A Computational Framework for Material Design

A computational framework is proposed that enables the integration of experimental and computational data, a variety of user-selected models, and a computer algorithm to direct a design optimization. To demonstrate this framework, a sample design of a ternary Ni-Al-Cr alloy with a high work-to-necking ratio is presented. This design example illustrates how CALPHAD phase-based, composition and temperature-dependent phase equilibria calculations and precipitation models are coupled with models for elastic and plastic deformation to calculate the stress-strain curves. A genetic algorithm then directs the search within a specific set of composition and processing constraints for the ideal composition and processing profile to optimize the mechanical properties. The initial demonstration of the framework provides a potential solution to initiate the material design process in a large space of composition and processing conditions. This framework can also be used in similar material systems or adapted for other material classes.

[1]  E. Kozeschnik,et al.  Yield strength prediction in Ni-base alloy 718Plus based on thermo-kinetic precipitation simulation , 2014 .

[2]  Rudi Denys,et al.  A generic stress–strain model for metallic materials with two-stage strain hardening behaviour , 2011 .

[3]  A. Ruban,et al.  First-principles modeling of energetic and mechanical properties of Ni–Cr, Ni–Re and Cr–Re random alloys , 2016 .

[4]  Franck Tancret,et al.  Computational thermodynamics and genetic algorithms to design affordable γ′-strengthened nickel–iron based superalloys , 2012 .

[5]  S. van der Zwaag,et al.  Modelling steady state deformation of fcc metals by non-equilibrium thermodynamics , 2007 .

[6]  P. Fratzl,et al.  Modelling of kinetics in multi-component multi-phase systems with spherical precipitates I. – Theory , 2004 .

[7]  N. Saunders,et al.  The coarsening kinetics of γ′ particles in nickel-based alloys , 2002 .

[8]  K. C. Russell.  Nucleation in solids: The induction and steady state effects , 1980 .

[9]  P. Senecal,et al.  NUMERICAL OPTIMIZATION USING THE GEN 4 MICRO-GENETIC ALGORITHM CODE , 2003 .

[10]  Nirupam Chakraborti,et al.  Genetic algorithms in materials design and processing , 2004 .

[11]  Peng Zhang,et al.  Plastic deformation behavior and processing maps of a Ni-based superalloy , 2015 .

[12]  G. B. Olson,et al.  Computational Design of Hierarchically Structured Materials , 1997 .

[13]  B. Shollock,et al.  Crystal plasticity and high-resolution electron backscatter diffraction analysis of full-field polycrystal Ni superalloy strains and rotations under thermal loading , 2014 .

[14]  Gregory B Olson,et al.  Computational materials design and engineering , 2009 .

[15]  B. Sundman,et al.  A thermodynamic database for Ni‐base superalloys , 2001 .

[16]  E. Fisher.  On the elastic moduli of nickel rich NiAl alloy single crystals , 1986 .

[17]  K. Ishida,et al.  Correlation between interfacial energy and phase diagram in ceramic-metal systems , 2001 .

[18]  D. McDowell,et al.  On the Eigenstrain Application of Shot-peened Residual Stresses within a Crystal Plasticity Framework: Application to Ni-base Superalloy Specimens (Postprint) , 2015 .

[19]  Y. Estrin,et al.  Critical grain size for dislocation storage and consequences for strain hardening of nanocrystalline materials , 2010 .

[20]  Surya R. Kalidindi,et al.  Computationally Efficient, Fully Coupled Multiscale Modeling of Materials Phenomena Using Calibrated Localization Linkages , 2012 .

[21]  A. Thompson.  Yielding in nickel as a function of grain or cell size , 1975 .

[22]  M. Albu,et al.  Multimodal size distributions of γ′ precipitates during continuous cooling of UDIMET 720 Li , 2009 .

[23]  Surya R. Kalidindi,et al.  PyMKS: Materials Knowledge System in Python , 2014 .

[24]  Biswanath Samanta,et al.  Artificial neural networks and genetic algorithm for bearing fault detection , 2006, Soft Comput..

[25]  J. Ågren,et al.  Analytical treatment of diffusion during precipitate growth in multicomponent systems , 2008 .

[26]  Tomoo Suzuki,et al.  Solid Solution Hardening of Nickel —Role of Transition Metal and B-subgroup Solutes— , 1986 .

[27]  S. Zwaag,et al.  Irreversible thermodynamics modelling of plastic deformation of metals , 2008 .

[28]  Charles Audet,et al.  Calculating Optimal Conditions for Alloy and Process Design Using Thermodynamic and Properties Databases, the FactSage Software and the Mesh Adaptive Direct Search (MADS) Algorithm , 2010 .

[29]  R. Arróyave,et al.  Describing the deformation behaviour of TRIP and dual phase steels employing an irreversible thermodynamics formulation , 2015 .

