An Info-gap Framework for Comparing Epistemic Uncertainty Models in Hybrid Structural Reliability Analysis

Antoine Ajenjo, Emmanuel Ardillon, Vincent Chabridon, Scott Cogan, Emeline Sadoulet-Reboul
Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications, PMLR 147:2-11, 2021.

Abstract

The main objective of this work is to study the effect of the choice of the input uncertainty model on robustness evaluations of probabilities of failure. Aleatory and epistemic uncertainty are jointly propagated by considering hybrid models and applying random set theory. The notion of horizon of uncertainty found in the info-gap theory, which is usually used to assess the robustness of a model to uncertainty, allows the bounds on the failure probability obtained from different epistemic uncertainty models to be compared at increasing levels of uncertainty. Info-gap robustness and opportuneness curves are obtained and compared considering the interval model, triangular and trapezoidal possibility distributions, the probabilistic uniform distribution and the paralellepiped convex model on two toy cases. A specific demand value, as introduced in the info-gap theory, is used as a value of information metric to quantify the gain of information on the probability of failure between a less informative uncertainty model and a more informative one.

Cite this Paper

BibTeX
@InProceedings{pmlr-v147-ajenjo21a, title = {An Info-gap Framework for Comparing Epistemic Uncertainty Models in Hybrid Structural Reliability Analysis}, author = {Ajenjo, Antoine and Ardillon, Emmanuel and Chabridon, Vincent and Cogan, Scott and Sadoulet-Reboul, Emeline}, booktitle = {Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications}, pages = {2--11}, year = {2021}, editor = {Cano, Andrés and De Bock, Jasper and Miranda, Enrique and Moral, Serafı́n}, volume = {147}, series = {Proceedings of Machine Learning Research}, month = {06--09 Jul}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v147/ajenjo21a/ajenjo21a.pdf}, url = {https://proceedings.mlr.press/v147/ajenjo21a.html}, abstract = {The main objective of this work is to study the effect of the choice of the input uncertainty model on robustness evaluations of probabilities of failure. Aleatory and epistemic uncertainty are jointly propagated by considering hybrid models and applying random set theory. The notion of horizon of uncertainty found in the info-gap theory, which is usually used to assess the robustness of a model to uncertainty, allows the bounds on the failure probability obtained from different epistemic uncertainty models to be compared at increasing levels of uncertainty. Info-gap robustness and opportuneness curves are obtained and compared considering the interval model, triangular and trapezoidal possibility distributions, the probabilistic uniform distribution and the paralellepiped convex model on two toy cases. A specific demand value, as introduced in the info-gap theory, is used as a value of information metric to quantify the gain of information on the probability of failure between a less informative uncertainty model and a more informative one.} }
Endnote
%0 Conference Paper %T An Info-gap Framework for Comparing Epistemic Uncertainty Models in Hybrid Structural Reliability Analysis %A Antoine Ajenjo %A Emmanuel Ardillon %A Vincent Chabridon %A Scott Cogan %A Emeline Sadoulet-Reboul %B Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications %C Proceedings of Machine Learning Research %D 2021 %E Andrés Cano %E Jasper De Bock %E Enrique Miranda %E Serafı́n Moral %F pmlr-v147-ajenjo21a %I PMLR %P 2--11 %U https://proceedings.mlr.press/v147/ajenjo21a.html %V 147 %X The main objective of this work is to study the effect of the choice of the input uncertainty model on robustness evaluations of probabilities of failure. Aleatory and epistemic uncertainty are jointly propagated by considering hybrid models and applying random set theory. The notion of horizon of uncertainty found in the info-gap theory, which is usually used to assess the robustness of a model to uncertainty, allows the bounds on the failure probability obtained from different epistemic uncertainty models to be compared at increasing levels of uncertainty. Info-gap robustness and opportuneness curves are obtained and compared considering the interval model, triangular and trapezoidal possibility distributions, the probabilistic uniform distribution and the paralellepiped convex model on two toy cases. A specific demand value, as introduced in the info-gap theory, is used as a value of information metric to quantify the gain of information on the probability of failure between a less informative uncertainty model and a more informative one.
APA
Ajenjo, A., Ardillon, E., Chabridon, V., Cogan, S. & Sadoulet-Reboul, E.. (2021). An Info-gap Framework for Comparing Epistemic Uncertainty Models in Hybrid Structural Reliability Analysis. Proceedings of the Twelveth International Symposium on Imprecise Probability: Theories and Applications, in Proceedings of Machine Learning Research 147:2-11 Available from https://proceedings.mlr.press/v147/ajenjo21a.html.

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