An immersed boundary-lattice Boltzmann framework for fully resolved simulations of non-spherical particle settling in unbounded domain

2021 ◽  
Vol 102 ◽  
pp. 206-219
Author(s):  
Rodrigo S. Romanus ◽  
Alan Lugarini ◽  
Admilson T. Franco
Keyword(s):  
Spherical Particle ◽  
Unbounded Domain ◽  
Lattice Boltzmann ◽  
Immersed Boundary ◽  
Particle Settling

Lattice Boltzmann simulation of dense rigid spherical particle suspensions using immersed boundary method

2018 ◽  
Vol 166 ◽  
pp. 286-294 ◽  
Author(s):  
Yann Thorimbert ◽  
Francesco Marson ◽  
Andrea Parmigiani ◽  
Bastien Chopard ◽  
Jonas Lätt
Keyword(s):  
Spherical Particle ◽  
Lattice Boltzmann ◽  
Immersed Boundary Method ◽  
Immersed Boundary ◽  
Particle Suspensions ◽  
Boundary Method ◽  
Lattice Boltzmann Simulation

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.

scholarly journals Research on Human Erythrocyte’s Threshold Free Energy for Hemolysis and Damage from Coupling Effect of Shear and Impact Based on Immersed Boundary-Lattice Boltzmann Method

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Zhong Yun ◽  
Chuang Xiang ◽  
Liang Wang
Keyword(s):  
Free Energy ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Coupling Effect ◽  
Threshold Value ◽  
Blood Pump ◽  
Immersed Boundary ◽  
Threshold Limit ◽  
Spring Network Model ◽  
Boltzmann Method

Researches on the principle of human red blood cell’s (RBC) injuring and judgment basis play an important role in decreasing the hemolysis in a blood pump. In the current study, the judgment of hemolysis in a blood pump study was through some experiment data and empirical formula. The paper forms a criterion of RBC’s mechanical injury in the aspect of RBC’s free energy. First, the paper introduces the nonlinear spring network model of RBC in the frame of immersed boundary-lattice Boltzmann method (IB-LBM). Then, the shape, free energy, and time needed for erythrocyte to be shorn in different shear flow and impacted in different impact flow are simulated. Combining existing research on RBC’s threshold limit for hemolysis in shear and impact flow with this paper’s, the RBC’s free energy of the threshold limit for hemolysis is found to be 3.46 × 10 − 15  J. The threshold impact velocity of RBC for hemolysis is 8.68 m/s. The threshold value of RBC can be used for judgment of RBC’s damage when the RBC is having a complicated flow of blood pumps such as coupling effect of shear and impact flow. According to the change law of RBC’s free energy in the process of being shorn and impacted, this paper proposed a judging criterion for hemolysis when the RBC is under the coupling effect of shear and impact based on the increased free energy of RBC.

scholarly journals Immersed boundary (IB) - Lattice Boltzmann Method (LBM) coupled with Adaptive MESH Refinement (AMR) techniques for simulation of Incompressible Viscous Flow

2021 ◽  
Author(s):  
Xixiong Guo
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Adaptive Mesh Refinement ◽  
Moving Objects ◽  
Mesh Refinement ◽  
Adaptive Mesh ◽  
Slip Boundary Condition ◽  
Immersed Boundary ◽  
Slip Boundary ◽  
Boltzmann Method

This study is aimed at developing a novel computational framework that seamlessly incorporates the feedback forcing model and adaptive mesh refinement mesh refinement (AMR) techniques in the immersed-boundary (IB) lattice Boltzmann method (LBM) approach, so that challenging problems, including the interactions between flowing fluids and moving objects, can be numerically investigated. Owing to the feedback forcing based IB model, the advantages, such as simple mechanics principle, explicit interpolations, and inherent satisfaction of no-slip boundary condition for solid surfaces are fully exhibited. Additionally, the "bubble' function is employed in the local mesh refinement process, so that the solution of second order accuracy at newly generated nodes can be obtained only by the spatial interpolation but no temporal interpolation. Focusing on both steady and unsteady flow around a single cylinder and bi-cylinders, a number of test cases performed in this study have demonstrated the usefulness and effectiveness of the present AMR IB-LBM approach.

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