Reliability-Based Design Optimization under Mixed Aleatory/Epistemic Uncertainties: Theory and Applications
- 1 September 2021
- journal article
- research article
- Published by American Society of Civil Engineers (ASCE) in ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
- Vol. 7 (3), 04021026
- https://doi.org/10.1061/ajrua6.0001147
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.Keywords
This publication has 35 references indexed in Scilit:
- On multinormal integrals by Importance Sampling for parallel system reliabilityStructural Safety, 2011
- The role of the design point for calculating failure probabilities in view of dimensionality and structural nonlinearitiesStructural Safety, 2010
- Reliability‐based robust design optimization: A multi‐objective framework using hybrid quality loss functionQuality and Reliability Engineering International, 2009
- Aleatory or epistemic? Does it matter?Structural Safety, 2009
- A sequential approximate programming strategy for performance-measure-based probabilistic structural design optimizationStructural Safety, 2008
- Robust Design Optimization in Computational MechanicsJournal of Applied Mechanics, 2008
- Reliability based robust design optimization of steel structuresInternational Journal for Simulation and Multidisciplinary Design Optimization, 2007
- A fast and elitist multiobjective genetic algorithm: NSGA-IIIEEE Transactions on Evolutionary Computation, 2002
- Efficient estimation of structural reliability for problems with uncertain intervalsComputers & Structures, 2002
- A New Study on Reliability-Based Design OptimizationJournal of Mechanical Design, 1999