Finite Difference Discretization of a Fourth Order Partial Differential Term

In summary, a common choice for a finite-difference discretization of the partial differential term \frac{\partial^4\phi}{\partial x^2\partial y^2} would be a formulation using bivariate terms, such as u(x-1,y+1), to create a solvable matrix. However, it is also possible to use unscaled terms or a higher order expansion, depending on the situation.
  • #1
Hypatio
151
1
What is a finite-difference discretization for the partial differential term:

[tex]\frac{\partial^4\phi}{\partial x^2\partial y^2}[/tex]

Thanks in advance.
 
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  • #2
There are as usual an infinite number, the choice of which depends upon the situation. A common choice would be
u(x-1,y+1) -2u(x+0,y+1) +u(x+1,y+1)
-2u(x-1,y+0) +4u(x+0,y+0) -2u(x+1,y+0)
+u(x-1,y-1) -2u(x+0,y-1) +u(x+1,y-1)
 
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  • #3
lurflurf said:
There are as usual an infinite number, the choice of which depends upon the situation. A common choice would be
u(x-1,y+1) -2u(x+0,y+1) u(x+1,y+1)
-2u(x-1,y+0) +4u(x+0,y+0) -2u(x+1,y+0)
u(x-1,y-1) -2u(x+0,y-1) u(x+1,y-1)

Thanks, but is there a formulation which does not use bivariate (?) terms? eg. 2u(x+0,y+1)*u(x+1,y+1)

I do not understand how it is possible to create a solvable matrix with a mix of bivariate terms in it, which is what I am trying to to do (stress function solution using gaussian elimination).
 
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  • #4
^Sorry that was implied addition not implied multiplication. Writen out in full we have
16uxxyy~u(x-1,y+1)-2u(x+0,y+1)+u(x+1,y+1)-2u(x-1,y+0)+4u(x+0,y+0)-2u(x+1,y+0)+u(x-1,y-1) -2u(x+0,y-1) +u(x+1,y-1)

or unscaled

(4st)2 uxxyy~u(x-s,y+t)-2u(x+0,y+t)+u(x+s,y+t)-2u(x-s,y+0)+4u(x+0,y+t)-2u(x+s,y+0)+u(x-s,y-t) -2u(x+0,y-t) +u(x+s,y-t)

A higher order or biased expansion could be used if needed.
 
  • #5
Ah, thank you for alleviating my fears, and for the help.
 

What is a fourth order partial differential term?

A fourth order partial differential term is a mathematical expression that includes fourth-order derivatives of a function with respect to one or more independent variables. It is commonly used in physics and engineering to model complex phenomena such as fluid flow, heat transfer, and structural mechanics.

Why is finite difference discretization used for fourth order partial differential terms?

Finite difference discretization is used to approximate the solutions of partial differential equations on a discrete grid of points. This approach is particularly useful for fourth order terms, as it allows for efficient and accurate computation of the derivatives needed to solve the equation.

What are the steps involved in discretizing a fourth order partial differential term using finite differences?

The first step is to define a grid of points in the domain on which the partial differential equation is to be solved. Next, the fourth order term is approximated using finite difference formulas, typically involving a combination of forward, backward, and central differences. Finally, the resulting discretized equation is solved using numerical methods.

What are the main advantages of using finite difference discretization for fourth order partial differential terms?

Finite difference discretization offers several advantages, including ease of implementation, flexibility in handling complex boundary conditions, and the ability to handle a wide range of problem domains. It also allows for efficient computation of derivatives, which is particularly important for fourth order terms.

Are there any limitations to using finite difference discretization for fourth order partial differential terms?

While finite difference discretization is a powerful and widely used method for solving partial differential equations, it does have some limitations. These include difficulties in handling irregular or non-uniform grids, as well as potential accuracy issues for problems with rapidly varying solutions.

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