Solving the Steady and Unsteady 2D Heat Conduction Equation by point Iterative techniques using MATLAB
OBJECTIVE:
To solve Steady and Unsteady state 2D Heat Conduction Equation by using the point iterative techniques such as Jacobi, Gauss Seidel & Successive over-relaxation for both implicit and explicit schemes using MATLAB.
Problem statement:
- Computation area is to be a square.
- Assume nx = ny [No. of points on x-direction is equal to no. of points in y-direction]
- We assume nx = ny = 10
- Boundary Conditions are
Left = 400k
Right = 600k
Top = 800k
Bottom = 900k - Apart from the boundary conditions, all other nodes are given an initial temperature of 300k.
- Various methods to be employed in solving the equation are given below:
- Various States: Steady-state & Unsteady-state Condition
- Various Schemes: Jacobi, Gauss-seidel & Successive over-relaxation
- Various Methods to be used in Unsteady-state: IMPLICIT & EXPLICIT
- Various States: Steady-state & Unsteady-state Condition
By using Point iterative method, solve the 2D Heat Conduction Equation and plot the Temperature Contour for all the three iterative methods namely Jacobi, Gauss-Siedel & SOR for Steady and Unsteady conditions under IMPLICIT scheme also additionally solving the EXPLICIT scheme for Unsteady Condition.
THEORY:
The heat equation is a partial differential equation that describes how the distribution of some quantity (such as heat) evolves over time in a solid medium, as it spontaneously flows from places where it is higher towards places where it is lower.
For a function
of three spatial variables
(see Cartesian coordinate system) and the time variable
, the heat equation is
where,
is a real coefficient called the diffusivity of the medium.
Types of Heat Conduction schemes
This transfer of Heat energy may occur under two conditions
- Steady-state condition
- Unsteady/Transient state condition
Unsteady state conditions are a precursor to steady state conditions. No system exists initially under steady state conditions. Some time must pass, after heat transfer is initiated, before the system reaches steady state. During that period of transition the system is under unsteady state conditions.
Time Loop Logic:
Boundary Condition Map:
Here,
`T_L` = Left boundary
`T_T` = Top boundary
`T_P` = Middle/Point boundary
`T_B` = Bottom boundary
`T_R` = Right boundary
Governing Equations
In order to solve the 2D Heat Conduction problem, the governing equations for respective conditions with respect to cartesian coordinates should be discretized to enter that in a code which is given under MAIN PROGRAM below.
MAIN PROGRAM:
Below there is a sequence of seven individual programs, starting with IMPLICIT Scheme of Steady & Unsteady-state conditions for three iterative methods Jacobi, Gauss-siedel & SOR followed by EXPLICIT Scheme for Unsteady/Transient Conditions.
IMPLICIT Scheme - Steady-state Condition Program:
Steady-state Equation discretization:
In steady-state conduction, the amount of heat entering any region of an object is equal to the amount of heat coming out (if this were not so, the temperature would be rising or falling, as thermal energy was tapped or trapped in a region).
