Numerical study of segregation using a new drag force correlation for polydisperse systems derived from lattice-Boltzmann simulations

2007 ◽  
Vol 62 (1-2) ◽  
pp. 246-255 ◽  
Author(s):  
R. Beetstra ◽  
M.A. van der Hoef ◽  
J.A.M. Kuipers
Keyword(s):  
Drag Force ◽  
Lattice Boltzmann ◽  
Numerical Study ◽  
Lattice Boltzmann Simulations

Lattice Boltzmann Simulations for Thermal Conductivity Estimation in Heterogeneous Materials

2009 ◽  
Vol 283-286 ◽  
pp. 364-369 ◽  
Author(s):  
M.R. Arab ◽  
Bernard Pateyron ◽  
Mohammed El Ganaoui ◽  
Nicolas Calvé
Keyword(s):  
Thermal Conductivity ◽  
Porous Medium ◽  
Lattice Boltzmann ◽  
Numerical Study ◽  
Theoretical Models ◽  
Short Description ◽  
Physical Parameters ◽  
Two Dimensional ◽  
Lattice Boltzmann Simulations ◽  
Boltzmann Method

For simulating flows in a porous medium, a numerical tool based on the Lattice Boltzmann Method (LBM) is developed with regards to the classical D2Q9 model. A short description of this model is presented. This technique, applied to two-dimensional configurations, indicates its ability to simulate phenomena of heat and mass transfer. The numerical study is extended to estimate physical parameters that characterize porous materials, like the so-called Effective Thermal Conductivity (ETC) which is of our interest in this paper. Obtained results are compared with those which could be found analytically and by theoretical models. Finally, a porous medium is considered to find its ETC.

scholarly journals Lattice Boltzmann simulations of low-Reynolds-number flows past fluidized spheres: effect of inhomogeneities on the drag force

2017 ◽  
Vol 833 ◽  
pp. 599-630 ◽  
Author(s):  
Gregory J. Rubinstein ◽  
Ali Ozel ◽  
Xiaolong Yin ◽  
J. J. Derksen ◽  
Sankaran Sundaresan
Keyword(s):  
Reynolds Number ◽  
Drag Force ◽  
Lattice Boltzmann ◽  
Volume Fraction ◽  
Low Reynolds Number ◽  
Particle Volume Fraction ◽  
Spherical Particles ◽  
Particle Volume ◽  
Lattice Boltzmann Simulations ◽  
Low Reynolds

The formation of inhomogeneities within fluidized beds, both in terms of the particle configurations and flow structures, have a pronounced effect on the interaction force between the fluid and particles. While recent numerical studies have begun to probe the effects of inhomogeneities on the drag force at the particle scale, the applicability of prior microscale constitutive drag relations is still limited to random, homogeneous distributions of particles. Since an accurate model for the drag force is needed to predict the fluidization behaviour, the current study utilizes the lessons of prior inhomogeneity studies in order to derive a robust drag relation that is both able to account for the effect of inhomogeneities and applicable as a constitutive closure to larger-scale fluidization simulations. Using fully resolved lattice Boltzmann simulations of systems composed of fluid and monodisperse spherical particles in the low-Reynolds-number (Re) regime, the fluid–particle drag force, normalized by the ideal Stokes drag force, is found to significantly decrease, over a range of length scales, as the extent of inhomogeneities increases. The extent of inhomogeneities is found to most effectively be quantified through one of two subgrid-scale quantities: the scalar variance of the particle volume fraction or the drift flux, which is the correlation between the particle volume fraction and slip velocity. Scale-similar models are developed to estimate these two subgrid measures over a wide range of system properties. Two new drag constitutive models are proposed that are not only functions of the particle volume fraction and the Stokes number ($St$), but also dependent on one of these subgrid measures for the extent of inhomogeneities. Based on the observed, appreciable effect of inhomogeneities on drag, these new low-Re drag models represent a significant advancement over prior constitutive relations.

Lattice Boltzmann simulations of low-Reynolds-number flow past fluidized spheres: effect of Stokes number on drag force

2016 ◽  
Vol 788 ◽  
pp. 576-601 ◽  
Author(s):  
Gregory J. Rubinstein ◽  
J. J. Derksen ◽  
Sankaran Sundaresan
Keyword(s):  
Reynolds Number ◽  
Drag Force ◽  
Lattice Boltzmann ◽  
Fluidized Beds ◽  
Low Reynolds Number ◽  
Stokes Number ◽  
Fluid Particle ◽  
Spherical Particles ◽  
Lattice Boltzmann Simulations ◽  
Low Reynolds

In a fluidized bed, the drag force acts to oppose the downward force of gravity on a particle, and thus provides the main mechanism for fluidization. Drag models that are employed in large-scale simulations of fluidized beds are typically based on either fixed-particle beds or the sedimentation of particles in liquids. In low-Reynolds-number ($Re$) systems, these two types of fluidized beds represent the limits of high Stokes number ($St$) and low $St$, respectively. In this work, the fluid–particle drag behaviour of these two regimes is bridged by investigating the effect of $St$ on the drag force in low-$Re$ systems. This study is conducted using fully resolved lattice Boltzmann simulations of a system composed of fluid and monodisperse spherical particles. In these simulations, the particles are free to translate and rotate based on the effects of the surrounding fluid. Through this work, three distinct regimes in the characteristics of the fluid–particle drag force are observed: low, intermediate and high $St$. It is found that, in the low-$Re$ regime, a decrease in $St$ results in a reduction in the fluid–particle drag. Based on the simulation results, a new drag relation is proposed, which is, unlike previous models, dependent on $St$.

scholarly journals Lattice-Boltzmann simulations of the drag force on a sphere approaching a superhydrophobic striped plane

2014 ◽  
Vol 140 (3) ◽  
pp. 034707 ◽  
Author(s):  
Alexander L. Dubov ◽  
Sebastian Schmieschek ◽  
Evgeny S. Asmolov ◽  
Jens Harting ◽  
Olga I. Vinogradova
Keyword(s):  
Drag Force ◽  
Lattice Boltzmann ◽  
Lattice Boltzmann Simulations

Modeling Elastic Walls in Lattice Boltzmann Simulations of Arterial Blood Flow

2013 ◽  
Vol 23 (2) ◽  
Author(s):  
Xenia Descovich ◽  
Giuseppe Pontrelli ◽  
Sauro Succi ◽  
Simone Melchionna ◽  
Manfred Bammer
Keyword(s):  
Blood Flow ◽  
Lattice Boltzmann ◽  
Arterial Blood Flow ◽  
Arterial Blood ◽  
Lattice Boltzmann Simulations ◽  
Elastic Walls

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.

Sign in / Sign up

Export Citation Format

Share Document