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A novel null-hypothesis approximation method of limit state function in multi-failure mode reliability analysis of structural system
A novel null-hypothesis approximation method of limit state function in multi-failure mode reliability analysis of structural system
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A novel null-hypothesis approximation method of limit state function in multi-failure mode reliability analysis of structural system
A novel null-hypothesis approximation method of limit state function in multi-failure mode reliability analysis of structural system

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A novel null-hypothesis approximation method of limit state function in multi-failure mode reliability analysis of structural system
A novel null-hypothesis approximation method of limit state function in multi-failure mode reliability analysis of structural system
Journal Article

A novel null-hypothesis approximation method of limit state function in multi-failure mode reliability analysis of structural system

2024
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Overview
Modern industrial products feature complex structures, multiple sub-structural systems, and high-reliability requirements, especially for aerospace products. For the reliability analysis (RA) of these products, even if the analysis error of single sub-structural systems is small, the one of global reliability may be very large, therefore, it is challenging to meet the reliability requirements for whole products. With regard to the high-reliability and multiple failure mode problems, this paper proposes a novel null-hypothesis approximation method (NHA) of limit surface function (LSF). It can obtain the points on LSF in the feasible domain. Then, a new RA framework is established by combining the convex point cloud model (CPCM) with NHA. CPCM can obtain the volume of the point cloud by focusing on the points on LSF in the feasible domain. Compared with traditional RA methods, the new RA framework is suitable for complex structural systems with high-reliability, and it can mitigate the analysis error that is caused by traditional RA methods that only concentrate on curvature in proximity to MPP. Finally, three numerical examples and an engineering example are used to test the performance of the proposed method. Results indicate that the proposed method has similar accuracy to the Monte Carlo simulation (MCS) for rare event probability, and the computational cost is acceptable for complex engineering problems.