Turbulent boundary layer trailing-edge noise: Theory, computation, experiment, and application Article Swipe
Seongkyu Lee
,
Lorna J. Ayton
,
Franck Bertagnolio
,
Stéphane Moreau
,
Tze Pei Chong
,
Phillip Joseph
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1016/j.paerosci.2021.100737
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1016/j.paerosci.2021.100737
When the pressure fluctuations caused by turbulence vorticity in the boundary layer are scattered by a sharp trailing edge, acoustic energy is generated and propagated to the far field. This trailing edge noise is emitted from aircraft wings, turbomachinery blades, wind turbine blades, helicopter blades, etc. Being dominant at high frequencies, this trailing-edge noise is a key element that annoys human hearing. This article covers virtually the entire landscape of modern research into trailing-edge noise including theoretical developments, numerical simulations, wind tunnel experiments, and applications of trailing-edge noise. The theoretical approach includes Green's function formulations, Wiener-Hopf methods that solve the mixed boundary-value problem, Howe's and Amiet's models that relate the wall pressure spectrum to acoustic radiation. Recent analytical developments for poroelasticity and serrations are also included. We discuss a hierarchy of numerical approaches that range from semi-empirical schemes that estimate the wall pressure spectrum using mean flow and turbulence statistics to high-fidelity unsteady flow simulations such as Large Eddy Simulation (LES) or Direct Numerical Simulation (DNS) that resolve the sound generation and scattering process based on the first-principles flow physics. Wind tunnel experimental research that provided benchmark data for numerical simulations and unravel flow physics is reviewed. In each theoretical, numerical, and experimental approach, noise control methods for mitigating trailing-edge noise are discussed. Finally, highlights of practical applications of trailing-edge noise prediction and reduction to wind turbine noise, fan noise, and rotorcraft noise are given. The current challenges in each approach are summarized with a look toward the future developments. The review could be useful as a primer for new researchers or as a reference point to the state of the art for experienced professionals.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.paerosci.2021.100737
- OA Status
- hybrid
- Cited By
- 157
- References
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W3168748462Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.paerosci.2021.100737Digital Object Identifier
- Title
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Turbulent boundary layer trailing-edge noise: Theory, computation, experiment, and applicationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-06-24Full publication date if available
- Authors
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Seongkyu Lee, Lorna J. Ayton, Franck Bertagnolio, Stéphane Moreau, Tze Pei Chong, Phillip JosephList of authors in order
- Landing page
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https://doi.org/10.1016/j.paerosci.2021.100737Publisher landing page
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.paerosci.2021.100737Direct OA link when available
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Trailing edge, Boundary layer, Turbulence, Noise (video), Computation, Mechanics, Acoustics, Statistical physics, Physics, Computer science, Algorithm, Artificial intelligence, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
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157Total citation count in OpenAlex
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2025: 54, 2024: 35, 2023: 40, 2022: 25, 2021: 3Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.included. | 125 |
| abstract_inverted_index.including | 75 |
| abstract_inverted_index.landscape | 68 |
| abstract_inverted_index.numerical | 78, 131, 189 |
| abstract_inverted_index.practical | 216 |
| abstract_inverted_index.reduction | 223 |
| abstract_inverted_index.reference | 264 |
| abstract_inverted_index.reviewed. | 196 |
| abstract_inverted_index.scattered | 13 |
| abstract_inverted_index.virtually | 65 |
| abstract_inverted_index.vorticity | 7 |
| abstract_inverted_index.Simulation | 159, 164 |
| abstract_inverted_index.analytical | 117 |
| abstract_inverted_index.approaches | 132 |
| abstract_inverted_index.challenges | 237 |
| abstract_inverted_index.discussed. | 212 |
| abstract_inverted_index.generation | 170 |
| abstract_inverted_index.helicopter | 43 |
| abstract_inverted_index.highlights | 214 |
| abstract_inverted_index.mitigating | 208 |
| abstract_inverted_index.numerical, | 200 |
| abstract_inverted_index.prediction | 221 |
| abstract_inverted_index.propagated | 24 |
| abstract_inverted_index.radiation. | 115 |
| abstract_inverted_index.rotorcraft | 231 |
| abstract_inverted_index.scattering | 172 |
| abstract_inverted_index.serrations | 122 |
| abstract_inverted_index.statistics | 149 |
| abstract_inverted_index.summarized | 242 |
| abstract_inverted_index.turbulence | 6, 148 |
| abstract_inverted_index.Wiener-Hopf | 95 |
| abstract_inverted_index.experienced | 273 |
| abstract_inverted_index.researchers | 260 |
| abstract_inverted_index.simulations | 154, 190 |
| abstract_inverted_index.theoretical | 76, 89 |
| abstract_inverted_index.applications | 84, 217 |
| abstract_inverted_index.developments | 118 |
| abstract_inverted_index.experimental | 182, 202 |
| abstract_inverted_index.experiments, | 82 |
| abstract_inverted_index.fluctuations | 3 |
| abstract_inverted_index.frequencies, | 50 |
| abstract_inverted_index.simulations, | 79 |
| abstract_inverted_index.theoretical, | 199 |
| abstract_inverted_index.developments, | 77 |
| abstract_inverted_index.developments. | 249 |
| abstract_inverted_index.formulations, | 94 |
| abstract_inverted_index.high-fidelity | 151 |
| abstract_inverted_index.trailing-edge | 52, 73, 86, 209, 219 |
| abstract_inverted_index.boundary-value | 101 |
| abstract_inverted_index.poroelasticity | 120 |
| abstract_inverted_index.professionals. | 274 |
| abstract_inverted_index.semi-empirical | 136 |
| abstract_inverted_index.turbomachinery | 38 |
| abstract_inverted_index.first-principles | 177 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 95 |
| corresponding_author_ids | https://openalex.org/A5030054230 |
| countries_distinct_count | 4 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I84218800 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8999999761581421 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.9985026 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |