Volume 1: Aircraft Engine; Fans and Blowers; Marine; Wind Energy; Scholar Lecture 2021
DOI: 10.1115/gt2021-58945
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Multi-Objective Optimization of Aero Engine Combustor Adopting an Integrated Procedure for Aero-Thermal Preliminary Design

Abstract: The preliminary design of an aero-engine combustor is a multidisciplinary process that involves an extensive and systematic analysis of the design space. Simulation-driven approaches, in which several design configurations are numerically analyzed, may lead to heterogeneous models interacting with each other, sharing miscellaneous information within the process. Iterative and user-defined approaches, moreover, are inefficient when multiple and conflicting requirements are in place. To rely on integrated design… Show more

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“…The ideal method for gas turbine combustor design optimization, which is difficult to evaluate performance and has many design targets, is to use an optimization tool that combines 3D performance prediction for multiple design targets. Recently, Elmi et al (2021) proposed one way to solve this problem by using a response surface method (RSM) that simulates multiple specific combustor configurations and elaborates the CFD results to build a meta-model of the combustor itself. Sampling methods and response surfaces evaluated for the specific optimization problem are shown in Figure 12.…”
Section: Combustor Design Methodsmentioning
confidence: 99%
“…The ideal method for gas turbine combustor design optimization, which is difficult to evaluate performance and has many design targets, is to use an optimization tool that combines 3D performance prediction for multiple design targets. Recently, Elmi et al (2021) proposed one way to solve this problem by using a response surface method (RSM) that simulates multiple specific combustor configurations and elaborates the CFD results to build a meta-model of the combustor itself. Sampling methods and response surfaces evaluated for the specific optimization problem are shown in Figure 12.…”
Section: Combustor Design Methodsmentioning
confidence: 99%