Jacobi Iteration
close all
clear all
clc
%Solving the Steady state 2D heat conduction (Jacobi Method)
%Input Parameters
%Number of grid points
nx = 10;
ny = nx;
x = linspace(0,1,nx);
y = linspace(0,1,ny);
dx = x(2) - x(1);
dy = dx;
%Absolute error criteria > tolerance
error = 9e9;
tolerance = 1e-4;
%Defining Boundary conditions
T_L = 400;
T_T = 600;
T_R = 800;
T_B = 900;
T = 300*ones(nx,ny);
T(2:ny - 1, 1) = T_L;
T(2:ny - 1, nx) = T_R;
T(1, 2:nx - 1) = T_T;
T(ny, 2:nx - 1) = T_B;
%Calculating Average temperature at corners
T(1,1) = (T_T + T_L)/2;
T(nx,ny) = (T_R + T_B)/2;
T(1,ny) = (T_T + T_R)/2;
T(nx,1) = (T_L + T_B)/2;
%Assigning orginal values to T
T_intial = T;
T_old = T;
%Calculation of 2D steady heat conduction EQUATION by JACOBI method
iterative_solver = 1;
if iterative_solver == 1
jacobi_iteration = 1;
while(error > tolerance)
for i = 2:nx - 1
for j = 2:ny - 1
T(i,j) = 0.25*(T_old(i-1,j) + T_old(i+1,j) + T_old(i,j-1) + T_old(i,j+1));
end
end
error = max(max(abs(T_old - T)));
T_old = T;
jacobi_iteration = jacobi_iteration + 1;
end
end
%Plotting
figure(1)
contourf(x,y,T)
clabel(contourf(x,y,T))
colorbar
colormap(jet)
set(gca, 'ydir', 'reverse')
xlabel('X-Axis')
ylabel('Y-Axis')
title(sprintf('No. of Jacobi Iterations(IMPLICIT) = %d', jacobi_iteration));
pause(0.03);
Output
Gauss-Siedel Iteration
close all
clear all
clc
%Solving the Steady state 2D heat conduction (Gauss-seidel Method)
%Input Parameters
%Number of grid points
nx = 10;
ny = nx;
x = linspace(0,1,nx);
y = linspace(0,1,ny);
dx = x(2) - x(1);
dy = dx;
%Absolute error criteria > tolerance
error = 9e9;
tolerance = 1e-4;
%Defining Boundary conditions
T_L = 400;
T_T = 600;
T_R = 800;
T_B = 900;
T = 300*ones(nx,ny);
T(2:ny - 1, 1) = T_L;
T(2:ny - 1, nx) = T_R;
T(1, 2:nx - 1) = T_T;
T(ny, 2:nx - 1) = T_B;
%Calculating Average temperature at corners
T(1,1) = (T_T + T_L)/2;
T(nx,ny) = (T_R + T_B)/2;
T(1,ny) = (T_T + T_R)/2;
T(nx,1) = (T_L + T_B)/2;
%Assigning orginal values to T
T_intial = T;
T_old = T;
%Calculation of 2D steady heat conduction EQUATION by Gauss-Seidel method
iterative_solver = 2;
if iterative_solver == 2
Gauss_seidel_iteration = 1;
while(error > tolerance)
for i = 2:nx - 1
for j = 2:ny - 1
T(i,j) = 0.25*(T(i-1,j) + T_old(i+1,j) + T(i,j-1) + T_old(i,j+1));
end
end
error = max(max(abs(T_old - T)));
T_old = T;
Gauss_seidel_iteration = Gauss_seidel_iteration + 1;
end
end
%Plotting
figure(1)
contourf(x,y,T)
clabel(contourf(x,y,T))
colorbar
colormap(jet)
set(gca, 'ydir', 'reverse')
xlabel('X-Axis')
ylabel('Y-Axis')
title(sprintf('No. of Gauss-Seidel Iterations(IMPLICIT) = %d', Gauss_seidel_iteration));
pause(0.03);
Output
Successive over-relaxation
close all
clear all
clc
%Solving the Steady state 2D heat conduction (Successive over-relaxation Method)
%Input Parameters
%Number of grid points
nx = 10;
ny = nx;
x = linspace(0,1,nx);
y = linspace(0,1,ny);
dx = x(2) - x(1);
