Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale
- Cornell Univ., Ithaca, NY (United States); Cornell University
Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.
- Research Organization:
- Cornell Univ., Ithaca, NY (United States)
- Sponsoring Organization:
- USDOE Chicago Operations Office (CO)
- DOE Contract Number:
- SC0004910
- OSTI ID:
- 1331205
- Report Number(s):
- DOE-Cornell--4910
- Country of Publication:
- United States
- Language:
- English
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