dc.contributor.author | Ali, S. | |
dc.contributor.author | Damodaran, Murali | |
dc.contributor.author | Patera, Anthony T. | |
dc.date.accessioned | 2003-11-19T20:50:04Z | |
dc.date.available | 2003-11-19T20:50:04Z | |
dc.date.issued | 2003-01 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/3706 | |
dc.description.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. | en |
dc.description.sponsorship | Singapore-MIT Alliance (SMA) | en |
dc.format.extent | 256590 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.relation.ispartofseries | High Performance Computation for Engineered Systems (HPCES); | |
dc.subject | reduced-basis | en |
dc.subject | a posteriori error estimation | en |
dc.subject | design optimization | en |
dc.subject | nonlinear optimization | en |
dc.subject | bilevel optimization | en |
dc.subject | inverse problems | en |
dc.title | Real-Time Optimal Parametric Design of a Simple Infiltration-Evaporation Model Using the Assess-Predict-Optimize (APO) Strategy | en |
dc.type | Article | en |