Improving predictions for water spills using DDDAS Conference Paper

abstract

• In dynamic data driven application systems, the predictions are improved based on measurements obtained in time. Predicted quantity often satisfies differential equation models with unknown initial conditions and source terms. A physical example of the problem we are attempting to solve is a major waste spill near a body of water. This can be, for example, near an aquifer, or possibly in a river or bay. Sensors can be used to measure where the contaminant was spilled, where it is, and where it will go. In this paper, we propose techniques for improving predictions by estimating initial conditions and source terms. We show how well we can solve the problem for a variety of data-driven models. 2008 IEEE.

name of conference

• 2008 IEEE International Symposium on Parallel and Distributed Processing

authors

• Efendiev, Yalchin

published proceedings

• 2008 IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL & DISTRIBUTED PROCESSING, VOLS 1-8

author list (cited authors)

• Douglas, C. C., Dostert, P., Efendiev, Y., Ewing, R. E., & Li, D.

citation count

• 0

complete list of authors

• Douglas, Craig C||Dostert, Paul||Efendiev, Yalchin||Ewing, Richard E||Li, Deng

publication date

• April 2008

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS  Journal

Digital Object Identifier (DOI)

• 10.1109/ipdps.2008.4536410

International Standard Book Number (ISBN) 13

• 978-1-4244-1693-6

start page

• 2595

end page

• +

URL

• http://dx.doi.org/10.1109/ipdps.2008.4536410