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Reliable Real-Time Optimization of Nonconvex Systems Described by Parametrized Partial Differential Equations

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dc.creator Oliveira, I.B.
dc.creator Patera, Anthony T.
dc.date 2003-11-19T20:52:21Z
dc.date 2003-11-19T20:52:21Z
dc.date 2003-01
dc.date.accessioned 2013-10-09T02:32:07Z
dc.date.available 2013-10-09T02:32:07Z
dc.date.issued 2013-10-09
dc.identifier http://hdl.handle.net/1721.1/3707
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description The solution of a single optimization problem often requires computationally-demanding evaluations; this is especially true in optimal design of engineering components and systems described by partial differential equations. We present a technique for the rapid and reliable optimization of systems characterized by linear-functional outputs of partial differential equations with affine parameter dependence. The critical ingredients of the method are: (i) reduced-basis techniques for dimension reduction in computational requirements; (ii) an "off-line/on-line" computational decomposition for the rapid calculation of outputs of interest and respective sensitivities in the limit of many queries; (iii) a posteriori error bounds for rigorous uncertainty and feasibility control; (iv) Interior Point Methods (IPMs) for efficient solution of the optimization problem; and (v) a trust-region Sequential Quadratic Programming (SQP) interpretation of IPMs for treatment of possibly non-convex costs and constraints.
dc.description Singapore-MIT Alliance (SMA)
dc.format 334725 bytes
dc.format application/pdf
dc.language en_US
dc.relation High Performance Computation for Engineered Systems (HPCES);
dc.subject parametrized partial differential equations
dc.subject reduced-basis
dc.subject computational decomposition
dc.subject a posteriori error bounds
dc.subject Interior Point Methods
dc.subject Sequential Quadratic Programming
dc.title Reliable Real-Time Optimization of Nonconvex Systems Described by Parametrized Partial Differential Equations
dc.type Article


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