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CFD-based design optimization of ducted hydrokinetic turbines
Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, imp...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589359/ https://www.ncbi.nlm.nih.gov/pubmed/37864063 http://dx.doi.org/10.1038/s41598-023-43724-4 |
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author | Park, Jeongbin Knight, Bradford G. Liao, Yingqian Mangano, Marco Pacini, Bernardo Maki, Kevin J. Martins, Joaquim R. R. A. Sun, Jing Pan, Yulin |
author_facet | Park, Jeongbin Knight, Bradford G. Liao, Yingqian Mangano, Marco Pacini, Bernardo Maki, Kevin J. Martins, Joaquim R. R. A. Sun, Jing Pan, Yulin |
author_sort | Park, Jeongbin |
collection | PubMed |
description | Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, improving the overall energy extraction efficiency. However, no substantial evidence has been provided so far for hydrokinetic turbines. To investigate this problem, we perform a CFD-based optimization study with a blade-resolved Reynolds-averaged Navier–Stokes (RANS) solver to explore the design of a ducted hydrokinetic turbine that maximizes the efficiency of energy extraction. A gradient-based optimization approach is utilized to effectively deal with the high-dimensional design space of the blade and duct geometry, with gradients being calculated through the adjoint method. The final design is re-evaluated through higher-fidelity unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an efficiency of about 54% over a range of operating conditions, higher than the typical 46% efficiency of unducted turbines. |
format | Online Article Text |
id | pubmed-10589359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105893592023-10-22 CFD-based design optimization of ducted hydrokinetic turbines Park, Jeongbin Knight, Bradford G. Liao, Yingqian Mangano, Marco Pacini, Bernardo Maki, Kevin J. Martins, Joaquim R. R. A. Sun, Jing Pan, Yulin Sci Rep Article Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, improving the overall energy extraction efficiency. However, no substantial evidence has been provided so far for hydrokinetic turbines. To investigate this problem, we perform a CFD-based optimization study with a blade-resolved Reynolds-averaged Navier–Stokes (RANS) solver to explore the design of a ducted hydrokinetic turbine that maximizes the efficiency of energy extraction. A gradient-based optimization approach is utilized to effectively deal with the high-dimensional design space of the blade and duct geometry, with gradients being calculated through the adjoint method. The final design is re-evaluated through higher-fidelity unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an efficiency of about 54% over a range of operating conditions, higher than the typical 46% efficiency of unducted turbines. Nature Publishing Group UK 2023-10-20 /pmc/articles/PMC10589359/ /pubmed/37864063 http://dx.doi.org/10.1038/s41598-023-43724-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Park, Jeongbin Knight, Bradford G. Liao, Yingqian Mangano, Marco Pacini, Bernardo Maki, Kevin J. Martins, Joaquim R. R. A. Sun, Jing Pan, Yulin CFD-based design optimization of ducted hydrokinetic turbines |
title | CFD-based design optimization of ducted hydrokinetic turbines |
title_full | CFD-based design optimization of ducted hydrokinetic turbines |
title_fullStr | CFD-based design optimization of ducted hydrokinetic turbines |
title_full_unstemmed | CFD-based design optimization of ducted hydrokinetic turbines |
title_short | CFD-based design optimization of ducted hydrokinetic turbines |
title_sort | cfd-based design optimization of ducted hydrokinetic turbines |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589359/ https://www.ncbi.nlm.nih.gov/pubmed/37864063 http://dx.doi.org/10.1038/s41598-023-43724-4 |
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