Black-box propagation of failure probabilities under epistemic uncertainty

Marco De Angelis; Scott Ferson; Edoardo Patelli; Vladik Kreinovich

doi:10.7712/120219.6373.18699

Black-box propagation of failure probabilities under epistemic uncertainty

Marco De Angelis, Scott Ferson, Edoardo Patelli, Vladik Kreinovich

Civil And Environmental Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

7 Citations (Scopus)

Abstract

In engineering simulation a black-box code is often a complex, legacy or proprietary (secret) black-box software used to describe the physics of the system under study. Strategies to propagate epistemic uncertainty through such codes are desperately needed, for code verification, sensitivity, and validation on experimental data. Very often in practice, the uncertainty in the inputs is characterised by imprecise probability distributions or distributions with interval parameters, also known as probability boxes. In this paper we propose a strategy based on line sampling to propagate both aleatory and epistemic uncertainty through black-box codes to obtain interval probabilities of failure. The efficiency of the proposed strategy is demonstrated on the NASA LaRC UQ problem.

Original language	English
Title of host publication	Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2019
Editors	M. Papadrakakis, V. Papadopoulos, G. Stefanou
Place of Publication	Athens
Pages	713-723
Number of pages	11
DOIs	https://doi.org/10.7712/120219.6373.18699
Publication status	Published - 24 Jun 2019
Event	3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering - Crete, Greece Duration: 24 Jun 2019 → 26 Jun 2019

Conference

Conference	3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering
Abbreviated title	UNCECOMP 2019
Country/Territory	Greece
City	Crete
Period	24/06/19 → 26/06/19

Funding

This research is funded by the Engineering & Physical Sciences Research Council (EPSRC) through the programme grant “Digital twins for improved dynamic design” with grant no. EP/R006768/1. EPSRC and the DigiTwin consortium are greatly acknowledged for their funding and support.

Keywords

black-box code
Cauchy-deviate method
digital twins
line sampling

Access to Document

10.7712/120219.6373.18699

Cite this

De Angelis, M., Ferson, S., Patelli, E., & Kreinovich, V. (2019). Black-box propagation of failure probabilities under epistemic uncertainty. In M. Papadrakakis, V. Papadopoulos, & G. Stefanou (Eds.), Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2019 (pp. 713-723). https://doi.org/10.7712/120219.6373.18699

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De Angelis, M, Ferson, S, Patelli, E & Kreinovich, V 2019, Black-box propagation of failure probabilities under epistemic uncertainty. in M Papadrakakis, V Papadopoulos & G Stefanou (eds), Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2019. Athens, pp. 713-723, 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, Crete, Greece, 24/06/19. https://doi.org/10.7712/120219.6373.18699

Black-box propagation of failure probabilities under epistemic uncertainty. / De Angelis, Marco; Ferson, Scott; Patelli, Edoardo et al.
Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2019. ed. / M. Papadrakakis; V. Papadopoulos; G. Stefanou. Athens, 2019. p. 713-723.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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De Angelis M, Ferson S, Patelli E, Kreinovich V. Black-box propagation of failure probabilities under epistemic uncertainty. In Papadrakakis M, Papadopoulos V, Stefanou G, editors, Proceedings of the 3rd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2019. Athens. 2019. p. 713-723 doi: 10.7712/120219.6373.18699

Black-box propagation of failure probabilities under epistemic uncertainty

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