5 Papers
B. Cui is an academic researcher from Harbin Engineering University. The author has contributed to research in topics: Turbulence & Airfoil. The author has an hindex of 1, co-authored 1 publications.
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Papers
Artificial neural network-substituted transition model for crossflow instability: Modeling strategy and application prospect
Lei Wu,B. Cui,Rui Wang,Zuoli Xiao +3 more
TL;DR: The results manifest that the SST-γANN model aligns well with the benchmark SST-γ model, and both can capture the CF transition accurately compared with their experiment counterpart, completely breaking through the disability of original SST-γ model without CF correction.
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Artificial neural network-based one-equation model for simulation of laminar-turbulent transitional flow
Lei Wu,B. Cui,Zuoli Xiao +2 more
TL;DR: In this paper , a two-way coupling artificial neural network (ANN) was proposed for turbulence modeling of Reynolds stress towards Reynolds-averaged Navier Stokes (RANS) simulation of laminar-to-turbulent transitional flows, especially those induced by Laminar separations.
Numerical study on the vertical motion of underwater vehicle with air bubbles attached in a gravity field
Yanzhuo Xue,B. Cui,B.Y. Ni +2 more
TL;DR: In this article, a body with an air bubble attached at a variable speed is simulated using the boundary-element method together with the potential theory, where the deformation of the bubble under the action of gravity is considered in a moving coordinate system fixed on the body.
Computable turbulence modeling of laminar-turbulent transition characterized boundary layer flows with the aid of artificial neural network
B. Cui,Lei Wu,Yu Liu +2 more
- 01 Apr 2024
TL;DR: A computable turbulence model is developed using an artificial neural network, achieving superior accuracy and robustness in predicting aerodynamic quantities and transition onset location for subsonic and transonic airfoil flows with improved convergence speed and computation efficiency.
Two-equation turbulent viscosity model for simulation of transitional flows: An efficient artificial neural network strategy
Lei Wu,B. Cui,Zuoli Xiao +2 more
TL;DR: In this paper , an industrial-practical transition-turbulence model with excellent accuracy, robustness, and efficiency is established by the fully connected artificial neural network (ANN), which maps the relation between the RANS mean flow variables and an intermittency factor.