A dynamic data-driven application simulation framework for contaminant transport problems |
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Affiliation: | 1. University of Kentucky Computer Science Department 773 Anderson Hall Lexington, KY 40506-0046, U.S.A.;2. Yale University Computer Science Department P.O. Box 208285 New Haven, CT 06520-8285, U.S.A. |
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Abstract: | We describe, devise, and augment dynamic data-driven application simulations (DDDAS). DDDAS offers interesting computational and mathematically unsolved problems, such as, how do you analyze, compute, and predict the solution of a generalized PDE when you do not know either where or what the boundary conditions are at any given moment in the simulation in advance? A summary of DDDAS features and why this is a intellectually stimulating new field are included in the paper.We apply the DDDAS methodology to some examples from a contaminant transport problem. We demonstrate that the multiscale interpolation and backward in time error monitoring are useful to long running simulations. |
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