ray diffraction patterns during tensile test at room temperature.
Figure 4 (a) True strain-stress curve, strain rate 0.001 s⁻¹; SEM of fractured sample after tensile test; (b) In situ synchrotron X-ray diffraction patterns during tensile test at room temperature.
Figure 5 (a) In situ synchrotron diffraction peaks of κ (200) and γ (200) of Fe-30Mn-8Al-1.2C alloy annealed at 600 °C for different times. (b) The lattice misfit between the kappa phase and the austenite matrix in Fe-30Mn-8Al-1.2C alloy [17].
Figure 6 The ultimate tensile strength (UTS) and the yield strength (Y.S.) (a) and the ductility (b) change with the increase of aging time during kappa phase formation at 600 °C in Fe-30Mn-8Al-1.2C alloy [17].
Figure 7 Comparison of strengthening by carbides in micro-alloyed steels [19] and kappa strengthening in high manganese steels [17].

Chapter 7

Figure 1 2-D microstructure of the Mg-20 wt.% Y alloy using optical microscope
Figure 2 (a) A tomography slice of the Mg–20 wt.% Y alloy and (b) the according 3-D reconstruction of the dendrites extracted from the quenched sample.
Figure 3 (a) The 3-D reconstructed dendrites extracted from the Mg–20 wt.% Y alloy. Dendrite morphologies with respect to three different view directions including {0001}, and were shown in (b) – (d) respectively.
Figure 4 Simulated dendritic morphology of the α-Mg dendrite: (a) simulated equiaxed dendritic morphology; (b) 3-D solute distribution map with a cooling rate of 80K/s; (c) – (d) the dendritic morphology on the xy- and xz- plane, respectively.

Chapter 8

Figure 1 (a) HAADF-STEM image of β₁ precipitates in a Mg-3wt.%Nd alloy aged for 3 hours and 200 °C and (b) digitized image with initial position of the dislocation.
Figure 2 (a) and (b) Gliding process of a screw dislocation (b = a/3 [110]_α) under an applied shear stress of 55 MPa at different time steps. The dislocation front is indicated by letter A in (b). After the dislocation bypasses the precipitates, some dislocation loops are left surrounding individual precipitates or clusters of precipitates, which are marked by letters B and C respectively in (b). (c) The dislocation has passed the entire microstructure when applied stress is increased to 65 MPa. Viewing direction is parallel to [0001]_α.
Figure 3 Distribution of the measured planar diameter of β₁ particles (0001)_α intersection plane in samples aged for 3 hours at 200 °C. The curve shows the fitting by the log-normal distribution.
Figure 4 Microstructures constructed to examine the effect of precipitate aspect ratio and number density on ΔCRSS increment. In figures (a)-(e), the volume fraction and number density of precipitates in each figure equals to those of β₁ in samples aged for 3 hours at 200°C. The precipitate aspect ratio is approximately (a) 1:1, (b) 10:1, (c) 20:1, (d) 40:1 and (e) 60:1. In figures (f) and (g), the volume fraction and aspect ratio of precipitates are identical to those of β₁ in samples aged for 3 hours at 200 °C, and the a number density of the distributions of precipitates are (f) 4252, and (g) 8504 μm⁻³. Viewing direction is parallel to [0001]_α.

Chapter 9

Figure 1 Comparison of the predicted and actual fatigue life (N_f) in aluminum castings. (a) 319 samples failed by porosity and (b) A356 samples failed by the cracked and debonded second phase particles [27].
Figure 2 Comparison of actual fatigue life (N_f) of 319T7 alloy samples failed by slip bands with the calculated life based on Equation (9). Arrows indicate runout samples which did not fail after 10 million cycles [27].
Figure 3 Comparison of actual fatigue life (N_f) of 319T7 alloy samples with crack initiation by slip bands with the calculated life based on Equation (7). Arrows indicate runout samples which did not fail after 10 million cycles [27].
Figure 4 Comparison of the actual fatigue life measured with the calculated fatigue life for various Mg alloys under (a) T4 and (b) T6 heat treatment conditions. The fatigue test is the rotating bending test (RB) at room temperature. [29]

