Fourier decomposition and heat equation

In summary, the conversation discusses finding a formula for computing initial coefficients in the heat equation, given an initial temperature distribution. It suggests using Fourier decomposition and taking into account the orthogonal nature of the eigenfunctions in order to simplify the equation and obtain a function of the initial coefficients.
  • #1
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Homework Statement



In the heat equation, we have $T(t,x)=sum of a_k(t)b_k(x)$.
Now I want to find a formula for computing the initial coefficients $a_k(0)$ given the initial temperature distribution $f(x)$.

Homework Equations


We know that in a heat equation , $f(0)=0$, $f(1)=0$



The Attempt at a Solution


Using Fourier decomposition, we know $f(x)=T(0,x)=a_1(0)b_1(x)+a_2(0)b_2(x)+...+a_k(0)b_k(x)$, and b_k(x) are
orthonormal, but then I don't know how to simplify this equation to get a function of $a_k(0)$
 
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  • #2
conisider inetgrating something like f(x)sin(kx) taking into account the orthogonal nature of the eigenfunctions
 

1. What is Fourier decomposition and how is it related to the heat equation?

Fourier decomposition is a mathematical technique used to decompose a complex function into simpler sine and cosine functions. It is closely related to the heat equation, which is a partial differential equation that describes the flow of heat through a given medium. The solution to the heat equation can be expressed as a sum of these simpler sine and cosine functions, making Fourier decomposition a useful tool in solving the heat equation.

2. How does Fourier decomposition help in understanding heat transfer?

Fourier decomposition allows us to break down a complex heat transfer process into simpler components, making it easier to analyze and understand. By decomposing the heat equation, we can identify the individual contributions of each sine and cosine function to the overall heat transfer process.

3. Can Fourier decomposition be used for non-linear heat equations?

No, Fourier decomposition is only applicable to linear partial differential equations, such as the heat equation. Non-linear heat equations involve terms that cannot be expressed as a sum of sine and cosine functions, making Fourier decomposition unsuitable for these types of equations.

4. How does the number of terms in a Fourier series affect the accuracy of the solution?

The more terms included in the Fourier series, the more accurate the solution will be. However, including too many terms can also lead to overfitting, where the solution becomes overly complex and no longer accurately represents the original function. Therefore, it is important to strike a balance between accuracy and simplicity when choosing the number of terms in a Fourier series.

5. Are there any limitations to using Fourier decomposition for solving the heat equation?

Yes, there are several limitations to using Fourier decomposition. As mentioned before, it can only be used for linear partial differential equations. Additionally, it assumes that the medium is homogeneous and isotropic, meaning that its properties do not vary with location or direction. In reality, many materials have varying properties and therefore Fourier decomposition may not provide an accurate solution for these cases.

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