标题:Level set-based heterogeneous object modeling and optimization
作者:Liu, Jikai; Chen, Qian; Zheng, Yufan; Ahmad, Rafiq; Tang, Jinyuan; Ma, Yongsheng
作者机构:[Liu, Jikai] Shandong Univ, Sch Mech Engn, Ctr Adv Jet Engn Technol CaJET, Jinan, Shandong, Peoples R China.; [Liu, Jikai] Shandong Univ, Minist Edu 更多
通讯作者:Tang, JY;Ma, YS;Tang, Jinyuan
通讯作者地址:[Tang, JY]Cent S Univ, State Key Lab High Performance Complex Mfg, Changsha, Hunan, Peoples R China;[Ma, YS]Univ Alberta, Dept Mech Engn, Edmonton, AB 更多
来源:COMPUTER-AIDED DESIGN
出版年:2019
卷:110
页码:50-68
DOI:10.1016/j.cad.2019.01.002
关键词:Heterogeneous object modeling; Heterogeneous object optimization; Level; set; Functionally graded material; Sensitivity analysis
摘要:This paper presents a level set-based heterogeneous object (HO) modeling and optimization method. This HO model employs multiple level set functions to build the geometry, utilizes zero-value level set contours as material source profiles, and realizes functionally graded material blending with a signed distance based blending function. More importantly, this HO model supports the concurrent structure and material optimization because of the unified level set framework for both structure and material composition representation. Beyond macro HO, heterogeneous meta-material optimization will be addressed as well. This new model remedies the shortage of traditional HO models that focus more on modeling but less on optimization. About the numerical optimization, design update with the sensitivity result will be carefully discussed, since there includes infeasible terms (in domain integration format). Two strategies will be explored to address this issue: ignoring the infeasible part of the sensitivity, or transforming the sensitivity result into a purely boundary integration-based expression. A few numerical examples will be studied to prove the effectiveness of the proposed HO modeling and optimization method. (C) 2019 Elsevier Ltd. All rights reserved.
收录类别:EI;SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060280460&doi=10.1016%2fj.cad.2019.01.002&partnerID=40&md5=e26c6ad2378f263f558381b89c8b66db
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