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[Time integration](@id time_integration)

TrixiParticles.jl uses a modular approach where time integration is just another module that can be customized and exchanged. The function semidiscretize returns an ODEProblem (see the OrdinaryDiffEq.jl docs), which can be integrated with OrdinaryDiffEq.jl.

In particular, a DynamicalODEProblem is returned, where the right-hand side is split into two functions, the kick!, which computes the derivative of the particle velocities and the drift!, which computes the derivative of the particle positions. This approach allows us to use [specialized time integration methods that do not work with general ODEProblems](@ref symplectic_schemes). Note that this is not a true DynamicalODEProblem where the kick does not depend on the velocity. Therefore, not all integrators designed for DynamicalODEProblems will work (properly) (see [below](@ref kick_drift_kick)). However, all integrators designed for general ODEProblems can be used.

Usage

After obtaining an ODEProblem from semidiscretize, let us call it ode, we can pass it to the function solve of OrdinaryDiffEq.jl. For most schemes, we do the following:

using OrdinaryDiffEqLowStorageRK
sol = solve(ode, Euler(),
            dt=1.0,
            save_everystep=false, callback=callbacks);

Here, Euler() should in practice be replaced by a more useful scheme. callbacks should be a CallbackSet containing callbacks like the InfoCallback. For callbacks, please refer to [the docs](@ref Callbacks) and the example files. In this case, we need to either set a reasonable, problem- and resolution-dependent step size dt, or use the StepsizeCallback, which overwrites the step size dynamically during the simulation based on a CFL-number. We always set save_everystep=false, or OrdinaryDiffEq.jl would return the solution vector for every time step, writing massive amounts of data into the RAM for large simulations. To visualize data for every time step, [callbacks](@ref Callbacks) can be used.

Some schemes, e.g. the two schemes RDPK3SpFSAL35 and RDPK3SpFSAL49 mentioned below, support automatic time stepping, where the step size is determined automatically based on error estimates during the simulation. These schemes do not use the keyword argument dt and will ignore the step size set by the StepsizeCallback. Instead, they will work with the tolerances abstol and reltol, which can be passed as keyword arguments to solve. The default tolerances are abstol=1e-6 and reltol=1e-3.

Recommended schemes

A list of schemes for general ODEProblems can be found here. We commonly use the following three schemes:

  • CarpenterKennedy2N54(williamson_condition=false): A five-stage, fourth order low-storage Runge-Kutta method designed by [Carpenter and Kennedy](@cite Carpenter1994) for hyperbolic problems.
  • RDPK3SpFSAL35(): A 5-stage, third order low-storage Runge-Kutta scheme with embedded error estimator, optimized for compressible fluid mechanics Ranocha2022.
  • RDPK3SpFSAL49(): A 9-stage, fourth order low-storage Runge-Kutta scheme with embedded error estimator, optimized for compressible fluid mechanics Ranocha2022.

[Symplectic schemes](@id symplectic_schemes)

Symplectic schemes like the leapfrog method are often used for SPH.

[Leapfrog kick-drift-kick](@id kick_drift_kick)

The kick-drift-kick scheme of the leapfrog method, updating positions u and velocities v with the functions \operatorname{kick} and \operatorname{drift}, reads:

$$\begin{align*} v^{1/2} &= v^0 + \frac{1}{2} \Delta t\, \operatorname{kick}(u^0, t^0), \\\ u^1 &= u^0 + \Delta t\, \operatorname{drift} \left( v^{1/2}, t^0 + \frac{1}{2} \Delta t \right), \\\ v^1 &= v^{1/2} + \frac{1}{2} \Delta t\, \operatorname{kick}(u^{1}, t^0 + \Delta t). \end{align*}$$

In this form, it is also identical to the velocity Verlet scheme. Note that this only works as long as \operatorname{kick} does not depend on v, i.e., in the inviscid case. Once we add viscosity, \operatorname{kick} depends on both u and v. Then, the calculation of v^1 requires v^1 and becomes implicit.

The way this scheme is implemented in OrdinaryDiffEq.jl as VerletLeapfrog, the intermediate velocity v^{1/2} is passed to \operatorname{kick} in the last stage, resulting in first-order convergence when the scheme is used in the viscid case.

!!! warning Please do not use VelocityVerlet and VerletLeapfrog with TrixiParticles.jl. They will require very small time steps due to first-order convergence in the viscid case.

Leapfrog drift-kick-drift

The drift-kick-drift scheme of the leapfrog method reads:

$$\begin{align*} u^{1/2} &= u^0 + \frac{1}{2} \Delta t\, \operatorname{drift}(v^0, t^0), \\\ v^1 &= v^0 + \Delta t\, \operatorname{kick} \left( u^{1/2}, t^0 + \frac{1}{2} \Delta t \right), \\\ u^1 &= u^{1/2} + \frac{1}{2} \Delta t\, \operatorname{drift}(v^{1}, t^0 + \Delta t). \end{align*}$$

In the viscid case where \operatorname{kick} depends on v, we can add another half step for v, yielding

$$\begin{align*} u^{1/2} &= u^0 + \frac{1}{2} \Delta t\, \operatorname{drift}(v^0, u^0, t^0), \\\ v^{1/2} &= v^0 + \frac{1}{2} \Delta t\, \operatorname{kick}(v^0, u^0, t^0), \\\ v^1 &= v^0 + \Delta t\, \operatorname{kick} \left( v^{1/2}, u^{1/2}, t^0 + \frac{1}{2} \Delta t \right), \\\ u^1 &= u^{1/2} + \frac{1}{2} \Delta t\, \operatorname{drift}(v^{1}, u^{1}, t^0 + \Delta t). \end{align*}$$

This scheme is implemented in OrdinaryDiffEq.jl as LeapfrogDriftKickDrift and yields the desired second order as long as \operatorname{drift} does not depend on u, which is always the case.

Symplectic position Verlet

When the density is integrated (with ContinuityDensity), the density is appended to v as an additional dimension, so all previously mentioned schemes treat the density similar to the velocity. The SPH code DualSPHysics implements a variation of the drift-kick-drift scheme where the density is updated separately. See [Domínguez et al. 2022, Section 2.5.2](@cite Dominguez2022). In the following, we will call the derivative of the density R(v, u, t), even though it is actually included in the \operatorname{kick} as an additional dimension.

This scheme reads

$$\begin{align*} u^{1/2} &= u^0 + \frac{1}{2} \Delta t\, \operatorname{drift}(v^0, u^0, t^0), \\\ v^{1/2} &= v^0 + \frac{1}{2} \Delta t\, \operatorname{kick}(v^0, u^0, t^0), \\\ \rho^{1/2} &= \rho^0 + \frac{1}{2} \Delta t\, R(v^0, u^0, t^0), \\\ v^1 &= v^0 + \Delta t\, \operatorname{kick} \left( v^{1/2}, u^{1/2}, t^0 + \frac{1}{2} \Delta t \right), \\\ \rho^1 &= \rho^0 \frac{2 - \varepsilon^{1/2}}{2 + \varepsilon^{1/2}}, \\\ u^1 &= u^{1/2} + \frac{1}{2} \Delta t\, \operatorname{drift}(v^{1}, u^{1}, t^0 + \Delta t), \end{align*}$$

where

$$\varepsilon^{1/2} = - \frac{R(v^{1/2}, u^{1/2}, t^0 + \frac{1}{2} \Delta t)}{\rho^{1/2}} \Delta t.$$

This scheme is implemented in TrixiParticles.jl as SymplecticPositionVerlet.

    SymplecticPositionVerlet