Solving PDE by using another function

In summary, the equation can be homogenized by replacing the boundary conditions equation with a new function $v$ that satisfies $u(x,t)=v(x,t)-\dfrac A{c^2}e^{-x}$.
  • #1
Markov2
149
0
Solve

$\begin{aligned} & {{u}_{tt}}={{c}^{2}}{{u}_{xx}}+A{{e}^{-x}},\text{ }0<x<L,\text{ }t>0, \\
& u(0,t)=B,\text{ }u(L,t)=M,\text{ }t>0, \\
& u(x,0)=0={{u}_{t}}(x,0),\text{ 0}<x<L.
\end{aligned}
$

What do I need to do first? Homogenize the first boundary conditions? Or first making the equation homogeneous? What's the shorter way?
 
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  • #2
First, introduce a new variable $v(t,x)$ such that $u(t,x) = v(t,x) + ax + b$ and choose $a$ and $b$ such that

$u(0,t)=B$ becomes $v(0,t) = 0$

and

$u(L,t)=M$ becomes $v(L,t) = 0$.

Then see how the PDE and IC's change.
 
  • #3
Okay you mean take $w(x,t)=u(x,t)-v(x,t)$ where $v(x,t)=B-(B-M)\dfrac xL,$ then $w(x,t)$ satisfies the first boundary conditions, is this the procedure?
 
  • #4
Next, to solve the homogenous problem

$w_{tt} = c^2 w_{xx}$

$w(0,t) = 0, w(L,t) = 0$

you would use separation of variables leading to

$u = \displaystyle\sum_{n=1}^{\infty} b_n \sin \dfrac{c n \pi}{L}t \sin \dfrac{n\pi}{L}x$.

However, since the new PDE is nonhomogeneous, you'll need to expand the source term (the exponential) in terms of a Fourier sine series and then seek a solution of the form

u = $\displaystyle\sum_{n=1}^{\infty} T_n(t) \sin \dfrac{n\pi}{L}x$.

See where that takes you.
 
  • #5
Okay, it looks a bit messy from there. I homogenized first the equation, so I let $v(x,t)=u(x,t)+\dfrac{A{{e}^{-x}}}{{{c}^{2}}}$ so that $u(x,t)=v(x,t)-\dfrac A{c^2}e^{-x}$ then $u_{tt}=v_{tt}$ and $u_x=v_x+\dfrac A{c^2}e^{-x}$ and $u_{xx}=v_{xx}-\dfrac A{c^2}e^{-x}$ so replacing this to the ODE I get $v_{tt}=c^2\left(v_{xx}-\dfrac A{c^2}e^{-x}\right)+Ae^{-x}=c^2v_{xx}.$ Now the boundaries are $u(0,t)=v(0,t)-\dfrac A{c^2}=B$ so $v(0,t)=B+\dfrac A{c^2}$ and $u(L,t)=v(L,t)-\dfrac A{c^2}e^{-L}=M$ so $v(L,t)=M+\dfrac A{c^2}e^{-L}$ and finally $u(x,0)=v(x,0)-\dfrac A{c^2}e^{-x}=0\implies v(x,0)=\dfrac A{c^2}e^{-x}$ and $u_t(x,0)=v_t(x,0)$ so the new equation equals:

$\begin{aligned} & {{v}_{tt}}={{c}^{2}}{{v}_{xx}} \\
& v(0,t)=B+\frac{A}{{{c}^{2}}},\text{ }v(L,t)=M+\frac{A}{{{c}^{2}}}{{e}^{-L}} \\
& v(x,0)=\frac{A}{{{c}^{2}}}{{e}^{-x}},\text{ }{{v}_{t}}(x,0)=0.
\end{aligned}
$

Do I need to define another function to homogenize boundary conditions? I'm worry about this since the $v(x,0)$ condition is not zero, how to proceed? Am I on the right track?
 
  • #6
I managed to get it. I was drowning myself on a glass of water, I hadn't checked my notes. Thanks for the help anyway!
 

FAQ: Solving PDE by using another function

What is the concept of solving PDE by using another function?

Solving PDE by using another function involves using a different function to represent the solution to a partial differential equation (PDE). This approach can simplify the process of solving PDEs and provide more insight into the problem at hand.

Why is solving PDE by using another function useful?

Using another function to solve PDEs can make the process more efficient and can provide a deeper understanding of the underlying problem. It can also help in finding solutions to complex PDEs that may be difficult to solve using traditional methods.

What are some common functions used to solve PDEs?

Some common functions used to solve PDEs include Fourier series, Laplace transforms, and separation of variables. These functions can help in solving various types of PDEs, such as elliptic, parabolic, and hyperbolic equations.

How does using another function change the approach to solving PDEs?

Using another function to solve PDEs often involves transforming the original equation into a simpler form, which can then be solved using techniques from calculus or linear algebra. This approach can provide a more intuitive understanding of the solution and can also lead to more efficient computational methods.

Are there any limitations to solving PDEs by using another function?

While using another function can be a powerful tool for solving PDEs, it may not always be applicable or feasible. In some cases, the transformation may not be possible or may lead to a more complex equation. Additionally, the choice of function may also affect the accuracy of the solution.

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