An automated shape optimization methodology for a typical heavy-duty gas turbine (GT) compressor rotor blade section is presented in this paper. The approach combines a Non-Uniform Rational B-Spline (NURBS) driven parametric geometry description, a two-dimensional flow analysis, and a Genetic Algorithm (GA)-based optimization route. The objective is minimizing the total pressure losses for design condition as well as maximizing the airfoils operating range which is an assessment of the off-design behavior. To achieve the goal, design optimization process is carried out by coupling an established MATLAB code for the Differential Evolution (DE)-based optimum parameterized curve fitting of the measured point cloud of the airfoils’ shape, a blade-to-blade flow analysis in COMSOL Multiphysics, and a developed real-coded GA in MATLAB script. Using the combination of these adaptive tools and methods, the first results are considerably promising in terms of computation time, ability to extend the methodology for three-dimensional and multidisciplinary approach, and last but not least airfoil shape performance enhancement from efficiency and pressure rise point of view.
A Novel Combination of Adaptive Tools for Turbomachinery Airfoil Shape Optimization Using a Real-Coded Genetic Algorithm
Safari, A, Lemu, HG, & Assadi, M. "A Novel Combination of Adaptive Tools for Turbomachinery Airfoil Shape Optimization Using a Real-Coded Genetic Algorithm." Proceedings of the ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. Volume 6B: Turbomachinery. San Antonio, Texas, USA. June 3–7, 2013. V06BT43A003. ASME. https://doi.org/10.1115/GT2013-94093
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