Abstract
Time-variant reliability analysis plays a vital role in improving the validity and practicability of product reliability evaluation over a specific time interval. Sampling-based extreme value method is the most direct way to implement accurate reliability assessment. Its adoption for time-variant reliability analysis, however, is limited due to the computational burden caused by repeatedly evaluating performance function. This paper proposes a semi-analytical extreme value method to improve the computational efficiency of extreme value method. The time-variant performance function is transformed into dependent instantaneous performance functions in which the stochastic processes are discretized by the expansion optimal linear estimation method to simulate the dependence among different time instants. Each instantaneous function is separately approximated by Taylor series expansion at the most probable point through instantaneous reliability analysis. Based on the approximated performance functions, the computational cost of sampling-based extreme value method is significantly reduced. Results of three numerical examples demonstrate the efficacy of the proposed method.
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Funding
The supports of the National Natural Science Foundation of China (Grant No. 11972143), the Fundamental Research Funds for the Central Universities of China (Grant Nos. JZ2020HGPA0112, JZ2020HGTA0080), State Key Laboratory of Reliability and Intelligence of Electrical Equipment (Grant No. EERI_KF2020002), and the Natural Science Foundation of Anhui Province (Grant No. 2008085QA21) are much appreciated.
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A detailed procedure and flowchart of the proposed method has been presented in Section 3.3 and one can follow them and reproduce the results. In case of further queries, please contact the corresponding author.
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Meng, Z., Zhao, J. & Jiang, C. An efficient semi-analytical extreme value method for time-variant reliability analysis. Struct Multidisc Optim 64, 1469–1480 (2021). https://doi.org/10.1007/s00158-021-02934-y
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DOI: https://doi.org/10.1007/s00158-021-02934-y