Active learning for the design of polycrystalline textures using conditional normalizing flows

Buzzy, Michael O.; Montes de Oca Zapiain, David; Generale, Adam P.; Kalidindi, Surya R.; Lim, Hojun

doi:10.1016/j.actamat.2024.120537

Title: Active learning for the design of polycrystalline textures using conditional normalizing flows

Journal Article · 12 November 2024 · Acta Materialia

DOI: https://doi.org/10.1016/j.actamat.2024.120537 · OSTI ID:2480227

^[1];

^[2]; Generale, Adam P. ^[1];

^[1];

^[2]

Georgia Institute of Technology, Atlanta, GA (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Generative modeling has opened new avenues for solving previously intractable materials design problems. However, these new opportunities are accompanied by a drastic increase in the required amount of training data. This is in stark juxtaposition to the high expense and difficulty in curating such large materials datasets. In this work, we propose a novel framework for integrating generative models within an active learning loop. Further, this enables the training of generative models with datasets significantly smaller than what has previously been demonstrated, providing a direct route for their application in data constrained environments. The functionality of this framework is then demonstrated by addressing the challenge of designing polycrystalline textures associated with target anisotropic mechanical properties. The developed protocol exhibited a cost reduction between 14 to 18 times over a randomly sampled experimental design.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: NA0003525

OSTI ID:: 2480227

Report Number(s):: SAND--2024-16420J

Journal Information:: Acta Materialia, Journal Name: Acta Materialia Journal Issue: 1 Vol. 284; ISSN 1359-6454

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (52)

