Validation of a BEM correction model for swept blades using experimental data Article Swipe
Erik Fritz
,
Koen Boorsma
,
Carlos Ferreira
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2767/2/022035
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2767/2/022035
This study validates a correction model, which extends standard blade element momentum theory to swept blades and, by doing so, enhances wind turbine simulation predictability for these advanced geometries. This correction model addresses limitations in BEM algorithms, accommodating the complexities of swept blades by considering the sweep-induced tip vortex displacement and curved bound vortex self-induction. The validation is based on previously published results from wind tunnel experiments on a horizontal axis wind turbine with straight and swept blades, providing blade-level aerodynamic data for comprehensive numerical comparisons. In both blade configurations (straight and swept), good agreement is found between experimental and numerical results, validating the numerical approach. For the swept blade case, an additional comparison to a BEM algorithm assuming a straight blade and to one accounting for crossflow is drawn, underscoring the former’s inadequacy for swept blades. Comparably minor differences between the fully-corrected and only crossflow-corrected algorithms render the assessment of the proposed BEM correction model’s added benefit uncertain. Using the validated BEM algorithm, the experimental results are corrected for twist deformations of individual blades, enabling a direct comparison of the campaigns with straight and swept blades. Results align with expectations, indicating sweep-induced reductions in axial induction and blade loads in the swept blade section.
Related Topics
Concepts
Blade (archaeology)
Turbine blade
Aerodynamics
Blade element momentum theory
Blade element theory
Displacement (psychology)
Vortex
Wind tunnel
Swept wing
Turbine
Momentum (technical analysis)
Structural engineering
Computer science
Mechanics
Engineering
Mechanical engineering
Physics
Psychotherapist
Finance
Economics
Psychology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/2767/2/022035
- OA Status
- diamond
- Cited By
- 1
- References
- 13
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399491145
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4399491145Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1742-6596/2767/2/022035Digital Object Identifier
- Title
-
Validation of a BEM correction model for swept blades using experimental dataWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-06-01Full publication date if available
- Authors
-
Erik Fritz, Koen Boorsma, Carlos FerreiraList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/2767/2/022035Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1088/1742-6596/2767/2/022035Direct OA link when available
- Concepts
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Blade (archaeology), Turbine blade, Aerodynamics, Blade element momentum theory, Blade element theory, Displacement (psychology), Vortex, Wind tunnel, Swept wing, Turbine, Momentum (technical analysis), Structural engineering, Computer science, Mechanics, Engineering, Mechanical engineering, Physics, Psychotherapist, Finance, Economics, PsychologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
13Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.vortex | 49, 54 |
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| abstract_inverted_index.between | 98, 141 |
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| abstract_inverted_index.blades. | 137, 187 |
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| abstract_inverted_index.results | 63, 167 |
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| abstract_inverted_index.approach. | 106 |
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| abstract_inverted_index.crossflow | 128 |
| abstract_inverted_index.induction | 197 |
| abstract_inverted_index.model’s | 156 |
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| abstract_inverted_index.providing | 79 |
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| abstract_inverted_index.additional | 113 |
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| abstract_inverted_index.algorithms | 147 |
| abstract_inverted_index.assessment | 150 |
| abstract_inverted_index.comparison | 114, 179 |
| abstract_inverted_index.correction | 5, 31, 155 |
| abstract_inverted_index.former’s | 133 |
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| abstract_inverted_index.fully-corrected | 143 |
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| abstract_inverted_index.crossflow-corrected | 146 |
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| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.9100000262260437 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.80702853 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |