Reliability-based topology optimization of geometrically nonlinear structures considering non-probabilistic load parameter and geometric field uncertainties

This paper presents a geometrically nonlinear non-probabilistic reliability-based topology optimization (GN-NRBTO) method that addresses non-probabilistic load parameters and geometric field uncertainties. The changes in load parameter conditions are managed using an ellipsoid convex model, while ge...

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Veröffentlicht in:	Structural and multidisciplinary optimization Jg. 68; H. 9; S. 187
Hauptverfasser:	Zhan, Junjie, Wang, Mingyue, Chen, Jiayi, Xing, Jian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2025 Springer Nature B.V
Schlagworte:	Asymptotes Computational Mathematics and Numerical Analysis Engineering Engineering Design Epistemology Load Manufacturing Neural networks Optimization Parameters Research Paper Structural reliability Theoretical and Applied Mechanics Topology optimization Uncertainty Geometrically nonlinear Non-probabilistic reliability-based optimization Bounded field model Ellipsoid convex model
ISSN:	1615-147X, 1615-1488
Online-Zugang:	Volltext
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