Thick anisotropy analysis for AA7B04 aluminum plate using CPFEM and its application for springback prediction in multi-point bending Liu, Chunguo; Li, Ming; Yue, Tao The International Journal of Advanced Manufacturing Technology, Vol. 115, Issue 4 https://doi.org/10.1007/s00170-021-07189-x	journal	May 2021
Concurrent multiscale modeling of microstructural effects on localization behavior in finite deformation solid mechanics Alleman, Coleman N.; Foulk, James W.; Mota, Alejandro Computational Mechanics, Vol. 61, Issue 1-2 https://doi.org/10.1007/s00466-017-1481-5	journal	November 2017
The third Sandia fracture challenge: predictions of ductile fracture in additively manufactured metal Kramer, Sharlotte L. B.; Jones, Amanda; Mostafa, Ahmed International Journal of Fracture, Vol. 218, Issue 1-2 https://doi.org/10.1007/s10704-019-00361-1	journal	July 2019
Deep reinforcement learning methods for structure-guided processing path optimization Dornheim, Johannes; Morand, Lukas; Zeitvogel, Samuel Journal of Intelligent Manufacturing, Vol. 33, Issue 1 https://doi.org/10.1007/s10845-021-01805-z	journal	July 2021
A tutorial on adaptive MCMC Andrieu, Christophe; Thoms, Johannes Statistics and Computing, Vol. 18, Issue 4 https://doi.org/10.1007/s11222-008-9110-y	journal	December 2008
Automated serial sectioning methods for rapid collection of 3-D microstructure data Uchic, Michael D.; Groeber, Michael A.; Rollett, Anthony D. JOM, Vol. 63, Issue 3 https://doi.org/10.1007/s11837-011-0041-2	journal	March 2011
Identifying Structure–Property Relationships Through DREAM.3D Representative Volume Elements and DAMASK Crystal Plasticity Simulations: An Integrated Computational Materials Engineering Approach Diehl, Martin; Groeber, Michael; Haase, Christian JOM, Vol. 69, Issue 5 https://doi.org/10.1007/s11837-017-2303-0	journal	March 2017
Reduced-Order Models for Ranking Damage Initiation in Dual-Phase Composites Using Bayesian Neural Networks Venkatraman, Aditya; Montes de Oca Zapiain, David; Kalidindi, Surya R. JOM, Vol. 72, Issue 12 https://doi.org/10.1007/s11837-020-04387-y	journal	October 2020
Development of a Deep Learning Model for Capturing Plastic Anisotropy–Texture Linkage Park, Taejoon; Montes de Oca Zapiain, David; Pourboghrat, Farhang JOM, Vol. 75, Issue 12 https://doi.org/10.1007/s11837-023-06124-7	journal	October 2023
Perspectives on the Impact of Machine Learning, Deep Learning, and Artificial Intelligence on Materials, Processes, and Structures Engineering Dimiduk, Dennis M.; Holm, Elizabeth A.; Niezgoda, Stephen R. Integrating Materials and Manufacturing Innovation, Vol. 7, Issue 3 https://doi.org/10.1007/s40192-018-0117-8	journal	August 2018
Mechanical Responses of Primary-α Ti Grains in Polycrystalline Samples: Part II—Bayesian Estimation of Crystal-Level Elastic-Plastic Mechanical Properties from Spherical Indentation Measurements Castillo, Andrew R.; Venkatraman, Aditya; Kalidindi, Surya R. Integrating Materials and Manufacturing Innovation, Vol. 10, Issue 1 https://doi.org/10.1007/s40192-021-00204-9	journal	March 2021
Crystallographic texture evolution in bulk deformation processing of FCC metals Kalidindi, S. R.; Bronkhorst, C. A.; Anand, L. Journal of the Mechanics and Physics of Solids, Vol. 40, Issue 3 https://doi.org/10.1016/0022-5096(92)80003-9	journal	January 1992
Incorporation of deformation twinning in crystal plasticity models Kalidindi, Surya R. Journal of the Mechanics and Physics of Solids, Vol. 46, Issue 2 https://doi.org/10.1016/S0022-5096(97)00051-3	journal	February 1998
Plane stress yield function for aluminum alloy sheets—part 1: theory Barlat, F.; Brem, J. C.; Yoon, J. W. International Journal of Plasticity, Vol. 19, Issue 9 https://doi.org/10.1016/S0749-6419(02)00019-0	journal	September 2003
On the prediction of yield surfaces by the crystal plasticity models for fcc polycrystals Kalidindi, S. R.; Schoenfeld, S. E. Materials Science and Engineering: A, Vol. 293, Issue 1-2 https://doi.org/10.1016/S0921-5093(00)01048-0	journal	November 2000
Elastic–plastic property closures for hexagonal close-packed polycrystalline metals using first-order bounding theories Wu, X.; Proust, G.; Knezevic, M. Acta Materialia, Vol. 55, Issue 8 https://doi.org/10.1016/j.actamat.2006.12.010	journal	May 2007
Formulation and calibration of higher-order elastic localization relationships using the MKS approach Fast, Tony; Kalidindi, Surya R. Acta Materialia, Vol. 59, Issue 11 https://doi.org/10.1016/j.actamat.2011.04.005	journal	June 2011
