Pennsylvania State Univ University Park Proposal Number: 0640443
CAREER: An Integrated Research/Educational Plan for a Grid-based Collaboratory to Support the Design and Management of Environmental Monitoring Systems
Cynthia J. Ekstein, Program Director (703) 292-7941
Problem: Long-term monitoring (LTM) design is a problem of paramount importance to the environmental engineering field because environmental observation data provide the sole means of assessing if engineered systems are successfully protecting human and ecologic health. LTM design is an extremely challenging problem, which requires engineers to capture an impacted system's governing processes, elucidate human and ecologic risks, limit management costs, and satisfy the interests of multiple stakeholders (e.g., site owners, regulators, and public advocates). In an effort to address these challenges, this proposed research and educational plan will develop the Adaptive Strategies for Sampling In Space and Time (ASSIST) collaboratory for the LTM community. Intellectual Merit: This research seeks to develop an open access monitoring framework that will allow users to combine a broader range of data sources with physical model predictions to improve spatiotemporal visualizations of impacted systems, reduce uncertainties, and decrease long-term management costs. To help ASSIST users balance these conflicting objectives, this proposed research will develop the first linkage-learning multiobjective genetic algorithm solver for grid computing environments. The multiobjective solver will be coupled with the C++ ASSIST Assimilation Toolbox to quantify monitoring design tradeoffs and provide spatiotemporal visualizations of their consequences. The C++ ASSIST Assimilation Toolbox will be developed using the Bayesian Maximum Entropy and Ensemble Kalman Filtering frameworks. The ASSIST collaboratory will enhance environmental engineers' abilities to (1) balance multiple design objectives, (2) merge high dimensional, nonlinear fate-and-transport model predictions with a broad range of data sources, (3) consider a much broader range of model and data uncertainties, and (4) adapt their objectives and system design to account for advances in real-time sensing. Three phases of testing and validation will be used to justify broad dissemination of the ASSIST collaboratory's decision support tools. Educational Merit: The ASSIST collaboratory will provide multi-media educational resources with interactive Microsoft Visual Basic software to help explain the underlying theory and implementation of the ASSIST framework's decision support tools. Classroom practices for incorporating the Microsoft Visual Basic educational software into undergraduate and graduate courses will be developed, assessed, and disseminated. Broader Impacts: The ASSIST decision support tools will be developed to maximize their ease-of-use in a wide array of water and environmental applications that require forecasting under uncertainty and/or multiobjective optimization (e.g., water distribution optimization under uncertainty, non-point source pollution management, water security, and multipurpose water systems control).
Normal 0 false false false EN-US X-NONE X-NONE Dr. Reed’s grant entitled "CAREER: An Integrated Research/Education Plan for a Grid-based Collaboratory to Support the Design and Management of Environmental Monitoring Systems" (BES-0640443, $400,000, 2007-2013) has contributed the Adaptive Strategies for Sampling in Space-and-Time (ASSIST) groundwater monitoring framework. The ASSIST framework has contributed massively parallel "many-objective" evolutionary search algorithms, innovations in bias-aware ensemble Kalman filtering and highly interactive visualization to support decision making for 2-10 conflicting objectives. This project has supported two PHD theses, three MS theses, and two undergraduate research theses. Reed has actively supported under-represented groups including 1 minority PHD female, 1 minority MS female, and 1 undergraduate female. The massively parallel optimization and visualization tools developed for this project have made substantial contributions to a broad range of highly challenging applications including groundwater management, urban water supply, water distribution networks, resource allocation, and operations research. Dr. Reed’s CAREER project has also facilitated a successful technology transfer and ongoing collaboration with The Aerospace Corporation (Aerospace) for spaced-based Earth observations systems design. Aerospace is a California nonprofit corporation that operates a federally funded research and development center (FFRDC) sponsored by the United States Air Force. Aerospace’s key FFRDC roles are to evaluate and advance space programs that serve national interest. The technology transfer and collaboration with Aerospace has yielded the Genetic Resources for Innovation and Problem Solving (GRIPS) decision support platform. The GRIPS platform combines massively parallel multiobjective optimization and visualization to provide a global perspective of the key tradeoffs that must be understood to make informed and defendable decisions when designing space-based Earth observation systems. GRIPS is being used operationally as a primary design tool within Aerospace. Many key decisions in the space systems-architecting domain can be traced to the GRIPS results provided to a wide range of high-level government officials. The joint GRIPS collaboration between Dr. Reed and Aerospace has yielded an innovative licensing agreement that is currently being used to initiate venture capital start-ups advancing multiobjective decision making in a range of application areas (aviation, finance, logistics, energy, and travel). Complimentary to this proposed project, Dr. Reed is continuing his collaboration with Aerospace as the PI on a NSF Blue Waters Petascale Resource Allocation (OCI-1144212) entitled "Collaborative Research: Petascale Design and Management of Satellite Assets to Advance Space Based Earth Science" that is exploiting the 750,000 core system for complex engineered systems design.
