Application of orthogonality condition

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Homework Help Overview

The discussion revolves around the application of orthogonality conditions in the context of a transient radial heat equation, where the temperature function T depends on both radial distance r and time t. The original poster has reached a point in their solution involving a summation that includes Bessel functions and is seeking assistance in determining coefficients using orthogonality.

Discussion Character

  • Exploratory, Assumption checking

Approaches and Questions Raised

  • The original poster attempts to apply the orthogonality condition to find coefficients but encounters difficulties due to the presence of the Y_0 function in their equation. They question how to proceed with the integration given this complication.
  • Some participants suggest considering the definition of Y_0 as a limit of linear combinations of J functions, while others caution about the divergence of Y_0 at the origin and the need for careful handling of limits.
  • There is discussion about ensuring the same index for J functions to facilitate the application of the orthogonality condition.

Discussion Status

The discussion is ongoing, with participants exploring various approaches to handle the orthogonality condition. Some guidance has been offered regarding the definitions of the Bessel functions and the implications of their properties, but no consensus or resolution has been reached yet.

Contextual Notes

Participants note the challenge posed by the divergence of Y_0 at the origin and the necessity of having matching indices for the J functions to apply orthogonality effectively. The original poster is also referencing a related problem for additional context.

itisali
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Homework Statement



I have applied separation of variables to a transient radial heat equation problem.

T is a function of r and t.

I have reached the following step:

Homework Equations



<br /> <br /> T_2(t,r) = \sum_{m=1}^ \infty c_m e^{-\alpha_2\lambda_m^2t}\left(\dfrac{-Y_0(\lambda_mb)J_0(\lambda_m r)}{J_0(\lambda_mb)}+Y_0(\lambda_mr)\right)<br /> <br />

The Attempt at a Solution



I need to find c_m which is usually found using orthogonality condition. This is done by multiplying both sides with rJ_0(λ_nr) and integrating both sides with respect to r. But here in above equation I can't apply the orthogonality condition due to presence of Y_0(λ_mr) on right side of equation.

How do I apply orthogonality condition in this case?

I just want to find out the coefficient c_m and somehow get rid of the summation sign.

Please help!
 
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Have you tried using the definition of ##Y_0## as a limit of a linear combination of ##J_{\pm\alpha}##?
 
@fzero:

This doesn't work because if I put \alpha = 0 then result would become infinity.

02c38389b2a52132a588e3def4871872.png
 
itisali said:
@fzero:

This doesn't work because if I put \alpha = 0 then result would become infinity.

02c38389b2a52132a588e3def4871872.png

##Y_\alpha(x)## diverges at the origin, but the functions are finite elsewhere. The limit in the definition is an indeterminate form and care must be taken when computing it. However, this expression can be taken as a definition of ##Y_\alpha(x)## and should be useful for your computation.

You should perform the integration before taking the limit. The resulting limit should involve fairly simple functions.
 
fzero said:
##Y_\alpha(x)## diverges at the origin, but the functions are finite elsewhere. The limit in the definition is an indeterminate form and care must be taken when computing it. However, this expression can be taken as a definition of ##Y_\alpha(x)## and should be useful for your computation.

You should perform the integration before taking the limit. The resulting limit should involve fairly simple functions.

Before I integrate, I should have same index for J, i.e. \alpha should be there in both J's. Only that way I can apply orthogonality condition.

Please help.
 
itisali said:
Before I integrate, I should have same index for J, i.e. \alpha should be there in both J's. Only that way I can apply orthogonality condition.

Please help.


I see, I was hoping that there was an appropriate integral formula to use there. I haven't been able to find a directly useful formula from tables, but I think that the definition of ##Y_\nu(x)## should be a clue. The whole point of defining the Bessel function of the 2nd kind is that for integer order, ##J_{\pm \nu}## are not linearly independent. So ##Y_\nu## is defined to be linearly independent to the ##J_\nu## for integral ##\nu##. Since ##J_0## and ##Y_0## have no common zeros, I believe the integrals you end up with should vanish. I haven't been able to prove this though, sorry.
 

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