Robust propagation of probability boxes by interval predictor models
Sadeghi, Jonathan and de Angelis, Marco and Patelli, Edoardo (2020) Robust propagation of probability boxes by interval predictor models. Structural Safety, 82. 101889. ISSN 0167-4730 (https://doi.org/10.1016/j.strusafe.2019.101889)
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Abstract
This paper proposes numerical strategies to robustly and efficiently propagate probability boxes through expensive black box models. An interval is obtained for the system failure probability, with a confidence level. The three proposed algorithms are sampling based, and so can be easily parallelised, and make no assumptions about the functional form of the model. In the first two algorithms, the performance function is modelled as a function with unknown noise structure in the aleatory space and supplemented by a modified performance function. In the third algorithm, an Interval Predictor Model is constructed and a re-weighting strategy used to find bounds on the probability of failure. Numerical examples are presented to show the applicability of the approach. The proposed method is flexible and can account for epistemic uncertainty contained inside the limit state function. This is a feature which, to the best of the authors’ knowledge, no existing methods of this type can deal with.
ORCID iDs
Sadeghi, Jonathan, de Angelis, Marco ORCID: https://orcid.org/0000-0001-8851-023X and Patelli, Edoardo ORCID: https://orcid.org/0000-0002-5007-7247;-
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Item type: Article ID code: 70283 Dates: DateEvent31 January 2020Published13 September 2019Published Online27 August 2019AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) Department: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 25 Oct 2019 09:20 Last modified: 22 Sep 2024 01:04 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/70283