Dynamic Data-Driven Contaminant Simulation

  • Craig C. Douglas
  • Yalchin Efendiev
  • Richard Ewing
  • Victor Ginting
  • Raytcho Lazarov
  • Martin J. Cole
  • Greg Jones
  • Chris R. Johnson
Conference paper

DOI: 10.1007/3-540-27912-1_3

Cite this paper as:
Douglas C.C. et al. (2005) Dynamic Data-Driven Contaminant Simulation. In: Zhang W., Tong W., Chen Z., Glowinski R. (eds) Current Trends in High Performance Computing and Its Applications. Springer, Berlin, Heidelberg

Summary

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Craig C. Douglas
    • 1
    • 2
  • Yalchin Efendiev
    • 3
  • Richard Ewing
    • 3
  • Victor Ginting
    • 3
  • Raytcho Lazarov
    • 3
  • Martin J. Cole
    • 4
  • Greg Jones
    • 4
  • Chris R. Johnson
    • 4
  1. 1.Department of Computer ScienceUniversity of KentuckyLexingtonUSA
  2. 2.Department of Computer ScienceYale UniversityNew HavenUSA
  3. 3.Texas A&M UniversityCollege StationUSA
  4. 4.Scientific Computing and Imaging InstituteUniversity of UtahSalt Lake CityUSA

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