Chapter 10

Figure 1 Schematic for thermal analysis experiment set-up
Figure 2 Liquidus projection of Ag-Cu-Zn alloys and the solidification path of sterling silver alloys [8]
Figure 3 Thermal analysis results (1) grain size (2) and microstructure (3) for (a) without gas bubble (b) with gas bubble
Figure 4 Solid fraction vs. temperature curve for (a) thermal analysis (b) thermodynamics model

Chapter 11

Figure 1 Schematic diagram of Load vs. load line displacement (P-u) curve. 2.2 Fracture Energy
Figure 2 Schematic diagram of the fabrication method, and the image for CFRP and C/C composites.
Figure 3 Schematic diagram of the specimen geometry.
Figure 4 Load vs. displacement curves for (a) CFRP and (b) C/C specimens, and (c) Mode II loads for a C/C specimen during fracture testing.
Figure 5 Numerical values of interlaminar fracture energy, G_IIC , based upon Eqs. 1 and 2 under Mode II loading of CFRP and C/C specimens.
Figure 6 Experimental values of interlaminar fracture energy, G_IIC, based upon Eqs. 3, 4 and 5 under Mode II loading of CFRP and C/C specimens.

Chapter 12

Figure 1 ICSE for unitized aluminum airframe components
Figure 2 The ICSE Team
Figure 3 Log, Coupon Blanks, and Design Feature Coupons [12]
Figure 4 Design Feature Coupon Results – Fatigue Crack Growth [12]

Chapter 13

Figure 1 Tracer diffusion coefficients of oxygen in fcc Ni computed using KMC versus 1000/T. Experimental data (Zolobov (1971) [13], Park (1987) [14], Goto (1967) [15], Alcock (1969) [16], Bartlow (1969) [17], Kerr (1972) [18] and Lloyd (1972) [19]) are included for comparison.
Figure 2 KMC predicted diffusion coefficients of oxygen in fcc Ni at various Al concentration x versus reciprocal temperature. The composition dependent values of the effective activation energy of oxygen (Q) are included in the inset for comparison.

Chapter 14

Figure 1 Physical fields and coupling interactions involved in quenching process (left), calculation scheme for quenching simulation of aluminium alloy (right).
Figure 2 Selected DSC cooling curves of alloy 6082 (left) and flow curves after different cooling rates at 250 °C (right).
Figure 3 Boltzmann approach for specific precipitation heat ∆H_total of two reactions (LT and HT), depending on temperature with the parameters ∆H (specific heat of each precipitation), T_Peak (peak temperature) and w (precipitation intensity).
Figure 4 Evolution of the low temperature and high temperature precipitation heats (left) and solid solution concentration (right).
Figure 5 Results of the yield strength model in comparison with experimentally determined values.

Chapter 15

Figure 1 phase contour measured by EBSD
Figure 2 Transparent martensitic phase with colorful Fe₃C phase dispersed
Figure 3 Elastic strains for precipitates and specific lattice planes in matrix in terms of applied stress when (a) stress is less than ∼1500 MPa, and (b) stress reaches ∼2000MPa.
Figure 4 Stress contour in matrix and precipitates after deformation

Chapter 16

Figure 1 Interval positions of atoms in R-MD.
Figure 2 Error generating function in f(r)
Figure 3 Sensitivity due to error in Fig. 2
Figure 4 Error generating function in ρ(r)
Figure 5 Sensitivity due to error in Fig. 4
Figure 6 Error generating function in F(ρ)
Figure 7 Sensitivity due to error in Fig. 6

Chapter 17

Figure 1 Test result for curve swarm algorithm by example of Rastrigin function (a) concurrent search algorithm without collective force (b) curve swarm algorithm (c) scalability test
Figure 2 Test result for curve swarm algorithm by example of Schwefel function (a) concurrent search algorithm without collective force (b) curve swarm algorithm (c) convergence test
Figure 3 Results of the example transition paths for the diffusion process of the hydrogen atoms in the FeTiH system (a) transition path No. 9; (b) transition path No. 10 (c) transition path No. 13

Chapter 18

Figure 1 The morphologies of γ in 200 × 200 × 200 lattices for a) 1000 grains and b) 50 grains of austenite.
Figure 2 The formation of an initial vector u due to the formation of martensite. (a) an austen-ite grain prior to transformation, with the ultimate location of a plate of martensite marked. (b) the following martensite transformation
Figure 3 The increase in the nucleation rate during initial part of transformation (autocataly-sis).
Figure 4 3D microstructure of martensite during a) free stress condition and b) under applied stress.
Figure 5 Microstructure evolution under plain strain deformation: (a)before deformation, (b) 1 pass, (c) 2 passes and (d) 3 passes.

