Pragmatic generative optimization of novel structural lattice metamaterials with machine learning

Garland, Anthony P.; White, Benjamin C.; Jensen, Scott C.; Boyce, Brad L.

doi:10.1016/j.matdes.2021.109632

Pragmatic generative optimization of novel structural lattice metamaterials with machine learning

Journal Article · Sat May 01 00:00:00 EDT 2021 · Materials & Design

DOI:https://doi.org/10.1016/j.matdes.2021.109632· OSTI ID:1768685

Garland, Anthony P.; White, Benjamin C.; Jensen, Scott C.; Boyce, Brad L.

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Sponsoring Organization:: USDOE

OSTI ID:: 1768685

Journal Information:: Materials & Design, Journal Name: Materials & Design Journal Issue: C Vol. 203; ISSN 0264-1275

Publisher:: ElsevierCopyright Statement

Country of Publication:: United Kingdom

Language:: English

References (44)

New Twists of 3D Chiral Metamaterials Fernandez‐Corbaton, I.; Rockstuhl, C.; Ziemke, P. Advanced Materials, Vol. 31, Issue 26 https://doi.org/10.1002/adma.201807742	journal	February 2019
Probabilistic Representation and Inverse Design of Metamaterials Based on a Deep Generative Model with Semi‐Supervised Learning Strategy Ma, Wei; Cheng, Feng; Xu, Yihao Advanced Materials, Vol. 31, Issue 35 https://doi.org/10.1002/adma.201901111	journal	July 2019
Leveraging of MEMS Technologies for Optical Metamaterials Applications Ren, Zhihao; Chang, Yuhua; Ma, Yiming Advanced Optical Materials https://doi.org/10.1002/adom.201900653	journal	July 2019
Machine‐Learning Designs of Anisotropic Digital Coding Metasurfaces Zhang, Qian; Liu, Che; Wan, Xiang Advanced Theory and Simulations, Vol. 2, Issue 2 https://doi.org/10.1002/adts.201800132	journal	September 2018
Effect of Constituent Materials on Composite Performance: Exploring Design Strategies via Machine Learning Chen, Chun‐Teh; Gu, Grace X. Advanced Theory and Simulations https://doi.org/10.1002/adts.201900056	journal	April 2019
Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active Learning Chen, Chun‐Teh; Gu, Grace X. Advanced Science, Vol. 7, Issue 5 https://doi.org/10.1002/advs.201902607	journal	January 2020
A hierarchical model for concurrent material and topology optimisation of three-dimensional structures Coelho, P. G.; Fernandes, P. R.; Guedes, J. M. Structural and Multidisciplinary Optimization, Vol. 35, Issue 2 https://doi.org/10.1007/s00158-007-0141-3	journal	June 2007
The Sandia Fracture Challenge: blind round robin predictions of ductile tearing Boyce, B. L.; Kramer, S. L. B.; Fang, H. E. International Journal of Fracture, Vol. 186, Issue 1-2 https://doi.org/10.1007/s10704-013-9904-6	journal	January 2014
Evolution of damage and failure in an additively manufactured 316L SS structure: experimental reinvestigation of the third Sandia fracture challenge Kramer, S. L. B.; Ivanoff, T. A.; Madison, J. D. International Journal of Fracture, Vol. 218, Issue 1-2 https://doi.org/10.1007/s10704-019-00357-x	journal	March 2019
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
Materials with prescribed constitutive parameters: An inverse homogenization problem Sigmund, Ole International Journal of Solids and Structures, Vol. 31, Issue 17 https://doi.org/10.1016/0020-7683(94)90154-6	journal	September 1994
CTH: A three-dimensional shock wave physics code McGlaun, J. M.; Thompson, S. L.; Elrick, M. G. International Journal of Impact Engineering, Vol. 10, Issue 1-4 https://doi.org/10.1016/0734-743X(90)90071-3	journal	January 1990
