A 3d multidisciplinary automated design optimization toolbox for wind turbine blades based on ns solver and experimental data

This thesis attempts to develop a framework to optimize wind turbine blades automatically by a multidisciplinary 3D modeling and simulation methods. The original NREL Phase VI wind turbine blade and its experimental measurements are used to validate the Computational Fluid Dynamics (CFD) model developed in ANSYS Fluent and based on the 3D Navier-Stokes (NS) solver with a realizable k-epsilon turbulence model, which is later used in the automation process. The automated design optimization process involves multiple modeling and simulation methods using Solidworks and ANSYS Mesher and ANSYS Fluent NS solver, which are integrated and controlled through Matlab by implementing the scripting capabilities of each software package. Then all scripts are integrated into one optimization cycle, with its optimization objective being the highest mean value of 3D Lift/Drag ratio (3DLDR) across the blade. A 3DLDR distribution across the blade can be calculated by the Inverse Blade Element Momentum (IBEM) Method based on experimental measurements. The optimization process is performed to find optimized twist angles across the blade using the Angle of Attack (AOA) with the highest 3DLDR as a reference, in order to 3 achieve the optimization objective. Therefore, the automatic optimization framework is based on 3D solid modeling and 3D aerodynamic simulation and guided by IBEM and experimental data. Thus the design tool is capable of exploiting the 3D stall delay of blades designed by the traditional 2D BEM method to enhance their performances. It is found that this automated framework can result in optimized blade geometries with the improvement of performance parameters compared to the original ones