Abstract
We generalize the idea of relaxation time stepping methods in order to preserve multiple nonlinear conserved quantities of a dynamical system by projecting along directions defined by multiple time stepping algorithms. Similar to the directional projection method of Calvo et. al. we use embedded Runge–Kutta methods to facilitate this in a computationally efficient manner. Proof of the accuracy of the modified RK methods and the existence of valid relaxation parameters are given, under some restrictions. Among other examples, we apply this technique to Implicit–Explicit Runge–Kutta time integration for the Korteweg–de Vries equation and investigate the feasibility and effect of conserving multiple invariants for multi-soliton solutions.
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Data Availability
The datasets and source code generated and analyzed during the current study are available in [2].
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This work was supported by funding from the King Abdullah University of Science and Technology.
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Appendices
A: List of RK Methods
See Tables 2, 3, 4, 5, 6 and 7.
B: Soliton Solutions
Different soliton solutions [20] of the KdV equation (32) are given below:
-
(a)
1-soliton solution:
$$\begin{aligned} u(x,t)= \beta _1 {{\,\textrm{sech}\,}}^2(\xi _1) \;, \end{aligned}$$(37)where \(\beta _1 = 1\) and \(\xi _1 = \frac{\sqrt{\beta _1}(x-2 \beta _1 t)}{\sqrt{2}}\).
-
(b)
2-soliton solution:
$$\begin{aligned} u(x, t) = -\frac{2(\beta _1-\beta _2)\left( \beta _2 {{\,\textrm{csch}\,}}^2(\xi _2)+\beta _1 {{\,\textrm{sech}\,}}^2(\xi _1)\right) }{\left( \sqrt{2 \beta _1} \tanh (\xi _1)-\sqrt{2 \beta _2} \coth (\xi _2)\right) ^2} \;, \end{aligned}$$(38)where \(\beta _1 = 0.5\), \(\beta _2 = 1\), \(\xi _1 = \frac{\sqrt{\beta _1}(x-2 \beta _1 t)}{\sqrt{2}}\), and \(\xi _2 = \frac{\sqrt{\beta _2}(x-2 \beta _2 t)}{\sqrt{2}}\).
-
(c)
3-soliton solution:
$$\begin{aligned} u(x, t)= & {} \beta _1{{\,\textrm{sech}\,}}^2(\xi _1)- \nonumber \\{} & {} \frac{2(\beta _2-\beta _3)\left( \frac{2(\beta _3-\beta _1)\left( \beta _3 {{\,\textrm{csch}\,}}^2(\xi _3)-\beta _1 {{\,\textrm{sech}\,}}^2(\xi _1)\right) }{\left( \sqrt{2 \beta _3} \tanh (\xi _3)-\sqrt{2 \beta _1} \tanh (\xi _1)\right) ^2}-\frac{2(\beta _1-\beta _2)\left( \beta _2 {{\,\textrm{csch}\,}}^2(\xi _2)+\beta _1 {{\,\textrm{sech}\,}}^2(\xi _1)\right) }{\left( \sqrt{2 \beta _1} \tanh (\xi _1)-\sqrt{2 \beta _2} \coth (\xi _2)\right) ^2} \right) }{\left( \frac{2(\beta _1-\beta _2)}{\sqrt{2 \beta _1} \tanh (\xi _1)-\sqrt{2 \beta _2} \coth (\xi _2)}-\frac{2(\beta _3-\beta _1)}{\sqrt{2 \beta _3} \tanh (\xi _3)-\sqrt{2 \beta _1} \coth (\xi _1)}\right) ^2}, \nonumber \\ \end{aligned}$$(39)where \(\beta _1 = 0.4\), \(\beta _2 = 0.7\), \(\beta _3 = 1\), \(\xi _1 = \frac{\sqrt{\beta _1}(x-2 \beta _1 t)}{\sqrt{2}}\), \(\xi _2 = \frac{\sqrt{\beta _2}(x-2 \beta _2 t)}{\sqrt{2}}\), and \(\xi _3 = \frac{\sqrt{\beta _3}(x-2 \beta _3 t)}{\sqrt{2}}\).
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Biswas, A., Ketcheson, D.I. Multiple-Relaxation Runge Kutta Methods for Conservative Dynamical Systems. J Sci Comput 97, 4 (2023). https://doi.org/10.1007/s10915-023-02312-4
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DOI: https://doi.org/10.1007/s10915-023-02312-4
Keywords
- Runge–Kutta methods
- Multiple-relaxation RK methods
- Conservative systems
- Invariants-preserving numerical methods