Please use this identifier to cite or link to this item: https://doi.org/10.1002/nme.1986
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dc.titleEnergetic-statistical size effect simulated by SFEM with stratified sampling and crack band model
dc.contributor.authorBažant, Z.P.
dc.contributor.authorPang, S.-D.
dc.contributor.authorVořechovský, M.
dc.contributor.authorNovák, D.
dc.date.accessioned2014-06-17T08:17:46Z
dc.date.available2014-06-17T08:17:46Z
dc.date.issued2007-09-10
dc.identifier.citationBažant, Z.P., Pang, S.-D., Vořechovský, M., Novák, D. (2007-09-10). Energetic-statistical size effect simulated by SFEM with stratified sampling and crack band model. International Journal for Numerical Methods in Engineering 71 (11) : 1297-1320. ScholarBank@NUS Repository. https://doi.org/10.1002/nme.1986
dc.identifier.issn00295981
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/65528
dc.description.abstractThe paper presents a model that extends the stochastic finite element method to the modelling of transitional energetic-statistical size effect in unnotched quasibrittle structures of positive geometry (i.e. failing at the start of macro-crack growth), and to the low probability tail of structural strength distribution, important for safe design. For small structures, the model captures the energetic (deterministic) part of size effect and, for large structures, it converges to Weibull statistical size effect required by the weakest-link model of extreme value statistics. Prediction of the tail of extremely low probability such as one in a million, which needs to be known for safe design, is made feasible by the fact that the form of the cumulative distribution function (cdf) of a quasibrittle structure of any size has been established analytically in previous work. Thus, it is not necessary to turn to sophisticated methods such as importance sampling and it suffices to calibrate only the mean and variance of this WE Two kinds of stratified sampling of strength in a finite element code are studied. One is the Latin hypercube sampling of the strength of each element considered as an independent random variable, and the other is the Latin square design in which the strength of each element is sampled from one overall cdf of random material strength. The former is found to give a closer estimate of variance, while the latter gives a cdf with smaller scatter and a better mean for the same number of simulations. For large structures, the number of simulations required to obtain the mean size effect is greatly reduced by adopting the previously proposed method of random property blocks. Each block is assumed to have a homogeneous random material strength, the mean and variance of which are scaled down according to the block size using the weakest-link model for a finite number of links. To check whether the theoretical cdf is followed at least up to tail beginning at the failure probability of about 0.01, a hybrid of stratified sampling and Monte Carlo simulations in the lowest probability stratum is used. With the present method, the probability distribution of strength of quasibrittle structures of positive geometry can be easily estimated for any structure size. Copyright © 2007 John Wiley & Sons, Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/nme.1986
dc.sourceScopus
dc.subjectExtreme value statistics
dc.subjectQuasibrittle fracture
dc.subjectScaling
dc.subjectSize effect
dc.subjectStochastic simulation
dc.typeArticle
dc.contributor.departmentCIVIL ENGINEERING
dc.description.doi10.1002/nme.1986
dc.description.sourcetitleInternational Journal for Numerical Methods in Engineering
dc.description.volume71
dc.description.issue11
dc.description.page1297-1320
dc.description.codenIJNMB
dc.identifier.isiut000249712600002
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