Discretization for a fourth-order PDE (and solution)

In summary, the conversation discusses solving a PDE for an L x L plate with boundary conditions and using substitutions to solve the problem. The person asks for advice on solving the problem without using substitutions and discusses their attempt at implementing second order boundary conditions. The conversation ends with a suggestion to try a different algorithm, specifically Gauss-Seidel SOR, to solve the equation.
  • #1
maistral
240
17
Hi. I have this PDE that governs an L x L plate (similar to the Poisson equation, it seems)

313ppgz.png


with boundary conditions F = 0 and F" = 0 along the edges. I have successfully solved the problem by setting up an equality W = ∇2F then I solved the two PDEs simultaneously:
W = ∇2F (boundary condition F = 0 along the edges)
φ = ∇2W (boundary condition W = 0 along the edges since W = F").

Simple discretization using second order derivatives followed, then poof. Answer.

What I would like to know is how to solve this without using substitutions (I mean, directly attacking the differentials using fourth-order finite differences). What I did is I took the second order derivative of the second-order finite differences with respect to the same variables (for the non-mixed derivative) and the other variable (for the mixed derivative).

My problem is coming from the boundary conditions. The boundary F = 0 is a no-brainer. The problem is how should I implement the second order boundary condition F" = 0. Does anyone have an idea on how to execute this properly?

What I did is that I tried using the second order three-point formula for the second derivative using double the steps then equated it to zero, then applied the resulting formula to the ghost points formed outside the boundary. ie.
(F(x+2Δx,y) - 2F(x,y) + F(x-2Δx,y)) / (2Δx)2 = 0 say, for points beside the right border then I solved for the ghost point F(x+2Δx,y). I applied the same to the points beside the top, bottom, and left borders.

And, this happened:

mts32h.png


:DD:DD:DD:DD

How should I implement the second order condition? I hope for any kind and generous response. Thanks!
 
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  • #2
Perhaps the algorithm is unstable. You could try with the Von Neumann stability analysis to see if the problem is in the scheme. However, the instability could be due to the boundary conditions. I think what you did is fine, but the problem is in the algorithm (of course this is under the assumption that you have made no coding mistakes). You should look for a stable algorithm to solve this equation, if that is actually the problem that makes everything blow up.

https://en.wikipedia.org/wiki/Von_Neumann_stability_analysis
 
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  • #3
Yeah, apparently the algorithm is unstable. A simple adjustment to Gauss-Seidel SOR made it work.

Thanks!
 
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Likes Telemachus

FAQ: Discretization for a fourth-order PDE (and solution)

What is discretization for a fourth-order PDE?

Discretization is a numerical method used to approximate the solution of a fourth-order partial differential equation (PDE). It involves breaking down the continuous problem into a set of discrete equations that can be solved using numerical techniques.

Why is discretization necessary for solving fourth-order PDEs?

Fourth-order PDEs are difficult to solve analytically, so discretization is necessary in order to obtain a numerical solution. It allows us to approximate the continuous problem with a finite number of discrete points, making it easier to solve using computational methods.

What are the different types of discretization methods for fourth-order PDEs?

There are several types of discretization methods, including finite differences, finite elements, and spectral methods. Each method has its own advantages and limitations, and the choice of method depends on the specific problem being solved.

What are the challenges of discretizing a fourth-order PDE?

Discretization of fourth-order PDEs can be challenging due to the high order of the equation and the presence of mixed derivatives. This can lead to issues such as numerical instability, convergence problems, and difficulty in accurately representing the solution.

How can one verify the accuracy of a solution obtained through discretization?

One way to verify the accuracy of a solution is to compare it with an analytical solution, if available. Additionally, one can perform grid refinement studies by using finer and finer discretization grids and checking for convergence. Other methods such as error analysis can also be used to assess the accuracy of the solution.

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