An efficient method for estimating conditional failure probabilities

Domenico Altieri, Edoardo Patelli

Research output: Contribution to conferencePaper

Abstract

Conditional reliability measures provide a more detailed description of the performance of a system, being representative of different initial configurations. Commonly, since the failure region is characterized by a small probability of occurrence, advanced sampling techniques are required to reduce the computational effort of a simulation based approach. These techniques if on one hand decrease the number of samples needed to identify the failure domain, on the other hand do not generally allow a direct estimation of the conditional failure probability for different given inputs. This study aims at providing an efficient and simple methodology to evaluate the conditional failure probability in the case of a static reliability analysis. In particular, under the assumption of probability density functions (PDFs) with a finite support, the failure region mapping process is carried out using surrogate PDFs associated with Sobol’ sequences in order to reduce as much as possible the model evaluations. Finally, the integration of the failure region in the standard normal space employs probabilistic weights instead of a classic indicator function to account for the uncertainty associated with the failure region definition. The approach is verified by comparing the results against those obtained from a Latin Hypercube Sampling. The performance of the proposed method is evaluated in terms of computational costs and accuracy
Original languageEnglish
Number of pages6
Publication statusPublished - 16 Jul 2018
Event8th International Workshop on Reliable Engineering Computing - Liverpool, United Kingdom
Duration: 16 Jul 201818 Jul 2018
https://riskinstitute.uk/events/rec2018/

Workshop

Workshop8th International Workshop on Reliable Engineering Computing
Abbreviated titleREC2018
CountryUnited Kingdom
CityLiverpool
Period16/07/1818/07/18
Internet address

Fingerprint

Failure Probability
Conditional probability
Probability density function
Sampling
Reliability analysis
Latin Hypercube Sampling
Model Evaluation
Normal Space
Indicator function
Reliability Analysis
Static Analysis
Computational Cost
Costs
Uncertainty
Decrease
Configuration
Methodology
Evaluate
Simulation

Keywords

  • conditional failure probability
  • reliability analysis
  • failure region

Cite this

Altieri, D., & Patelli, E. (2018). An efficient method for estimating conditional failure probabilities. Paper presented at 8th International Workshop on Reliable Engineering Computing, Liverpool, United Kingdom.
Altieri, Domenico ; Patelli, Edoardo. / An efficient method for estimating conditional failure probabilities. Paper presented at 8th International Workshop on Reliable Engineering Computing, Liverpool, United Kingdom.6 p.
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Altieri, D & Patelli, E 2018, 'An efficient method for estimating conditional failure probabilities' Paper presented at 8th International Workshop on Reliable Engineering Computing, Liverpool, United Kingdom, 16/07/18 - 18/07/18, .

An efficient method for estimating conditional failure probabilities. / Altieri, Domenico; Patelli, Edoardo.

2018. Paper presented at 8th International Workshop on Reliable Engineering Computing, Liverpool, United Kingdom.

Research output: Contribution to conferencePaper

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M3 - Paper

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Altieri D, Patelli E. An efficient method for estimating conditional failure probabilities. 2018. Paper presented at 8th International Workshop on Reliable Engineering Computing, Liverpool, United Kingdom.