Partial differential equation discretization. HELP D:

In summary, the conversation discusses the concept of discretization in solving partial differential equations, specifically in regards to the equation ∂2u/(∂x∂y). The individual asking the questions is self-studying PDEs and is unsure about the correct method of discretization. The conversation also mentions the potential impact of varying values of μ on the accuracy of the approximation.
  • #1
maistral
240
17
So figuratively, I'm trying to win a nuclear war with a stick. :smile: I did not take any course in PDEs, I just self-studied some of them, and now I'm toast. :smile:

First, please feel free to hurl rocks at me if my simplification is incorrect:

https://fbcdn-sphotos-g-a.akamaihd.net/hphotos-ak-prn2/t1/q71/1545789_719161698116788_1463986171_n.jpg

Second, how do you discretize ∂2u/(∂x∂y)? Is it:

(ux+1,y - 2ux,y + ux-1,y)(ux,y+1 - 2ux,y + ux,y-1)/((xi+1 - xi)(yi+1 - yi))

I might have a few more questions after this. Sorry if everything I'm saying is incorrect, please don't be harsh. I'm telling the truth when I say that we didn't cover this in our numerical methods class and I didn't take a PDE course. Thanks!
 
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  • #2
First:
Your equations looks right as long as [itex] \mu [/itex] does not depend on x…
(If [itex] \mu [/itex] does depend on x, they might still be a decent approximation if [itex] \mu [/itex] does not vary much, but I don't know what problem you are working on... )

Second:

Last section of: http://en.wikipedia.org/wiki/Finite_difference . ;)

I don't have any PDE courses either, so not sure exactly how to derive it. I think you can derive it straight from the definiton of the taylor series of a function of two variables and dropping higher order terms :)
 
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FAQ: Partial differential equation discretization. HELP D:

What is the purpose of discretizing a partial differential equation (PDE)?

Discretizing a PDE involves converting a continuous problem into a discrete problem by dividing the domain into a finite number of smaller elements. This allows for numerical methods to be used to approximate the solution of the original PDE, which may not have an analytical solution.

What are the different methods of discretization for PDEs?

The most commonly used methods for discretizing PDEs are finite difference, finite element, and finite volume methods. Each method has its own advantages and is suitable for different types of PDEs and boundary conditions.

How does the choice of discretization method affect the accuracy of the solution?

The choice of discretization method can significantly impact the accuracy of the solution. Finite difference methods tend to be more accurate for problems with smooth solutions, while finite element methods are better suited for problems with complex geometries and discontinuous solutions.

What is the role of the discretization size in solving PDEs?

The discretization size, also known as the mesh size, is the size of the elements used in the discretization process. A smaller mesh size can lead to a more accurate solution, but it also increases the computational cost. Therefore, the discretization size must be chosen carefully to balance accuracy and efficiency.

How can one validate the accuracy of a discretized solution to a PDE?

There are several methods for validating the accuracy of a discretized solution, such as comparing it to an analytical solution (if available), using convergence analysis to check for convergence as the mesh size decreases, and performing sensitivity analysis to see how changes in the input parameters affect the solution.

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