Dynamic Data-Driven Contaminant Simulation
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In this paper we discuss a numerical procedure for performing dynamic data driven simulations (DDDAS). In dynamic data driven simulations our goal is to update the solution as well as input parameters involved in the simulation based on local measurements. The updates are performed in time. In the paper we discuss (1) updating the solution using multiscale interpolation technique (2) recovering as well as updating initial conditions based on least squares approach (3) updating the permeability field using Markov Chain Monte Carlo techniques. We test our method on various synthetic examples.
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- Dynamic Data-Driven Contaminant Simulation
- Book Title
- Current Trends in High Performance Computing and Its Applications
- Book Subtitle
- Proceedings of the International Conference on High Performance Computing and Applications, August 8–10, 2004, Shanghai, P.R. China
- Book Part
- Part I
- pp 25-36
- Print ISBN
- Online ISBN
- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
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- Editor Affiliations
- 1. School of Computer Engineering and Science, Shanghai University
- 2. Department of Mathematics, Southern Methodist University
- 3. Department of Mathematics, University of Houston
- Author Affiliations
- 4. Department of Computer Science, University of Kentucky, 773 Anderson Hall, Lexington, KY, 40506-0046, USA
- 5. Department of Computer Science, Yale University, P.O. Box 208285, New Haven, CT, 06520-8285, USA
- 6. Texas A&M University, College Station, TX, USA
- 7. Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA
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