GPU simulation of wake effects at the Horns Rev 1 offshore wind farm using the CFD porous disk wake model

Takanori Uchida; Teppei Tanaka; Ryuta Shizui; Hiroto Ichikawa; Ryo Takayama; Kazuomi Yahagi; Ryoya Okubo

doi:10.1177/0309524X221132003

GPU simulation of wake effects at the Horns Rev 1 offshore wind farm using the CFD porous disk wake model

Takanori Uchida, Teppei Tanaka, Ryuta Shizui, Hiroto Ichikawa, Ryo Takayama, Kazuomi Yahagi, Ryoya Okubo

Research output: Contribution to journal › Article › peer-review

Abstract

To verify the effectiveness of the GPU simulation of wake effects at a large-scale offshore wind farm, we ran an in-house large-eddy simulation (LES) solver with a CFD porous disk wake model for the Horns Rev 1 wind farm. For this numerical research, we prepared the latest workstation equipped with a Xeon W-2265 CPU and an NVIDIA RTX A6000 GPU. We clarified that the calculation speed of the single GPU of the NVIDIA RTX A6000 is approximately 10 times faster than the calculation speed of the Xeon W-2265. Careful data analysis and visualization of the unsteady turbulent flow fields obtained in the current LES study suggest that the mutual interference of the wakes developed by wind turbines may frequently form a local speed-up region around wind turbines, located on the downstream side of large offshore wind farms.

Original language	English
Journal	Wind Engineering
DOIs	https://doi.org/10.1177/0309524X221132003
Publication status	Accepted/In press - 2022
Externally published	Yes

All Science Journal Classification (ASJC) codes

Renewable Energy, Sustainability and the Environment
Energy Engineering and Power Technology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1177/0309524X221132003

Cite this

@article{216ba30986214e85aaba777d01866785,

title = "GPU simulation of wake effects at the Horns Rev 1 offshore wind farm using the CFD porous disk wake model",

abstract = "To verify the effectiveness of the GPU simulation of wake effects at a large-scale offshore wind farm, we ran an in-house large-eddy simulation (LES) solver with a CFD porous disk wake model for the Horns Rev 1 wind farm. For this numerical research, we prepared the latest workstation equipped with a Xeon W-2265 CPU and an NVIDIA RTX A6000 GPU. We clarified that the calculation speed of the single GPU of the NVIDIA RTX A6000 is approximately 10 times faster than the calculation speed of the Xeon W-2265. Careful data analysis and visualization of the unsteady turbulent flow fields obtained in the current LES study suggest that the mutual interference of the wakes developed by wind turbines may frequently form a local speed-up region around wind turbines, located on the downstream side of large offshore wind farms.",

author = "Takanori Uchida and Teppei Tanaka and Ryuta Shizui and Hiroto Ichikawa and Ryo Takayama and Kazuomi Yahagi and Ryoya Okubo",

note = "Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Part of this work was supported by joint research with Eurus Energy Holdings Corporation and the Adaptable and Seamless Technology Transfer Program through Target-Driven R&D (A-STEP) from Japan{\textquoteright}s Science and Technology Agency (JST), grant number JPMJTR211C. Publisher Copyright: {\textcopyright} The Author(s) 2022.",

year = "2022",

doi = "10.1177/0309524X221132003",

language = "English",

journal = "Wind Engineering",

issn = "0309-524X",

publisher = "Multi-Science Publishing Co. Ltd",

}

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T1 - GPU simulation of wake effects at the Horns Rev 1 offshore wind farm using the CFD porous disk wake model

AU - Uchida, Takanori

AU - Tanaka, Teppei

AU - Shizui, Ryuta

AU - Ichikawa, Hiroto

AU - Takayama, Ryo

AU - Yahagi, Kazuomi

AU - Okubo, Ryoya

N1 - Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Part of this work was supported by joint research with Eurus Energy Holdings Corporation and the Adaptable and Seamless Technology Transfer Program through Target-Driven R&D (A-STEP) from Japan’s Science and Technology Agency (JST), grant number JPMJTR211C. Publisher Copyright: © The Author(s) 2022.

PY - 2022

Y1 - 2022

N2 - To verify the effectiveness of the GPU simulation of wake effects at a large-scale offshore wind farm, we ran an in-house large-eddy simulation (LES) solver with a CFD porous disk wake model for the Horns Rev 1 wind farm. For this numerical research, we prepared the latest workstation equipped with a Xeon W-2265 CPU and an NVIDIA RTX A6000 GPU. We clarified that the calculation speed of the single GPU of the NVIDIA RTX A6000 is approximately 10 times faster than the calculation speed of the Xeon W-2265. Careful data analysis and visualization of the unsteady turbulent flow fields obtained in the current LES study suggest that the mutual interference of the wakes developed by wind turbines may frequently form a local speed-up region around wind turbines, located on the downstream side of large offshore wind farms.

AB - To verify the effectiveness of the GPU simulation of wake effects at a large-scale offshore wind farm, we ran an in-house large-eddy simulation (LES) solver with a CFD porous disk wake model for the Horns Rev 1 wind farm. For this numerical research, we prepared the latest workstation equipped with a Xeon W-2265 CPU and an NVIDIA RTX A6000 GPU. We clarified that the calculation speed of the single GPU of the NVIDIA RTX A6000 is approximately 10 times faster than the calculation speed of the Xeon W-2265. Careful data analysis and visualization of the unsteady turbulent flow fields obtained in the current LES study suggest that the mutual interference of the wakes developed by wind turbines may frequently form a local speed-up region around wind turbines, located on the downstream side of large offshore wind farms.

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U2 - 10.1177/0309524X221132003

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M3 - Article

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SN - 0309-524X

JO - Wind Engineering

JF - Wind Engineering

ER -

GPU simulation of wake effects at the Horns Rev 1 offshore wind farm using the CFD porous disk wake model

Abstract

All Science Journal Classification (ASJC) codes

UN SDGs

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