Bayesian prediction for a jump diffusion process with application to crack growth in fatigue experiments

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dc.contributor.authorHermann, Simone
dc.contributor.authorIckstadt, Katja
dc.contributor.authorMüller, Christine H.
dc.date.accessioned2015-08-18T16:45:19Z
dc.date.available2015-08-18T16:45:19Z
dc.date.issued2015
dc.description.abstractIn many felds of technological developments, understanding and controlling material fatigue is an important point of interest. This article is concerned with statistical modeling of the damage process of prestressed concrete under low cyclic load. A crack width process is observed which exhibits jumps with increasing frequency. Firstly, these jumps are modeled using a Poisson process where two intensity functions are presented and compared. Secondly, based on the modeled jump process, a stochastic process for the crack width is considered through a stochastic differential equation (SDE). It turns out that this SDE has an explicit solution. For both modeling steps, a Bayesian estimation and prediction procedure is presented.en
dc.identifier.urihttp://hdl.handle.net/2003/34192
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-16271
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;30/2015
dc.subjectNonhomogeneous Poisson process (NHPP)en
dc.subjectpredictive distributionen
dc.subjectBayesian estimationen
dc.subjectcrack growthen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleBayesian prediction for a jump diffusion process with application to crack growth in fatigue experimentsen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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