Efficient generation of anisotropic N-field microstructures from 2-point statistics using multi-output Gaussian random fields Robertson, Andreas E.; Kalidindi, Surya R. Acta Materialia, Vol. 232 https://doi.org/10.1016/j.actamat.2022.117927	journal	June 2022
Multi-objective materials bayesian optimization with active learning of design constraints: Design of ductile refractory multi-principal-element alloys Khatamsaz, Danial; Vela, Brent; Singh, Prashant Acta Materialia, Vol. 236 https://doi.org/10.1016/j.actamat.2022.118133	journal	September 2022
Local–Global Decompositions for Conditional Microstructure Generation Robertson, Andreas E.; Kelly, Conlain; Buzzy, Michael Acta Materialia, Vol. 253 https://doi.org/10.1016/j.actamat.2023.118966	journal	July 2023
Statistically conditioned polycrystal generation using denoising diffusion models Buzzy, Michael O.; Robertson, Andreas E.; Kalidindi, Surya R. Acta Materialia, Vol. 267 https://doi.org/10.1016/j.actamat.2024.119746	journal	April 2024
Stress integration-based on finite difference method and its application for anisotropic plasticity and distortional hardening under associated and non-associated flow rules Choi, Hyunsung; Yoon, Jeong Whan Computer Methods in Applied Mechanics and Engineering, Vol. 345 https://doi.org/10.1016/j.cma.2018.10.031	journal	March 2019
A uniquely defined multiplicative elasto-plasticity model with orthotropic yield function and plastic spin Ulz, Manfred H.; Celigoj, Christian C. Computer Methods in Applied Mechanics and Engineering, Vol. 374 https://doi.org/10.1016/j.cma.2020.113565	journal	February 2021
Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties Vlassis, Nikolaos N.; Sun, WaiChing Computer Methods in Applied Mechanics and Engineering, Vol. 413 https://doi.org/10.1016/j.cma.2023.116126	journal	August 2023
Application of microstructure sensitive design to structural components produced from hexagonal polycrystalline metals Fast, Tony; Knezevic, Marko; Kalidindi, Surya R. Computational Materials Science, Vol. 43, Issue 2 https://doi.org/10.1016/j.commatsci.2007.12.002	journal	August 2008
Batch active learning for accelerating the development of interatomic potentials Wilson, Nathan; Willhelm, Daniel; Qian, Xiaoning Computational Materials Science, Vol. 208 https://doi.org/10.1016/j.commatsci.2022.111330	journal	June 2022
LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales Thompson, Aidan P.; Aktulga, H. Metin; Berger, Richard Computer Physics Communications, Vol. 271 https://doi.org/10.1016/j.cpc.2021.108171	journal	February 2022
Orthotropic yield criterion for hexagonal closed packed metals Cazacu, Oana; Plunkett, Brian; Barlat, Frédéric International Journal of Plasticity, Vol. 22, Issue 7 https://doi.org/10.1016/j.ijplas.2005.06.001	journal	July 2006
Delineation of first-order closures for plastic properties requiring explicit consideration of strain hardening and crystallographic texture evolution Knezevic, Marko; Kalidindi, Surya R.; Mishra, Raja K. International Journal of Plasticity, Vol. 24, Issue 2 https://doi.org/10.1016/j.ijplas.2007.05.002	journal	February 2008
Grain-scale experimental validation of crystal plasticity finite element simulations of tantalum oligocrystals Lim, H.; Carroll, J. D.; Battaile, C. C. International Journal of Plasticity, Vol. 60 https://doi.org/10.1016/j.ijplas.2014.05.004	journal	September 2014
Plastic deformation of commercially-pure titanium: experiments and modeling Baral, Madhav; Hama, Takayuki; Knudsen, Erik International Journal of Plasticity, Vol. 105 https://doi.org/10.1016/j.ijplas.2018.02.009	journal	June 2018
Determination of anisotropy and material hardening for aluminum sheet metal Tardif, Nicolas; Kyriakides, Stelios International Journal of Solids and Structures, Vol. 49, Issue 25 https://doi.org/10.1016/j.ijsolstr.2012.01.011	journal	December 2012
Anisotropic plasticity model forms for extruded Al 7079: Part I, calibration Corona, E.; Kramer, S. L. B.; Scherzinger, W. M. International Journal of Solids and Structures, Vol. 213 https://doi.org/10.1016/j.ijsolstr.2020.11.030	journal	March 2021
Query-by-committee improvement with diversity and density in batch active learning Kee, Seho; del Castillo, Enrique; Runger, George Information Sciences, Vol. 454-455 https://doi.org/10.1016/j.ins.2018.05.014	journal	July 2018
Procedures for construction of anisotropic elastic–plastic property closures for face-centered cubic polycrystals using first-order bounding relations Proust, G.; Kalidindi, S. Journal of the Mechanics and Physics of Solids, Vol. 54, Issue 8 https://doi.org/10.1016/j.jmps.2006.01.010	journal	August 2006
