NUMERICAL approach to NONLINEAR PDE

In summary, we have a conversation about simulating wave propagation for a nonlinear dispersive wave PDE and the difficulties in finding proper resources for handling it numerically. The PDE is in the form of utt-(au+bu2+cu3+duxx)xx=0, and the initial and boundary conditions are clamped at both ends. The suggested approach is to use finite differences, specifically central differences in time and space, and to control stability with a small enough time step. There is some discussion about which FD approach would work best for this problem, with suggestions including explicit and fully implicit methods.
  • #1
Romik
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Hi guys,

I need to simulate wave propagation for a nonlinear dispersive wave PDE and since I can't find proper resources for handling nonlinear PDEs numerically, I would appreciate any help and clues.

the PDE is in the form of
utt-(au+bu2+cu3+duxx)xx=0

Romik

Ps:
BC: Clamped at both ends
IC: u(x,0)=f, ut(x,0)=g
 
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  • #2
Romik said:
Hi guys,

I need to simulate wave propagation for a nonlinear dispersive wave PDE and since I can't find proper resources for handling nonlinear PDEs numerically, I would appreciate any help and clues.

the PDE is in the form of
utt-(au+bu2+cu3+duxx)xx=0

Romik
What are the initial and boundary conditions?
 
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  • #3
I assume that clamped at both ends means zero displacement and zero slope, correct? You need to solve the equation numerically. You can use central differences wr to time and x. You can look up finite difference approximations to the derivatives in Abramowitz and Stegun. Also, the following link presents some good numerical schemes you can use:
http://pauli.uni-muenster.de/tp/fileadmin/lehre/NumMethoden/WS1011/script1011Wave.pdf

Skip the first part where they talk about analytic methods.
 
  • #4
Thanks Chester for your reply.

yes, that means zero displacement at both ends.

finite difference (FD) is the first approach that came in mind and I searched over internet to find similar PDEs with FD, and all I found was linear wave PDE (same as your link), or nonlinear first order hyperbolic PDEs.
My question is more about nonlinear and dispersive terms in this PDE which I don't know how to treat them with this approach, or even if the FD method is the best option for this problem.
or among FD approaches which one is better for this type of problem? Central? forward? backward? Upwind? Lax-Wendroff? Crank-Nicolson?

Thanks
 
  • #5
Romik said:
Thanks Chester for your reply.

yes, that means zero displacement at both ends.

finite difference (FD) is the first approach that came in mind and I searched over internet to find similar PDEs with FD, and all I found was linear wave PDE (same as your link), or nonlinear first order hyperbolic PDEs.
My question is more about nonlinear and dispersive terms in this PDE which I don't know how to treat them with this approach, or even if the FD method is the best option for this problem.
or among FD approaches which one is better for this type of problem? Central? forward? backward? Upwind? Lax-Wendroff? Crank-Nicolson?

Thanks
This can't take more than a couple of hours to program using explicit finite differences, with central differences in time and space. For time, use the same explicit approach as linear, with (ut+Δt-2ut+ut-Δt)/(Δt)2 for the time derivative. If that doesn't stay stable, I would go directly to fully implicit at t + Δt. But I think that if you use explicit, you can control stability with a small enough time step and get what you want in a manageable amount of computation time.

Chet

Chet
 

Related to NUMERICAL approach to NONLINEAR PDE

1. What is a numerical approach to solving nonlinear PDEs?

A numerical approach to solving nonlinear PDEs involves using numerical methods and algorithms to approximate the solution of a nonlinear PDE. This allows for the solution to be computed in a discrete form, making it easier to handle computationally.

2. What are the advantages of using a numerical approach for nonlinear PDEs?

One advantage is that it allows for a wider range of PDEs to be solved, including those that do not have analytical solutions. Additionally, numerical methods can often provide more accurate and precise solutions compared to analytical methods.

3. What are some common numerical methods used for solving nonlinear PDEs?

Some common numerical methods include finite difference methods, finite element methods, and spectral methods. These methods involve discretizing the PDE and solving the resulting system of equations to approximate the solution.

4. How do you determine the accuracy of a numerical solution for a nonlinear PDE?

The accuracy of a numerical solution can be determined by comparing it to a known solution or by performing convergence analysis. Convergence analysis involves decreasing the size of the discretization and observing if the solution approaches a specific limit.

5. Are there any limitations to using a numerical approach for nonlinear PDEs?

One limitation is that the accuracy of the solution depends on the discretization used, so a fine mesh may be required for more complex PDEs. Additionally, the computational cost can be high for large-scale problems.

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