Table of Content

Open Access iconOpen Access

PROCEEDINGS

crossmark

Numerical Simulation of Non-Gaussian Winds and Application on Floating Offshore Wind Turbines

Shu Dai1,*, Bert Sweetman2

1 Shanghai Investigation, Design, and Research Institute Co. , Ltd., 65 Linxin Road, Shanghai, 200335, China
2 Texas A&M University, 200 Seawolf Pkwy, Galveston, 77554, USA

* Corresponding Author: Shu Dai. Email: email

The International Conference on Computational & Experimental Engineering and Sciences 2023, 27(2), 1-1. https://doi.org/10.32604/icces.2023.09687

Abstract

Short-term wind process is normally assumed to be a Gaussian distribution, such as TurbSim, the widely used 3D wind field tool. Nowadays, newest researches indicate that non-Gaussian wind model is believed to be more accurate according to the field observation data. A new numerical method is proposed to generate non-Gaussian wind filed using translation process theory and spectral representation method. This study presents a comprehensive investigation on power production and blades fatigue damage of floating offshore wind turbines (FOWTs) to the non-Gaussian wind field. The comparisons of Gaussian and non-Gaussian simulation results indicate that the non-Gaussian wind fields will cost obviously worse power performance and severe fatigue damage of FOWTs.

Keywords


Cite This Article

APA Style
Dai, S., Sweetman, B. (2023). Numerical simulation of non-gaussian winds and application on floating offshore wind turbines. The International Conference on Computational & Experimental Engineering and Sciences, 27(2), 1-1. https://doi.org/10.32604/icces.2023.09687
Vancouver Style
Dai S, Sweetman B. Numerical simulation of non-gaussian winds and application on floating offshore wind turbines. Int Conf Comput Exp Eng Sciences . 2023;27(2):1-1 https://doi.org/10.32604/icces.2023.09687
IEEE Style
S. Dai and B. Sweetman, “Numerical Simulation of Non-Gaussian Winds and Application on Floating Offshore Wind Turbines,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 27, no. 2, pp. 1-1, 2023. https://doi.org/10.32604/icces.2023.09687



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 354

    View

  • 243

    Download

  • 0

    Like

Share Link