Adaptive importance sampling for seismic fragility curve estimation
- URL: http://arxiv.org/abs/2109.04323v1
- Date: Thu, 9 Sep 2021 14:56:33 GMT
- Title: Adaptive importance sampling for seismic fragility curve estimation
- Authors: Clement Gauchy, Cyril Feau, and Josselin Garnier
- Abstract summary: It is necessary to study the fragility of mechanical and civil engineered structures when subjected to seismic loads.
The estimation of fragility curves relies on time-consuming numerical simulations.
We propose and implement an active learning methodology based on adaptive importance sampling.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: As part of Probabilistic Risk Assessment studies, it is necessary to study
the fragility of mechanical and civil engineered structures when subjected to
seismic loads. This risk can be measured with fragility curves, which express
the probability of failure of the structure conditionally to a seismic
intensity measure. The estimation of fragility curves relies on time-consuming
numerical simulations, so that careful experimental design is required in order
to gain the maximum information on the structure's fragility with a limited
number of code evaluations. We propose and implement an active learning
methodology based on adaptive importance sampling in order to reduce the
variance of the training loss. The efficiency of the proposed method in terms
of bias, standard deviation and prediction interval coverage are theoretically
and numerically characterized.
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