2D PDE Solution with Neumann BC: Plot Comparison

In summary, the conversation discusses using NDSolveValueMesh to solve a 2D PDE with a Neumann boundary condition. The top plot shows the boundary condition and functional value, while the lower plot shows the directional derivative evaluated on the same boundary. This discrepancy could be due to the difference in the quantities being represented and the shape and orientation of the boundary. To improve accuracy and convergence, it is suggested to check the orientation and shape of the boundary and the numerical solution.
  • #1
member 428835
Hi PF!

I'm solving a 2D PDE using NDSolveValueMesh. On one boundary I apply a Neumann BC. Attached are two plots: the top is the boundary condition and the functional value. Notice both are exactly the same.

However, the lower plot shows a directional derivative evaluated on the same boundary. Notice the plots look nothing alike.

Why is this? They seem like they should agree much more than they do. Any ideas?
 

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  • #2


Hi there!

It's great that you're using NDSolveValueMesh to solve your 2D PDE. Neumann boundary conditions can sometimes be tricky to handle, so I can understand why you might be seeing some discrepancies in your results.

Firstly, it's important to note that a Neumann boundary condition specifies the derivative of the solution at a given boundary, rather than the solution itself. So while the top plot may show the same values for the boundary condition and the functional value, they are actually representing different quantities.

The directional derivative, on the other hand, is evaluating the change in the solution in a particular direction at the boundary. This can be affected by the shape and orientation of the boundary, as well as the behavior of the solution in that region.

Without more information about your specific problem and the boundary conditions you are using, it's difficult to pinpoint the exact reason for the discrepancies you are seeing. However, I would suggest checking the orientation and shape of your boundary, as well as the accuracy and convergence of your numerical solution.

I hope this helps! Let me know if you have any further questions or if you'd like to provide more details about your problem. Good luck with your PDE solving!
 

1. What is a 2D PDE solution?

A 2D PDE solution refers to a solution of a partial differential equation (PDE) that involves two independent variables, typically representing spatial dimensions. It is a mathematical concept used in various scientific fields, such as physics, engineering, and biology, to model and analyze systems that vary in two dimensions.

2. What is a Neumann boundary condition?

A Neumann boundary condition is a type of boundary condition used in PDEs, where the value of the derivative of the solution at the boundary is specified. In the context of a 2D PDE solution, this means that the gradient of the solution is fixed at the boundary, rather than the solution itself.

3. How is a 2D PDE solution with Neumann BC plotted?

To plot a 2D PDE solution with Neumann BC, the solution needs to be discretized into a grid of points in the two-dimensional domain. The boundary conditions are then applied to the boundary points, and the solution is solved for the interior points using numerical methods. The resulting solution values can then be plotted using a visualization tool.

4. What is the purpose of a plot comparison in 2D PDE solutions with Neumann BC?

A plot comparison in 2D PDE solutions with Neumann BC is used to compare the solutions obtained using different numerical methods or parameters. It can also be used to compare the solution to a known analytical solution, if one exists. This allows for the evaluation of the accuracy and effectiveness of the chosen method or parameters.

5. What are some common challenges in 2D PDE solutions with Neumann BC?

Some common challenges in 2D PDE solutions with Neumann BC include choosing appropriate numerical methods and parameters, ensuring accurate boundary conditions, and dealing with complex boundary geometries. Additionally, convergence issues and instability can arise in certain cases, requiring careful analysis and selection of appropriate methods to overcome these challenges.

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