Numerical solution to the second order wave equation

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Homework Help Overview

The discussion revolves around the numerical solution of the second order wave equation, specifically the equation u_{tt} = 4u_{xx}. The original poster is attempting to rewrite this equation as a system of first order equations and is exploring the use of the Crank-Nicolson method for solving it.

Discussion Character

  • Exploratory, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • The original poster rewrites the wave equation as a system of first order equations but expresses difficulty in decoupling the system due to the presence of a term involving u. Other participants engage by confirming the nature of the transformation matrix T as a matrix of eigenvectors and offer to share their past experiences with similar methods.

Discussion Status

The discussion is ongoing, with participants providing insights and sharing resources. The original poster has received confirmation about the transformation matrix and is awaiting further guidance from others who have experience with similar problems.

Contextual Notes

The original poster mentions initial and boundary conditions but indicates they are not the primary focus at this stage. There is a suggestion of potential copyright issues regarding shared resources, which may affect the discussion's direction.

tjackson3
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Homework Statement


Consider the second order wave equation

[tex]u_{tt} = 4u_{xx}[/tex]

There are initial and boundary conditions attached, but I'm less concerned with those for the moment. I think I can figure those out if I can figure out where to get started.

Rewrite this as a system of first order equations of the form [itex]\mathbf{u}_t = A\mathbf{u}_x + B\mathbf{u}[/itex] where [itex]\mathbf{u} = (u,u_t,u_x)^T[/itex] and solve using the Crank-Nicolson method.

Homework Equations



The Crank-Nicolson method (which is implicit) is given by

[tex]u_j^{n+1} - (1/4)\lambda(u_{j+1}^{n+1} - u_{j-1}^{1}) = u_j^n + (1/4)\lambda(u_{j+1}^n - j_{j-1}^n[/tex]

The Attempt at a Solution



The first thing I did was to rewrite the equation as a system, as instructed. This came out to be

[tex]\left[\begin{array}{c}u \\ u_t \\ u_x\end{array}\right]_t = \left[\begin{array}{ccc}0 & 0 &0\\ 0&0&4\\ 0&1&0\end{array}\right]\left[\begin{array}{c}u\\ u_t \\ u_x\end{array}\right]_x + \left[\begin{array}{ccc}0 & 1 &0\\ 0&0&0\\ 0&0&0\end{array}\right]\left[\begin{array}{c}u\\ u_t \\ u_x\end{array}\right][/tex]

I feel stuck from here, though. Typically when you deal with systems of equations in PDEs, you decouple the system by diagonalizing it. This was the suggested step even in this case, in one of the books I found. You write [itex]A = T^{-1}\Lambda T[/itex] and premultiply by T to get

[tex]T\mathbf{u}_t = \Lambda T\mathbf{u}_x + TB\mathbf{u}[/tex]

In theory, then, you can make a change of variables [itex]w = Tu[/itex] to get a completely decoupled system. In this case, however, the presence of that u term makes it impossible to completely decouple. After computing T, I ended up with this system:

[tex]\mathbf{v}_t = \left[\begin{array}{ccc}-2 & 0 &0\\ 0&2&0\\ 0&0&0\end{array}\right]\mathbf{v}_x + \left[\begin{array}{ccc}0 & 0 &0\\ 0&-2&0\\ 0&1&0\end{array}\right]\mathbf{u}[/tex]

I'm not sure where to go from here, since I can't even eliminate u. Does anyone have any experience with this? Thanks!

edit: forgot to include u at the end
 
Last edited:
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Is the transformation matrix T a matrix of eigenvectors?
 
Yes, T is a matrix of eigenvectors with [itex]\Lambda[/itex] the corresponding diagonal matrix of eigenvalues
 
I'll post, step by step, how I used this method for a heat conduction problem a number of years ago. First I'll try photographing it from a journal article. If that is illegible, I'll type it out. Equation will be first order in time. I'll post within 2 hours.
 
Awesome, thank you!
 
Here are some pictures of pages from something that belongs to me so there are no copyright issues. I'm not a lawyer. Method is same as was used in journal article I cited above. Hope this helps you out.
 

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That was very helpful. Thank you again!
 

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