On the Use of Fidelity Transformation Method for Stress‐Constrained Reliability‐Based Topology Optimization of Continuum Structure With High Accuracy

ABSTRACT Stress‐constrained reliability‐based topology optimization (RBTO) method has incurred considerable attention owing to its superiority of enhancing the structural safety. However, the traditional reliability methods encounter inaccurate issue for evaluating the failure probability of stress‐constrained structure. In this work, the failure mechanism of the stress‐constrained RBTO problem is analyzed for continuum structure, which reveals that the correlation between different stress constraints and utilization of aggregation function significantly impacts the accuracy. Then, a novel stress‐constrained system RBTO framework is suggested to enhance computational efficiency and accuracy for system reliability analysis. Furthermore, an accurate and efficient semi‐analytical method is suggested to approximate the performance functions through first‐order Taylor series expansion, in which the intricate implicit expressions are substituted by the straightforward analytic expressions. In addition, the fidelity transformation method is employed for converting the semi‐analytical RBTO method to classical RBTO method. To demonstrate the practicability of the proposed framework, three benchmark cases, including 2D and 3D problems, are tested. The results reveal that the proposed framework achieves high accuracy and efficiency.

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Publication Details

Journal
International Journal for Numerical Methods in Engineering
Published
2024-10-09
DOI
https://doi.org/10.1002/nme.7602
Citations
8
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
2.09

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article

On the Use of Fidelity Transformation Method for Stress‐Constrained Reliability‐Based Topology Optimization of Continuum Structure With High Accuracy

Peng Hao, Q. Q. Qian, Zeng Meng
8 citations
International Journal for Numerical Methods in Engineering
Topology Optimization in Engineering
2.09
article

On the Use of Fidelity Transformation Method for Stress‐Constrained Reliability‐Based Topology Optimization of Continuum Structure With High Accuracy

Peng Hao, Q. Q. Qian, Zeng Meng
article en
8 citations

Abstract

ABSTRACT Stress‐constrained reliability‐based topology optimization (RBTO) method has incurred considerable attention owing to its superiority of enhancing the structural safety. However, the traditional reliability methods encounter inaccurate issue for evaluating the failure probability of stress‐constrained structure. In this work, the failure mechanism of the stress‐constrained RBTO problem is analyzed for continuum structure, which reveals that the correlation between different stress constraints and utilization of aggregation function significantly impacts the accuracy. Then, a novel stress‐constrained system RBTO framework is suggested to enhance computational efficiency and accuracy for system reliability analysis. Furthermore, an accurate and efficient semi‐analytical method is suggested to approximate the performance functions through first‐order Taylor series expansion, in which the intricate implicit expressions are substituted by the straightforward analytic expressions. In addition, the fidelity transformation method is employed for converting the semi‐analytical RBTO method to classical RBTO method. To demonstrate the practicability of the proposed framework, three benchmark cases, including 2D and 3D problems, are tested. The results reveal that the proposed framework achieves high accuracy and efficiency.

International Journal for Numerical Methods in EngineeringVol. 126(1)
Hefei University of Technology (CN), Dalian University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 14%
Topology Optimization in Engineering
2.09
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On the Use of Fidelity Transformation Method for Stress‐Constrained Reliability‐Based Topology Optimization of Continuum Structure With High Accuracy — Peng Hao, Q. Q. Qian, et al. · International Journal for Numerical Methods in Engineering (2024) | TGRS Research Map | TGRS