A dynamic data-driven application simulation framework for contaminant transport problems Export

@article{citeulike:5898954, 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.}, author = {Douglas, C. C. and Efendiev, Y.}, citeulike-article-id = {5898954}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.camwa.2006.05.003}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0898122106001325}, doi = {10.1016/j.camwa.2006.05.003}, issn = {08981221}, journal = {Computers \& Mathematics with Applications}, keywords = {06, dddas, simulation, transportation}, month = {June}, number = {11}, pages = {1633--1646}, posted-at = {2009-10-06 15:26:12}, priority = {2}, title = {A dynamic data-driven application simulation framework for contaminant transport problems}, url = {http://dx.doi.org/10.1016/j.camwa.2006.05.003}, volume = {51}, year = {2006} }

TY - JOUR ID - citeulike:5898954 L3 - citeulike-article-id:5898954 N2 - 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. IS - 11 JF - Computers & Mathematics with Applications SN - 08981221 EP - 1646 TI - A dynamic data-driven application simulation framework for contaminant transport problems VL - 51 SP - 1633 KW - 06 KW - dddas KW - simulation KW - transportation AU - Douglas, CC AU - Efendiev, Y PY - 2006/06// UR - http://dx.doi.org/10.1016/j.camwa.2006.05.003 ER -