Interpolation and update in dynamic data-driven application simulations

Craig C. Douglas, Yalchin Efendiev*, Richard Ewing, Raytcho Lazarov, Martin J. Cole, Greg Jones, Chris R. Johnson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations


In this paper we discuss numerical techniques involved in dynamic data driven application simulations (DDDAS). We present an interpolation technique and update procedures. A multiscale interpolation technique is designed to map the sensor data into the solution space. In particular we show that frequent updating of the sensor data in the simulations can significantly improve the prediction results and thus important for applications. The frequency of sensor data updating in the simulations is related to streaming capabilities and addressed within DDDAS framework (Douglas et al., 2003). We discuss the update of permeability and initial data.

Original languageEnglish (US)
Title of host publicationAir, Water and Soil Quality Modelling for Risk and Impact Assessment
Number of pages12
StatePublished - 2007
Externally publishedYes

Publication series

NameNATO Security through Science Series C: Environmental Security
ISSN (Print)1871-4668


  • Dynamic data driven application
  • Multiscale
  • Porous media
  • Update

ASJC Scopus subject areas

  • General Environmental Science


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