Application of Digital Twins to Large-Scale Complex Systems

Description

This workshop integrates all of the issues related to data assimilation & inverse problems, optimal control & decision making, model reduction & surrogates, and uncertainty quantification addressed in the first three workshops in the context of challenging scientific, engineering, and technological problems. It also addresses problem-specific challenges that arise, including: (1) efficient gradient-based optimization methods rely on solution of adjoint PDEs, which can be problematic for operator-split multiphysics solvers, nonsmooth dynamics, and chaotic systems; (2) stability of individual assimilation and control constituents does not ensure stability of the coupled DA system; (3) ROMs and surrogates can be combined with high fidelity models via multi-fidelity variance reduction methods, but how best to do this in the coupled data assimilation and optimal control setting needs to be established; and (4) how to represent uncertainty in the model itself (structural uncertainty) remains a fundamental challenge. These and other issues will be explored in the context of complex applications of DTs, in such areas as aerospace, biomedicine, climate, energy, environment, infrastructure, manufacturing, materials, natural hazards, and process systems.

Registration

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