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dc.contributor.authorFlorentin, Eric
dc.contributor.authorDíez, Pedro
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental
dc.date.accessioned2018-04-25T10:00:44Z
dc.date.available2018-04-25T10:00:44Z
dc.date.issued2012-06
dc.identifier.citationFlorentin, E., Diez, P. Adaptive reduced basis strategy based on goal oriented error assessment for stochastic problems. "Computer methods in applied mechanics and engineering", Juny 2012, vol. 225-228, p. 116-127.
dc.identifier.issn0045-7825
dc.identifier.urihttp://hdl.handle.net/2117/116664
dc.description.abstractIn the framework of stochastic non-intrusive finite element modeling, a common practice is using Monte Carlo simulation. The main drawback of this approach is the computational cost, because it requires computing a large number of deterministic finite element solutions. The different Monte Carlo samplings correspond to realizations of the random variables characterizing the stochastic behavior of the model. Thus, this requires solving a set deterministic problems with the same structure, that is with variations concerning the material parameters and the loading data. Consequently, the different problems to be solved are in practice similar to each other. The reduced basis strategy is therefore a sensible option to reduce computational cost, provided that the quality of the numerical solution is guaranteed. The paper introduces a goal-oriented strategy allowing to successively enrich the reduced basis along the Monte Carlo process. The method is based on assessing the error of the reduced basis solution with a residual estimate for the prescribed quantity of interest. The efficiency of the proposed approach, which is particularly important if the number of independent random variables is large, is illustrated in 1D and 2D mechanical examples.
dc.format.extent12 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica::Anàlisi multivariant
dc.subject.lcshNumerical analysis
dc.subject.lcshStochastic analysis
dc.subject.otherReduced basis
dc.subject.otherAdaptivity
dc.subject.otherStochastic modeling
dc.subject.otherGoal-oriented error assessment
dc.titleAdaptive reduced basis strategy based on goal oriented error assessment for stochastic problems
dc.typeArticle
dc.subject.lemacAnàlisi numèrica
dc.subject.lemacAnàlisi estocàstica
dc.contributor.groupUniversitat Politècnica de Catalunya. LACÀN - Mètodes Numèrics en Ciències Aplicades i Enginyeria
dc.identifier.doi10.1016/j.cma.2012.03.016
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::65 Numerical analysis::65G Error analysis and interval analysis
dc.subject.amsClassificació AMS::60 Probability theory and stochastic processes::60H Stochastic analysis
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0045782512000928?via%3Dihub
dc.rights.accessOpen Access
local.identifier.drac10616329
dc.description.versionPostprint (author's final draft)
local.citation.authorFlorentin, E.; Diez, P.
local.citation.publicationNameComputer methods in applied mechanics and engineering
local.citation.volume225-228
local.citation.startingPage116
local.citation.endingPage127


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