Scalable Multilevel Uncertainty Quantification Concepts for Extreme-Scale Multiscale Problems
Our work in this project is aimed at making fundamental advances in multilevel and multiscale methods for problems with uncertainties related to flows in porous media. The main thrust of this research is to develop a systematic multiscale, multilevel parallel approaches for problems with uncertainties and use them in the uncertainty quantification. A key emphasis is on problems without an apparent scale separation in space, time, and uncertainty spaces. Multiscale solution methods are currently under active investigation. However, the develop- ment of multiscale methods for problems with uncertainties where the scales and uncertainties are tightly coupled is a research area that is less explored. During this project, we have made some significant contributions to the developments of multiscale methods, the uncertainty quantification for multiscale methods, multiscale model learning, uncertainty quantification in inverse problems, and applications.
- Research Organization:
- Texas A & M Univ., College Station, TX (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- DOE Contract Number:
- FG02-13ER26165; SC0010713
- OSTI ID:
- 1485812
- Report Number(s):
- DOE-TAMU-ER-26165
- Country of Publication:
- United States
- Language:
- English
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