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Vijayakumar, Ganesh (ORCID:0000000152282511)

Publications and source records attributed to Vijayakumar, Ganesh (ORCID:0000000152282511).

Three-Dimensional Aerodynamics and Vortex-Shedding Characteristics of Wind Turbine Airfoils over 360-Degree Angles of Attack

In this work, we present the first three-dimensional (3D) computational investigation of wind turbine airfoils over 360° angles of attack to predict unsteady aerodynamic loads and vortex-shedding characteristics. To this end, static–airfoil simulations are performed for the FFA-W3 airfoil family at a Reynolds number of 107 with the Improved Delayed Detached Eddy Simulation turbulence model. Aerodynamic forces reveal that the onset of boundary-layer instabilities and flow separation does not necessarily coincide with the onset of stall. In addition, a comparison with two-dimensional simulation data and flat plate theory extension of airfoil polars, suggest that, in the deep stall regime, 3D effects remain critical for predicting both the unsteady loads and the vortex-shedding dynamics. For all airfoils, the vortex-shedding frequencies are found to be inversely proportional to the wake width. In the case of slender airfoils, the frequencies are nearly independent of the airfoil thickness, and their corresponding Strouhal number St is approximately 0.15. Based on the calculated St, the potential for shedding frequencies to coincide with the natural frequencies of the International Energy Agency 15 MW reference wind turbine blades is investigated. The analysis shows that vortex-induced vibrations occur primarily at angles of attack of around ±90° for all airfoils.

17 WIND ENERGY↗

Design Space Exploration for Novel Reduced-Vortex Turbine Rotors Using Free Vortex Wake Methods

In this work, we explore the use of mid-fidelity free vortex wake (FVW) tools, namely NREL's cOnvecting LAgrangian Filaments (OLAF) tool, to design and analyze wind turbine rotor blades. The goal of the exercise is to determine whether designs exist that out-perform traditional blade designs, which are optimized using the Blade-Element Momentum (BEM) method. We find that using design of experiments to generate simple modifications of the blade tip, OLAF predicts higher performance in terms of power coefficient for redesigned blades that are non-optimal according to BEM. We then use optimization methods with OLAF in the loop to attempt to automatically find OLAF-optimal designs. We analyze the results of these optimizations, demonstrating that some roadblocks exist before OLAF and FVW tools can be used to automatically find FVW-optimal blade designs that might exceed the performance of BEM-optimal blade designs.

blade design↗

Enabling Innovation in Wind Turbine Design Using Artificial Intelligence

The Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements (INTEGRATE) project is developing a new inverse-design capability for wind turbine rotors using invertible neural networks. This artificial intelligence (AI)-based technology can capture complex nonlinear aerodynamic effects 100 times faster than alternative design approaches.

aerodynamics↗