Design for Additive Manufacturing: Trends, opportunities, considerations, and constraints Thompson, Mary Kathryn; Moroni, Giovanni; Vaneker, Tom CIRP Annals, Vol. 65, Issue 2 https://doi.org/10.1016/j.cirp.2016.05.004	journal	January 2016
Prediction and optimization of mechanical properties of composites using convolutional neural networks Abueidda, Diab W.; Almasri, Mohammad; Ammourah, Rami Composite Structures, Vol. 227 https://doi.org/10.1016/j.compstruct.2019.111264	journal	November 2019
Cushion performance of cylindrical negative stiffness structures: Analysis and optimization Wang, Bing; Tan, Xiaojun; Zhu, Shaowei Composite Structures, Vol. 227 https://doi.org/10.1016/j.compstruct.2019.111276	journal	November 2019
Design and validation of metamaterials for multiple structural stop bands in waveguides Claeys, Claus; Rocha de Melo Filho, Noé Geraldo; Van Belle, Lucas Extreme Mechanics Letters, Vol. 12 https://doi.org/10.1016/j.eml.2016.08.005	journal	April 2017
De novo composite design based on machine learning algorithm Gu, Grace X.; Chen, Chun-Teh; Buehler, Markus J. Extreme Mechanics Letters, Vol. 18 https://doi.org/10.1016/j.eml.2017.10.001	journal	January 2018
Mechanical responses of titanium 3D kagome lattice structure manufactured by selective laser melting Wei, Kai; Yang, Qidong; Ling, Bin Extreme Mechanics Letters, Vol. 23 https://doi.org/10.1016/j.eml.2018.07.001	journal	September 2018
Stepwise graded struts for maximizing energy absorption in lattices Mueller, Jochen; Shea, Kristina Extreme Mechanics Letters, Vol. 25 https://doi.org/10.1016/j.eml.2018.10.006	journal	November 2018
Coulombic friction in metamaterials to dissipate mechanical energy Garland, Anthony P.; Adstedt, Katarina M.; Casias, Zachary J. Extreme Mechanics Letters, Vol. 40 https://doi.org/10.1016/j.eml.2020.100847	journal	October 2020
Mechanical properties and energy absorption capability of functionally graded F2BCC lattice fabricated by SLM Al-Saedi, Dheyaa S. J.; Masood, S. H.; Faizan-Ur-Rab, Muhammad Materials & Design, Vol. 144 https://doi.org/10.1016/j.matdes.2018.01.059	journal	April 2018
Mechanical properties and deformation behavior of additively manufactured lattice structures of stainless steel Köhnen, Patrick; Haase, Christian; Bültmann, Jan Materials & Design, Vol. 145 https://doi.org/10.1016/j.matdes.2018.02.062	journal	May 2018
Failure and energy absorption characteristics of four lattice structures under dynamic loading Jin, Nan; Wang, Fuchi; Wang, Yangwei Materials & Design, Vol. 169 https://doi.org/10.1016/j.matdes.2019.107655	journal	May 2019
SLM lattice structures: Properties, performance, applications and challenges Maconachie, Tobias; Leary, Martin; Lozanovski, Bill Materials & Design, Vol. 183 https://doi.org/10.1016/j.matdes.2019.108137	journal	December 2019
Multi-morphology lattices lead to improved plastic energy absorption Alberdi, Ryan; Dingreville, Rémi; Robbins, Joshua Materials & Design, Vol. 194 https://doi.org/10.1016/j.matdes.2020.108883	journal	September 2020
Intelligent layout design of curvilinearly stiffened panels via deep learning-based method Hao, Peng; Liu, Dachuan; Zhang, Kunpeng Materials & Design, Vol. 197 https://doi.org/10.1016/j.matdes.2020.109180	journal	January 2021
Voxel design of additively manufactured digital material with customized thermomechanical properties Yuan, Chao; Wang, Fangfang; Rosen, David W. Materials & Design, Vol. 197 https://doi.org/10.1016/j.matdes.2020.109205	journal	January 2021
