Volume 17, Issue 10 (1-2018)                   Modares Mechanical Engineering 2018, 17(10): 176-184 | Back to browse issues page

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Yazdani A, Mohseni A. Three-Dimensional Aerothermodynamic Optimization of the Stator Blade of an Axial-Flow Gas Turbine in an Open-Source Platform. Modares Mechanical Engineering. 2018; 17 (10) :176-184
URL: http://mme.modares.ac.ir/article-15-3642-en.html
1- Faculty of Mechanical and Energy Engineering, Shahid Beheshti University (SBU)
Abstract:   (3028 Views)
Gas turbines are among the most important power generation equipment in industries. One of the methods to enhance the performance of this equipment is the aerodynamic performance optimization of its stator and rotor blades. This paper presents an automatic aerothermodynamic optimization platform for the optimization of 3D stator blade geometry in axial-flow gas turbines using open-source software. This platform can be used for 3D aerothermodynamics optimization of 3D blades and includes parametric 3D modeling, mesh generation, CFD simulation, and implementation of optimization algorithm. 3D models are formed from 2D sections defined by Bézier curves and connected by spline stacking curve. Simulation of flow field includes the solution of compressible viscous flow on structured multi-block grid using parallel processing. Genetic algorithm is used as optimization algorithm. 45 optimization variables govern blade thickness variation in five sections and blade lean, sweep, and twist. Total pressure is selected as objective function and the result of optimization shows 5% decrease of total pressure loss coefficient in the blade. The use of open-source software in the optimization platform provides maximum customization capability to the user. The application of this platform for stator blade optimization shows that the platform can be used for aerothermodynamic optimization of turbomachines effectively.
Full-Text [PDF 1550 kb]   (4340 Downloads)    
Article Type: Research Article | Subject: Fluids Machines
Received: 2017/08/15 | Accepted: 2017/09/19 | Published: 2017/10/13

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