An FW-H based prediction model for the landing gear wake-flap interaction noise
An FW-H based prediction model for the landing gear wake-flap interaction noise
A semi-empirical prediction model for landing gear wake-flap interaction noise is proposed in this paper. The prediction model is based on the time-domain Ffowcs Williams and Hawkings (FW-H) equations.The model is developed to predict the increase of noise due to the installation of a landing gear under a wing with deployed high-lift devices. The model uses FW-H samples collected during numerical simulations of an isolated landing gear and an isolated high-lift wing. To validate this model, the rod-airfoil benchmark case is testedin this paper. A Lattice Boltzmann Method (LBM) solver LaBS is used for the Computational Fluid Dynamics (CFD) simulations. The isolated rod simulation was performed to generate the necessary databases for the prediction model. The rod airfoil benchmark was simulated to validate the model’s prediction against the LBM/FW-H results. It was found the model yielded similar predictions as the simulation, and both compare excellently to experimental data. The ability of the model to predict the effect of the airfoil’s angle of attack and the gap between the rod and airfoil was investigated. The prediction model was found to predict spectra very similar to the LBM/FW-H methodology. The method does not require the interaction to be explicitly modelled and only uses isolated component simulations as an input. Therefore, the computational costs are much lower than if the turbulent wake and its impingement on the wing has to be explicitly modelled. The model has the potential to be a useful design tool to analyse landing gear/high-lift wing interaction noise.
American Institute of Aeronautics and Astronautics
Hou, Yu
2e1a4d31-91c2-4886-b5d6-b805b511c103
Angland, David
b86880c6-31fa-452b-ada8-4bbd83cda47f
8 June 2023
Hou, Yu
2e1a4d31-91c2-4886-b5d6-b805b511c103
Angland, David
b86880c6-31fa-452b-ada8-4bbd83cda47f
Hou, Yu and Angland, David
(2023)
An FW-H based prediction model for the landing gear wake-flap interaction noise.
In AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023.
American Institute of Aeronautics and Astronautics..
(doi:10.2514/6.2023-4172).
Record type:
Conference or Workshop Item
(Paper)
Abstract
A semi-empirical prediction model for landing gear wake-flap interaction noise is proposed in this paper. The prediction model is based on the time-domain Ffowcs Williams and Hawkings (FW-H) equations.The model is developed to predict the increase of noise due to the installation of a landing gear under a wing with deployed high-lift devices. The model uses FW-H samples collected during numerical simulations of an isolated landing gear and an isolated high-lift wing. To validate this model, the rod-airfoil benchmark case is testedin this paper. A Lattice Boltzmann Method (LBM) solver LaBS is used for the Computational Fluid Dynamics (CFD) simulations. The isolated rod simulation was performed to generate the necessary databases for the prediction model. The rod airfoil benchmark was simulated to validate the model’s prediction against the LBM/FW-H results. It was found the model yielded similar predictions as the simulation, and both compare excellently to experimental data. The ability of the model to predict the effect of the airfoil’s angle of attack and the gap between the rod and airfoil was investigated. The prediction model was found to predict spectra very similar to the LBM/FW-H methodology. The method does not require the interaction to be explicitly modelled and only uses isolated component simulations as an input. Therefore, the computational costs are much lower than if the turbulent wake and its impingement on the wing has to be explicitly modelled. The model has the potential to be a useful design tool to analyse landing gear/high-lift wing interaction noise.
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Published date: 8 June 2023
Venue - Dates:
AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023, , San Diego, United States, 2023-06-12 - 2023-06-16
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Local EPrints ID: 509787
URI: http://eprints.soton.ac.uk/id/eprint/509787
PURE UUID: 9df34753-ee9e-45c5-9ee1-efde3434aad5
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Date deposited: 05 Mar 2026 22:40
Last modified: 07 Mar 2026 02:57
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Author:
Yu Hou
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