Threshold shift method for reliability-based design optimization

Structural and Multidisciplinary Optimization - Tập 60 - Trang 2053-2072 - 2019
Somdatta Goswami1, Souvik Chakraborty2,3, Rajib Chowdhury4, Timon Rabczuk5
1Institute of Structural Mechanics, Bauhaus-Universität Weimar, Weimar, Germany
2Center for Informatics and Computational Science, University of Notre Dame, Notre Dame, USA
3Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, USA
4Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee, India
5Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

Tóm tắt

We present a novel approach, referred to as the “threshold shift method” (TSM), for reliability-based design optimization (RBDO). The proposed approach is similar in spirit with the sequential optimization and reliability analysis (SORA) method where the RBDO problem is decoupled into an optimization and a reliability analysis problem. However, unlike SORA that utilizes shift vector to shift the design variables within a constraint (independently), in TSM, we propose to shift the threshold of the constraints. We argue that modifying a constraint, either by shifting the design variables (SORA) or by shifting the threshold of the constraints (TSM), influences the other constraints of the system. Therefore, we propose to determine the thresholds for all the constraints by solving a single optimization problem. Additionally, the proposed TSM is equipped with an active-constraint determination scheme. To make the method scalable, a practical algorithm for TSM that utilizes two surrogate models is proposed. Unlike the conventional RBDO methods, the proposed approach has the ability to handle highly non-linear probabilistic constraints. The performance of the proposed approach is examined on six benchmark problems selected from the literature. The proposed approach yields excellent results outperforming other popular methods in literature. As for the computational efficiency, the proposed approach is found to be highly efficient, indicating it’s future application to other real–life problems.

Tài liệu tham khảo

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