Cited 0 time in
A two-phase topology optimization method for manufacturable functionally-graded lattice structures with casting process
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Yi, Bing | - |
| dc.contributor.author | Liu, Long | - |
| dc.contributor.author | Wang, Tianci | - |
| dc.contributor.author | Peng, Xiang | - |
| dc.contributor.author | Yoon, Gil-Ho | - |
| dc.date.accessioned | 2026-06-17T03:00:13Z | - |
| dc.date.available | 2026-06-17T03:00:13Z | - |
| dc.date.issued | 2026-12 | - |
| dc.identifier.issn | 0307-904X | - |
| dc.identifier.issn | 1872-8480 | - |
| dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213325 | - |
| dc.description.abstract | Topology optimization often yields intricate truss-like structures that are challenging to fabricate using conventional manufacturing methods. To deal with this issue, this paper proposes a two-phase topology optimization method to enhance the manufacturability of functionally-graded lattice structures with the casting process. Specifically, the minimal length scales of two phases, including void and solid phases are proposed to exactly align with the manufacturing constraints of the final product and its mold. Additionally, a penalty function is employed to eliminate grey elements, ensuring a clear, easily manufacturable solution for both the cast product and its mold. Finally, the two-phase-based topology optimization of both conventional continuous structures and functionally-graded lattice structures is formulated, and the product and its mold are optimized simultaneously via the Method of Moving Asymptotes (MMA). Numerical examples of both the conventional SIMP method and the integration of functionally-graded lattice structures are used to demonstrate the effectiveness of the proposed method in simultaneously optimizing both the product and casting. To validate the approach, a functionally-graded lattice structure was successfully cast using aluminum alloy, confirming the practical applicability of the method. | - |
| dc.format.extent | 14 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | ELSEVIER SCIENCE INC | - |
| dc.title | A two-phase topology optimization method for manufacturable functionally-graded lattice structures with casting process | - |
| dc.type | Article | - |
| dc.publisher.location | 미국 | - |
| dc.identifier.doi | 10.1016/j.apm.2026.117097 | - |
| dc.identifier.scopusid | 2-s2.0-105040687622 | - |
| dc.identifier.wosid | 001788391400001 | - |
| dc.identifier.bibliographicCitation | APPLIED MATHEMATICAL MODELLING, v.160, pp 1 - 14 | - |
| dc.citation.title | APPLIED MATHEMATICAL MODELLING | - |
| dc.citation.volume | 160 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 14 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Engineering | - |
| dc.relation.journalResearchArea | Mathematics | - |
| dc.relation.journalResearchArea | Mechanics | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Multidisciplinary | - |
| dc.relation.journalWebOfScienceCategory | Mathematics, Interdisciplinary Applications | - |
| dc.relation.journalWebOfScienceCategory | Mechanics | - |
| dc.subject.keywordPlus | MINIMUM LENGTH SCALE | - |
| dc.subject.keywordPlus | DESIGN | - |
| dc.subject.keywordPlus | SCHEME | - |
| dc.subject.keywordAuthor | Minimal length scale | - |
| dc.subject.keywordAuthor | Two-phase | - |
| dc.subject.keywordAuthor | Functionally-graded lattice structure | - |
| dc.subject.keywordAuthor | Topology optimization | - |
| dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0307904X26003586?via%3Dihub | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
222, Wangsimni-ro, Seongdong-gu, Seoul, 04763, Korea+82-2-2220-1366
COPYRIGHT © 2024 HANYANG UNIVERSITY.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