Chapter 19

Figure 1 Pictorial description of how various libraries and QE-nipy-advanced are connected.
Figure 2 Functionalities of modules in QE-nipy-advanced
Figure 3 Calculated phonon dispersion curves and density of states for cubic SiC.
Figure 4 The calculated thermal expansion of SiC versus experimental data: a) Coefficient of Linear thermal expansion and b) Lattice constant as a function of temperature. The experimental results shown in figure (a) and (b) are from reference [21] [22] respectively.
Figure 5 SiC: (a) heat capacity and (b) entropy as a function of temperature. Experimental results are from the reference [21], [22] for figure (a) and (b) respectively.
Figure 6 (a) Thermal Conductivity SiC and (b) ThO₂ compared with pure cubic ZrO₂

Chapter 20

Figure 1 Basic topology of a software tool in an ICME setting. This topology allows assembling respective “puzzle parts” along the time/history (from initial conditions to output/final conditions) and across the scales via exchange of boundary conditions and effective values [8]
Figure 2 The “initial conditions” entering a microstructure simulation as initial microstructure may originate from a variety of sources (see text)
Figure 3 The “output” of a microstructure simulation may become subject to a large variety of further operations (see text)
Figure 4 Basic structure of HDF5 comprising “cell data”, “field data” and “ensemble data”. For explanations see text. The figure has been taken from the Dream3D manual [3]

Chapter 21

Figure 1 Schematic of the interacting elements for the ICME approach to corrosion prediction.
Figure 2 Mass fractions of predicted equilibrium phases in AA3003 as a function of temperature.

Chapter 22

Figure 1 Side view of the new Faircrest Steel Plant jumbo vertical bloom continuous caster. Areas of note for further discussion are a) tundish, b) soft reduction rolls, c) transfer & cooling beds.
Figure 2 Views of an optimum flow pattern at a local area inside the tundish for effective inclusion removal and superior steel cleanness. Left: visual results from a computational steady-state flow simulation. Right: visual of the flow pattern inside the physical water model showing great agreement with the computational results.
Figure 3 Plot comparing the tundish residence time distribution curves (C-curves) from the computational fluid dynamics model and the physical water model.
Figure 4 Screenshots from DEFORM showing the a) soft reduction layout and b) finite element mesh for each reduction. The mesh also displays the relative elemental density contour which is a minimum in the center and gradually increases to 1 (fully solid) in a radial fashion.
Figure 5 Plot of maximum strain at the solid-liquid interface and minimum density at the bloom center (percent increase over starting density) after three soft reduction roll stations for three cases with increasing amounts of total reduction.
Figure 6 Plot of surface temperature measurements (open circles) as compared to the predicted surface temperature (solid line) from the internal TimkenSteel prediction model. Data are plotted for 14 blooms for 3.5 hours after blooms were cut from caster strand.

Chapter 23

Figure 1 Q-Weld Analysis Flow
Figure 2 Finite Element Mesh for continuous and intermittent welds
Figure 3 Predicted Weld Temperature Distribution
Figure 4 Predicted weld residual stress distribution
Figure 5 Out-of-Plane distortion distribution
Figure 6 Welded panel with continuous weld and intermittent weld
Figure 7 Weld Shrinkages with continuous weld and intermittent weld
Figure 8 Finite Element Mesh for FCAW and HLAW
Figure 9 Predicted Distortion Contour
Figure 10 Distortion Comparison between Arc Welding and HLAW [16]
Figure 11 Input a designed plate shape and a plate initial shape
Figure 12 Predicted heat patterns for plate thermal forming

Chapter 24

Figure 1 Typical microstructure of WC-10%Co cemented carbide.
Figure 2 a) Isoplethal section for 10 wt% Co. b) The C-window as function of the relative Ni and Fe content [8] for 10 wt% Fe-Ni binder. Calculated using the TFCE7 database [7].
Figure 3 a) Cohens reciprocity and b) Hierarchy of models and experimental techniques. [13].
Figure 4 Gradient design in cemented carbides. a) Supercell configuration used to track the (MSD) mean square displacement of atoms (b) by AIMD. The calculated diffusion coefficients (c) are used in DICTRA simulations (d).
Figure 5 Hardness at different temperatures for different binders [11].
Figure 6 W solubility in the W-C-10wt%Co system using the TCFE7 database [7].
Figure 7 W solubility in the W-C-10wt%(Fe,Ni) system using the TCFE7 database [7].

