The design of complex systems often requires reliability assessments involving a large number of uncertainties and low probability of failure estimations (in the order of 10−4). Estimating such rare event probabilities with crude Monte Carlo (CMC) is computationally intractable. Specific numerical methods to reduce the computational cost and the variance estimate have been developed such as importance sampling or subset simulation. However, these methods assume that the uncertainties are defined within the probability formalism. Regarding epistemic uncertainties, the interval formalism is particularly adapted when only their definition domain is known. In this paper, a method is derived to assess the reliability of a system with uncertainties described by both probability and interval frameworks. It allows one to determine the bounds of the failure probability and involves a sequential approach using subset simulation, kriging, and an optimization process. To reduce the simulation cost, a refinement strategy of the surrogate model is proposed taking into account the presence of both aleatory and epistemic uncertainties. The method is compared to existing approaches on an analytical example as well as on a launch vehicle fallout zone estimation problem.
Skip Nav Destination
Article navigation
November 2016
Research-Article
Reliability Analysis in the Presence of Aleatory and Epistemic Uncertainties, Application to the Prediction of a Launch Vehicle Fallout Zone
Loïc Brevault,
Loïc Brevault
Research Engineer
Onera—The French Aerospace Lab,
Palaiseau F-91123, France
e-mail: loic.brevault@onera.fr
Onera—The French Aerospace Lab,
Palaiseau F-91123, France
e-mail: loic.brevault@onera.fr
Search for other works by this author on:
Sylvain Lacaze,
Sylvain Lacaze
Application Support Engineer
The Mathworks,
10 Cowley Park,
Cambridge CB4 0HH, UK
e-mail: sylvain.lacaze@mathworks.co.uk
The Mathworks,
10 Cowley Park,
Cambridge CB4 0HH, UK
e-mail: sylvain.lacaze@mathworks.co.uk
Search for other works by this author on:
Mathieu Balesdent,
Mathieu Balesdent
Research Engineer
Onera—The French Aerospace Lab,
Palaiseau F-91123, France
e-mail: mathieu.balesdent@onera.fr
Onera—The French Aerospace Lab,
Palaiseau F-91123, France
e-mail: mathieu.balesdent@onera.fr
Search for other works by this author on:
Samy Missoum
Samy Missoum
Associate Professor
Aerospace and Mechanical
Engineering Department,
University of Arizona,
Tucson, AZ 85721
e-mail: smissoum@email.arizona.edu
Aerospace and Mechanical
Engineering Department,
University of Arizona,
Tucson, AZ 85721
e-mail: smissoum@email.arizona.edu
Search for other works by this author on:
Loïc Brevault
Research Engineer
Onera—The French Aerospace Lab,
Palaiseau F-91123, France
e-mail: loic.brevault@onera.fr
Onera—The French Aerospace Lab,
Palaiseau F-91123, France
e-mail: loic.brevault@onera.fr
Sylvain Lacaze
Application Support Engineer
The Mathworks,
10 Cowley Park,
Cambridge CB4 0HH, UK
e-mail: sylvain.lacaze@mathworks.co.uk
The Mathworks,
10 Cowley Park,
Cambridge CB4 0HH, UK
e-mail: sylvain.lacaze@mathworks.co.uk
Mathieu Balesdent
Research Engineer
Onera—The French Aerospace Lab,
Palaiseau F-91123, France
e-mail: mathieu.balesdent@onera.fr
Onera—The French Aerospace Lab,
Palaiseau F-91123, France
e-mail: mathieu.balesdent@onera.fr
Samy Missoum
Associate Professor
Aerospace and Mechanical
Engineering Department,
University of Arizona,
Tucson, AZ 85721
e-mail: smissoum@email.arizona.edu
Aerospace and Mechanical
Engineering Department,
University of Arizona,
Tucson, AZ 85721
e-mail: smissoum@email.arizona.edu
Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received February 14, 2016; final manuscript received June 22, 2016; published online September 12, 2016. Assoc. Editor: Mian Li.
J. Mech. Des. Nov 2016, 138(11): 111401 (11 pages)
Published Online: September 12, 2016
Article history
Received:
February 14, 2016
Revised:
June 22, 2016
Citation
Brevault, L., Lacaze, S., Balesdent, M., and Missoum, S. (September 12, 2016). "Reliability Analysis in the Presence of Aleatory and Epistemic Uncertainties, Application to the Prediction of a Launch Vehicle Fallout Zone." ASME. J. Mech. Des. November 2016; 138(11): 111401. https://doi.org/10.1115/1.4034106
Download citation file:
Get Email Alerts
A Mixed-Methods Investigation of How Digital Immersion Affects Design for Additive Manufacturing Evaluations
J. Mech. Des (November 2024)
A Fuzzy Ontology-Based Decision Tool for Concept Selection to Maintain Consistency Throughout Design Iterations
J. Mech. Des (October 2024)
Related Articles
Multi-Task Learning for Design Under Uncertainty With Multi-Fidelity Partially Observed Information
J. Mech. Des (August,2024)
Proper Orthogonal Decomposition-Based Surrogate Modeling Approximation for Aeroengines Nonlinear Unbalance Responses
J. Eng. Gas Turbines Power (January,2024)
Adaptive Surrogate Modeling for Time-Dependent Multidisciplinary Reliability Analysis
J. Mech. Des (February,2018)
Related Proceedings Papers
Related Chapters
STRUCTURAL RELIABILITY ASSESSMENT OF PIPELINE GIRTH WELDS USING GAUSSIAN PROCESS REGRESSION
Pipeline Integrity Management Under Geohazard Conditions (PIMG)
Application of Experiment Design Method in System Simulation of Flight Vehicle
International Conference on Information Technology and Computer Science, 3rd (ITCS 2011)
PSA Level 2 — NPP Ringhals 2 (PSAM-0156)
Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)