[30]  Somnath Ghosh,et al.  Hierarchical crystal plasticity FE model for nickel-based superalloys: Sub-grain microstructures to polycrystalline aggregates , 2015 .

[31]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[32]  R. Reed,et al.  Analysis of the Chemistry of Ni-Base Turbine Disk Superalloys Using An Alloys-By-Design Modeling Approach , 2013, Metallurgical and Materials Transactions A.

[33]  Y. Lin,et al.  Microstructural evolution of a nickel-based superalloy during hot deformation , 2015 .

[34]  R. J. Bishop,et al.  Modern physical metallurgy and materials engineering : science, process, applications , 1999 .

[35]  G. Henkelman,et al.  Optimizing core-shell nanoparticle catalysts with a genetic algorithm. , 2009, The Journal of chemical physics.

[36]  R. Wagner,et al.  Homogeneous Second‐Phase Precipitation , 2013 .

[37]  L. Höglund,et al.  Thermo-Calc & DICTRA, computational tools for materials science , 2002 .

[38]  H. Harada,et al.  Microstructural Evolution and Mechanical Properties of a Ni-Based Superalloy, TMW-4 , 2009 .

[39]  Nirupam Chakraborti,et al.  Evolutionary Design of Nickel-Based Superalloys Using Data-Driven Genetic Algorithms and Related Strategies , 2015 .

[40]  C. Sinclair,et al.  A model for the grain size dependent work hardening of copper , 2006 .

[41]  Jose María Cabrera,et al.  High temperature deformation of Inconel 718 , 2006 .

[42]  B. Sundman,et al.  Applications of Thermodynamics in the Synthesis and Processing of Materials , 1995 .

[43]  Yuri Estrin,et al.  A unified phenomenological description of work hardening and creep based on one-parameter models , 1984 .

[44]  Robert Cimrman.  SfePy - Write Your Own FE Application , 2014, ArXiv.

[45]  N. Saunders,et al.  Using JMatPro to model materials properties and behavior , 2003 .

[46]  S. Kar,et al.  Microstructure based and temperature dependent model of flow behavior of a polycrystalline nickel based superalloy , 2014 .

[47]  D. Dimiduk,et al.  Numerical study of the flow responses and the geometric constraint effects in Ni-base two-phase single crystals using strain gradient plasticity , 2005 .

[48]  W. Shao,et al.  Flow behavior and microstructures of superalloy 718 during high temperature deformation , 2008 .

[49]  Franck Tancret,et al.  Computational thermodynamics, Gaussian processes and genetic algorithms: combined tools to design new alloys , 2013 .

[50]  Jiao Deng,et al.  Hot deformation behavior and processing map of a typical Ni-based superalloy , 2014 .

[51]  Adele P. Peskin,et al.  Informatics Infrastructure for the Materials Genome Initiative , 2016 .

[52]  Tresa M. Pollock,et al.  Strengthening Mechanisms in Polycrystalline Multimodal Nickel-Base Superalloys , 2009 .

[53]  U. F. Kocks,et al.  Kinetics of flow and strain-hardening☆ , 1981 .

[54]  D. Seidman,et al.  Effects of solute concentrations on kinetic pathways in Ni–Al–Cr alloys , 2007, 0706.3916.

[55]  Carlos A. Coello Coello,et al.  A Micro-Genetic Algorithm for Multiobjective Optimization , 2001, EMO.

[56]  M. Ashby,et al.  Deformation-Mechanism Maps: The Plasticity and Creep of Metals and Ceramics , 1982 .

[57]  Surrey Gu,et al.  THE APPLICATION OF CALPHAD CALCULATIONS TO NI-BASED SUPERALLOYS , 2000 .

[58]  Muratahan Aykol,et al.  Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD) , 2013 .

[59]  P. Rivera-Díaz-del-Castillo,et al.  Computational design of nanostructured steels employing irreversible thermodynamics , 2013 .

[60]  Günter Rudolph,et al.  Convergence analysis of canonical genetic algorithms , 1994, IEEE Trans. Neural Networks.

[61]  David L. McDowell,et al.  Linking phase field and finite element modeling for process-structure-property relations of a Ni-base superalloy , 2012 .

[62]  Woei-Ren Wang,et al.  Hot deformation characteristics and strain-dependent constitutive analysis of Inconel 600 superalloy , 2012, Journal of Materials Science.

[63]  Benoit Devincre,et al.  Dislocation dynamics simulations of precipitation hardening in Ni-based superalloys with high γ′ volume fraction , 2009 .

[64]  F. Feyel,et al.  Modelling crystal plasticity by 3D dislocation dynamics and the finite element method: The Discrete-Continuous Model revisited , 2014 .

[65]  Howard Stone,et al.  A modelling approach to yield strength optimisation in a nickel-base superalloy , 2014 .

