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A Comprehensive Model for Structural Non-Probabilistic Reliability and the Key Algorithms

Wencai Sun1, ∗, Zichun Yang1
1 Naval University of Engineering, Wuhan, 430033, China.
∗ Corresponding Author: Wencai Sun. Email: .
(This article belongs to this Special Issue: Numerical Modeling and Simulation for Structural Safety and Disaster Mitigation)

Computer Modeling in Engineering & Sciences 2020, 123(1), 309-332.

Received 22 August 2019; Accepted 23 October 2019; Issue published 01 April 2020


It is very difficult to know the exact boundaries of the variable domain for problems with small sample size, and the traditional convex set model is no longer applicable. In view of this, a novel reliability model was proposed on the basis of the fuzzy convex set (FCS) model. This new reliability model can account for different relations between the structural failure region and variable domain. Key computational algorithms were studied in detail. First, the optimization strategy for robust reliability is improved. Second, Monte Carlo algorithms (i.e., uniform sampling method) for hyper-ellipsoidal convex sets were studied in detail, and errors in previous reports were corrected. Finally, the Gauss-Legendre integral algorithm was used for calculation of the integral reliability index. Three numerical examples are presented here to illustrate the rationality and feasibility of the proposed model and its corresponding algorithms.


Structural reliability, non-probabilistic, fuzzy convex set, robust reliability, volume ratio-based reliability, Monte Carlo, Gauss-Legendre integral formula.

Cite This Article

Sun, W., Yang, Z. (2020). A Comprehensive Model for Structural Non-Probabilistic Reliability and the Key Algorithms. CMES-Computer Modeling in Engineering & Sciences, 123(1), 309–332.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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