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Title: 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:
 [1]; ORCiD logo [2]
  1. 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
  2. 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) (SC-22); National Science Foundation (NSF); USDOD
OSTI Identifier:
1429062
Grant/Contract Number:  
SC0008926; 1610077
Resource Type:
Journal Article: 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. doi: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. doi:10.1016/j.actamat.2018.01.004.
@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 = {Sat Feb 03 00:00:00 EST 2018},
month = {Sat Feb 03 00:00:00 EST 2018}
}

Journal Article:
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