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Award Abstract #0540136
DDDAS-TMRP: Collaborative Research: Adaptive Data-Driven Sensor Configuration, Modeling, and Deployment for Oil, Chemical, and Biological Contamination near Coastal Facilities


NSF Org: CNS
Division of Computer and Network Systems
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Initial Amendment Date: September 19, 2005
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Latest Amendment Date: June 18, 2008
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Award Number: 0540136
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Award Instrument: Standard Grant
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Program Manager: Anita J. LaSalle
CNS Division of Computer and Network Systems
CSE Directorate for Computer & Information Science & Engineering
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Start Date: October 1, 2005
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Expires: September 30, 2008 (Estimated)
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Awarded Amount to Date: $81000
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Investigator(s): Yalchin Efendiev efendiev@math.tamu.edu (Principal Investigator)
Richard Ewing (Former Principal Investigator)
Raytcho Lazarov (Co-Principal Investigator)
Guan Qin (Co-Principal Investigator)
Yalchin Efendiev (Former Co-Principal Investigator)
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Sponsor: Texas A&M Research Foundation
400 Harvey Mitchell Parkway, S
College Station, TX 77845 979/845-8600
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NSF Program(s): ITR-DYNAMIC DATA DRIV APP SYS
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Field Application(s): 0000912 Computer Science
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Program Reference Code(s): HPCC, 9218
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Program Element Code(s): 7581

ABSTRACT

The project is aimed at developing a variable light wave sensor array that we will integrate into an ocean observational system. This system will be superior to most near coastal ocean models, which are typically wind driven but not contamination transport driven, in that our new model will be both. These objectives will be accomplished through the dynamic injection of observed ocean data into multiscale mathematical models and computer simulations. The project will create research topics in multiscale mathematics, statistics, and software application integration with a flexible, Grid-based

database and problem solving environment. The project will follow an integrated approach that addresses technical issues at each step of the process: 1) the dynamic simulation instructs the sensors what to look for and reprograms it for those analytes, 2) the sensors report to the simulation the new observed data, and 3) the simulation then incorporates the new data, updates its predictions, and reprograms the sensors as necessary in a closed loop. We will reduce the amount of human intervention needed to monitor spills and other contamination events, making DDDAS viable for sensors going to locations that are difficult to communicate with the sensors in real-time (e.g., an unreliable satellite link or another planetary body in the future). The work will build on the successful results of research previously funded by the NSF, including the SURA Coastal Ocean Observation and Prediction and two ITR projects to develop algorithms, error controls, and

middleware to optimally manage provably scalable computing resources for Grid computing. The project has the ultimate objective to guide the development of hardware and software to enable performing both lab and ocean test, but these tasks will be relegated for follow-on efforts to the present project. Both academic and industrial partners will be involved in the present effort. The research in this project will be extendable to other application environments.


PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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B. Dai, A. Urbas, C. C. Douglas, and R. A. Lodder. "Molecular factor computing for predictive spectroscopy," Pharmaceutical Research, v.24, 2007, p. 1441.

C. C. Douglas and Deng Li. "Dynamic Data-Driven Application Simulation Projects," Bulletin of the Japanese Society of Industrial and Applied Mathematics, v.15, 2005, p. 75-78.

C. C. Douglas, Deng Li, T. Kako, M. Suzuki, and I. Hagiwari,. "On a novel perturbation expansion method for coupled systems of acoustics and structures," Computer and Mathematics with Applications, v.51, 2006, p. 1689.

C. C. Douglas, Y. Efendiev, R. Ewing, V. Ginting, and R. Lazarov. "Dynamic data driven simulations in stochastic environments," Computing, v.77, 2006, p. 321-332.

C. C. Douglas, Y. Efendiev, V. Ginting, and R. Lazarov. "A dynamic data-driven application simulation framework for contaminant transport problems," Computer and Mathematics with Applications, v.51, 2006, p. 1633.

G. Kumfert, D.E. Bernholdt, T.G.W. Epperly, J.A. Kohl, L.C. McInnes, S. Parker, J. Ray. "How the common component architecture advances computational science," J. Phys.: Conf. Ser., v.46, 2006, p. 479.

I. Altintas, O. Barney, Z. Cheng, T. Critchlow, B. Ludaescher, S.G. Parker, A. Shoshani, M. Vouk. "Accelerating the scientific exploration process with scientific workflows," J. Phys. : Conf. Ser., v.46, 2006, p. 468.

J.C. Levin, M. Iskandarani, and D.B. Haidvogel. "To continue or discontinue: comparisons of continuous and discontinuous Galerkin formulations in a spectral element ocean model," Ocean Modelling, v.15, 2006, p. 56.

R. Sinha, R.E. Ewing, and R.D. Lazarov. "Some new error estimates of a semidiscrete finite volume element method for parabolic integro-differential equation with nonsmooth initial data," SIAM Journal on Numerical Analysis, v.43, 2006, p. 2320-2343.

T. Munzner, C.R. Johnson, R. Moorhead, H. Pfister, P. Rheingans, and T. Yoo. "NIH/NSF visualization research challenges report summary," IEEE Computer Graphics and Applications, v.2 (26), 2006, p. 20-24.


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Last Updated:April 2, 2007