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Article: Application of simulated annealing to inverse design of transonic turbomachinery cascades

TitleApplication of simulated annealing to inverse design of transonic turbomachinery cascades
Authors
KeywordsInverse Design
Optimization
Simulated Annealing
Turbomachinery Cascade
Issue Date2002
PublisherProfessional Engineering Publishing Ltd. The Journal's web site is located at http://journals.pepublishing.com/link.asp?id=119773
Citation
Proceedings Of The Institution Of Mechanical Engineers, Part A: Journal Of Power And Energy, 2002, v. 216 n. 1, p. 59-74 How to Cite?
AbstractIn turbomachinery blade design, inverse methods and optimization techniques are often applied independently to produce high performance blade shapes. The idea of using an optimization algorithm to seek the optimal target distribution for an inverse design methodology has been explored. However, these efforts have been made mainly in the design of single aerofoils. In this paper, a new inverse design method is coupled with a simulated annealing algorithm to search for the optimum turbomachinery cascade shape. In order to speed up the algorithm, a database of generated designs is set up and the nearest match is selected to initialize subsequent calculation. The proposed computational procedure equips engineers with an automatic design tool with which the inverse method may be applied in isolation or combined with the optimization algorithm to produce the optimum. The inverse methodology is based on a cell vertex, finite volume time-marching flow solver that gives the viscous cascade flow solution in both the subsonic and the transonic flow regimes. The cascade shape is computed subject to an imposed distribution of the mass-averaged tangential velocity and a specified tangential thickness profile. The solver code is validated using experimental data and the accuracy of the inverse method is verified by regenerating a known cascade geometry starting from a different one using its mass-averaged tangential velocity distribution. In combining the inverse methodology with the optimization algorithm, the mass-averaged tangential velocity distribution is parametrized using a cubic B-spline curve and the proposed simulated annealing algorithm is applied to predict the optimal distribution by minimizing loss. The overall procedure is demonstrated to produce optimum shapes of a transonic axial turbine and an axial compressor rotor.
Persistent Identifierhttp://hdl.handle.net/10722/155859
ISSN
2015 Impact Factor: 0.689
2015 SCImago Journal Rankings: 0.521
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorTiow, WTen_US
dc.contributor.authorYiu, KFCen_US
dc.contributor.authorZangeneh, Men_US
dc.date.accessioned2012-08-08T08:38:04Z-
dc.date.available2012-08-08T08:38:04Z-
dc.date.issued2002en_US
dc.identifier.citationProceedings Of The Institution Of Mechanical Engineers, Part A: Journal Of Power And Energy, 2002, v. 216 n. 1, p. 59-74en_US
dc.identifier.issn0957-6509en_US
dc.identifier.urihttp://hdl.handle.net/10722/155859-
dc.description.abstractIn turbomachinery blade design, inverse methods and optimization techniques are often applied independently to produce high performance blade shapes. The idea of using an optimization algorithm to seek the optimal target distribution for an inverse design methodology has been explored. However, these efforts have been made mainly in the design of single aerofoils. In this paper, a new inverse design method is coupled with a simulated annealing algorithm to search for the optimum turbomachinery cascade shape. In order to speed up the algorithm, a database of generated designs is set up and the nearest match is selected to initialize subsequent calculation. The proposed computational procedure equips engineers with an automatic design tool with which the inverse method may be applied in isolation or combined with the optimization algorithm to produce the optimum. The inverse methodology is based on a cell vertex, finite volume time-marching flow solver that gives the viscous cascade flow solution in both the subsonic and the transonic flow regimes. The cascade shape is computed subject to an imposed distribution of the mass-averaged tangential velocity and a specified tangential thickness profile. The solver code is validated using experimental data and the accuracy of the inverse method is verified by regenerating a known cascade geometry starting from a different one using its mass-averaged tangential velocity distribution. In combining the inverse methodology with the optimization algorithm, the mass-averaged tangential velocity distribution is parametrized using a cubic B-spline curve and the proposed simulated annealing algorithm is applied to predict the optimal distribution by minimizing loss. The overall procedure is demonstrated to produce optimum shapes of a transonic axial turbine and an axial compressor rotor.en_US
dc.languageengen_US
dc.publisherProfessional Engineering Publishing Ltd. The Journal's web site is located at http://journals.pepublishing.com/link.asp?id=119773en_US
dc.relation.ispartofProceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energyen_US
dc.subjectInverse Designen_US
dc.subjectOptimizationen_US
dc.subjectSimulated Annealingen_US
dc.subjectTurbomachinery Cascadeen_US
dc.titleApplication of simulated annealing to inverse design of transonic turbomachinery cascadesen_US
dc.typeArticleen_US
dc.identifier.emailYiu, KFC:cedric@hkucc.hku.hken_US
dc.identifier.authorityYiu, KFC=rp00206en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1243/095765002760024845en_US
dc.identifier.scopuseid_2-s2.0-0036224944en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036224944&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume216en_US
dc.identifier.issue1en_US
dc.identifier.spage59en_US
dc.identifier.epage74en_US
dc.identifier.isiWOS:000175567400007-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridTiow, WT=6508344848en_US
dc.identifier.scopusauthoridYiu, KFC=24802813000en_US
dc.identifier.scopusauthoridZangeneh, M=7003688013en_US

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