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Seismic reliability analysis using Subset Simulation enhanced with an explorative adaptive conditional sampling algorithm
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DOI：10.1016/j.probengmech.2024.103690.png)
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Abstract
En 中文
Reliability analysis of structures under earthquake loading represents a significant engineering challenge. This is due to the required and rather numerically involving non-linear dynamic analysis, the large computational burden when targeting small failure probabilities, and the synthetic earthquake model representation that may contain thousands of random variables. Subset Simulation is an efficient reliability analysis technique that can handle the challenge of a high-dimensional space with a reduced number of structural analysis calls compared to crude Monte Carlo Simulation. In this contribution, firstly, we investigate the conditions for which Subset Simulation performs efficiently. Thereafter we propose an enhancement to the existing Subset Simulation schemes that shows significant potentials for enhancing the strategy for the starting of the Markov Chain Monte Carlo simulations whenever a new level is reached in the Subset Simulation. Finally, the information gathered from the simulations is investigated to verify that Subset Simulation provides meaningful results from a physical point of view.
Keywords:
Adaptive conditional sampling
Subset simulation
OpenSees
Reliability analysis
Structural reliability
Seismic reliability
Advanced simulation techniques
Non-linear structural analysis
Monte Carlo simulation techniques
Markov chain Monte Carlo
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