Discretizing PDEs with Boundaries/ICs

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In summary: So if x=1, f''(x)=1. If x=-1, then f''(x)=0.In summary, the author is trying to solve a wave equation, and is using a discrete delta function.
  • #1
matematikawan
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I'm working on discretizing pde with boundary and initial conditions. The assumption of the method is that functions must be at least twice differentiable. I have an intial condition given by the following function
[tex]u(x,0)=f(x)=\left\{\begin{array}{cc}x,&\mbox{ } 0 \leq x <1\\2-x, & \mbox{ } 1 \leq x <2 \end{array}\right.[/tex]

I can calculate the first derivative as
[tex]f'(x)=\left\{\begin{array}{cc}1,&\mbox{ } 0 \leq x <1\\-1, & \mbox{ } 1 \leq x <2 \end{array}\right.[/tex]
Nevermind that the derivative at x=1 is not correct. We use discrete variable.

What about the second derivative. Is it equal to [tex]\delta (x-1) [/tex] or zero? How do we discretize a delta function?
 
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  • #2
"Must be at least twice differentiable" ... this means the second derivative must be an actual function, not a generalized function like the delta function. But to answer your question, yes the second derivative is a delta function. It's whatever you have to integrate to recover the previous derivative.
 
  • #3
Why do you differentiate the initial conditions? Simply use it as it is, which is continuous. No need for a delta functional.

Anyway, when a delta functional appears in the pde, you will have to solve it in some weak sense.
 
  • #4
g_edgar said:
"Must be at least twice differentiable" ... this means the second derivative must be an actual function, not a generalized function like the delta function. But to answer your question, yes the second derivative is a delta function. It's whatever you have to integrate to recover the previous derivative.

It's clear that f"(x) is not zero. Is it a Dirac delta function or an impulse function ? A Dirac delta function would be difficult to write a program code because it involves infinity.
https://www.physicsforums.com/showthread.php?t=309469

As you pointed out, we need to recover the previous derivative. How is this possible? As I see it (for unit impulse)
[tex]\int_0^x \delta(t-1) dt =\left\{\begin{array}{cc}0,&\mbox{ } 0 \leq x <1\\1, & \mbox{ } 1 \leq x <2 \end{array}\right.[/tex]

I do not know how to do it for Dirac delta function.
 
  • #5
defunc said:
Why do you differentiate the initial conditions? Simply use it as it is, which is continuous. No need for a delta functional.

Anyway, when a delta functional appears in the pde, you will have to solve it in some weak sense.

I'm trying to solve a simple wave equation utt=uxx. One method that I read from a paper is to use discretize iteration to approximate the solution (the paper claim the method works for Burger equation and Sine-Gordon equation)

[tex] \ddot{U}_{s+1,i} = U''_{s,i} [/tex]

I need the initial u"(x,0) to proceed.
 
  • #6
[tex]f''(x) = -2 \delta(x-1) [/tex]. Discrete delta is a box with area equal to 1, with a width that depends on the size of your step.
 

FAQ: Discretizing PDEs with Boundaries/ICs

What is the purpose of discretizing PDEs with boundaries/ICs?

The purpose of discretizing PDEs (partial differential equations) with boundaries/ICs (initial conditions) is to approximate a continuous PDE problem with a discrete set of equations. This allows for easier computation and solution of the problem using numerical methods.

How are boundaries and initial conditions incorporated into the discretized PDE equations?

Boundaries and initial conditions are incorporated into the discretized PDE equations by using finite difference methods. This involves dividing the domain into a grid and approximating the derivatives in the PDE using finite difference formulas. The boundary conditions are then applied at the edges of the grid, while the initial conditions are used to determine the values at the start of the computation.

What are some common numerical methods used for discretizing PDEs with boundaries/ICs?

Some common numerical methods used for discretizing PDEs with boundaries/ICs include finite difference methods, finite element methods, and spectral methods. Each method has its own advantages and is suitable for different types of PDE problems.

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

The choice of discretization method can greatly affect the accuracy of the solution. For example, finite difference methods can introduce truncation errors and may not accurately capture steep gradients in the solution. On the other hand, finite element methods can provide more accurate solutions by using higher-order approximations and allowing for more flexibility in the grid.

Are there any limitations to discretizing PDEs with boundaries/ICs?

Yes, there are some limitations to discretizing PDEs with boundaries/ICs. One limitation is that the discretization process introduces errors, which can affect the accuracy of the solution. Additionally, certain types of PDEs, such as nonlinear or time-dependent PDEs, may be more difficult to discretize and may require more advanced numerical methods.

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