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Friday, May 10

A Modular Uncertainty Quantification Framework for Multi-physics Systems

Xiao Chen, Postdoctoral Research Staff Member, Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, ORNL
Computer Science and Mathematics Division Seminar
10:00 AM — 11:00 AM, Joint Institute for Computational Sciences (JICS Auditorium) , Building 5100, Room 128
Contact: Clayton Webster (webstercg@ornl.gov), 865.574.3649

Abstract

This talk presents a modular uncertainty quantification (UQ) methodology for multi-physics applications in which each physics module can be independently embedded with its internal UQ method (intrusive or non-intrusive). This methodology offers the advantage of "plug-and-play" flexibility (i.e., UQ enhancements to one module do not require updates to the other modules) without losing the "global" uncertainty propagation property. (This means that, by performing UQ in this modular manner, all inter-module uncertainty and sensitivity information is preserved.) In addition, using this methodology one can also track the evolution of global uncertainties and sensitivities at the grid point level, which may be useful for model improvement. We demonstrate the utility of such a framework for error management and Bayesian inference on a practical application involving a multi-species flow and reactive transport in randomly heterogeneous porous media.

If you would like to meet with Xiao Chen, please contact Billy Fields or Clayton Webster at any time.