Multiscale Interpolation, Backward in Time Error Analysis for Data-Driven Contaminant Simulation

Craig C. Douglas1,2, Yalchin Efendiev3, Richard Ewing3, Victor Ginting3, Raytcho Lazarov3, Martin J. Cole4, Greg Jones4, and Chris R. Johnson4

1University of Kentucky, Department of Computer Science, 325 McVey Hall, Lexington, KY 40506-0045, USA
craig.douglas@uky.edu
ceshan0@uky.edu

2Yale University, Department of Computer Science, P.O. Box 208285, New Haven, CT 06520-8285, USA
douglas-craig@cs.yale.edu

3Texas A&M University, ISC, College Station, TX, USA
efendiev@math.tamu.edu
richard-ewing@tamu.edu
ginting@math.tamu.edu
lazarov@math.tamu.edu

4Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA
mjc@sci.utah.edu
gjones@sci.utah.edu
crj@cs.utah.edu

Abstract. We describe, devise, and augment dynamic data-driven application simulations (DDDAS). DDDAS offers interesting computational and mathematically unsolved problems. In this paper, we discuss how to update the solution as well as input parameters involved in the simulation based on local measurements. The updates are performed in time. We test our method on various synthetic examples.

LNCS 3515, pp. 640-647.

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