A multilevel approach to single- and multiobjective aerodynamic optimization

Kampolis, IC; Giannakoglou, KC

dc.contributor.author	Kampolis, IC	en
dc.contributor.author	Giannakoglou, KC	en
dc.date.accessioned	2014-03-01T01:27:42Z
dc.date.available	2014-03-01T01:27:42Z
dc.date.issued	2008	en
dc.identifier.issn	0045-7825	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18552
dc.subject	Design optimization	en
dc.subject	Evolutionary algorithms	en
dc.subject	Gradient-based optimization	en
dc.subject	Metamodels	en
dc.subject.classification	Engineering, Multidisciplinary	en
dc.subject.classification	Mathematics, Interdisciplinary Applications	en
dc.subject.classification	Mechanics	en
dc.subject.other	Airfoils	en
dc.subject.other	Approximation theory	en
dc.subject.other	Evolutionary algorithms	en
dc.subject.other	Gradient methods	en
dc.subject.other	Mathematical models	en
dc.subject.other	Multiobjective optimization	en
dc.subject.other	Pareto principle	en
dc.subject.other	Radial basis function networks	en
dc.subject.other	Structural design	en
dc.subject.other	Gradient-based optimization	en
dc.subject.other	Metamodels	en
dc.subject.other	Aerodynamics	en
dc.subject.other	Aerodynamics	en
dc.subject.other	Airfoils	en
dc.subject.other	Approximation theory	en
dc.subject.other	Evolutionary algorithms	en
dc.subject.other	Gradient methods	en
dc.subject.other	Mathematical models	en
dc.subject.other	Multiobjective optimization	en
dc.subject.other	Pareto principle	en
dc.subject.other	Radial basis function networks	en
dc.subject.other	Structural design	en
dc.title	A multilevel approach to single- and multiobjective aerodynamic optimization	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.cma.2008.01.015	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.cma.2008.01.015	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	An optimization platform with multilevel structure, which is capable of efficiently solving design-optimization problems in aerodynamics, is proposed. The multilevel structure relies on a two-way regular exchange of information between successive search levels. Each level can be associated with a different evaluation software, different problem parameterization and/or different search tool, for the minimization of the same objective function(s). The combination of some or all of the aforementioned strategies is possible, although beyond the scope of this paper. The basic optimization tool, which is associated with at least one of the levels, is a metamodel-assisted evolutionary algorithm; candidate solutions that have previously been examined are memorized and serve to train radial basis function networks, operating as local surrogate evaluation models. To handle multiobjective optimization problems with different search techniques at each level, we hybridize an evolutionary algorithm that computes the front of Pareto optimal solutions at the lower level(s) with a gradient-based method at the upper level, for the purpose of refinement through local search. In aerodynamic optimization, the adjoint method is used to compute the gradient of the objective function. For the gradient method to apply to a front of solutions rather than a single individual, an approximation of the SPEA-2 utility function gradient needs to be devised. The multilevel platform is demonstrated on mathematical problems as well as the design of isolated and compressor cascade airfoils. (C) 2008 Elsevier B.V. All rights reserved.	en
heal.publisher	ELSEVIER SCIENCE SA	en
heal.journalName	Computer Methods in Applied Mechanics and Engineering	en
dc.identifier.doi	10.1016/j.cma.2008.01.015	en
dc.identifier.isi	ISI:000257666400018	en
dc.identifier.volume	197	en
dc.identifier.issue	33-40	en
dc.identifier.spage	2963	en
dc.identifier.epage	2975	en