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Time-dependent system reliability analysis by adaptive importance sampling

127 citations0/0 files storedStructural Safety

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Probabilistic and Robust Engineering Design Reliability and Maintenance Optimization Structural Integrity and Reliability Analysis

Abstract

A method for evaluating time-dependent reliability of a structural system subjected to stochastic loads is presented. Structural deterioration due to environmental stressors is also taken into account. An adaptive Monte Carlo simulation procedure combined with conditional expectation is proposed. The optimum common ratio of the standard deviation of an importance sampling variables to that of the corresponding original valuables is estimated iteratively as well as their mean values. Unlike systems evaluated by simple Monte Carlo simulations, the accuracy of the failure probability evaluated by adaptive importance sampling is relatively insensitive to the magnitude of the probability.

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References

2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code 2017Structural Reliability Analysis and Prediction 2016Simulation and the Monte Carlo Method 1979Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code 1981Simulation and the Monte Carlo Method 1979Narrow Reliability Bounds for Structural Systems 1982Structural Reliability Theory and Its Applications 1989Importance sampling in structural systems

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2016Confidence-based adaptive extreme response surface for time-variant reliability analysis under random excitation 2000Adaptive simulation for system reliability analysis of large structures 1998Ductile structural system reliability analysis using adaptive importance sampling 1994Structural system reliability assessment using directional simulation 2019Efficient methods by active learning Kriging coupled with variance reduction based sampling methods for time-dependent failure probability

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