# 2.3 Introduction to Finite Difference Methods

## 2.3.3 Finite Difference Method applied to 1-D Convection

In this example, we solve 1-D convection,

 $\frac{\partial U}{\partial t} + u\frac{\partial U}{\partial x} = 0,$ (2.58)

using a central difference spatial approximation with a forward Euler time integration,

 $\frac{U_ i^{n+1}-U_ i^ n}{{\Delta t}} + u_{i}^ n\delta _{2x} U^ n_{i} = 0.$ (2.59)

Note: this approximation is the Forward Time-Central Space method from Equation (2.57) with the diffusion terms removed.

Specifically, we will use a constant velocity $$u=1$$ and set the initial condition to be a Gaussian disturbance:

 $U_0(x) = 0.75e^{-\left(\frac{x-0.5}{0.1}\right)^2}.$ (2.60)

We consider the domain $$\Omega =[0.1]$$, with periodic boundary conditions. A MATLAB® script that implements this algorithm is:

% This MATLAB script solves the one-dimensional convection
% equation using a finite difference algorithm.  The
% discretization uses central differences in space and forward
% Euler in time.

clear all;
close all;

% Number of points
Nx = 50;
x = linspace(0,1,Nx+1)
dx = 1/Nx;

%velocity
u=1;

% Set final time
tfinal = 10.0;

% Set timestep
dt = 0.001;

% Set initial condition
Uo = 0.75*exp(-((x-0.5)/0.1).^2)';
t = 0;

U = Uo;

% Loop until t > tfinal
while (t < tfinal)
% Forward Euler Step
U(2:end) = U(2:end) - dt*u*centraldiff(U(2:end));
U(1) = U(end); % enforce periodicity

% Increment time
t = t + dt;

% Plot current solution
clf
plot(x,Uo,'b*');
hold on;
plot(x,U,'*','color',[0 0.5 0]);
xlabel('x','fontsize',16); ylabel('U','fontsize',16);
title(sprintf('t = %f\n',t));
axis([0, 1, -0.5, 1.5]);
grid on;
drawnow;
end


Figures 2.102.11, and 2.12 plot the finite difference solution at times $$t=0.25, t=0.5$$ and $$t=1.0$$. The exact solution for this problem has $$U(x,t) = U_0(x)$$ for any integer time $$(t=1,2, \ldots ).$$. When the numerical method is run, the Gaussian disturbance is convected across the domain, however small oscillations are observed at $$t=0.5$$ which begin to pollute the numerical solution. Eventually, these oscillations grow until the entire solution is contaminated. We will later show that the $$FTCS$$ algorithm is unstable for any $$\Delta t$$ for pure convection. Thus, what we are observing is an instability that can be predicted through some analysis. Figure 2.10: Forward Time-Central Space method for 1-D convection at $$t=0.25$$ Figure 2.11: Forward Time-Central Space method for 1-D convection at $$t=0.5$$ Figure 2.12: Forward Time-Central Space method for 1-D convection at $$t=1.0$$