Response surface methodology for design of gas turbine combustor

Mahto, Navin; Chakravarthy, Satyanarayanan R.

doi:10.1016/j.applthermaleng.2022.118449

Cited by 8 publications

(2 citation statements)

References 25 publications

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“…Although the geometry, validation, and workflow have been discussed earlier [12][13] , the main ideas are summarized here and changes required for the current study are discussed.…”

Section: Methodsmentioning

confidence: 99%

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Comparison of Response Surface Based Preliminary Design Methodologies for a Gas Turbine Combustor

Mahto,

Chakravarthy

2024

Def. Sc. J.

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Preliminary design of gas turbine combustor is a multi-objective optimization problem. The methodology to be used at the preliminary design stage depends on the freedom of design choices available. In this article, we explore three preliminary design methodologies for gas turbine combustor - M1: combustion liner design for a given casing; M2: combustion liner design without the casing and M3: coupled design of combustion liner and casing. A workflow for the automated design space exploration of gas turbine combustor using response surface methodology is presented. Computational fluid dynamics studies along with central composite design for design of experiments and genetic aggregation for response surface generation are used to quantify the combustor performance in design space. Comparison of three different design methodologies (M1, M2 and M3) is made to show how the choice of design methodology changes the available design space and limits/expands combustor performance. Candidate optimal designs and associated trade-offs from the optimization study are also presented. This study can aid combustor design engineers choose the most suitable preliminary design methodology for their specific use case.

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“…Although the geometry, validation, and workflow have been discussed earlier [12][13] , the main ideas are summarized here and changes required for the current study are discussed.…”

Section: Methodsmentioning

confidence: 99%

“…Validation is carried out using the numerical models discussed above by comparing the experimental temperature measurements with CFD predictions at different axial locations 13 . The prediction accuracy from the numerical models is found to be adequate for the current design study.…”

Section: Cfd Solver Setupmentioning

confidence: 99%