I have been working on a project where I need to find a solution to the given nonlinear differential equation, see figure below:
Now, I have tried using matlabs built-in function bvp4c, but the syntax is difficult and I don't know if the results are reliable. For some values the bvp4c function only generates an error. I also have boundary conditions to take into consideration, see figures below:
I am sorry for the terrible sizes of the figures. Now I know this is not a mathforum, but I need to numerically solve this and I want to solve it with the best method available. My code as of now is seen below:
function [theta_0 y2]=flow_BVP
theta_0=linspace(0,1,1000); % pi/18
solinit2=bvpinit(theta_0,[0 1 1]);
sol2=bvp4c(@flow_ode,@flow_bc,solinit2);
x2=sol2.x;
y2=sol2.y(1,:);
hold on
%plot(x1,y1) %gammal
plot(x2,y2) %ny
%hold off
function v=flow_init(x)
v=[sin(x); 1; 1];
function dydx=flow_ode(x,y)
q=0.0005;
v=1;
dydx = [y(2); y(3); 2*q/v*y(1)*y(2)-4*y(2)];
function res=flow_bc(ya,yb)
res=[ya(1);yb(1);ya(2)-5.59];
To repeat my question, which is the best method, easiest, simplest to understand and implement to solve this? Shooting perhaps?
Best regards SimpleP.
Edit The result I have gotten so far is this
The plot shows f vs. \theta . The integral is 1, as it should be.
The generic way to incorporate the integral is to add the anti-derivative F
of f
to the ODE system. That is, as fourth component and variable
F' = f with F(0)=0, F(alpha)=1
and the other components need to be shifted one index,
function v=flow_init(x)
v=[sin(x); 1; 1; 1-cos(x)];
function dydx=flow_ode(x,y)
% y is [ f, f', f'', F ]
q=0.0005;
v=1;
dydx = [y(2); y(3); 2*q/v*y(1)*y(2)-4*y(2); y(1)];
function res=flow_bc(ya,yb)
res=[ya(1); ya(4); yb(1); yb(4)-1];
Using python:
q, v = 0.0005, 1
def flow_ode(t,u): return [ u[1], u[2], 2*q/v*u[0]*u[1]-4*u[1], u[0] ]
def flow_bc(u0, u1): return [ u0[0], u0[3], u1[0], u1[3]-1 ]
x = x_init = np.linspace(0,1,11);
u_init = [ 6*x*(1-x), 0*x, 0*x, x ]
res = solve_bvp(flow_ode, flow_bc, x_init, u_init, tol = 1e-5)
print res.message
if res.success:
x = x_sol = np.linspace(0,1,201);
u_sol = res.sol(x_sol);
plt.subplot(2,1,1)
plt.plot(x_sol, u_sol[0]); plt.plot(x, 6*x*(1-x), lw=0.5); plt.grid()
plt.subplot(2,1,2)
plt.plot(x_sol, u_sol[3]); plt.grid()
plt.show()
As one can see, the initial guess here is quite close. As the ODE is a small perturbation of 4f'+f'''=0
, the solution has to be close to its solution a+b*sin(2x)+c*cos(2x)
which with the boundary conditions evaluates to
f(x)=A * [ (1-cos(2))*sin(2*x)-sin(2)*(1-cos(2*x)) ]
= 4*A*sin(1) * sin(x)*sin(1-x)
with A
such that the integral is one.
If the parameter values in the ODE were switched, q=1
and v=0.0005
, the solution would have boundary layers of size sqrt(v/q)
.