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dc.contributor.authorArslan, Sibel
dc.contributor.authorDemirbas, Munise Didem
dc.contributor.authorÇakır, Didem
dc.contributor.authorOzturk,Celal
dc.date.accessioned2023-06-23T08:25:23Z
dc.date.available2023-06-23T08:25:23Z
dc.date.issued16.08.2022tr
dc.identifier.citationFunctionally Graded Materials (FGMs) are designed for use in high-temperature applications. Since the mass production of FGM has not yet been made, the determination of its thermomechanical limits depends on the compositional gradient exponent value. In this study, an efficient working model is created for the thermal stress problem of the 2D-FG plate using Multi-gene Genetic Programming (MGGP). In our MGGP model in this study, data sets obtained from the numerical analysis results of the thermal stress problem are used, and formulas that give equivalent stress levels as output data, with the input data being the compositional gradient exponent, are obtained. For the current problem, efficient models that reduce CPU processing time are obtained by using the MGGP method.tr
dc.identifier.urihttps://www.mdpi.com/2076-3417/12/16/8198
dc.identifier.urihttps://hdl.handle.net/20.500.12418/14054
dc.description.abstractFunctionally Graded Materials (FGMs) are designed for use in high-temperature applications. Since the mass production of FGM has not yet been made, the determination of its thermomechanical limits depends on the compositional gradient exponent value. In this study, an efficient working model is created for the thermal stress problem of the 2D-FG plate using Multi-gene Genetic Programming (MGGP). In our MGGP model in this study, data sets obtained from the numerical analysis results of the thermal stress problem are used, and formulas that give equivalent stress levels as output data, with the input data being the compositional gradient exponent, are obtained. For the current problem, efficient models that reduce CPU processing time are obtained by using the MGGP method.tr
dc.language.isoengtr
dc.publisherMDPIST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLANDtr
dc.relation.isversionof10.3390/app12168198tr
dc.rightsinfo:eu-repo/semantics/embargoedAccesstr
dc.subjectmulti-gene genetic programmingtr
dc.subjectgenetic programmingtr
dc.subjectthermal stress problemtr
dc.subjectcompositional gradient exponenttr
dc.subjectfunctionally graded materialtr
dc.titleStress Analysis of 2D-FG Rectangular Plates with Multi-Gene Genetic Programmingtr
dc.typearticletr
dc.relation.journalAPPLIED SCIENCES-BASELtr
dc.contributor.departmentTeknoloji Fakültesitr
dc.contributor.authorID0000-0003-3626-553Xtr
dc.identifier.volume12tr
dc.identifier.issue16tr
dc.relation.publicationcategoryUluslararası Editör Denetimli Dergide Makaletr


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