Publication result detail

Failure probability estimation of functions with binary outcomes via adaptive sequential sampling

VOŘECHOVSKÝ, M.

Original Title

Failure probability estimation of functions with binary outcomes via adaptive sequential sampling

English Title

Failure probability estimation of functions with binary outcomes via adaptive sequential sampling

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

A novel method for estimation of rare event probability is proposed, which works also for computational models returning categorical information only: success or failure. It combines the robustness of simulation methods (counting failure events) with the strength of approximation methods which refine the boundary between the failure and safe sets. Two basic tasks are identified: (i) extension of the experimental design (ED) and (ii) estimation of probabilities. The new extension algorithm adds points for limit state evaluation to the ED by balancing the global exploration and local exploitation, and the estimation uses the pointwise information to build a simple surrogate and perform a novel optimized importance sampling. No connection is presumed between the limit function value at point and its proximity to the failure surface. A new global sensitivity measure of the failure probability to individual variables is proposed and obtained as a by-product of the proposed methods.

English abstract

A novel method for estimation of rare event probability is proposed, which works also for computational models returning categorical information only: success or failure. It combines the robustness of simulation methods (counting failure events) with the strength of approximation methods which refine the boundary between the failure and safe sets. Two basic tasks are identified: (i) extension of the experimental design (ED) and (ii) estimation of probabilities. The new extension algorithm adds points for limit state evaluation to the ED by balancing the global exploration and local exploitation, and the estimation uses the pointwise information to build a simple surrogate and perform a novel optimized importance sampling. No connection is presumed between the limit function value at point and its proximity to the failure surface. A new global sensitivity measure of the failure probability to individual variables is proposed and obtained as a by-product of the proposed methods.

Keywords

exploitation, exploration, reliability

Key words in English

exploitation, exploration, reliability

Authors

VOŘECHOVSKÝ, M.

RIV year

2023

Released

07.11.2022

ISBN

978-80-261-1116-0

Book

PROCEEDINGS OF COMPUTATIONAL MECHANICS 2022

Pages from

173

Pages to

174

Pages count

2

BibTex

@inproceedings{BUT182554,
  author="Miroslav {Vořechovský}",
  title="Failure probability estimation of functions with binary outcomes via adaptive sequential sampling",
  booktitle="PROCEEDINGS OF COMPUTATIONAL MECHANICS 2022",
  year="2022",
  pages="173--174",
  isbn="978-80-261-1116-0"
}