The diffusion equationsɎ2t + qg= (1/α) (d t/d r)Governs the...
In unsteady state condition, there is no internal heat generation.
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The diffusion equationsɎ2t + qg= (1/α) (d t/d r)Governs the...
The diffusion equation is commonly written as:
∂u/∂t = D∇²u
where u is the concentration or density of the diffusing species, t is time, D is the diffusion coefficient, and ∇² is the Laplacian operator.
To solve this equation for a one-dimensional case (assuming u is only a function of position x), we can rewrite it as:
∂u/∂t = D∂²u/∂x²
where ∂²u/∂x² represents the second derivative of u with respect to x.
To solve this equation numerically, we can use a finite difference method. We divide the spatial domain into a grid of points, with each point representing a discrete location. We can then approximate the second derivative using finite difference approximations.
For example, using the central difference approximation, we can write the equation as:
∂u/∂t ≈ D(u(x+Δx, t) - 2u(x, t) + u(x-Δx, t))/Δx²
where Δx is the spacing between grid points.
We can discretize the time domain as well, using a time step Δt. Using an explicit finite difference scheme, we can update the concentration at each grid point at each time step using the above equation:
u(x, t+Δt) = u(x, t) + (DΔt/Δx²)(u(x+Δx, t) - 2u(x, t) + u(x-Δx, t))
This equation allows us to simulate the diffusion of a species over time in a one-dimensional system. However, it should be noted that this is a simplified version and there may be additional terms or considerations depending on the specific problem being studied.