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dc.contributor.authorCanuto, Claudio
dc.contributor.authorHoel, Haakon
dc.contributor.authorIcardi, Matteo
dc.contributor.authorQuadrio, Nathan
dc.contributor.authorTempone, Raul
dc.date.accessioned2017-06-05T08:35:46Z
dc.date.available2017-06-05T08:35:46Z
dc.date.issued2015-01-07
dc.identifier.urihttp://hdl.handle.net/10754/624050
dc.description.abstractMultilevel Monte Carlo (MLMC) is an efficient and flexible solution for the propagation of uncertainties in complex models, where an explicit parametrization of the input randomness is not available or too expensive. We propose a general-purpose algorithm and computational code for the solution of Partial Differential Equations (PDEs) on random geoemtry and with random parameters. We make use of the key idea of MLMC, based on different discretization levels, extending it in a more general context, making use of a hierarchy of physical resolution scales, solvers, models and other numerical/geometrical discretization parameters. Modifications of the classical MLMC estimators are proposed to further reduce variance in cases where analytical convergence rates and asymptotic regimes are not available. Spheres, ellipsoids and general convex-shaped grains are placed randomly in the domain with different placing/packing algorithms and the effective properties of the heterogeneous medium are computed. These are, for example, effective diffusivities, conductivities, and reaction rates. The implementation of the Monte-Carlo estimators, the statistical samples and each single solver is done efficiently in parallel.
dc.titleFlow, transport and diffusion in random geometries I: a MLMC algorithm
dc.typePoster
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.conference.dateJanuary 6-9, 2015
dc.conference.nameAdvances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2015)
dc.conference.locationKAUST
dc.contributor.institutionUniversity of Oslo
dc.contributor.institutionPolitecnico di Torino
kaust.personIcardi, Matteo
kaust.personQuadrio, Nathan
kaust.personTempone, Raul
refterms.dateFOA2018-06-14T04:26:44Z


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