An efficient algorithm for generating diverse microstructure sets and delineating properties closures
Abstract
Properties closures delineate the theoretical objective space for materials design problems, allowing designers to make informed trade-offs between competing constraints and target properties. In this paper, we present a new algorithm called hierarchical simplex sampling (HSS) that approximates properties closures more efficiently and faithfully than traditional optimization based approaches. By construction, HSS generates samples of microstructure statistics that span the corresponding microstructure hull. As a result, we also find that HSS can be coupled with synthetic polycrystal generation software to generate diverse sets of microstructures for subsequent mesoscale simulations. Finally, by more broadly sampling the space of possible microstructures, it is anticipated that such diverse microstructure sets will expand our understanding of the influence of microstructure on macroscale effective properties and inform the construction of higher-fidelity mesoscale structure-property models.
- Authors:
-
- Brigham Young Univ., Provo, UT (United States). Dept. of Mechanical Engineering; Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Materials Science and Engineering
- Brigham Young Univ., Provo, UT (United States). Dept. of Mechanical Engineering
- Publication Date:
- Research Org.:
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Brigham Young Univ., Provo, UT (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF); USDOD
- OSTI Identifier:
- 1429062
- Alternate Identifier(s):
- OSTI ID: 1548772
- Grant/Contract Number:
- SC0008926; 1610077
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Acta Materialia
- Additional Journal Information:
- Journal Volume: 147; Journal ID: ISSN 1359-6454
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; 36 MATERIALS SCIENCE; 42 ENGINEERING; microstructure; microstructure hull; properties closure; microstructure design
Citation Formats
Johnson, Oliver K., and Kurniawan, Christian. An efficient algorithm for generating diverse microstructure sets and delineating properties closures. United States: N. p., 2018.
Web. doi:10.1016/j.actamat.2018.01.004.
Johnson, Oliver K., & Kurniawan, Christian. An efficient algorithm for generating diverse microstructure sets and delineating properties closures. United States. https://doi.org/10.1016/j.actamat.2018.01.004
Johnson, Oliver K., and Kurniawan, Christian. Sat .
"An efficient algorithm for generating diverse microstructure sets and delineating properties closures". United States. https://doi.org/10.1016/j.actamat.2018.01.004. https://www.osti.gov/servlets/purl/1429062.
@article{osti_1429062,
title = {An efficient algorithm for generating diverse microstructure sets and delineating properties closures},
author = {Johnson, Oliver K. and Kurniawan, Christian},
abstractNote = {Properties closures delineate the theoretical objective space for materials design problems, allowing designers to make informed trade-offs between competing constraints and target properties. In this paper, we present a new algorithm called hierarchical simplex sampling (HSS) that approximates properties closures more efficiently and faithfully than traditional optimization based approaches. By construction, HSS generates samples of microstructure statistics that span the corresponding microstructure hull. As a result, we also find that HSS can be coupled with synthetic polycrystal generation software to generate diverse sets of microstructures for subsequent mesoscale simulations. Finally, by more broadly sampling the space of possible microstructures, it is anticipated that such diverse microstructure sets will expand our understanding of the influence of microstructure on macroscale effective properties and inform the construction of higher-fidelity mesoscale structure-property models.},
doi = {10.1016/j.actamat.2018.01.004},
journal = {Acta Materialia},
number = ,
volume = 147,
place = {United States},
year = {2018},
month = {2}
}