Partial Differential Equation using separation of variables

In summary, the problem at hand involves solving a heat flow problem using the method of separation of variables. The given partial differential equation, boundary conditions, and initial conditions are stated. The attempt at a solution involves separating the variables and applying the boundary conditions, but there is difficulty in applying the piecewise initial condition. To solve this, one must find the Fourier cosine coefficients by integrating from 0 to L/4, L/4 to 3L/4, and 3L/4 to L, and then use the whole interval to determine the normalization constant.
  • #1
Hendrick
43
0

Homework Statement


Solve the heat flow problem using the method of separation of variables:


Homework Equations


PDE:[tex]\frac{\partial u}{\partial t}=k\frac{\partial^{2} u}{\partial t^{2}}[/tex]
for 0<x<L, 0<t<[tex]\infty[/tex]

BC's:[tex]\frac{\partial u}{\partial x}(0,t)=0,\frac{\partial u}{\partial x}(L,t)=0[/tex]
for 0<t<[tex]\infty[/tex]

IC's: [tex]u(x,0)=[/tex]
{0, [tex]0<x<L/4[/tex]
{1, [tex]L/4<x<3L/4[/tex]
{0, [tex]3L/4<x<L[/tex]
(Piecewise IC)

The Attempt at a Solution


I have separated the variables, then applied the boundary conditions. I am stuck on applying the initial conditions.

I have come up with a general product solution of [tex]u_{n}=F_{n}cos(\frac{n \pi x}{L}) e^{-k(\frac{n \pi x}{L})^{2}t}[/tex]

Trying to combine all product solutions and match the initial data:
[tex]u(x,0)=f(x)[/tex]
[tex]\sum^{\infty}_{n=1}u_{n}(x,0)=f(x)[/tex]
[tex]\sum^{\infty}_{n=1}F_{n}cos(\frac{n \pi x}{L})=f(x)[/tex]


I don't know how to apply the piecewise initial condition, any help would be appreciated. Thank you
 
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  • #2
Once you have
[tex]\sum^{\infty}_{n=1}F_{n}cos(\frac{n \pi x}{L})=f(x)[/tex]
you do it exactly the same way you would if f were not "piecewise". Find the Fourier cosine coefficients by doing the appropriate integrals for C0 and Cn for n> 0. The only difference "piecewise" makes is that instead of integrating a single formula from 0 to L, you integrate using the given formulas from 0 to L/4, L/4 to 3L/4, 3L/4 to L and adding those integrals. (Which I notice now is just integrating from L/4 to 3L/4 since outside that the function is 0. The difference between this and just doing the problem on the interval from L/4 to 3L/4 is that you use the whole interval, of length L in determining the "normalization" constant.)
 

What is a partial differential equation?

A partial differential equation (PDE) is a mathematical equation that involves multiple variables and their partial derivatives. It describes the relationship between an unknown function and its partial derivatives with respect to the independent variables.

What is separation of variables?

Separation of variables is a method used to solve partial differential equations by separating the dependent variables into simpler functions of individual independent variables. This allows the PDE to be broken down into a series of ordinary differential equations that are easier to solve.

When is separation of variables used?

Separation of variables is typically used to solve PDEs that are linear and homogeneous, meaning they can be written as a linear combination of the unknown function and its partial derivatives. It is also used when the boundary conditions are specified at different points in the domain of the PDE.

What are the steps of separation of variables?

The steps of separation of variables include: 1) identifying the dependent and independent variables, 2) writing the PDE in terms of these variables, 3) separating the variables by assuming that the solution is a product of simpler functions, 4) substituting the separated variables into the PDE, 5) solving the resulting ordinary differential equations, and 6) combining the solutions to obtain the general solution of the PDE.

What are some applications of partial differential equations and separation of variables?

Partial differential equations and separation of variables are used in many fields of science and engineering, including physics, chemistry, biology, economics, and engineering. They are used to model and understand complex systems and phenomena, such as heat transfer, fluid dynamics, electromagnetic fields, and quantum mechanics.

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