Multi-fidelity Bayesian Optimisation of Wind Farm Wake Steering using Wake Models and Large Eddy Simulations
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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Multi-fidelity Bayesian Optimisation of Wind Farm Wake Steering using Wake Models and Large Eddy Simulations ; day:23 ; month:12 ; year:2024 ; pages:1-26
Flow, turbulence and combustion ; (23.12.2024), 1-26
- Creator
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Mole, Andrew
Laizet, Sylvain
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s10494-024-00629-0
- URN
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urn:nbn:de:101:1-2503032110474.746928780212
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:29 AM CEST
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Associated
- Mole, Andrew
- Laizet, Sylvain
- SpringerLink (Online service)
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Sensitivity analysis of wake steering optimisation for wind farm power maximisation
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From wake steering to flow control
A physically interpretable statistical wake steering model
Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations
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Optimizing Wind Farm Control through Wake Steering using Surrogate Models based on High Fidelity Simulations
Development of a multi-fidelity optimisation strategy based on hybrid methods
Addressing deep array effects and impacts to wake steering with the cumulative-curl wake model
Multifidelity multiobjective optimization for wake-steering strategies
Multifidelity Multiobjective Optimization for Wake Steering Strategies
Wake steering optimization under uncertainty
Sensitivity analysis of wake steering optimisation for wind farm power maximisation
Sensitivity analysis of wake steering optimisation for wind farm power maximisation
From wake steering to flow control
A physically interpretable statistical wake steering model
Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations
Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations
Optimizing Wind Farm Control through Wake Steering using Surrogate Models based on High Fidelity Simulations
Development of a multi-fidelity optimisation strategy based on hybrid methods