# Tag Info

8

It's easy to derive that equation from Fick's law. You have this diffusion equation as: $$\frac{\partial C}{\partial t} = D \nabla^{2} C$$ The mean square displacement weighted by the concentration profile is defined as: $$\langle r^{2}(t) \rangle = \int_{\Omega} |\vec{r}|^{2} C(\vec{r},t) d^{3} \vec{r}$$ The time-evolution of this mean square ...

5

You are starting from a uniform temperature and you have insulated boundary conditions; so there is no heat conduction occurring. Likewise, your initial mole fraction is also constant in $x$ so that the heat input is uniform along the length. So the fact that the temperature and mole fraction don't change as a function of $x$ is exactly what you should ...

5

Yes, the problem with mixed boundary conditions is well posed. What's not clear to me is this: Why do you approximate the derivative via the two-sides approximation? Shouldn't it be enough to just the following? $$\frac{f_6 - f_{6-\Delta x}}{\Delta x} = 0.$$ In your animations, what is the size of $\Delta x$? Your curve looks very smooth, which can be ...

2

It seems still you don't specify your boundary conditions explicitly despite the suggestion given in one of your previous questions. As far as I understand from your MATLAB code, your boundary conditions don't make sense at all. You have two Neumann boundary conditions at the left and right sides of your 1D domain: -D\frac{\partial C}{\partial x}|_{x=0} = ...

1

What you find is indeed correct. It is known that positivity is lost if very small time steps are chosen, see https://doi.org/10.1515/cmam-2015-0018 This loss of positivity happens even for semi-discrete scheme. The analysis for 1-d case is given in section 6 of this paper.

1

Take the first expression and start to reduce the $x$ values to $x_i$, \begin{align} \frac{u_{i+1}^n - u_i^n}{x_{i+\frac{1}{2}}} - \frac{u_i^n - u_{i-1}^n}{x_{i-\frac{1}{2}}} &= \frac{(x_i-\frac12Δx)(u_{i+1}^n - u_i^n) - (x_i+\frac12Δx)(u_i^n - u_{i-1}^n)}{x_{i-\frac{1}{2}}x_{i+\frac{1}{2}}} \\ &=\frac{x_i}{x_i^2-\frac14Δx^2}(u_{i+1}^n - 2u_i^n + u_{...

1

Problem well posed Your problem is well posed. On the discretization with Crank-Nicholson I am not familiar with MMS, and I wonder how you got that ungeneralised form of the diffusion equation. Anyways, as I understand it, you are using the Crank-Nicholson method to discretize the following differential equation: \$\frac{\partial f}{\partial t} = x^2 \...

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