Estimating seismic performance uncertainty using IDA with progressive accelerogram-wise latin hypercube sampling

Vamvatsikos, D

dc.contributor.author	Vamvatsikos, D	en
dc.date.accessioned	2014-03-01T02:53:16Z
dc.date.available	2014-03-01T02:53:16Z
dc.date.issued	2011	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36201
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-84856714167&partnerID=40&md5=8cd066835c8d082b1f484ffecc64fcc6	en
dc.subject	Incremental dynamic analysis	en
dc.subject	Latin hypercube sampling	en
dc.subject	Monte Carlo Simulation	en
dc.subject	Non-linear dynamic analysis	en
dc.subject	Uncertainty analysis	en
dc.subject.other	Efficient algorithm	en
dc.subject.other	Fundamental changes	en
dc.subject.other	Ground-motion	en
dc.subject.other	Improved algorithm	en
dc.subject.other	Incremental dynamic analysis	en
dc.subject.other	Large-scale applications	en
dc.subject.other	Latin hypercube sampling	en
dc.subject.other	Model parameters	en
dc.subject.other	Monte Carlo Simulation	en
dc.subject.other	Non-linear dynamic analysis	en
dc.subject.other	Number of samples	en
dc.subject.other	Rapid estimation	en
dc.subject.other	Sample sizes	en
dc.subject.other	Seismic Performance	en
dc.subject.other	Small samples	en
dc.subject.other	Steel moment resisting frame	en
dc.subject.other	Structural models	en
dc.subject.other	Test case	en
dc.subject.other	Algorithms	en
dc.subject.other	Civil engineering	en
dc.subject.other	Dynamic analysis	en
dc.subject.other	Model structures	en
dc.subject.other	Monte Carlo methods	en
dc.subject.other	Random variables	en
dc.subject.other	Uncertainty analysis	en
dc.title	Estimating seismic performance uncertainty using IDA with progressive accelerogram-wise latin hypercube sampling	en
heal.type	conferenceItem	en
heal.publicationDate	2011	en
heal.abstract	An efficient algorithm is presented that allows the rapid estimation of the influence of model parameter uncertainties on the seismic performance of structures using Incremental Dynamic Analysis (IDA) and Monte Carlo simulation with latin hypercube sampling. The fundamental blocks of this methodology have already been proposed as a means to quantify the uncertainty for structural models with non-deterministic parameters, whereby each model realization out of a predetermined sample size is subjected to a full IDA under multiple ground motion records. However, any practical application is severely restricted due to a) our inability to determine a priori the required number of samples and b) the disproportionate increase in the number of analyseswhen dealing with many random variables. Thus, two fundamental changes are incorporated. First, latin hypercube sampling is applied incrementally by starting with a small sample that is doubled successively until adequate accuracy has been achieved. At the same time, instead of maintaining the same properties for a given model realization over an entire ground-motion record suite, parameter sampling is performed on a record-by-record basis, efficiently expanding the model sample size without increasing the number of nonlinear dynamic analyses. Using a steel moment-resisting frame building as a test case, it is shown that the improved algorithm allows excellent scalability and extends the original methodology to be easily applicable to realistic large-scale applications with hundreds of random variables. © 2011 Taylor & Francis Group, London.	en
heal.journalName	Applications of Statistics and Probability in Civil Engineering -Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering	en
dc.identifier.spage	2704	en
dc.identifier.epage	2710	en