The ability to develop science-based and validated computational tools to simulate and facilitate the development of clean, highly efficient energy systems of the future requires innovation in several key computational science technologies, including scientific data management, scientific visualization, scientific software environments, and scientific computing. The overall objective of this work is to leverage our expertise and experience in both scientific visualization and complex science-based simulations toward the accurate and robust simulation of science-based phenomena in the area of unconventional and renewable energy research. This work is aimed at garnering a better understanding of science-based phenomena in energy research and also the advancement of the Uintah software system. The Uintah software system accommodates the massive amounts of data and advanced algorithmic, software, and hardware technologies required to deal with the enormity and complexity of the simulation data in this area of research. To accomplish these goals, we are creating new numerical and visualization techniques needed to assess the uncertainty of the simulation, extend the Uintah scientific problem-solving environment for large-scale simulation of science-based systems, and integrate and extend the data provenance infrastructure of Uintah to systematically capture provenance information and track simulation parameter studies.
1) Extend the Uintah scientific problem-solving environment to simulate large multi-scale, multi-physics science-based energy systems.
2) Research and develop large-scale visualization techniques for science-based energy system simulation applications.
3) Research science-based simulations on present GPUs and future extensions.
4) Research uncertainty estimation techniques for science-based energy system simulations.
5) Extend the VisTrails infrastructure to provenance-enable the Uintah problem-solving environment to capture provenance information and provide support for publishing and sharing the simulation results and associated data products.