A mechanical property evaluation of graded density Al-Si10-Mg lattice structures manufactured by selective laser melting Maskery, I.; Aboulkhair, N. T.; Aremu, A. O. Materials Science and Engineering: A, Vol. 670 https://doi.org/10.1016/j.msea.2016.06.013	journal	July 2016
Multiphysical Digital Coding Metamaterials for Independent Control of Broadband Electromagnetic and Acoustic Waves with a Large Variety of Functions Zhang, Cheng; Cao, Wen Kang; Yang, Jin ACS Applied Materials & Interfaces, Vol. 11, Issue 18 https://doi.org/10.1021/acsami.9b02490	journal	April 2019
Deep-Learning-Enabled On-Demand Design of Chiral Metamaterials Ma, Wei; Cheng, Feng; Liu, Yongmin ACS Nano, Vol. 12, Issue 6 https://doi.org/10.1021/acsnano.8b03569	journal	May 2018
Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design Lookman, Turab; Balachandran, Prasanna V.; Xue, Dezhen npj Computational Materials, Vol. 5, Issue 1 https://doi.org/10.1038/s41524-019-0153-8	journal	February 2019
Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment Gu, Grace X.; Chen, Chun-Teh; Richmond, Deon J. Materials Horizons, Vol. 5, Issue 5 https://doi.org/10.1039/C8MH00653A	journal	January 2018
Acoustic cloaking in three dimensions using acoustic metamaterials Chen, Huanyang; Chan, C. T. Applied Physics Letters, Vol. 91, Issue 18 https://doi.org/10.1063/1.2803315	journal	October 2007
A constitutive model for metals applicable at high‐strain rate Steinberg, D. J.; Cochran, S. G.; Guinan, M. W. Journal of Applied Physics, Vol. 51, Issue 3 https://doi.org/10.1063/1.327799	journal	March 1980
A constitutive model for strain rates from 10 ⁻ ⁴ to 10 ⁶ s ⁻ ¹ Steinberg, D. J.; Lund, C. M. Journal of Applied Physics, Vol. 65, Issue 4 https://doi.org/10.1063/1.342968	journal	February 1989
Artificial intelligence design algorithm for nanocomposites optimized for shear crack resistance Yu, Chi-Hua; Qin, Zhao; Buehler, Markus J. Nano Futures, Vol. 3, Issue 3 https://doi.org/10.1088/2399-1984/ab36f0	journal	August 2019
A fast and elitist multiobjective genetic algorithm: NSGA-II Deb, K.; Pratap, A.; Agarwal, S. IEEE Transactions on Evolutionary Computation, Vol. 6, Issue 2 https://doi.org/10.1109/4235.996017	journal	April 2002
Ultralight, ultrastiff mechanical metamaterials Zheng, X.; Lee, H.; Weisgraber, T. H. Science, Vol. 344, Issue 6190 https://doi.org/10.1126/science.1252291	journal	June 2014
Three-dimensional mechanical metamaterials with a twist Frenzel, Tobias; Kadic, Muamer; Wegener, Martin Science, Vol. 358, Issue 6366 https://doi.org/10.1126/science.aao4640	journal	November 2017
A survey on Image Data Augmentation for Deep Learning Shorten, Connor; Khoshgoftaar, Taghi M. Journal of Big Data, Vol. 6, Issue 1 https://doi.org/10.1186/s40537-019-0197-0	journal	July 2019
Soft optical metamaterials Chen, Yixin; Ai, Bin; Wong, Zi Jing Nano Convergence, Vol. 7, Issue 1 https://doi.org/10.1186/s40580-020-00226-7	journal	May 2020
Active-learning and materials design: the example of high glass transition temperature polymers Kim, Chiho; Chandrasekaran, Anand; Jha, Anurag MRS Communications, Vol. 9, Issue 3 https://doi.org/10.1557/mrc.2019.78	journal	June 2019
Fastai: A Layered API for Deep Learning Howard, Jeremy; Gugger, Sylvain Information, Vol. 11, Issue 2 https://doi.org/10.3390/info11020108	journal	February 2020
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations Hanin, Boris Mathematics, Vol. 7, Issue 10 https://doi.org/10.3390/math7100992	journal	October 2019

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