Aerodynamic Optimization of the Archimedes Spiral Wind Turbine Blade Based on the Kriging Surrogate Model and Differential Evolution.
Saved in:
| Title: | Aerodynamic Optimization of the Archimedes Spiral Wind Turbine Blade Based on the Kriging Surrogate Model and Differential Evolution. |
|---|---|
| Authors: | Li, Mengyao1,2 (AUTHOR), Li, Zhi1,2 (AUTHOR), Xu, Shuhui1,2 (AUTHOR) xushuhui@qlu.edu.cn |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 10, p2298. 23p. |
| Subject Terms: | *Differential evolution, *Turbine blades, *Wind power, *Gaussian processes, *Computational fluid dynamics, *Wind turbine efficiency, *Computational aerodynamics |
| Abstract: | The Archimedes Spiral Wind Turbine (ASWT) is a novel horizontal axis wind turbine for urban low-wind-speed applications. To improve the wind energy capture efficiency of the ASWT, this study adopted a multivariable global optimization strategy. A differential evolution–Kriging surrogate model method was employed for blade structural optimization. The blade geometry was parametrically modeled, and three design variables were selected: spiral pitch, opening angle, and spiral rotation number (SRN). Latin hypercube sampling was used to generate sample points in the design space. The power coefficients (Cp) of all design samples were calculated by Computational Fluid Dynamics (CFD) simulations. A Kriging surrogate model was constructed to map the nonlinear relationship between the design variables and Cp. The optimal blade geometry was obtained by solving the surrogate model with differential evolution (DE) and validated by CFD. The results showed that at the design condition of a wind speed of 8 m/s and a tip speed ratio (TSR) of 1.875, the relative error between Kriging model predictions and CFD simulations was only 0.27%. The optimized blade achieved a Cp of 0.3085, representing a 4.78% improvement over the best sample blade, with both achieving their peak power coefficients at TSR = 1.875. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: enr DbLabel: Energy & Power Source An: 194141413 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Aerodynamic Optimization of the Archimedes Spiral Wind Turbine Blade Based on the Kriging Surrogate Model and Differential Evolution. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Mengyao%22">Li, Mengyao</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Zhi%22">Li, Zhi</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Shuhui%22">Xu, Shuhui</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> xushuhui@qlu.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. May2026, Vol. 19 Issue 10, p2298. 23p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Differential+evolution%22">Differential evolution</searchLink><br />*<searchLink fieldCode="DE" term="%22Turbine+blades%22">Turbine blades</searchLink><br />*<searchLink fieldCode="DE" term="%22Wind+power%22">Wind power</searchLink><br />*<searchLink fieldCode="DE" term="%22Gaussian+processes%22">Gaussian processes</searchLink><br />*<searchLink fieldCode="DE" term="%22Computational+fluid+dynamics%22">Computational fluid dynamics</searchLink><br />*<searchLink fieldCode="DE" term="%22Wind+turbine+efficiency%22">Wind turbine efficiency</searchLink><br />*<searchLink fieldCode="DE" term="%22Computational+aerodynamics%22">Computational aerodynamics</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The Archimedes Spiral Wind Turbine (ASWT) is a novel horizontal axis wind turbine for urban low-wind-speed applications. To improve the wind energy capture efficiency of the ASWT, this study adopted a multivariable global optimization strategy. A differential evolution–Kriging surrogate model method was employed for blade structural optimization. The blade geometry was parametrically modeled, and three design variables were selected: spiral pitch, opening angle, and spiral rotation number (SRN). Latin hypercube sampling was used to generate sample points in the design space. The power coefficients (Cp) of all design samples were calculated by Computational Fluid Dynamics (CFD) simulations. A Kriging surrogate model was constructed to map the nonlinear relationship between the design variables and Cp. The optimal blade geometry was obtained by solving the surrogate model with differential evolution (DE) and validated by CFD. The results showed that at the design condition of a wind speed of 8 m/s and a tip speed ratio (TSR) of 1.875, the relative error between Kriging model predictions and CFD simulations was only 0.27%. The optimized blade achieved a Cp of 0.3085, representing a 4.78% improvement over the best sample blade, with both achieving their peak power coefficients at TSR = 1.875. [ABSTRACT FROM AUTHOR] |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=194141413 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/en19102298 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 2298 Subjects: – SubjectFull: Differential evolution Type: general – SubjectFull: Turbine blades Type: general – SubjectFull: Wind power Type: general – SubjectFull: Gaussian processes Type: general – SubjectFull: Computational fluid dynamics Type: general – SubjectFull: Wind turbine efficiency Type: general – SubjectFull: Computational aerodynamics Type: general Titles: – TitleFull: Aerodynamic Optimization of the Archimedes Spiral Wind Turbine Blade Based on the Kriging Surrogate Model and Differential Evolution. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Mengyao – PersonEntity: Name: NameFull: Li, Zhi – PersonEntity: Name: NameFull: Xu, Shuhui IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 05 Text: May2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961073 Numbering: – Type: volume Value: 19 – Type: issue Value: 10 Titles: – TitleFull: Energies (19961073) Type: main |
| ResultId | 1 |