A physically based model of temperature and strain rate dependent yield in BCC metals: Implementation into crystal plasticity Lim, Hojun; Battaile, Corbett C.; Carroll, Jay D. Journal of the Mechanics and Physics of Solids, Vol. 74 https://doi.org/10.1016/j.jmps.2014.10.003	journal	January 2015
Perspective: Machine learning in experimental solid mechanics Brodnik, N. R.; Muir, C.; Tulshibagwale, N. Journal of the Mechanics and Physics of Solids, Vol. 173 https://doi.org/10.1016/j.jmps.2023.105231	journal	April 2023
Predicting plastic anisotropy using crystal plasticity and Bayesian neural network surrogate models Montes de Oca Zapiain, David; Lim, Hojun; Park, Taejoon Materials Science and Engineering: A, Vol. 833 https://doi.org/10.1016/j.msea.2021.142472	journal	January 2022
Microstructure design using machine learning generated low dimensional and continuous design space Jung, Jaimyun; Yoon, Jae Ik; Park, Hyung Keun Materialia, Vol. 11 https://doi.org/10.1016/j.mtla.2020.100690	journal	June 2020
Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials Dan, Yabo; Zhao, Yong; Li, Xiang npj Computational Materials, Vol. 6, Issue 1 https://doi.org/10.1038/s41524-020-00352-0	journal	June 2020
Inverse design of two-dimensional materials with invertible neural networks Fung, Victor; Zhang, Jiaxin; Hu, Guoxiang npj Computational Materials, Vol. 7, Issue 1 https://doi.org/10.1038/s41524-021-00670-x	journal	December 2021
Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review Cowles, Mary Kathryn; Carlin, Bradley P. Journal of the American Statistical Association, Vol. 91, Issue 434 https://doi.org/10.1080/01621459.1996.10476956	journal	June 1996
Modelling the plastic anisotropy of aluminum alloy 3103 sheets by polycrystal plasticity Zhang, K.; Holmedal, B.; Hopperstad, O. S. Modelling and Simulation in Materials Science and Engineering, Vol. 22, Issue 7 https://doi.org/10.1088/0965-0393/22/7/075015	journal	October 2014
BayesFlow: Learning Complex Stochastic Models With Invertible Neural Networks Radev, Stefan T.; Mertens, Ulf K.; Voss, Andreas IEEE Transactions on Neural Networks and Learning Systems, Vol. 33, Issue 4 https://doi.org/10.1109/TNNLS.2020.3042395	journal	April 2022
Normalizing Flows: An Introduction and Review of Current Methods Kobyzev, Ivan; Prince, Simon; Brubaker, Marcus IEEE Transactions on Pattern Analysis and Machine Intelligence https://doi.org/10.1109/TPAMI.2020.2992934	journal	January 2020
Guiding and Trapping Cracks With Compliant Inclusions for Enhancing Toughness of Brittle Composite Materials Brodnik, Neal R.; Hsueh, Chun-Jen; Faber, Katherine T. Journal of Applied Mechanics, Vol. 87, Issue 3 https://doi.org/10.1115/1.4045682	journal	January 2020
The materials innovation ecosystem: A key enabler for the Materials Genome Initiative McDowell, David L.; Kalidindi, Surya R. MRS Bulletin, Vol. 41, Issue 4 https://doi.org/10.1557/mrs.2016.61	journal	April 2016
Active Learning with Statistical Models Cohn, D. A.; Ghahramani, Z.; Jordan, M. I. Journal of Artificial Intelligence Research, Vol. 4 https://doi.org/10.1613/jair.295	journal	January 1996
Stochastic Design Optimization of Microstructural Features Using Linear Programming for Robust Design Acar, Pinar; Sundararaghavan, Veera AIAA Journal, Vol. 57, Issue 1 https://doi.org/10.2514/1.J057377	journal	January 2019
Efficient Exploration of Microstructure-Property Spaces via Active Learning Morand, Lukas; Link, Norbert; Iraki, Tarek Frontiers in Materials, Vol. 8 https://doi.org/10.3389/fmats.2021.824441	journal	February 2022
Digital Twins for Materials Kalidindi, Surya R.; Buzzy, Michael; Boyce, Brad L. Frontiers in Materials, Vol. 9 https://doi.org/10.3389/fmats.2022.818535	journal	March 2022
Development of a Robust CNN Model for Capturing Microstructure-Property Linkages and Building Property Closures Supporting Material Design Mann, Andrew; Kalidindi, Surya R. Frontiers in Materials, Vol. 9 https://doi.org/10.3389/fmats.2022.851085	journal	March 2022

Similar Records

16. 7% efficient, laser textured, buried contact polycrystalline silicon solar cell

Journal Article · 1989 · Applied Physics Letters; (USA) · OSTI ID:5206522

Zolper, J C; Narayanan, S; Wenham, S R; +1 more

Texturing of polycrystalline silicon

Book · 1994 · OSTI ID:191072

Stocks, M J; Carr, A J; Blakers, A W

A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds

Journal Article · 2016 · Scientific Reports · OSTI ID:1377526

de Jong, Maarten; Chen, Wei; Notestine, Randy; +5 more

Related Subjects

36 MATERIALS SCIENCE
Active learning
Plastic anisotropy
Texture

Title: Active learning for the design of polycrystalline textures using conditional normalizing flows

Citation Formats

References (52)

Similar Records

Related Subjects