Chapter 25

Figure 1 Schematic of a LMC furnace
Figure 2 The sample casting for validation experiment
Figure 3 comparison of the calculated and experimental results
Figure 4 The calculated mushy zone of the sample casting during LMC directional solidification
Figure 5 Geometry of the blade casting
Figure 6 Mesh generation of the blade casting
Figure 7 Grain structure of the hollow industrial gas turbine blade under the original casting process
Figure 8 Variable withdrawing process for the manufacturing of the industrial gas turbine blade
Figure 9 Calculated mushy zone of the blade casting under the original (constant withdrawal rate) process
Figure 10 Calculated mushy zone of the blade casting under the new process (variable withdrawal rate)
Figure 11 Simulated grain structure of the blade casting under the original and new casting processes

Chapter 26

Figure 1 Flow chart of microstructure level simulation tools. Microstructure images from [2].
Figure 2 left: Melt pool depth simulation vs. experiment; right: Comparison of hatching structure between simulation (white line) and experiment on a flat metal plate
Figure 3 Defect density of the bulk material achieved by different parameter setups. The simulation can represent the experimentally observed effects.
Figure 4 Example temperature cycle over build-time.
Figure 5 a) simple cooling and aging example; b) complex heat treatment; c) evolution of grainboundary δ-phase for 2 different grain sizes (40 μm and 300 μm) at 2 temperatures. Experimental data from [6, 15, 16].
Figure 6 Aspects of the microstructure sensitive strength model.

Chapter 27

Figure 1 Comparison of strain fields predicted with MKS and FEM approaches for a low contrast cubic material. a) Microstructure discretized by 21 × 21 × 21 uniform tessellation with each color representing a distinct crystal orientation selected randomly from the complete cubic fundamental zone. b) Frequency plot of ϵ₁₁ for MKS and FEM distributions. c) and d) show middle slices of strain fields predicted by MKS and FEM approaches, respectively.
Figure 2 Comparison of strain fields predicted with MKS and FEM approaches for low contrast multiphase polycrystal α-β-Ti. (a) Microstructure discretized by 21 × 21 × 21 uniform tessellation with each color representing a distinct crystal orientation selected from the cubic and hexagonal fundamental zones randomly. (b) Distribution of α and β phases where black color represents α phase. (c) Frequency plot of ϵ₁₁ for MKS and FEM distributions. (d) and (e) are the middle slices of strain fields predicted by MKS and FEM approaches, respectively.

Chapter 28

Figure 1 a) Stress vs strain curve, and b) Transformation stress ratio of AE events during compression tests on Ni-Co-Al specimens.
Figure 2 Multiscale model of an embedded SMA particle, represented by MD, into an Al metal matrix, represented by FEM.
Figure 3 Stress vs strain curve during tension-compression cyclic loading of a simulated Ni-Co-Al system at T = 550 K.
Figure 4 Series of snapshots taken at the indicated times of the multiscale model during shock wave propagation generated in the (a,b) z:[001] direction (vertical), and (c,d) x:[110] direction (horizontal). The color of the centered circular particle, also zoomed in the insets, represents the crystallographic state as defined by the CNA as indicated in the figure, while the color of the surrounding continuum represents the level of strain.
Figure 5 (a) Differential virial stress, Δσ, between the transformed SMA particle and the reference inert particle for the two loading directions, [001] and [110]; (b) Content of the B2 (bcc), L1₀ (fcc+hcp), and L1₀ twins (hcp) atoms in the SMA particle with time.

