Level set-based heterogeneous object modeling and optimization.
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| Title: | Level set-based heterogeneous object modeling and optimization. |
|---|---|
| Authors: | Liu, Jikai1,2, Chen, Qian3, Zheng, Yufan4, Ahmad, Rafiq4, Tang, Jinyuan1,5 jytangcsu@163.com, Ma, Yongsheng1,4 yongsheng.ma@ualberta.ca |
| Source: | Computer-Aided Design. May2019, Vol. 110, p50-68. 19p. |
| Subjects: | Object monitors (Computer software), Program transformation, Concurrent engineering, Level set methods, Sensitivity analysis |
| Abstract: | Abstract 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. Highlights • Presents a level set-based heterogeneous object (HO) modeling and optimization method. • Features in topology optimization of functionally graded structures • Explores the optimal designs with different material blending coefficients. • Develops the accurate sensitivity result rather than ignoring the non-implementable part of the original sensitivity. • Investigates functionally graded meta-material optimization. [ABSTRACT FROM AUTHOR] |
| Copyright of Computer-Aided Design is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 134863885 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Level set-based heterogeneous object modeling and optimization. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liu%2C+Jikai%22">Liu, Jikai</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Qian%22">Chen, Qian</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Zheng%2C+Yufan%22">Zheng, Yufan</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Ahmad%2C+Rafiq%22">Ahmad, Rafiq</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Tang%2C+Jinyuan%22">Tang, Jinyuan</searchLink><relatesTo>1,5</relatesTo><i> jytangcsu@163.com</i><br /><searchLink fieldCode="AR" term="%22Ma%2C+Yongsheng%22">Ma, Yongsheng</searchLink><relatesTo>1,4</relatesTo><i> yongsheng.ma@ualberta.ca</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computer-Aided+Design%22">Computer-Aided Design</searchLink>. May2019, Vol. 110, p50-68. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Object+monitors+%28Computer+software%29%22">Object monitors (Computer software)</searchLink><br /><searchLink fieldCode="DE" term="%22Program+transformation%22">Program transformation</searchLink><br /><searchLink fieldCode="DE" term="%22Concurrent+engineering%22">Concurrent engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Level+set+methods%22">Level set methods</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract 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. Highlights • Presents a level set-based heterogeneous object (HO) modeling and optimization method. • Features in topology optimization of functionally graded structures • Explores the optimal designs with different material blending coefficients. • Develops the accurate sensitivity result rather than ignoring the non-implementable part of the original sensitivity. • Investigates functionally graded meta-material optimization. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computer-Aided Design is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.cad.2019.01.002 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 50 Subjects: – SubjectFull: Object monitors (Computer software) Type: general – SubjectFull: Program transformation Type: general – SubjectFull: Concurrent engineering Type: general – SubjectFull: Level set methods Type: general – SubjectFull: Sensitivity analysis Type: general Titles: – TitleFull: Level set-based heterogeneous object modeling and optimization. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liu, Jikai – PersonEntity: Name: NameFull: Chen, Qian – PersonEntity: Name: NameFull: Zheng, Yufan – PersonEntity: Name: NameFull: Ahmad, Rafiq – PersonEntity: Name: NameFull: Tang, Jinyuan – PersonEntity: Name: NameFull: Ma, Yongsheng IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 00104485 Numbering: – Type: volume Value: 110 Titles: – TitleFull: Computer-Aided Design Type: main |
| ResultId | 1 |