Soft Computing Methods for Thermo-Acoustic Simulation

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dc.contributor.authorSelimefendigil, F
dc.contributor.authorÖztop, HF
dc.date.accessioned2024-07-18T11:51:21Z
dc.date.available2024-07-18T11:51:21Z
dc.description.abstractIn the present study, soft computing methods are employed for thermoacoustic simulation. A ducted Burke-Schumann diffusion flame is used as the heat source for a horizontal duct. First, a dynamic model is constructed from the input-output data sets (velocity forcing - heat release) generated from the Burke-Schumann flame using Comsol. An efficient and cheap model of heat source is obtained using dynamic fuzzy identification. The full thermoacoustic system is simulated in a time domain with the Galerkin method using the identified heat source model. Finally, dynamic neural networks are utilized for obtaining a dynamic fit for a set of operating conditions for the acoustic velocity at the heater location. The overall agreement between the outputs of the soft computing tools (fuzzy and neural network tools) with the Comsol and Galerkin solver is found to be satisfactory.
dc.identifier.issn1040-7782
dc.identifier.other1521-0634
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/4777
dc.language.isoEnglish
dc.publisherTAYLOR & FRANCIS INC
dc.subjectARTIFICIAL NEURAL-NETWORKS
dc.subjectCONVECTION HEAT-TRANSFER
dc.subjectSYSTEM-IDENTIFICATION
dc.subjectMIXED CONVECTION
dc.subjectINSTABILITY
dc.subjectMODEL
dc.subjectFLOW
dc.subjectOSCILLATIONS
dc.subjectPREDICTION
dc.subjectDYNAMICS
dc.titleSoft Computing Methods for Thermo-Acoustic Simulation
dc.typeArticle

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