Chapter 29

Figure 1 (a) The solid with dilute and traction-free voids, (b) mesoscopic RVE model with a central void, (c) detailed void shape and parameters
Figure 2 Mesoscale RVE model in the FE calculation and several central void shapes
Figure 3 Relationship of H_i, Σ′_i/Σ_e and Σ_m/Σ_e for the material with n = 5 in (a) x direction (b) y direction and (c) z direction
Figure 4 Condition of Σ_m/Σ_e during the cogging process of the large ingot
Figure 5 Specimens (a) before and (b) after deformation
Figure 6 Comparison of the predicted and measured void volumes
Figure 7 (a)Void volume ratio after the first cogging stage and (b)after the second cogging stage

Chapter 30

Figure 1 ICME Framework Developed for the FEP on Build Residual Stress in Ni Rotors
Figure 2 The Data Management Infrastructure as a Foundation
Figure 3 Database Mirroring
Figure 4 Single Database Administrator Approach
Figure 5 The Need to Involve Subject Matter Experts

Chapter 31

Figure 1 Data used in the Analysis of Carburization Quenching Tempering Process
Figure 2 Bayesian Network for CQT
Figure 3 Optimization Based Model for CQT
Figure 4 Error from inverse inference
Figure 5 Carburization temperature vs time from inverse inference (Symbols are outcomes from inverse inference and line is the best fit exponential relationship line)

Chapter 32

Figure 1 NanoPlasticity Lab output incorporating uncertainty quantification. Figure 1a) shows the Response curve for the yield stress, given a single value for the Poisson's ratio and grain boundary sliding energy barrier, and Gaussian distributions for the elastic constants and Pierel's energy barrier using a first degree polynomial expansion with the Smolyak and Polynomial Chaos with Legendre basis functions method.

Chapter 33

Figure 1 The SMDDP database interfaces with the NIST Materials Data Repository, which is based on the DSpace platform. The project team used data from multiple sources and readily available data management tools.

Chapter 34

Figure 1 System Context Diagram for ICE

Chapter 35

Figure 1 C and Si ranges for cast iron.
Figure 2 Density as a function of carbon equivalent is plotted for gray, compacted, and ductile iron material.
Figure 3 Ultimate Tensile Strength is plotted for gray, compacted, and ductile iron material as a function of carbon equivalent.
Figure 4 Thermal conductivity is plotted for gray, compacted, and ductile iron material as a function of carbon equivalent.
Figure 5 Ultrasonic velocity is plotted for gray, compacted, and ductile iron material as a function of carbon equivalent.

Chapter 36

Figure 1 (a) Upsetting specimen at 27.62% reduction; (b) comparison between the numerical and experimental relative void volume at 27.62% reduction.
Figure 2 Experimental crack phenomenon and the corresponding simulation prediction
Figure 3 (a) Diagram of the inhomogeneous hot forming and position for sampling; (b) grain size comparison between measured and simulation at the sample points
Figure 4 The simulation results of a forging stretching process of SA508-3 steel ingot; (a) accumulated damage factor; (b) relative void volume.
Figure 5 Final shape of the head of nuclear power vessel after multi-step forging in practice.
Figure 6 The simulation results for forming of pressure vessel head; (a) accumulative damage factor; (b) average grain size.

Chapter 37

Figure 1 Solution Strategy. Adapted from [8].
Figure 2 Ternary Plot for Caster
Figure 3 Ternary Plot for Tundish

Chapter 38

Figure 1 Workflow for ICME based approach for gear design
Figure 2 Schematic of the steps involved in IDEM
Figure 3 Schematic of input, intermediate and output variables and their mapping functions
Figure 4 Illustration of the overall solution method
Figure 5 Application of HD-EMI to determine feasible design space

Chapter 39

Figure 1 Integrated approach for rapid prototyping with interconnected components
Figure 2 Two-dimensional draw bending process (left) with resulting spring-back (right)
Figure 3 Influence of process parameters on result (full factorial screening design)
Figure 4 Optimal Young's modulus (x₁) and punch velocity (x₇) for minimum spring-back y (d-optimal design)
Figure 5 Extension of integrated approach with respect to design space
Figure 6 Extension of integrated approach with respect to response space

Chapter 40

Figure 1 The Generic Form of the Compromise Decision Support Problem (cDSP) [4]
Figure 2 The Robust Concept Exploration Method with Error Margin Indices [8]
Figure 3 The Inductive Design Exploration Method [8, 15]

Chapter 41

Figure 1 Schematic illustration of a FSW simulation: (a) side view of a tool consisting of pin and shoulder and (b) FSW configuration
Figure 2 (a) Deductive exploration: Cause and Effect - Structure - Property – Performance
Figure 2 (b) Inductive exploration: Goals and Means - Performance - Property - Structure
Figure 3 Example of FE model for FSW: (a) FE modeling and (b) temperature distribution
Figure 4 Feasible points for satisfying the various requirements of (a) Q_total ≤ 500 kw, P_wt ≤ 40 MW, 2) Q_total ≤ 500 kw, P_wt ≤ 20 MW, and 3) Q_total ≤ 200 kw, P_wt ≤ 40 MW for Q_total
Figure 5 Feasible points for satisfying the requirements of Q_total ≤ 500 kw, P_wt ≤ 40 MW: (a) solution spaces for Q_total in Case II, and solution spaces for P_wt in (b) Case I and (c) Case III.

