Multi-condition hydrofoil optimisation using an adjoint velocity prediction program
Multi-condition hydrofoil optimisation using an adjoint velocity prediction program
Hydrofoils are usually operated across a wide range of conditions. This results in different states and trims of the vessel and must be considered in hydrofoil optimisation. Therefore, an adjoint velocity prediction program (VPP) is developed and integrated it into a gradient-based optimisation routine. The method allows accurate optimisation with the full yacht model and hundreds of design variables at a small computational cost. The framework has previously been used for single condition optimisation but is now extended for multiple conditions. This is achieved by solving the VPP for different conditions and averaging the resulting velocities made good (VMG) and gradients. The method is applied to an AC75 America's Cup yacht. Its hydrofoils are optimised for six conditions derived from historical weather data. The optimal foil is 7.2 % faster than the initial foil in terms of average VMG which results in an 81.9 s timesaving over a race. The multi-condition foil is compared to foils optimised for the individual conditions. The individual foils perform best in their respective niches, whereas the multi-condition foil performs best across the range of conditions. The multi-condition optimisation can be performed at no additional cost and demonstrates the immense capabilities of adjoint VPP-based hydrofoil optimisation.
Adjoint method, Algorithmic differentiation, Hydrofoil, Multi-condition, Optimisation
Tannenberg, Rafael
bd497a87-ea59-4798-a28e-804d3fcb713b
Hochkirch, Karsten
11d869b5-8f02-46a8-8851-abe2105048fd
Turnock, Stephen R.
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Boyd, Stephen W.
bcbdefe0-5acf-4d6a-8a16-f4abf7c78b10
4 July 2025
Tannenberg, Rafael
bd497a87-ea59-4798-a28e-804d3fcb713b
Hochkirch, Karsten
11d869b5-8f02-46a8-8851-abe2105048fd
Turnock, Stephen R.
d6442f5c-d9af-4fdb-8406-7c79a92b26ce
Boyd, Stephen W.
bcbdefe0-5acf-4d6a-8a16-f4abf7c78b10
Tannenberg, Rafael, Hochkirch, Karsten, Turnock, Stephen R. and Boyd, Stephen W.
(2025)
Multi-condition hydrofoil optimisation using an adjoint velocity prediction program.
Ocean Engineering, 339 (1), [122030].
(doi:10.1016/j.oceaneng.2025.122030).
Abstract
Hydrofoils are usually operated across a wide range of conditions. This results in different states and trims of the vessel and must be considered in hydrofoil optimisation. Therefore, an adjoint velocity prediction program (VPP) is developed and integrated it into a gradient-based optimisation routine. The method allows accurate optimisation with the full yacht model and hundreds of design variables at a small computational cost. The framework has previously been used for single condition optimisation but is now extended for multiple conditions. This is achieved by solving the VPP for different conditions and averaging the resulting velocities made good (VMG) and gradients. The method is applied to an AC75 America's Cup yacht. Its hydrofoils are optimised for six conditions derived from historical weather data. The optimal foil is 7.2 % faster than the initial foil in terms of average VMG which results in an 81.9 s timesaving over a race. The multi-condition foil is compared to foils optimised for the individual conditions. The individual foils perform best in their respective niches, whereas the multi-condition foil performs best across the range of conditions. The multi-condition optimisation can be performed at no additional cost and demonstrates the immense capabilities of adjoint VPP-based hydrofoil optimisation.
Text
Multi-Condition_Hydrofoil_Optimisation-Tannenberg_et_al_3
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Accepted/In Press date: 25 June 2025
e-pub ahead of print date: 4 July 2025
Published date: 4 July 2025
Keywords:
Adjoint method, Algorithmic differentiation, Hydrofoil, Multi-condition, Optimisation
Identifiers
Local EPrints ID: 506039
URI: http://eprints.soton.ac.uk/id/eprint/506039
ISSN: 0029-8018
PURE UUID: 866a9527-f3a0-49c9-9d26-d4218d9d2fef
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Date deposited: 28 Oct 2025 17:33
Last modified: 29 Oct 2025 03:01
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Contributors
Author:
Rafael Tannenberg
Author:
Karsten Hochkirch
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