scholarly journals Macroscopic Lattice Boltzmann Method

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 61
Author(s):  
Jian Guo Zhou
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Fluid Flows ◽  
Fluid Viscosity ◽  
Science And Engineering ◽  
Physical Problems ◽  
Lattice Size ◽  
Particle Speed ◽  
Physical Variables ◽  
Boltzmann Method

The lattice Boltzmann method (LBM) is a highly simplified model for fluid flows using a few limited fictitious particles. It has been developed into a very efficient and flexible alternative numerical method in computational physics, demonstrating its great power and potential for resolving more and more challenging physical problems in science and engineering covering a wide range of disciplines such as physics, chemistry, biology, material science and image analysis. The LBM is implemented through the two routine steps of streaming and collision using the three parameters of the lattice size, particle speed and collision operator. A fundamental question is if the two steps are integral to the method or if the three parameters can be reduced to one for a minimal lattice Boltzmann method. In this paper, it is shown that the collision step can be removed and the standard LBM can be reformulated into a simple macroscopic lattice Boltzmann method (MacLAB). This model relies on macroscopic physical variables only and is completely defined by one basic parameter of the lattice size δx, bringing the LBM into a precise “lattice” Boltzmann method. The viscous effect on flows is naturally embedded through the particle speed, making it an ideal automatic simulator for fluid flows. Three additional advantages compared to the existing LBMs are that: (i) physical variables can directly be retained as the boundary conditions; (ii) much less computational memory is required; and (iii) the model is unconditionally stable. The findings are demonstrated and confirmed with numerical tests including flows that are independent of and dependent on fluid viscosity, 2D and 3D cavity flows and an unsteady Taylor–Green vortex flow. This provides an efficient and powerful model for resolving physical problems in various disciplines of science and engineering.

Simulation of Hypersonic Viscous Flow Past a 2D Circular Cylinder Using Lattice Boltzmann Method

2010 ◽  
Author(s):  
R. Kamali ◽  
A. H. Tabatabaee Frad
Keyword(s):  
Circular Cylinder ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
High Speed ◽  
Fluid Flows ◽  
Boltzmann Distribution ◽  
Equilibrium Distribution Function ◽  
Complex Flows ◽  
Compressible Viscous Flows ◽  
Boltzmann Method

It is known that the Lattice Boltzmann Method is not very effective when it is being used for the high speed compressible viscous flows; especially complex fluid flows around bodies. Different reasons have been reported for this unsuccessfulness; Lacking in required isotropy in the employed lattices and the restriction of having low Mach number in Taylor expansion of the Maxwell Boltzmann distribution as the equilibrium distribution function, might be mentioned as the most important ones. In present study, a new numerical method based on Li et al. scheme is introduced which enables the Lattice BoltzmannMethod to stably simulate the complex flows around a 2D circular cylinder. Furthermore, more stable implementation of boundary conditions in Lattice Boltzmann method is discussed.

Numerical Investigation of Flow Over an Airfoil by the Lattice Boltzmann Method

2013 ◽  
Author(s):  
Felipe A. Valenzuela ◽  
Amador M. Guzmán ◽  
Andrés J. Díaz
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Preliminary Investigation ◽  
Computational Cost ◽  
Fluid Flows ◽  
Laminar Flows ◽  
Navier Stokes ◽  
Laminar Separation ◽  
Refinement Method ◽  
Boltzmann Method

During the last years the aerodynamics characteristics of airfoils have been studied solving numerically the Navier-Stokes (NS) equations. These calculations require a significant computational cost due to both the second order and the nonlinear characteristics of the NS partial differential equations. Therefore, efforts have been devoted to reduce this cost and increase the accuracy of the numerical methods. The Lattice-Boltzmann Method (LBM) has become a great alternative to simulate this problem and a variety of fluid flows. In this method, the convective operator is linear and the pressure is calculated directly by the equation of state without implementing iterative methods. This work represents a preliminary investigation of a laminar flow over airfoils under low Reynolds number conditions (Re = 500). Solutions are obtained using a Multi-Block mesh refinement method. In order to validate the computational code, calculations are performed on a SD7003 airfoil at an angle of attack of 4° and 30°, which corresponds to the available numerical and experimental results. The results of this study agree well with previous experimental and numerical studies demonstrating the capabilities of the LBM to simulate accurately laminar flows over airfoils as well as capturing and predicting the laminar separation bubbles.

A Meshfree-Based Lattice Boltzmann Approach for Simulation of Fluid Flows Within Complex Geometries

2018 ◽  
pp. 188-222 ◽  
Author(s):  
Sonam Tanwar
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Moving Boundary ◽  
Fluid Flows ◽  
Computational Domain ◽  
Time Step ◽  
Boundary Problems ◽  
Complex Process ◽  
Element Free ◽  
Boltzmann Method

This chapter develops a meshless formulation of lattice Boltzmann method for simulation of fluid flows within complex and irregular geometries. The meshless feature of proposed technique will improve the accuracy of standard lattice Boltzmann method within complicated fluid domains. Discretization of such domains itself may introduce significant numerical errors into the solution. Specifically, in phase transition or moving boundary problems, discretization of the domain is a time-consuming and complex process. In these problems, at each time step, the computational domain may change its shape and need to be re-meshed accordingly for the purpose of accuracy and stability of the solution. The author proposes to combine lattice Boltzmann method with a Galerkin meshfree technique popularly known as element-free Galerkin method in this chapter to remove the difficulties associated with traditional grid-based methods.

Immersed Boundary Lattice Boltzmann Method to Simulate Fluid Flows with Flexible Boundaries

2014 ◽  
Vol 670-671 ◽  
pp. 659-663
Author(s):  
Yong Guang Chen ◽  
Li Wan
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Large Scale ◽  
Implementation Process ◽  
Fluid Flows ◽  
Combination Method ◽  
Immersed Boundary ◽  
Key Factors ◽  
Boltzmann Method ◽  
Flexible Boundaries

The immersed boundary method (IBM) for the simulation of the interaction between fluid and flexible boundaries in combination with the lattice Boltzmann method (LBM) is described. The LBM is used to compute the flow field, the interaction between fluid and flexible boundaries to be treated by the IBM. To analyze the key factors of combination method and implementation process. An example is presented to verify the efficiency and accuracy of the described algorithm. These will provide a base for large scale simulation involving flexible boundaries in the future.

Challenges on Porting Lattice Boltzmann Method on Accelerators

2018 ◽  
pp. 30-53 ◽  
Author(s):  
Claudio Schepke ◽  
João V. F. Lima ◽  
Matheus S. Serpa
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
High Performance ◽  
Three Dimensional ◽  
Fluid Flows ◽  
Xeon Phi ◽  
Performance Impact ◽  
Operation Rules ◽  
Dimensional Version ◽  
Boltzmann Method

Currently NVIDIA GPUs and Intel Xeon Phi accelerators are alternatives of computational architectures to provide high performance. This chapter investigates the performance impact of these architectures on the lattice Boltzmann method. This method is an alternative to simulate fluid flows iteratively using discrete representations. It can be adopted for a large number of flows simulations using simple operation rules. In the experiments, it was considered a three-dimensional version of the method, with 19 discrete directions of propagation (D3Q19). Performance evaluation compare three modern GPUs: K20M, K80, and Titan X; and two architectures of Xeon Phi: Knights Corner (KNC) and Knights Landing (KNL). Titan X provides the fastest execution time of all hardware considered. The results show that GPUs offer better processing time for the application. A KNL cache implementation presents the best results for Xeon Phi architectures and the new Xeon Phi (KNL) is two times faster than the previous model (KNC).

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