Wake modeling and simulation of a real scale wind turbine using large eddy simulation and dynamic adaptive mesh refinement Article Swipe
Leandro José Lemes Stival
,
Joshua Brinkerhoff
,
Fernando Oliveira de Andrade
,
João Marcelo Vedovotto
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1590/0001-3765202520240875
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1590/0001-3765202520240875
Wind energy has gained visibility in terms of progress and potential worldwide. In this context, scientific research in wind energy has shown significant progress, particularly in the development of computational fluid dynamics approaches that resolve the real scale wind turbines. The present study aims to apply Large Eddy Simulation (LES) to provide crucial spatial and temporal information on the flowfield surrounding a full-scale NREL 5 MW wind turbine in order to investigate the following: (i) wind turbine-generated wakes and their effects, (ii) interactions between the wind and turbine in terms of power generation, and (iii) wake effects for back to back turbines related to energy production efficiency. The numerical framework used in the simulations performs LES under a block-structured mesh that is dynamically refined to increase accuracy and reduce computational costs. The simulated 5MW NREL presented lower recovery velocities around the hub-height centerline in the near wake compared to other selected numerical results, which could be attributed to the simplification of the blade resolving geometry applied in the previous studies. Despite that, most results presented differences lower than 10% among the profiles. In addition, the power generation is validated with NREL experimental data with a difference of around 3.5%.
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- article
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- https://doi.org/10.1590/0001-3765202520240875
- OA Status
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- References
- 40
- OpenAlex ID
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Wake modeling and simulation of a real scale wind turbine using large eddy simulation and dynamic adaptive mesh refinementWork title
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2025Year of publication
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2025-01-01Full publication date if available
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Leandro José Lemes Stival, Joshua Brinkerhoff, Fernando Oliveira de Andrade, João Marcelo VedovottoList of authors in order
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https://doi.org/10.1590/0001-3765202520240875Publisher landing page
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40Number of works referenced by this work
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| abstract_inverted_index.research | 17 |
| abstract_inverted_index.results, | 153 |
| abstract_inverted_index.selected | 151 |
| abstract_inverted_index.studies. | 170 |
| abstract_inverted_index.temporal | 56 |
| abstract_inverted_index.turbines | 102 |
| abstract_inverted_index.addition, | 184 |
| abstract_inverted_index.flowfield | 60 |
| abstract_inverted_index.framework | 110 |
| abstract_inverted_index.numerical | 109, 152 |
| abstract_inverted_index.potential | 11 |
| abstract_inverted_index.presented | 136, 175 |
| abstract_inverted_index.profiles. | 182 |
| abstract_inverted_index.progress, | 24 |
| abstract_inverted_index.resolving | 164 |
| abstract_inverted_index.simulated | 133 |
| abstract_inverted_index.turbines. | 40 |
| abstract_inverted_index.validated | 189 |
| abstract_inverted_index.Simulation | 49 |
| abstract_inverted_index.approaches | 33 |
| abstract_inverted_index.attributed | 157 |
| abstract_inverted_index.centerline | 143 |
| abstract_inverted_index.difference | 196 |
| abstract_inverted_index.following: | 74 |
| abstract_inverted_index.full-scale | 63 |
| abstract_inverted_index.generation | 187 |
| abstract_inverted_index.hub-height | 142 |
| abstract_inverted_index.production | 106 |
| abstract_inverted_index.scientific | 16 |
| abstract_inverted_index.velocities | 139 |
| abstract_inverted_index.visibility | 5 |
| abstract_inverted_index.worldwide. | 12 |
| abstract_inverted_index.development | 28 |
| abstract_inverted_index.differences | 176 |
| abstract_inverted_index.dynamically | 123 |
| abstract_inverted_index.efficiency. | 107 |
| abstract_inverted_index.generation, | 93 |
| abstract_inverted_index.information | 57 |
| abstract_inverted_index.investigate | 72 |
| abstract_inverted_index.significant | 23 |
| abstract_inverted_index.simulations | 114 |
| abstract_inverted_index.surrounding | 61 |
| abstract_inverted_index.experimental | 192 |
| abstract_inverted_index.interactions | 83 |
| abstract_inverted_index.particularly | 25 |
| abstract_inverted_index.computational | 30, 130 |
| abstract_inverted_index.simplification | 160 |
| abstract_inverted_index.block-structured | 119 |
| abstract_inverted_index.turbine-generated | 77 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.31184182 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |