Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164720
Title: Arbitrary hybrid turbulence modeling approach for high-fidelity NREL phase VI wind turbine CFD simulation
Authors: Kamalov, Bagdaulet
Batay, Sagidolla
Zhangaskhanov, Dinmukhamed
Zhao, Yong
Ng, Eddie Yin Kwee
Keywords: Engineering::Mechanical engineering
Issue Date: 2022
Source: Kamalov, B., Batay, S., Zhangaskhanov, D., Zhao, Y. & Ng, E. Y. K. (2022). Arbitrary hybrid turbulence modeling approach for high-fidelity NREL phase VI wind turbine CFD simulation. Fluids, 7(7), 7070236-. https://dx.doi.org/10.3390/fluids7070236
Journal: Fluids 
Abstract: Today, growth in renewable energy is increasing, and wind energy is one of the key renewable energy sources which is helping to reduce carbon emissions and build a more sustainable world. Developed countries and worldwide organizations are investing in technology and industrial application development. However, extensive experiments using wind turbines are expensive, and numerical simulations are a cheaper alternative for advanced analysis of wind turbines. The aerodynamic properties of wind turbines can be analyzed and optimized using CFD tools. Currently, there is a general lack of available high-fidelity analysis for the wind turbine design community. This study aims to fill this urgent gap. In this paper, an arbitrary hybrid turbulence model (AHTM) was implemented in the open-source code OpenFOAM and compared with the traditional URANS model using the NREL Phase VI wind turbine as a benchmark case. It was found that the AHTM model gives more accurate results than the traditional URANS model. Furthermore, the results of the VLES and URANS models can be improved by improving the mesh quality for usage of higher-order schemes and taking into consideration aeroelastic properties of the wind turbine, which will pave the way for high-fidelity concurrent multidisciplinary design optimization of wind turbines.
URI: https://hdl.handle.net/10356/164720
ISSN: 2311-5521
DOI: 10.3390/fluids7070236
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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