Reliability-Based Design Optimization under Mixed Aleatory/Epistemic Uncertainties: Theory and Applications
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 3
Abstract
Reliability-based design optimization (RBDO) is a well-known design strategy in engineering. However, RBDO usually requires uncertainties to be modeled by statistical distributions. This requires the availability of sufficient sample size so that these variables can be represented accurately by probabilistic distributions. In the design of new systems and structures, usually there is a lack of information about some uncertain variables or parameters and only a reduced set of samples might be available. This prevents their treatment as probability distributions. This type of uncertainty is called epistemic uncertainty. This paper proposes two effective multiobjective evolutionary algorithms to solve design problems under both types of uncertainty: aleatory and epistemic. Two objective functions, namely the cost of the structures and the probability of failure, are considered. The results are Pareto fronts with a trade-off between cost and reliability associated with a specified level of confidence. Pareto fronts show minimum achievable values for the probability of failure for a given cost. The effect of the epistemic uncertainty on the solution is also investigated. An analytical example and two structural examples are solved to show the applicability of the approach and how epistemic uncertainty may affect the results.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The list of available materials consists of Matlab files, OpenSees scripts, and data tables used to plot Pareto fronts.
Acknowledgments
This work has received a research grant from the Instituto de Estudios Riojanos of the Autonomous Community of La Rioja, Spain. The authors gratefully acknowledge this support.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7 • Issue 3 • September 2021
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© 2021 American Society of Civil Engineers.
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Received: Jul 13, 2020
Accepted: Mar 15, 2021
Published online: May 26, 2021
Published in print: Sep 1, 2021
Discussion open until: Oct 26, 2021
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