Rapid Prediction of High-Resolution 3D Ship Airwake in the Glide Path Based on CFD, BP Neural Network, and DWL Article Swipe
Qingsong Liu
,
Gan Ren
,
Dingfu Zhou
,
Bo Liu
,
Zexiang Li
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/app15158336
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/app15158336
To meet the requirements of the high spatiotemporal three-dimensional (3D) airflow field within the glide path corridor during carrier-based aircraft/unmanned aerial vehicles (UAVs) landings, this paper proposes a prediction method for high spatiotemporal resolution 3D ship airwake along the glide path by integrating computational fluid dynamics (CFD), backpropagation (BP) neural network, and Doppler wind lidar (DWL). Firstly, taking the conceptual design aircraft carrier model as the research object, CFD numerical simulations of the ship airwake within the glide path region are carried out using the Poly-Hexcore grid and the detached eddy simulation (DES)/the Reynolds-averaged Navier–Stokes (RANS) turbulence models. Then, using the high spatial resolution ship airwake along the glide path obtained from steady RANS computations under different inflow conditions as a sample dataset, the BP neural network prediction models were trained and optimized. Along the ideal glide path within 200 m behind the stern, the correlation coefficients between the predicted results of the BP neural network and the headwind, crosswind, and vertical wind of the testing samples exceeded 0.95, 0.91, and 0.82, respectively. Finally, using the inflow speed and direction with high temporal resolution from the bow direction obtained by the shipborne DWL as input, the BP prediction models can achieve accurate prediction of the 3D ship airwake along the glide path with high spatiotemporal resolution (3 m, 3 Hz).
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app15158336
- https://www.mdpi.com/2076-3417/15/15/8336/pdf?version=1753537554
- OA Status
- gold
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4412698178
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4412698178Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/app15158336Digital Object Identifier
- Title
-
Rapid Prediction of High-Resolution 3D Ship Airwake in the Glide Path Based on CFD, BP Neural Network, and DWLWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-07-26Full publication date if available
- Authors
-
Qingsong Liu, Gan Ren, Dingfu Zhou, Bo Liu, Zexiang LiList of authors in order
- Landing page
-
https://doi.org/10.3390/app15158336Publisher landing page
- PDF URL
-
https://www.mdpi.com/2076-3417/15/15/8336/pdf?version=1753537554Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2076-3417/15/15/8336/pdf?version=1753537554Direct OA link when available
- Concepts
-
Reynolds-averaged Navier–Stokes equations, Computational fluid dynamics, Inflow, Artificial neural network, Marine engineering, Path (computing), Turbulence, Computer science, Simulation, Aerospace engineering, Meteorology, Engineering, Artificial intelligence, Physics, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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33Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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