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For the following hyperbolic equation of conservation:

$$\frac{\partial f}{\partial t}+\frac{\partial G(f)}{\partial x}=0$$

I need your help to understand how we derive the following scheme so-called $S^{\alpha}_{\beta}$ \begin{aligned} & \tilde{f}_{i}=(1-\beta) f_{i}^{n}+\beta f_{i+1}^{n}-\alpha \frac{\Delta t}{\Delta x}\left(G_{i+1}^{n}-G_{i}^{n}\right) \\ & f_{i}^{n+1}=f_{i}^{n}-\frac{\Delta t}{2 \alpha \Delta x}\left[(\alpha-\beta) G_{i+1}^{n}+(2 \beta-1) G_{i}^{n} + (1-\alpha-\beta) G_{i-1}^{n}+\tilde{G}_{i}-\tilde{G}_{i-1}\right] \end{aligned} where $\tilde{G}_{i} = G( \tilde{f}_{i})$. Also, I need to know how we can calculate the amplification matrix, the modified equation, and how we could find optimal values of $\alpha$ and $\beta$ to get a better approximation. Any readings, insights, examples, are most welcome. Thanks for your help.

EditPiAf
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1 Answers1

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This is a predictor-corrector scheme of a similar kind than the Richtmyer and MacCormack methods (see this article and references therein). Note that if $\alpha = 1$ and $\beta = 0$, then \begin{aligned} \tilde{f}_{i} &= f_{i}^{n}-\tfrac{\Delta t}{\Delta x}\left(G_{i+1}^{n}-G_{i}^{n}\right) \\ f_{i}^{n+1} &=f_{i}^{n}-\tfrac{\Delta t}{2 \Delta x}\big[ G_{i+1}^{n}- G_{i}^{n} +\tilde{G}_{i}-\tilde{G}_{i-1}\big] \\ &= \tfrac12( f_{i}^{n} + \tilde f_i ) -\tfrac{\Delta t}{2 \Delta x}\big[ \tilde{G}_{i}-\tilde{G}_{i-1}\big] \end{aligned} gives exactly the MacCormack method. If $\alpha = 1$ and $\beta= \frac12$, then \begin{aligned} \tilde{f}_{i} &= \tfrac12(f_{i}^{n} + f_{i+1}^{n})-\tfrac{\Delta t}{\Delta x}\left(G_{i+1}^{n}-G_{i}^{n}\right)\\ f_{i}^{n+1} &=f_{i}^{n}-\tfrac{\Delta t}{2 \Delta x}\big[\tfrac12 G_{i+1}^{n}- \tfrac12 G_{i-1}^{n} +\tilde{G}_{i}-\tilde{G}_{i-1}\big] \\ &= \tfrac12\left( f_{i}^{n} -\tfrac{\Delta t}{2 \Delta x}\big[ G_{i+1}^{n}- G_{i-1}^{n}\big] + f_{i}^{n} -\tfrac{\Delta t}{\Delta x}\big[\tilde G_{i+1}- \tilde G_{i}\big] \right) \end{aligned} gives an average of the Richtmyer and explicit centered methods. Therefore, the present method is a variation of these methods, with linear averages and weighted extrapolations.

Now, consider the case where $G(f) = af$ is linear with slope $a>0$. We find by substitution that $$ f_i^{n+1} = f_i^n - \frac{a \Delta t}{2 \Delta x} \left( f_{i+1}^n - f_{i-1}^n\right) + \frac{a^2 \Delta t^2}{2\alpha \Delta x^2}(f_{i+1}^n - 2f_{i}^n + f_{i-1}^n) \, . $$ A general centered time-stepping formula is recovered, where the numerical viscosity term (second-order centered spatial difference) is divided by $\alpha$. If $\alpha = 1$, $a \, {\Delta t}/{\Delta x}$ or $a^2$, then the Lax-Wendroff, upwind scheme and Lax-Friedrichs methods are obtained, respectivelly.

EditPiAf
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  • Thanks a lot @EditPiaf for your effort. I know the different second-order schemes that we can obtain for various values of $\alpha$ and $\beta$, but I still stuck with the Fourier stability analysis of this generalized scheme (the amplification matrix, the modified equation, and how we could find optimal values of $\alpha$ and $\beta$ ) – Almendrof66 Jun 17 '20 at 05:10
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    @Almendrof66 I'd perform Neumann stability analysis in the linear case only (because Fourier transform is linear, see related posts). Modified equations are deduced from 2D Taylor series, see related post. If not specific enough, ask a new question – EditPiAf Jun 17 '20 at 06:54
  • Thanks a lot for this interesting answer – Almendrof66 Jun 17 '20 at 14:57