[66]  R. Reed,et al.  Alloys-By-Design: Application to nickel-based single crystal superalloys , 2009 .

[67]  X. Sauvage,et al.  Modeling of precipitation kinetics in multicomponent systems: Application to model superalloys , 2015 .

[68]  Eric Jones,et al.  SciPy: Open Source Scientific Tools for Python , 2001 .

[69]  P. Jablonski,et al.  Homogenizing a Nickel-Based Superalloy: Thermodynamic and Kinetic Simulation and Experimental Results , 2009 .

[70]  S. Kalidindi.  Modeling the strain hardening response of low SFE FCC alloys , 1998 .

[71]  D. Seidman,et al.  Effects of a tungsten addition on the morphological evolution, spatial correlations and temporal evolution of a model Ni-Al-Cr superalloy , 2007, 0710.3610.

[72]  Gregory B Olson,et al.  Genomic materials design: The ferrous frontier , 2013 .

[73]  Surya R. Kalidindi,et al.  Formulation and calibration of higher-order elastic localization relationships using the MKS approach , 2011 .

[74]  R. J. Bishop,et al.  Chapter 13 – Biomaterials , 1999 .

[75]  Jason Sebastian,et al.  Precipitation model validation in 3RD generation aeroturbine disc alloys , 2008 .

[76]  P. Voorhees,et al.  Ostwald ripening in multicomponent alloys , 2013 .

[77]  Robert F. Singer,et al.  Single-crystal nickel-based superalloys developed by numerical multi-criteria optimization techniques: design based on thermodynamic calculations and experimental validation , 2015 .

[78]  U. Ramamurty,et al.  Tensile Properties of Ni-Based Superalloy 720Li: Temperature and Strain Rate Effects , 2008 .

[79]  Lei Liu,et al.  Application of a modified Ostwald ripening theory in coarsening of γ′ phases in Ni based single crystal superalloys , 2015 .

[80]  Ying Yang,et al.  PANDAT software with PanEngine, PanOptimizer and PanPrecipitation for multi-component phase diagram calculation and materials property simulation , 2009 .

[81]  C. Davis,et al.  Modeling solid solution strengthening in nickel alloys , 1997 .

[82]  F. Tancret,et al.  Multi-objective constrained design of nickel-base superalloys using data mining- and thermodynamics-driven genetic algorithms , 2016 .

[83]  H. Fraser,et al.  Coarsening kinetics of γ′ precipitates in the commercial nickel base Superalloy René 88 DT , 2009 .

[84]  W. Boettinger,et al.  Development of a Diffusion Mobility Database for Co-Based Superalloys , 2002, Journal of Phase Equilibria and Diffusion.

[85]  Surya R. Kalidindi,et al.  A new framework for computationally efficient structure–structure evolution linkages to facilitate high-fidelity scale bridging in multi-scale materials models , 2011 .

[86]  Michel Perez,et al.  Implementation of classical nucleation and growth theories for precipitation , 2008 .

[87]  D. McDowell,et al.  Effects of Microstructure Variability on Intrinsic Fatigue Resistance of Nickel-base Superalloys – A Computational Micromechanics Approach , 2006 .

[88]  Hao Zhou,et al.  Modeling and optimization of the NOx emission characteristics of a tangentially fired boiler with artificial neural networks , 2004 .

[89]  Woei-Ren Wang,et al.  Tensile Flow Behavior in Inconel 600 Alloy Sheet at Elevated Temperatures , 2012 .

[90]  C. Gandin,et al.  Numerical simulation of precipitation in multicomponent Ni-base alloys , 2013 .

[91]  P. Voorhees,et al.  Computer simulations for the prediction of microstructure/property variation in aeroturbine disks , 2004 .

[92]  Y. Estrin.  Constitutive modelling of creep of metallic materials: Some simple recipes , 2007 .

[93]  H. J. McQueen,et al.  Constitutive analysis in hot working , 2002 .

[94]  D. Seidman,et al.  On the nanometer scale phase separation of a low-supersaturation Ni–Al–Cr alloy , 2010 .

[95]  R. Reed,et al.  Modelling of the influence of alloy composition on flow stress in high-strength nickel-based superalloys , 2014 .

[96]  W. Poole,et al.  A mathematical model coupled to CALPHAD to predict precipitation kinetics for multicomponent aluminum alloys , 2012 .

[97]  Mahdi Mahfouf,et al.  Optimal Design of Alloy Steels Using Multiobjective Genetic Algorithms , 2005 .

[98]  Y. Ikeda.  A New Method of Alloy Design Using a Genetic Algorithm and Molecular Dynamics Simulation and Its Application to Nickel-Based Superalloys , 1997 .

[99]  Q. Feng,et al.  Paired Dislocations and Their Interactions with γ′ Particles in Polycrystalline Superalloy GH4037 , 2014, Journal of Materials Engineering and Performance.