A sequential optimization framework for simultaneous design variables optimization and probability uncertainty allocation

In engineering design, the performance of the system and the budget of design uncertainty should be balanced, which means that it is best to optimize design variables and allocate the manufacturing uncertainty simultaneously. This work formulates this problem as an uncertainty optimization problem,...

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Bibliographic Details
Published in:Structural and multidisciplinary optimization 2021-03, Vol.63 (3), p.1307-1325
Main Authors: Fang, Hai, Gong, Chunlin, Li, Chunna, Zhang, Yunwei, Da Ronch, Andrea
Format: Article
Language:English
Subjects:
Accuracy
Cantilever beams
Computational Mathematics and Numerical Analysis
Design engineering
Design optimization
Engineering
Engineering Design
I beams
Mathematical problems
Optimization
Polynomials
Research Paper
Theoretical and Applied Mechanics
Uncertainty analysis
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Summary:In engineering design, the performance of the system and the budget of design uncertainty should be balanced, which means that it is best to optimize design variables and allocate the manufacturing uncertainty simultaneously. This work formulates this problem as an uncertainty optimization problem, where the input uncertainty is modeled by the probability method and both the design variables and the uncertainty magnitude are included in the optimization variables. A sequence optimization framework is proposed to solve the optimization problem. The Taylor-based first-order method is used to translate the probability constraint into a deterministic constraint. A correction coefficient is calculated by the dimensional adaptive polynomial chaos expansion method to improve the accuracy of the uncertainty analysis. The constraint translation and the correction coefficient calculation are executed sequentially. The accuracy and effectiveness of the proposed framework are validated by three benchmark problems, including a mathematical problem, a cantilever I-beam, and a ten-bar truss case.
ISSN:1615-147X
1615-1488
DOI:10.1007/s00158-020-02759-1