Certified Rapid Solution of Partial Differential Equations for Real-Time Parameter Estimation and Optimization

Abstract

Engineering analysis requires the prediction of selected ?outputs? s relevant to ultimate component and system performance; typical outputs include critical stresses or strains, flow rates or pressure drops, and various measures of temperature and heat flux. These outputs are functions of ?inputs? ? that serve to identify a particular configuration of the component or system; typical inputs reflect geometry, properties, and boundary conditions and loads. In many cases, the input-output function is best articulated as a (say) linear functional ? of a field variable u(?) that is the solution to an input-parameterized partial differential equation (PDE); typical field variables and associated PDEs include temperature and steady/unsteady conduction, displacement and equilibrium elasticity/Helmholtz, and velocity and steady incompressible Navier?Stokes. System behavior is thus described by an input-output relation s(?) = ?(u(?)), the evaluation of which requires solution of the underlying PDE. Our focus is on ?deployed? systems?components or processes in operation in the field?and associated ?Assess-Act? scenarios. In the Assess stage we pursue robust parameter estimation (inverse) procedures that map measured-observable outputs to (all) possible system-characteristic and environment-state inputs. In the subsequent Act stage we then pursue adaptive design (optimization) procedures that map mission-objective outputs to best control-variable inputs.

Publication
Real-Time PDE-Constrained Optimization
Click the Cite button above to import publication metadata into your reference management software.
Ngoc Cuong Nguyen
Ngoc Cuong Nguyen
Principal Research Scientist

My research interests include computational mechanics, molecular mechanics, nanophotonics, scientific computing, and machine learning.