Finite difference method to solve first-order, multivariable

In summary: W_i^{m+1}, T_i^{m+1}, and T_i^{*m+1} are also known, as they are the final values of the variables at the next time step.
  • #1
idraftscience
4
0
I'm trying to replicate the model presented in this [paper](http://www.sciencedirect.com/science/article/pii/S1359431103000474), which is basically to model heat and mass transfer along a one-dimensional duct.

There are four characteristic equations for this problem :

Momentum conservation

$$\frac{\partial Y}{\partial t} +V\frac{\partial Y}{\partial z}+\omega_1\frac{\partial W}{\partial t}=0 $$

Mass transfer:

$$ \frac{\partial W}{\partial t} + \omega_2 (Y_w - Y) = 0 $$

Energy conservation:

$$ \frac{\partial T}{\partial t} + V\frac{\partial T}{\partial z} + \omega_3\frac{\partial T^*}{\partial t} = \omega_4 (Y-Y_w) $$and Heat Transfer

$$\frac{\partial T^*}{\partial t} + \omega_5 (T^* - T) + \omega_6 (Y_w - Y) + \omega_7 (Y_w - Y)(T-T^*) = 0$$

I'm attempting to use a forward-difference approximation method, i.e.
$$ \frac{\partial Y}{\partial z} = \frac{ Y_{i+1}^m - Y_i^m }{\Delta z}$$
and so on for the other variables, where i is the spatial index in z and m is the time index. The $\omega$s and $V$ are constants.

I have initial and boundary values for all the parameters, so that leaves me needing to find $$Y_i^{m+1}, Y_{i+1}^m, W_i^{m+1}, T_i^{m+1}, T_{i+1}^m, T_i^{*m+1} $$

I have four equations and six unknowns. The paper states that an 'implicit up-wind difference form' and Gauss-Jordan elimination is used, but I can't see how my approach differs from that. I do acknowledge that my approach is an explicit method, but I believe the issue of indeterminacy remains. Am I missing something in my approach?
 
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  • #2
What are the boundary conditions for this particular problem, and why are you trying to use an explicit method? Is there a particular reason?

I don't see your explicit formulation, only a first-order approximation to the partial derivative.

Depending what information they give you, I'd think that the implicit method is the easier method to use in this case. I'm interested in what the assumptions/BCs are though.
 
  • #3
Initial conditions given are T(z,0), Y(z,0), T*(z,0), W(z,0), Yw(z,0), and boundary conditions are T(0,t) and Y(0,t). My formulation is to replace the approximation into the four equations above, and separate the parameters such that they can be represented in the form Ax=b, where x are the parameters T,Y,W, etc. So I guess I'm not sure whether that approach is explicit/implicit.

I'm trying to verify that my approach is valid, since it seems to be in order with other examples I've seen of first-order pde methods.
 
  • #4
idraftscience said:
I have initial and boundary values for all the parameters, so that leaves me needing to find $$Y_i^{m+1}, Y_{i+1}^m, W_i^{m+1}, T_i^{m+1}, T_{i+1}^m, T_i^{*m+1} $$

I have four equations and six unknowns.

[itex]Y_{i+1}^m[/itex] and [itex]T_{i+1}^m[/itex] are known: you were either given them as boundary or initial conditions, or you calculated them from the values at the previous time step.
 

1. What is the Finite Difference Method (FDM)?

The Finite Difference Method is a numerical technique used to solve differential equations by approximating the derivatives of a function at discrete points. It is widely used in various fields of science and engineering to solve problems that cannot be solved analytically.

2. How does the Finite Difference Method work?

The Finite Difference Method works by dividing the domain of a function into a finite number of points and approximating the derivatives at these points using a set of difference equations. These equations are derived from the Taylor series expansion of the function and then solved iteratively to obtain a numerical solution.

3. What are the advantages of using the Finite Difference Method?

The Finite Difference Method is a simple and easy-to-implement technique that can handle complex boundary conditions and non-linear equations. It also allows for the analysis of systems with multiple variables and can be used to model a wide range of physical phenomena.

4. What are the limitations of the Finite Difference Method?

The Finite Difference Method can suffer from numerical instability if the step size is not chosen carefully. It also requires a high number of grid points to achieve accurate results, making it computationally expensive for large systems. Additionally, it may not always provide a unique solution and can be sensitive to small changes in the boundary conditions.

5. How is the Finite Difference Method applied to solve first-order, multivariable problems?

To apply the Finite Difference Method to solve first-order, multivariable problems, the equations are discretized in both space and time. The spatial derivatives are approximated using central difference schemes, and the time derivatives are approximated using either an explicit or implicit scheme. The resulting set of equations is then solved iteratively until a solution is obtained.

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