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Mallick, Bani

Publications and source records attributed to Mallick, Bani.

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.

97 MATHEMATICS AND COMPUTING↗

Bayesian Uncertainty Quantification in Predictions of Flows in Highly Heterogeneous Media and Its Applications to the CO 2 Sequestration

In this proposal, we have worked on Bayesian uncertainty quantification for predictions of fows in highly heterogeneous media. The research in this proposal is broad and includes: prior modeling for heterogeneous permeability fields; effective parametrization of heterogeneous spatial priors; efficient ensemble- level solution techniques; efficient multiscale approximation techniques; study of the regularity of complex posterior distribution and the error estimates due to parameter reduction; efficient sampling techniques; applications to multi-phase ow and transport. We list our publications below and describe some of our main research activities. Our multi-disciplinary team includes experts from the areas of multiscale modeling, multilevel solvers, Bayesian statistics, spatial permeability modeling, and the application domain.

97 MATHEMATICS AND COMPUTING↗