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A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects

Jie Gao et al · KeAi Communications Co., Ltd · 2020

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Abstract Topology Optimization (TO) is a powerful numerical technique to determine the optimal material layout in a design domain, which has accepted considerable developments in recent years. The classic Finite Element Method (FEM) is applied to compute the unknown structural responses in TO. However, several numerical deficiencies of the FEM significantly influence the effectiveness and efficiency of TO. In order to eliminate the negative influence of the FEM on TO, IsoGeometric Analysis (IGA) has become a promising alternative due to its unique feature that the Computer-Aided Design (CAD) model and Computer-Aided Engineering (CAE) model can be unified into a same mathematical model. In the paper, the main intention is to provide a comprehensive overview for the developments of Isogeometric Topology Optimization (ITO) in methods and applications. Finally, some prospects for the developments of ITO in the future are also presented.

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APA 7

al, J. G. E. (2020). A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects. https://doi.org/10.1186/s10033-020-00503-w

MLA

al, Jie Gao et. "A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects." 2020. https://doi.org/10.1186/s10033-020-00503-w.

Chicago

al, Jie Gao et. 2020. "A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects.". https://doi.org/10.1186/s10033-020-00503-w.

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al, J. G. E. 2020, A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects, KeAi Communications Co, Ltd, available at: https://doi.org/10.1186/s10033-020-00503-w [Accessed 10 Aug. 2026].

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Title
A Comprehensive Review of Isogeometric Topology Optimization: Methods, Applications and Prospects
Author / contributors
Jie Gao et al
Publisher
KeAi Communications Co., Ltd
Publication year
2020
ISSN
1000-9345
ISSN
1000-9345
Language
English

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