dy = dx;
%Absolute error criteria > tolerance
error = 9e9;
tolerance = 1e-4;
omega = 1.2;
%Defining Boundary conditions
T_L = 400;
T_T = 600;
T_R = 800;
T_B = 900;
T = 300*ones(nx,ny);
T(2:ny - 1, 1) = T_L;
T(2:ny - 1, nx) = T_R;
T(1, 2:nx - 1) = T_T;
T(ny, 2:nx - 1) = T_B;
%Calculating Average temperature at corners
T(1,1) = (T_T + T_L)/2;
T(nx,ny) = (T_R + T_B)/2;
T(1,ny) = (T_T + T_R)/2;
T(nx,1) = (T_L + T_B)/2;
%Assigning orginal values to T
T_intial = T;
T_old = T;
%Calculation of 2D steady heat conduction EQUATION by Successive over-relaxation method
iterative_solver = 3;
if iterative_solver == 3
Successive_Over_Relaxation_iteration = 1;
while(error > tolerance)
for i = 2:nx - 1
for j = 2:ny - 1
T(i,j) = omega*(0.25*(T(i-1,j) + T_old(i+1,j) + T(i,j-1) + T_old(i,j+1))) + (1 - omega)*T_old(i,j);
end
end
error = max(max(abs(T_old - T)));
T_old = T;
Successive_Over_Relaxation_iteration = Successive_Over_Relaxation_iteration + 1;
end
end
%Plotting
figure(1)
contourf(x,y,T)
clabel(contourf(x,y,T))
colorbar
colormap(jet)
set(gca, 'ydir', 'reverse')
xlabel('X-Axis')
ylabel('Y-Axis')
title(sprintf('No. of Successive Over-Relaxation Iterations(IMPLICIT) = %d', Successive_Over_Relaxation_iteration));
pause(0.03);
Output
IMPLICIT Scheme Unsteady/Transient-state Condition Program:
Unsteady-state Equation discretization:
Non-steady-state situations appear after an imposed change in temperature at a boundary as well as inside of an object, as a result of a new source or sink of heat suddenly introduced within an object, causing temperatures near the source or sink to change in time.
Jacobi Iteration
close all
clear all
clc
%Solving the Unsteady state 2D heat conduction by Jacobi Method(IMPLICIT SCHEME)
%Input Parameters
%Number of grid points
nx = 10;
ny = nx;
nt = 1400;
x = linspace(0,1,nx);
y = linspace(0,1,ny);
dx = x(2) - x(1);
dy = dx;
%Absolute error criteria > tolerance
error = 9e9;
tolerance = 1e-4;
dt = 1e-3;
%Defining Boundary conditions
T_L = 400;
T_T = 600;
T_R = 800;
T_B = 900;
T = 300*ones(nx,ny);
T(2:ny - 1, 1) = T_L;
T(2:ny - 1, nx) = T_R;
T(1, 2:nx - 1) = T_T;
T(ny, 2:nx - 1) = T_B;
%Calculating Average temperature at corners
T(1,1) = (T_T + T_L)/2;
T(nx,ny) = (T_R + T_B)/2;
T(1,ny) = (T_T + T_R)/2;
T(nx,1) = (T_L + T_B)/2;
%Assigning orginal values to T
T_old = T;
T_intial = T;
%Calculation of 2D steady heat conduction EQUATION by Successive over-relaxation method
k1 = 1.1*(dt/(dx^2));
k2 = 1.1*(dt/(dy^2));
Jacobi_iteration = 1;
for k = 1:nt
error = 9e9;
while(error > tolerance)
for i = 2:nx - 1
for j = 2:ny - 1
Term_1 = 1/(1 + (2*k1) + (2*k2));
Term_2 = k1*Term_1;
Term_3 = k2*Term_1;
H = (T_old(i-1,j)) + (T_old(i+1,j));
V = (T_old(i,j+1)) + (T_old(i,j-1));
T(i,j) = (T_intial(i,j)*Term_1) + (H*Term_2) + (V*Term_3);
end
end
error = max(max(abs(T_old - T)));
T_old = T;
Jacobi_iteration = Jacobi_iteration + 1;
end
T_intial = T;
%Plotting
