Design and Optimization of a Low TSR HDarrieus Turbine Based on Geometry Parameterization Through Joukowsky Transformation - Baca, Giusep [UNESP]; Dos Santos, Gabriel Bertacco [UNESP]; Salviano, Leandro Oliveira [UNESP] (My University, 2024)
Amidst the reserves of fossil fuels and surging energy demands, the focus has shifted towards harnessing renewable energy sources like wind energy. This research endeavors to pinpoint the optimal design for a low Tip Speed Ratio (TSR) H-Darrieus turbine at three distinct TSRs: 2.33, 2.64, and 3.09. The study synergizes Computational Fluid Dynamics (CFD) with the Metamodel of Optimal Prognosis (MOP) response surface methodology. The Joukowsky transformation parametrization is applied to symmetrical airfoils, evaluating three pivotal parameters: the a/b ratio, m, and pitch angle. Notably, the pitch angle emerges as the predominant contributor, accounting for over 76% of the effect. Through Gradient-based optimization techniques, the refined turbine design achieved a performance enhancement, peaking at 14.73% for a profile optimized at a TSR of 2.64. Additionally, this work presents an insightful comparison of the non-dimensional velocity and torque coefficients across the considered TSRs. The integration of Ansys Fluent and Ansys OptiSlang in this research affirms a robust, cost-efficient, and fitting approach to dissect fluid dynamics in intricate, computation-intensive CFD models across varying TSRs.
Keywords: Computational Fluid Dynamics (CFD); H-Darrieus turbine; Low Tip Speed Ratio (TSR); Metamodel of Optimal Prognosis (MOP); Pitch angle