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A refined subset simulation for the reliability analysis using the subset control variate
Highlights The proposed SCV method refines subset simulation by using control variates technique. Assess the efficiency of SCV through a new formulation for coefficient of variation. The proposed approach overcomes the convectional subset simulation drawbacks. Assessed the efficiency of SCV method on some challenging examples.
Abstract The reliability analysis of an engineering system with a small failure probability (Pf) and a complex-geometry performance function is a major challenge in the probabilistic engineering mechanics for which the subset simulation (SS) is a promising addressing algorithm. However, SS is potentially problematic when solving complex problems. This has triggered an interest in improving and reformulating the SS. This paper presents the subset control variate (SCV) technique, a novel approach to reformulate the conventional SS, and provides the statistical properties such as coefficient of variation (c.o.v) of the estimate of Pf using SCV. SCV enhances and generalizes the original SS. It improves the conventional SS formulation and can employ different sampling approaches in the SS to properly find the most probable failure domain with complex and misleading geometry. The proposed method’s capabilities are compared with those of the conventional SS and examined by solving several numerical and practical problems with challenging performance functions. The results, validated by the Monte Carlo Simulation (MCS), show that the SCV improved the SS robustness for solving highly nonlinear problems involving misleading performance functions and its c.o.v is less than that of the original SS for all the numerical examples considered in this study.
A refined subset simulation for the reliability analysis using the subset control variate
Highlights The proposed SCV method refines subset simulation by using control variates technique. Assess the efficiency of SCV through a new formulation for coefficient of variation. The proposed approach overcomes the convectional subset simulation drawbacks. Assessed the efficiency of SCV method on some challenging examples.
Abstract The reliability analysis of an engineering system with a small failure probability (Pf) and a complex-geometry performance function is a major challenge in the probabilistic engineering mechanics for which the subset simulation (SS) is a promising addressing algorithm. However, SS is potentially problematic when solving complex problems. This has triggered an interest in improving and reformulating the SS. This paper presents the subset control variate (SCV) technique, a novel approach to reformulate the conventional SS, and provides the statistical properties such as coefficient of variation (c.o.v) of the estimate of Pf using SCV. SCV enhances and generalizes the original SS. It improves the conventional SS formulation and can employ different sampling approaches in the SS to properly find the most probable failure domain with complex and misleading geometry. The proposed method’s capabilities are compared with those of the conventional SS and examined by solving several numerical and practical problems with challenging performance functions. The results, validated by the Monte Carlo Simulation (MCS), show that the SCV improved the SS robustness for solving highly nonlinear problems involving misleading performance functions and its c.o.v is less than that of the original SS for all the numerical examples considered in this study.
A refined subset simulation for the reliability analysis using the subset control variate
Abdollahi, Azam (author) / Azhdary Moghaddam, Mehdi (author) / Hashemi Monfared, Seyed Arman (author) / Rashki, Mohsen (author) / Li, Yong (author)
Structural Safety ; 87
2020-06-29
Article (Journal)
Electronic Resource
English
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