figure(1)
contourf(x,y,T)
clabel(contourf(x,y,T))
colorbar
colormap(jet)
set(gca, 'ydir', 'reverse')
xlabel('X-Axis')
ylabel('Y-Axis')
title(sprintf('No. of Unsteady Jacobi Iterations(EXPLICIT) = %d', Jacobi_iteration));
pause(0.03)
end
Output
Gauss-Siedel Iteration
close all
clear all
clc
%Solving the Unsteady state 2D heat conduction by Gauss Seidel Method(IMPLICIT SCHEME)
%Input Parameters
%Number of grid points
nx = 10;
ny = nx;
nt = 1400;
x = linspace(0,1,nx);
y = linspace(0,1,ny);
dx = x(2) - x(1);
dy = dx;
%Absolute error criteria > tolerance
error = 9e9;
tolerance = 1e-4;
dt = 1e-3;
%Defining Boundary conditions
T_L = 400;
T_T = 600;
T_R = 800;
T_B = 900;
T = 300*ones(nx,ny);
T(2:ny - 1, 1) = T_L;
T(2:ny - 1, nx) = T_R;
T(1, 2:nx - 1) = T_T;
T(ny, 2:nx - 1) = T_B;
%Calculating Average temperature at corners
T(1,1) = (T_T + T_L)/2;
T(nx,ny) = (T_R + T_B)/2;
T(1,ny) = (T_T + T_R)/2;
T(nx,1) = (T_L + T_B)/2;
%Assigning orginal values to T
T_old = T;
T_intial = T;
%Calculation of 2D steady heat conduction EQUATION by Successive over-relaxation method
k1 = 1.1*(dt/(dx^2));
k2 = 1.1*(dt/(dy^2));
Gauss_Seidel_iteration = 1;
for k = 1:nt
error = 9e9;
while(error > tolerance)
for i = 2:nx - 1
for j = 2:ny - 1
Term_1 = 1/(1 + (2*k1) + (2*k2));
Term_2 = k1*Term_1;
Term_3 = k2*Term_1;
H = (T(i-1,j)) + (T_old(i+1,j));
V = (T(i,j+1)) + (T_old(i,j-1));
T(i,j) = (T_intial(i,j)*Term_1) + (H*Term_2) + (V*Term_3);
end
end
error = max(max(abs(T_old - T)));
T_old = T;
Gauss_Seidel_iteration = Gauss_Seidel_iteration + 1;
end
T_intial = T;
%Plotting
figure(1)
contourf(x,y,T)
clabel(contourf(x,y,T))
colorbar
colormap(jet)
set(gca, 'ydir', 'reverse')
xlabel('X-Axis')
ylabel('Y-Axis')
title(sprintf('No. of Unsteady Gauss-Seidel Iterations(IMPLICIT) = %d', Gauss_Seidel_iteration));
pause(0.03)
end
Output
Successive over-relaxation
close all
clear all
clc
%Solving the Unsteady state 2D heat conduction by Successive over-relaxation Method(IMPLICIT SCHEME)
%Input Parameters
%Number of grid points
nx = 10;
ny = nx;
nt = 1400;
x = linspace(0,1,nx);
y = linspace(0,1,ny);
dx = x(2) - x(1);
dy = dx;
%Absolute error criteria > tolerance
error = 9e9;
tolerance = 1e-4;
dt = 1e-3;
omega = 1.1;
%Defining Boundary conditions
T_L = 400;
T_T = 600;
T_R = 800;
T_B = 900;
T = 300*ones(nx,ny);
T(2:ny - 1, 1) = T_L;
T(2:ny - 1, nx) = T_R;
T(1, 2:nx - 1) = T_T;
T(ny, 2:nx - 1) = T_B;
%Calculating Average temperature at corners
T(1,1) = (T_T + T_L)/2;
T(nx,ny) = (T_R + T_B)/2;
T(1,ny) = (T_T + T_R)/2;
T(nx,1) = (T_L + T_B)/2;
%Assigning orginal values to T
T_old = T;
T_intial = T;
T_end = T;
%Calculation of 2D steady heat conduction EQUATION by Successive over-relaxation method
k1 = 1.1*(dt/(dx^2));
k2 = 1.1*(dt/(dy^2));
Successive_over_relaxation_iteration = 1;
for k = 1:nt
error = 9e9;
while(error > tolerance)
for i = 2:nx - 1
for j = 2:ny - 1
Term_1 = 1/(1 + (2*k1) + (2*k2));
