Treffer: A Review of Computational Fluid Dynamics Techniques and Methodologies in Vertical Axis Wind Turbine Development.
Weitere Informationen
This review provides a comprehensive and systematic examination of Computational Fluid Dynamics (CFD) techniques and methodologies applied to the development of Vertical Axis Wind Turbines (VAWTs). Although VAWTs offer significant advantages for urban wind applications, such as omnidirectional wind capture and a compact, ground-accessible design, they face substantial aerodynamic challenges, including dynamic stall, blade–wake interactions, and continuously varying angles of attack throughout their rotation. The review critically evaluates how CFD has been leveraged to address these challenges, detailing the modelling frameworks, simulation setups, mesh strategies, turbulence models, and boundary condition treatments adopted in the literature. Special attention is given to the comparative performance of 2-D vs. 3-D simulations, static and dynamic meshing techniques (sliding, overset, morphing), and the impact of near-wall resolution on prediction fidelity. Moreover, this review maps the evolution of CFD tools in capturing key performance indicators including power coefficient, torque, flow separation, and wake dynamics, while highlighting both achievements and current limitations. The synthesis of studies reveals best practices, identifies gaps in simulation fidelity and validation strategies, and outlines critical directions for future research, particularly in high-fidelity modelling and cost-effective simulation of urban-scale VAWTs. By synthesizing insights from over a hundred referenced studies, this review serves as a consolidated resource to advance VAWT design and performance optimization through CFD. These include studies on various aspects such as blade geometry refinement, turbulence modeling, wake interaction mitigation, tip-loss reduction, dynamic stall control, and other aerodynamic and structural improvements. This, in turn, supports their broader integration into sustainable energy systems. [ABSTRACT FROM AUTHOR]
Copyright of Computer Modeling in Engineering & Sciences (CMES) is the property of Tech Science Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)