Chapter 42

Figure 1 The shematic diagram of the milling process
Fig 1 (a)
Fig 1 (b)
Fig 1(c) The graph of immersion angle against Axial Distance
Figure 2a Axial force against axial distance
Figure 2b Axial force against axial distance
Figure 2c Axial force against axial distance
Figure 2d Axial force against axial distance
Figure 3 Cutting forces against cutter rotation angle
Figure 4 (a-b) Coefficient of friction against Axial distance

Preface

This is a collection of manuscripts presented at the 3rd World Congress on Integrated Computational Materials Engineering, a specialty conference organized by The Minerals, Metals & Materials Society (TMS) and the seven congress organizers, and held in Colorado Springs, Colorado, USA, on May 31 to June 4, 2015.

Integrated Computational Materials Engineering (ICME) has received international attention and has been proven to shorten product and process development time, while lowering cost and improving outcome. Building on the great success of the frst two World Congresses on Integrated Computational Materials Engineering, the 3rd World Congress on ICME convened researchers, educators, and engineers to assess the state-of-the-art ICME and determine paths to further the global advancement of ICME. Over 150 authors and attendees from all over the world contributed to this congress in the form of presentations, lively discussions, and manuscripts presented in this volume. The international advisory committee members representing 10 different countries actively participated and promoted the congress.

The specifc topics highlighted during this congress included: ICME Success Stories and Applications with separate sessions on Lightweighting, Composites, Ferrous, and Non-ferrous Applications, ICME Infrastructure and Tools, Modelling at Different Length Scales, Process and Performance Modelling, ICME Implementation and Case Studies. The congress consisted of both plenary sessions and parallel sessions with 20 invited presentations from international experts and a special panel discussion. From the evening poster sessions, outstanding posters were selected for awards, which were presented to the authors at the congress dinner. The congress ended with a closing panel of experts focusing the discussion on the needed next steps forward to help ensure a boarder and more global implementation of ICME in the future.

The 42 papers presented in these proceedings represent a cross section of the presentations and discussions from this congress. It is our hope that the 3rd World Congress on ICME and these proceedings will further the global implementation of ICME, broaden the variety of applications to which ICME is applied, and ultimately help industry design and produce new materials more effciently and effectively.

Acknowledgments

The organizers/editors would like to acknowledge the contributions of a number of people without whom this 3rd World Congress, and the proceedings, would not have been possible.

First, we would like to offer many thanks to the TMS staff who worked tirelessly to make this an outstanding congress and excellent proceedings.

Second, we want to thank the international advisory committee for their input in the planning, the promotion and their participation in the congress. This international committee included:

John Ågren, KTH - Royal Institute of Technology, Sweden
John Allison, University of Michigan, USA
Dipankar Banerjee, Indian Institute of Technology, India
Dennis Dimiduk, U.S. Air Force Research Laboratory, USA
Mathew Halls, Schrodinger, USA
Juergen Hirsch, Hydro Aluminum, Germany
Dorte Juul Jensen, Risoe National Laboratory, Denmark
Nack Kim, Pohang University of Science and Technology, Korea
Peter Lee, Imperial College, UK
Mei Li, Ford Motor Company, USA
Baicheng Liu, Tsinghua University, China
Jiang-Feng Nie, Monash University, Australia
Tresa Pollock, University of California Santa Barbara, USA
Anoush Poursartip, University of British Columbia, Canada
Gary Purdy, McMaster University, Canada
Alejandro Strachan, Purdue University, USA
Anthony Waas, University of Michigan, USA
James Warren, National Institute of Standards and Technology, USA

Finally, we would especially like to acknowledge the fnancial support of all our sponsors. We are also grateful for the participation and contributions of all of the attendees.