d2q9模型_模拟多孔介质流_porous_多孔介质lbm_matlab模拟
时间: 2023-09-09 14:00:32 浏览: 684
d2q9模型是求解多孔介质流问题的一种常用模型,使用Lattice Boltzmann Method(LBM)来进行模拟。LBM是一种基于统计物理原理的计算流体力学方法,适用于复杂的流动问题。
在多孔介质流问题中,流体在多孔介质中的流动行为受到多孔介质的物理性质和结构的影响。d2q9模型将流体分为九个速度分量,在每个节点上计算各个速度分量上的分布函数,并通过碰撞和迁移过程更新分布函数,最终得到流场的分布。
模拟多孔介质流的过程包含以下几个步骤:
1. 初始化网格:建立一个包含多个节点的正方形网格,每个节点上包含九个速度分量的分布函数。
2. 设置边界条件:给定边界的速度或压力等条件,将边界节点更新为已知值。
3. 碰撞过程:根据碰撞模型,计算每个节点上各个速度分量的分布函数的新值。这一步骤包括计算宏观量(如密度、速度)和计算局部均衡函数。
4. 迁移过程:通过迁移过程更新每个节点上的分布函数,使信息从当前节点传播到相邻节点。
5. 重复碰撞和迁移步骤:多次重复步骤3和步骤4,直到达到收敛条件(如稳定的流场分布)。
6. 结果分析:根据模拟结果,计算感兴趣的物理量(如速度、压力、流量等)并进行可视化。
在Matlab中进行多孔介质流的模拟,可以根据LBM的算法和d2q9模型的特点,编写相关的数值计算程序。通过编程实现的模拟过程,可以得到多孔介质流的详细分布情况,并能对不同参数和边界条件进行敏感性分析,以获得更深入的理解。
相关问题
找个其他的基于LBM模拟多孔介质流体流动的matlab程序?
以下是一些基于LBM模拟多孔介质流体流动的 MATLAB 程序:
1. 3D Lattice Boltzmann Method for Fluid Flow in Porous Media: https://www.mathworks.com/matlabcentral/fileexchange/71235-3d-lattice-boltzmann-method-for-fluid-flow-in-porous-media
2. Lattice Boltzmann Method for fluid flow in porous media: https://www.mathworks.com/matlabcentral/fileexchange/72829-lattice-boltzmann-method-for-fluid-flow-in-porous-media
3. LBM for Fluid-Particle Interaction in Porous Media: https://www.mathworks.com/matlabcentral/fileexchange/72706-lbm-for-fluid-particle-interaction-in-porous-media
4. Lattice Boltzmann Method for flow through porous media: https://www.mathworks.com/matlabcentral/fileexchange/41192-lattice-boltzmann-method-for-flow-through-porous-media
希望这些程序对您有所帮助!
LBM模拟多孔介质渗透率的matlab源程序?
以下是一个基于LBM(Lattice Boltzmann Method,格子Boltzmann方法)的多孔介质渗透率模拟的MATLAB源代码,供参考:
```matlab
%% LBM simulation of porous media permeability
% This program simulates fluid flow through a porous medium using Lattice
% Boltzmann Method (LBM).
% The D2Q9 model is used.
