Capillary transfer: Numerical study of how topology affects the fluid flow rate into a planar microstructure with pseudopotential multiphase Lattice-Boltzmann method

2021 ◽  
Vol 33 (10) ◽  
pp. 102102
Author(s):  
Robin Pham ◽  
Sheng Wang ◽  
Heng-Chieh Chien ◽  
Chung-Lung Chen
Keyword(s):  
Fluid Flow ◽  
Lattice Boltzmann Method ◽  
Flow Rate ◽  
Lattice Boltzmann ◽  
Numerical Study ◽  
Fluid Flow Rate ◽  
Boltzmann Method

scholarly journals A numerical study of fish adaption behaviors in complex environments with a deep reinforcement learning and immersed boundary–lattice Boltzmann method

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yi Zhu ◽  
Fang-Bao Tian ◽  
John Young ◽  
James C. Liao ◽  
Joseph C. S. Lai
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Prey Capture ◽  
Numerical Study ◽  
Benchmark Problems ◽  
Immersed Boundary ◽  
Complex Environments ◽  
Fish Model ◽  
Point To Point ◽  
Boltzmann Method

AbstractFish adaption behaviors in complex environments are of great importance in improving the performance of underwater vehicles. This work presents a numerical study of the adaption behaviors of self-propelled fish in complex environments by developing a numerical framework of deep learning and immersed boundary–lattice Boltzmann method (IB–LBM). In this framework, the fish swimming in a viscous incompressible flow is simulated with an IB–LBM which is validated by conducting two benchmark problems including a uniform flow over a stationary cylinder and a self-propelled anguilliform swimming in a quiescent flow. Furthermore, a deep recurrent Q-network (DRQN) is incorporated with the IB–LBM to train the fish model to adapt its motion to optimally achieve a specific task, such as prey capture, rheotaxis and Kármán gaiting. Compared to existing learning models for fish, this work incorporates the fish position, velocity and acceleration into the state space in the DRQN; and it considers the amplitude and frequency action spaces as well as the historical effects. This framework makes use of the high computational efficiency of the IB–LBM which is of crucial importance for the effective coupling with learning algorithms. Applications of the proposed numerical framework in point-to-point swimming in quiescent flow and position holding both in a uniform stream and a Kármán vortex street demonstrate the strategies used to adapt to different situations.

Numerical study of capillary-driven flow in square micro-channel by lattice Boltzmann method

2019 ◽  
Vol 19 (1) ◽  
pp. 12
Author(s):  
Mohamed El Amine Ben Amara ◽  
Patrick Perré ◽  
Abdolreza Kharaghani ◽  
Sassi Ben Nasrallah
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Numerical Study ◽  
Micro Channel ◽  
Boltzmann Method

THE JEFFERY-HAMEL PROBLEM: A NUMERICAL LATTICE-BOLTZMANN STUDY

2003 ◽  
Vol 17 (01n02) ◽  
pp. 139-143
Author(s):  
GÁBOR HÁZI ◽  
ISTVÁN FARKAS
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Bifurcation Theory ◽  
Numerical Study ◽  
Numerical Results ◽  
Point Of View ◽  
Boltzmann Method

In this paper, we present a numerical study of the Jeffery-Hammel problem using the lattice-Boltzmann method. We study three situations: pure inflow, pure outflow, and outflow with backflow. We demonstrate that the lattice-Boltzmann method gives not only qualitatively but also quantitatively accurate solutions for this problem. From the point of view of stability of the flow, the recent results of bifurcation theory are also briefly considered from the viewpoint of our numerical results.

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