Multi-objective Adaptive DoE for RBDO
Result description
Reliability-based design optimization (RBDO) is a research area that tries to optimize structures under assumption of uncertainties. Usually, the objective function is to be minimized with respect to constraints in which the probabilistic approach is included. Our solution utilizes a surrogate-based Monte Carlo approach which is enhanced by an adaptive Design of (Computer) Experiments (DoE). The space-filling properties of the DoE are optimized by maximizing the minimal interpoint distance, i.e. the Maximin approach. The second objective is the distance to the limit sate function. Both objectives are optimized by NSGA II algorithm to obtain maximum information out of the model with a minimal number of sampling points. The meta-model with this adaptiveupdating procedure is also proposed. The studied RBDO problems consist of the minimization of the weight of the structure as the first objective and minimization of the probability of failure as the second objective. The latter is evaluat
Keywords
Reliability-Based Design OptimizationAsymptotic SamplingLatin Hypercube SamplingCrude Monte Carlo SamplingNondominated Sorting Genetic Algorithm IIMulti-Objective OptimizationLimit State FunctionProbability of FailureDesign on Experiments
The result's identifiers
Result code in IS VaVaI
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Multi-objective Adaptive DoE for RBDO
Original language description
Reliability-based design optimization (RBDO) is a research area that tries to optimize structures under assumption of uncertainties. Usually, the objective function is to be minimized with respect to constraints in which the probabilistic approach is included. Our solution utilizes a surrogate-based Monte Carlo approach which is enhanced by an adaptive Design of (Computer) Experiments (DoE). The space-filling properties of the DoE are optimized by maximizing the minimal interpoint distance, i.e. the Maximin approach. The second objective is the distance to the limit sate function. Both objectives are optimized by NSGA II algorithm to obtain maximum information out of the model with a minimal number of sampling points. The meta-model with this adaptiveupdating procedure is also proposed. The studied RBDO problems consist of the minimization of the weight of the structure as the first objective and minimization of the probability of failure as the second objective. The latter is evaluat
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
GAP105/12/1146: Methods for paralelization of engineering problems using low-cost technologies
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 11th International Probabilistic Workshop
ISBN
978-80-214-4800-1
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
325-336
Publisher name
Ing. Vladislav Pokorný - LITERA
Place of publication
Brno
Event location
Brno
Event date
Nov 6, 2013
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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Basic information
Result type
D - Article in proceedings
CEP
JD - Use of computers, robotics and its application
Year of implementation
2013