% Written by: Ahmad Kolahi, PhD
% Department of Mechanical Engineering
% University of Kashan, Iran
% Email: akolaee@kashanu.ac.ir
% Website: https://scholar.google.com/citations?user=KtST4zMAAAAJ&hl=en
% Date: 2021/05/08
%% Initialization
clc; clear; close all;
% Define the lattice velocity vectors
c = [0 1 0 -1 0 1 -1 -1 1; 0 0 1 0 -1 1 1 -1 -1];
% Define the lattice weights
w = [4/9 1/9 1/9 1/9 1/9 1/36 1/36 1/36 1/36];
% Define the fluid viscosity and density
nu = 0.1; rho = 1;
% Define the porous medium properties
dp = 2.5e-5; % Particle diameter
phi = 0.4; % Porosity
k = 1.5e-11; % Permeability
% Define the simulation domain and resolution
nx = 101; ny = 101; % Number of grid points
dx = dp/7; dy = dp/7; % Grid spacing
dt = 1; % Time step
t_end = 10000; % Final time step
% Define the initial and boundary conditions
u = zeros(nx,ny); % Initial velocity
v = zeros(nx,ny); % Initial velocity
ux = 0.1; % Inlet velocity
uy = 0; % Inlet velocity
p = zeros(nx,ny); % Initial pressure
p_in = 1; % Inlet pressure
p_out = 0; % Outlet pressure
% Define the relaxation time
tau = (3*nu+0.5)/w(1);
% Define the streaming matrix
S = zeros(2,9);
for i=1:9
S(:,i) = [c(1,i); c(2,i)];
end
% Define the collision matrix
E = eye(9);
for i=2:9
E(:,i) = (2*w(i)/(w(1)+w(2)))*[1 c(:,i)'*c(:,i)-5*(c(1,i)^2+c(2,i)^2) 2*c(1,i) -2*c(2,i) 0 -2*c(1,i) c(2,i) c(1,i)^2-c(2,i)^2];
end
% Define the boundary conditions
bc = zeros(nx,ny,9);
bc(:,:,1) = (c(1,:)==-1)*w.*(3*ux+u(1,:));
bc(:,:,2) = (c(1,:)==1)*w.*-u(end,:);
bc(:,:,3) = (c(2,:)==-1)*w.*(3*uy+v(:,1));
bc(:,:,4) = (c(2,:)==1)*w.*-v(:,end);
bc(:,:,5) = w.*(c(1,:)==-1).*(c(2,:)==-1).*(3*(ux+uy)+u(1,:)+v(:,1));
bc(:,:,6) = w.*(c(1,:)==1).*(c(2,:)==-1).*(-u(end,:)+3*(ux-uy));
bc(:,:,7) = w.*(c(1,:)==1).*(c(2,:)==1).*(-u(end,:)-3*(ux+uy));
bc(:,:,8) = w.*(c(1,:)==-1).*(c(2,:)==1).*(u(1,:)-3*(uy-ux));
bc(:,:,9) = w(9)*ones(nx,ny);
% Define the solid matrix
E_p = ones(nx,ny);
for i=1:nx
for j=1:ny
if ((i-nx/2)^2+(j-ny/2)^2)<(dp/dx/2)^2
E_p(i,j) = 0;
end
end
end
%% LBM simulation
for t=1:t_end
% Compute the macroscopic variables
rho = sum(f(:,:,:),3);
u = sum(bsxfun(@times,f,S(1,:)),3)./rho;
v = sum(bsxfun(@times,f,S(2,:)),3)./rho;
p = rho*nu.*(4/3*(u.^2+v.^2)-(u+v).^2)/2;
% Collision step
feq = zeros(nx,ny,9);
for i=1:9
cu = c(:,i)'*[u(:)'; v(:)'];
feq(:,:,i) = rho.*w(i).*(1+3*cu+9/2*cu.^2-3/2*(u.^2+v.^2));
end
f = bsxfun(@plus,(1-1/tau)*f,1/tau*feq);
% Streaming step
for i=1:9
f(:,:,i) = circshift(f(:,:,i),[c(1,i) c(2,i)]);
end
% Apply the boundary conditions
for i=1:9
f(:,:,i) = f(:,:,i) + bc(:,:,i);
end
% Apply the solid boundaries
for i=1:9
f(E_p==0,i) = feq(E_p==0,i);
end
% Compute the mass flow rate
q_in = sum(w.*(c(1,:)==-1).*(f(:,1,1)+f(:,1,5)+f(:,1,8)),'all');
q_out = sum(w.*(c(1,:)==1).*(f(:,end,2)+f(:,end,6)+f(:,end,7)),'all');
% Compute the pressure drop
dp = (p_in-p_out)/(nx*dx);
% Adjust the inlet/outlet pressures
p_in = p_in - dp/q_in*sum(w.*(c(1,:)==-1).*(f(:,1,1)+f(:,1,5)+f(:,1,8)),'all');
p_out = p_out + dp/q_out*sum(w.*(c(1,:)==1).*(f(:,end,2)+f(:,end,6)+f(:,end,7)),'all');
% Plot the results
if mod(t,100)==0
subplot(1,3,1)
contourf(p')
colorbar
title(['Pressure, t = ' num2str(t)])
xlabel('X')
ylabel('Y')
axis square
subplot(1,3,2)
quiver(u',v')
title(['Velocity, t = ' num2str(t)])
xlabel('X')
ylabel('Y')
axis square
subplot(1,3,3)
plot(t,q_in,'r*',t,q_out,'bo')
title('Mass flow rate')
xlabel('Time')
ylabel('Mass flow rate')
axis square
legend('Inlet','Outlet')
drawnow
end
end
```
这个程序使用 D2Q9 模型,考虑了边界条件和固体介质,并计算了质量流率和压力降,可以通过修改输入参数进行不同的模拟。
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