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For the slab shown, we have derived the equations of the temperature distribution on the Two dimensions to be: 2. T(x,y)-o, (sin A, xHsinh , y) Where an the coefficient of boundary conditions using Orthogonality was given by:-- 2-1 f(x)sin λxar L sinh λ W If: fx) - To.sin(x/a), where To is constant Find equations for temperature distribution, txy) and heat flux gtry your works in sequence, formula cited firs and then numerical values Units need for all answers. f the or formulas not listed, the answers EVENIE correct will have no points Page: 2 You shal show all
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Answer #1

The given temperature distribution T ( x, y ) is
  T(x,y)=\sum_{n=1}^{\infty}a_n\sin(\lambda_n x)\sinh(\lambda_n y)
And so,
\frac{\partial T}{\partial x}=\sum_{n=1}^{\infty}a_n\lambda_n\cos(\lambda_n x)\sinh(\lambda_n y)
And
  \frac{\partial^2 T}{\partial x^2}=\frac{\partial }{\partial x}\left ( \frac{\partial T}{\partial x} \right )=-\sum_{n=1}^{\infty}a_n\lambda_n^2\sin(\lambda_n x)\sinh(\lambda_n y)
And similarly
     \frac{\partial T}{\partial y}=\sum_{n=1}^{\infty}a_n\lambda_n\sin(\lambda_n x)\cosh(\lambda_n y)
And
  \frac{\partial^2 T}{\partial y^2}=\frac{\partial }{\partial y}\left ( \frac{\partial T}{\partial y} \right )=\sum_{n=1}^{\infty}a_n\lambda_n^2\sin(\lambda_n x)\sinh(\lambda_n y)
And thus we get
\frac{\partial^2 T}{\partial x^2}=-\sum_{n=1}^{\infty}a_n\lambda_n^2\sin(\lambda_n x)\sinh(\lambda_n y)=-\frac{\partial^2 T}{\partial y^2}
  \Rightarrow \frac{\partial^2 T}{\partial x^2}+\frac{\partial^2 T}{\partial y^2}=0

And the heat flux is defined as
  \vec{q}(x,y)=-k\nabla T(x,y)=-k\left ( \hat{x}\frac{\partial T}{\partial x}+\hat{y}\frac{\partial T}{\partial y} \right )
where, k is the heat conductivity. And so,
  \Rightarrow \vec{q}(x,y)=-k\left ( \hat{x}\sum_{n=1}^{\infty}a_n\lambda_n\cos(\lambda_n x)\sinh(\lambda_n y)+\hat{y}\sum_{n=1}^{\infty}a_n\lambda_n\sin(\lambda_n x)\cosh(\lambda_n y) \right )

\Rightarrow \vec{q}(x,y)=-k \sum_{n=1}^{\infty}a_n\lambda_n\left (\hat{x}\cos(\lambda_n x)\sinh(\lambda_n y)+\hat{y}\sin(\lambda_n x)\cosh(\lambda_n y) \right )

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