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Time-variant reliability analysis using phase-type distribution-based methods
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DOI：10.1016/j.advengsoft.2024.103792.png)
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Abstract
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The performance of engineering structures often varies over time due to the randomness and time variability of material properties, environmental conditions and load effects. This paper proposes phase-type (PH) distributionbased methods for efficient time-variant reliability analysis. The core of the proposed methods is to approximate the extreme value of a stochastic process as a PH distributed random variable, and treat the time parameter as a uniformly distributed variable. Consequently, the time-variant reliability problem is transformed into a timeinvariant one. Three representative time-invariant reliability methods, first-order reliability method (FORM), importance sampling (IS) and adaptive Kriging (AK) surrogate model-based IS method (AK-IS), are integrated with the PH distribution-based approximation strategy to form the proposed methods, namely PH-FORM, PH-IS and PH-AKIS. The efficiency and accuracy of these methods are demonstrated through three examples. All codes in the study are implemented in MATLAB and provided as supplementary materials.
Keywords:
Time-variant reliability
Stochastic process
Phase-type distribution
Extreme value
Time-invariant reliability methods
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