Term_2 = k1*Term_1;
Term_3 = k2*Term_1;
H = (T(i-1,j)) + (T_old(i+1,j));
V = (T(i,j+1)) + (T_old(i,j-1));
T(i,j) = (T_intial(i,j)*Term_1) + (H*Term_2) + (V*Term_3);
T_end(i,j) = ((1-omega)*T_old(i,j)) + (T(i,j)*omega);
end
end
error = max(max(abs(T_old - T)));
T_old = T_end;
Successive_over_relaxation_iteration = Successive_over_relaxation_iteration + 1;
end
T_intial = T_end;
%Plotting
figure(1)
contourf(x,y,T)
clabel(contourf(x,y,T))
colorbar
colormap(jet)
set(gca, 'ydir', 'reverse')
xlabel('X-Axis')
ylabel('Y-Axis')
title(sprintf('No. of Unsteady SOR Iterations(IMPLICIT) = %d', Successive_over_relaxation_iteration));
pause(0.03)
end
Output
EXPLICIT Scheme - Unsteady/Transient state Condition Program
Unsteady-state Equation discretization(EXPLICIT):
Explicit Scheme:
close all
clear all
clc
%Solving the Unsteady state 2D heat conduction (EXPLICIT SCHEME)
%Input Parameters
%Number of grid points
nx = 10;
ny = nx;
nt = 1400;
x = linspace(0,1,nx);
y = linspace(0,1,ny);
dx = x(2) - x(1);
dy = dx;
%Absolute error criteria > tolerance
error = 9e9;
tolerance = 1e-4;
dt = 1e-3;
omega = 1.1;
%Defining Boundary conditions
T_L = 400;
T_T = 600;
T_R = 800;
T_B = 900;
T = 300*ones(nx,ny);
T(2:ny - 1, 1) = T_L;
T(2:ny - 1, nx) = T_R;
T(1, 2:nx - 1) = T_T;
T(ny, 2:nx - 1) = T_B;
%Calculating Average temperature at corners
T(1,1) = (T_T + T_L)/2;
T(nx,ny) = (T_R + T_B)/2;
T(1,ny) = (T_T + T_R)/2;
T(nx,1) = (T_L + T_B)/2;
%Assigning orginal values to T
T_intial = T;
T_old = T;
%Calculation of 2D steady heat conduction EQUATION by Successive over-relaxation method
iterative_solver = 1;
k1 = 1.1*(dt/(dx^2));
k2 = 1.1*(dt/(dy^2));
if iterative_solver == 1
Steady_Explicit = 1;
for k = 1:nt
error = 1;
while(error > tolerance)
for i = 2:nx - 1
for j = 2:ny - 1
Term_1 = T_old(i,j);
Term_2 = k1*(T_old(i+1,j) - 2*T_old(i,j) + (T_old(i-1,j)));
Term_3 = k2*(T_old(i,j+1) - 2*T_old(i,j) + T_old(i,j-1));
T(i,j) = Term_1 + Term_2 + Term_3;
end
end
error = max(max(abs(T_old - T)));
T_old = T;
Steady_Explicit = Steady_Explicit + 1;
end
end
end
%Plotting
figure(1)
contourf(x,y,T)
clabel(contourf(x,y,T))
colorbar
colormap(jet)
set(gca, 'ydir', 'reverse')
xlabel('X-Axis')
ylabel('Y-Axis')
title(sprintf('No. of Unsteady Iterations(EXPLICIT) = %d', Steady_Explicit));
pause(0.03);
Output:
CONCLUSIONS:
From the above outputs of various methods & comparing their No. of iterations, we can conclude that
- Jacobi > Gauss-seidel > Successive over-relaxation according to the No. of iterations computed for all methods & Schemes.
- When comparing Steady state and Unsteady state, it is proven that Steady state is the most successful one as it takes least number of iterations and least time to compute.
- SOR iteration method is the most effective iteration method as it took least No. of iterations for coverging solutions in both the schemes (EXPLICIT & IMPLICIT) compared to Jacobi & Gauss-siedel.
