Real-Time Optimal Parametric Design of a Simple Infiltration-Evaporation Model Using the Assess-Predict-Optimize (APO) Strategy
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HPCES019.pdf
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Author(s)
Ali, S.
Damodaran, Murali
Patera, Anthony T.
Date Issued
January 2003
Series/Report no.
High Performance Computation for Engineered Systems (HPCES);
Abstract
Optimal parametric design of a system must be able to respond quickly to short term needs as well as long term conditions. To this end, we present an Assess-Predict-Optimize (APO) strategy which allows for easy modification of a system’s characteristics and constraints, enabling quick design adaptation. There are three components to the APO strategy: Assess - extract necessary information from given data; Predict - predict future behavior of system; and Optimize – obtain optimal system configuration based on information from the other components. The APO strategy utilizes three key mathematical ingredients to yield real-time results which would certainly conform to given constraints: dimension reduction of the model, a posteriori error estimation, and optimization methods. The resulting formulation resembles a bilevel optimization problem with an inherent nonconvexity in the inner level. Using a simple infiltration-evaporation model to simulate an irrigation system, we demonstrate the APO strategy’s ability to yield real-time optimal results. The linearized model, described by a coercive elliptic partial differential equation, is discretized by the reduced-basis output bounds method. A primal-dual interior point method is then chosen to solve the resulting APO problem.
Subjects
reduced-basis
a posteriori error estimation
design optimization
nonlinear optimization
bilevel optimization
inverse problems
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