ITR: A prototype to support near real-time environmental characterization

Funding (Duration): $568,418 (09/03 – 08/07)

Sponsor: National Science Foundation (Information Technology Research Program)

PI: G. Mahinthakumar

Co-PIs: R. Ranjithan (NCSU), N. Karonis (NIU)

Short Abstract: The overall goal of this proposal is to investigate formal computational approaches that can readily harness grid computing for the solution of environmental characterization problems. To this end, we will develop a grid-enabled software framework. Two alternative paradigms, based on the grid-enabled version of MPI and Java, respectively, will be explored. The framework will be applied to groundwater and air pollution problems, both of which are of prime societal importance. Acknowledging that, even within a grid environment, inverse problems are computationally challenging, model surrogates (e.g., statistical approximations using artificial neural networks) will be explored. Further, Modeling to Generate Alternatives (MGA), a technique that identifies a set of good yet very different solutions, will be investigated for dynamically steering the search process through human-computer interaction. Alternatives generated via MGA will be used also to address the commonly encountered non-uniqueness issue (i.e., where multiple characterizations can match the same measured data) in inverse problems.