Finite Difference Approach for a Moving Boundary Problem

In summary, the conversation involves a person seeking help with a finite difference question related to a 1-D space and time problem. They explain their approach of using central finite difference schemes for interior nodes and a forward and backward difference for the end nodes. Another person suggests extending the grid and using boundary conditions in terms of central finite differences. The original poster discusses their boundary conditions and the equation they are trying to solve. The conversation ends with a suggestion to linearly extrapolate to find the right tip.
  • #1
member 428835
Hi PF!

I was wondering if anyone could help me with a finite difference question? The problem I am doing is a 1-D space and time problem, so ##z## (space variable, from left to right) and ##t## (time) are my independent variables and my dependent variable is ##h##, the height, governed by a PDE I don't think we need to get into. There is a moving boundary at both ends of ##z##, however.

My question is, in writing a code I am doing a central finite difference scheme for all interior nodes and then for the node on the far left I am taking a forward difference and for the node are the far right I am taking a backward difference in order to evaluate these endpoints.

Is this a legitimate approach or is there something I am missing?

Thanks so much for your input!

Josh
 
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  • #2
What is your boundary condition? You could extend your grid by adding an aditional fictitious point at each end and by imposing the boundary condition in terms of central finite differences you get the condition for the actual end points.
 
  • #3
The boundary conditions are the right tip is zero and the left is 1. I believe I understand what you're proposing; not a bad idea.

Is there anything wrong with the technique I have used though? For some reason my code isn't working and I'm troubleshooting it. I can give this technique a try, though, but is there something wrong that you can see from what I've explained?
 
  • #4
The method you described should work, I have no experience with moving boundary conditions. To maintain the accuracy probably one uses a different stencil at the boundary. This modifies the symmetry of the matrix and in case of a dedicated matrix solver you can get into trouble. You can reduce the accurary at the boundary by using a first order stencil which preserve the symmetry of the matrix.

Can you write here the equation which you try to solve?
 
  • #5
The "zero boundary condition" means ##f(z_b)=0## or ##f(z_b)\rightarrow 0## at boundary ##z_b##?
 
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  • #6
The equation is $$h_t = h_{zz} \cdot h + 2 (h_z)^2$$. There is an integral constraint that dictates the position of the left tip, and a linear solution in time and space solves this PDE, which implies the right tip is linear; thus I linearly extrapolate to find it.
 

What is a finite difference question?

A finite difference question is a mathematical problem that involves approximating the solution to a differential equation by using a finite number of discrete points. This method is often used in scientific and engineering applications to solve problems that are too complex to solve analytically.

How is a finite difference question solved?

A finite difference question is typically solved by dividing the domain of the problem into a finite grid of points. The values at each point are then used to calculate the approximate solution to the differential equation using a set of equations known as finite difference equations.

What are the advantages of using finite difference methods?

Finite difference methods are relatively simple to implement and can provide accurate solutions to complex problems. They are also computationally efficient, making them useful for solving problems with large numbers of discrete points.

What are the limitations of finite difference methods?

Finite difference methods are limited by the accuracy of the discrete points used to approximate the solution. They also require a large number of points to accurately represent complex functions, which can make them computationally intensive.

How are finite difference methods used in scientific research?

Finite difference methods are used in a wide range of scientific fields, including physics, engineering, and economics. They are often used to model and simulate complex systems, such as fluid dynamics, heat transfer, and financial markets.

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