Abstract
The robust design optimization of an airfoil needs to continuously realize the probability-based aerodynamic simulation for various combinations of geometry and wind climate parameters. The simulation time is lengthy when a full aerodynamic model is embedded for the numerical iteration. To this end, a second-order polynomial-based response surface model is first presented to relate the airfoil performance indicator with geometry and random aerodynamic variables. This allows to quickly evaluate the response moments and optimization constraints. Then, the robust design optimization is formulated to simultaneously maximize the mean aerodynamic performance and minimize the variance of design results due to the variation of geometry and aerodynamic parameters. The robust design optimization based on the NACA63418 and the DU93-W-210 airfoils with random Mach and Reynolds numbers is presented to demonstrate potential applications of this proposed model. Results have shown that the mean-value aerodynamic indicator is generally improved, whereas the variance is minimized to archive the robust design objective. The proposed approach is simple and accurate, suggesting an attractive tool for robust design optimization of airfoils with random aerodynamic variables.
Highlights
As a key facility to convert wind energy into electricity, the design and analysis of wind turbines have received considerable attention in recent years.[1]
The aerodynamic performance, for example, the lift-todrag ratio Cld of an airfoil directly affects the aerodynamic performance of wind turbine blades in engineering reality
Note that XFOIL package is used to simulate the performance of an airfoil with various geometry and aerodynamic parameters
Summary
As a key facility to convert wind energy into electricity, the design and analysis of wind turbines have received considerable attention in recent years.[1] Along with probabilistic methods to quantify fatigue and reliability problems of wind turbine structures,[2,3,4] the consideration of randomly aerodynamic parameters becomes crucial for the design optimization of wind turbine airfoils. Numerical optimization of an airfoil is typically divided into several sub-problems, that is, geometry modelling, aerodynamic simulation and robust design optimization. In this regard, the geometry modelling of the airfoil can be realized using a group of basis functions to translate the discrete geometry data into a continuous and smooth profile. The CST and School of Mechanical Engineering and Automation, Northeastern University, Shenyang, China
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