Entropically Damped Artificial Compressibility (EDAC) for SPH

As opposed to the weakly compressible SPH scheme, which uses an equation of state, this scheme uses a pressure evolution equation to calculate the pressure

\[\frac{\mathrm{d} p_a}{\mathrm{d}t} = - \rho c_s^2 \nabla \cdot v + \nu \nabla^2 p,\]

which is derived by Clausen (2013). This equation is similar to the continuity equation (first term, see ContinuityDensity), but also contains a pressure damping term (second term, similar to density diffusion see DensityDiffusion), which reduces acoustic pressure waves through an entropy-generation mechanism.

The pressure evolution is discretized with the SPH method by Ramachandran (2019) as following:

The first term is equivalent to the classical artificial compressible methods, which are commonly motivated by assuming the artificial equation of state (StateEquationCole with exponent=1) and is discretized as

\[- \rho c_s^2 \nabla \cdot v = \sum_{b} m_b \frac{\rho_a}{\rho_b} c_s^2 v_{ab} \cdot \nabla_{r_a} W(\Vert r_a - r_b \Vert, h),\]

where $\rho_a$, $\rho_b$, $r_a$, $r_b$, denote the density and coordinates of particles $a$ and $b$ respectively, $c_s$ is the speed of sound and $v_{ab} = v_a - v_b$ is the difference in the velocity.

The second term smooths the pressure through the introduction of entropy and is discretized as

\[\nu \nabla^2 p = \frac{V_a^2 + V_b^2}{m_a} \tilde{\eta}_{ab} \frac{p_{ab}}{\Vert r_{ab}^2 \Vert + \eta h_{ab}^2} \nabla_{r_a} W(\Vert r_a - r_b \Vert, h) \cdot r_{ab},\]

where $V_a$, $V_b$ denote the volume of particles $a$ and $b$ respectively and $p_{ab}= p_a -p_b$ is the difference in the pressure.

The viscosity parameter $\eta_a$ for a particle $a$ is given as

\[\eta_a = \rho_a \frac{\alpha h c_s}{8},\]

where it is found in the numerical experiments of Ramachandran (2019) that $\alpha = 0.5$ is a good choice for a wide range of Reynolds numbers (0.0125 to 10000).

Note

The EDAC formulation keeps the density constant and this eliminates the need for the continuity equation or the use of a summation density to find the pressure. However, in SPH discretizations, $m/\rho$ is typically used as a proxy for the particle volume. The density of the fluids can therefore be computed using the summation density approach. [19]

TrixiParticles.EntropicallyDampedSPHSystemType
EntropicallyDampedSPHSystem(initial_condition, smoothing_kernel,
                            smoothing_length, sound_speed;
                            pressure_acceleration=inter_particle_averaged_pressure,
                            density_calculator=SummationDensity(),
                            transport_velocity=nothing,
                            alpha=0.5, viscosity=nothing,
                            acceleration=ntuple(_ -> 0.0, NDIMS), buffer_size=nothing,
                            source_terms=nothing)

System for particles of a fluid. As opposed to the weakly compressible SPH scheme, which uses an equation of state, this scheme uses a pressure evolution equation to calculate the pressure. See Entropically Damped Artificial Compressibility for SPH for more details on the method.

Arguments

  • initial_condition: Initial condition representing the system's particles.
  • sound_speed: Speed of sound.
  • smoothing_kernel: Smoothing kernel to be used for this system. See Smoothing Kernels.
  • smoothing_length: Smoothing length to be used for this system. See Smoothing Kernels.

Keyword Arguments

  • viscosity: Viscosity model for this system (default: no viscosity). Recommended: ViscosityAdami.
  • acceleration: Acceleration vector for the system. (default: zero vector)
  • pressure_acceleration: Pressure acceleration formulation (default: inter-particle averaged pressure). When set to nothing, the pressure acceleration formulation for the corresponding density calculator is chosen.
  • density_calculator: Density calculator (default: SummationDensity)
  • transport_velocity: Transport Velocity Formulation (TVF). Default is no TVF.
  • buffer_size: Number of buffer particles. This is needed when simulating with OpenBoundarySPHSystem.
  • source_terms: Additional source terms for this system. Has to be either nothing (by default), or a function of (coords, velocity, density, pressure, t) (which are the quantities of a single particle), returning a Tuple or SVector that is to be added to the acceleration of that particle. See, for example, SourceTermDamping. Note that these source terms will not be used in the calculation of the boundary pressure when using a boundary with BoundaryModelDummyParticles and AdamiPressureExtrapolation. The keyword argument acceleration should be used instead for gravity-like source terms.
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Transport Velocity Formulation (TVF)

Standard SPH suffers from problems like tensile instability or the creation of void regions in the flow. To address these problems, Adami (2013) modified the advection velocity and added an extra term to the momentum equation. The authors introduced the so-called Transport Velocity Formulation (TVF) for WCSPH. Ramachandran (2019) applied the TVF also for the EDAC scheme.

The transport velocity $\tilde{v}_a$ of particle $a$ is used to evolve the position of the particle $r_a$ from one time step to the next by

\[\frac{\mathrm{d} r_a}{\mathrm{d}t} = \tilde{v}_a\]

and is obtained at every time-step $\Delta t$ from

\[\tilde{v}_a (t + \Delta t) = v_a (t) + \Delta t \left(\frac{\tilde{\mathrm{d}} v_a}{\mathrm{d}t} - \frac{1}{\rho_a} \nabla p_{\text{background}} \right),\]

where $\rho_a$ is the density of particle $a$ and $p_{\text{background}}$ is a constant background pressure field. The tilde in the second term of the right hand side indicates that the material derivative has an advection part.

The discretized form of the last term is

\[ -\frac{1}{\rho_a} \nabla p_{\text{background}} \approx -\frac{p_{\text{background}}}{m_a} \sum_b \left(V_a^2 + V_b^2 \right) \nabla_a W_{ab},\]

where $V_a$, $V_b$ denote the volume of particles $a$ and $b$ respectively. Note that although in the continuous case $\nabla p_{\text{background}} = 0$, the discretization is not 0th-order consistent for non-uniform particle distribution, which means that there is a non-vanishing contribution only when particles are disordered. That also means that $p_{\text{background}}$ occurs as prefactor to correct the trajectory of a particle resulting in uniform pressure distributions. Suggested is a background pressure which is in the order of the reference pressure but can be chosen arbitrarily large when the time-step criterion is adjusted.

The inviscid momentum equation with an additional convection term for a particle moving with $\tilde{v}$ is

\[\frac{\tilde{\mathrm{d}} \left( \rho v \right)}{\mathrm{d}t} = -\nabla p + \nabla \cdot \bm{A},\]

where the tensor $\bm{A} = \rho v\left(\tilde{v}-v\right)^T$ is a consequence of the modified advection velocity and can be interpreted as the convection of momentum with the relative velocity $\tilde{v}-v$.

The discretized form of the momentum equation for a particle $a$ reads as

\[\frac{\tilde{\mathrm{d}} v_a}{\mathrm{d}t} = \frac{1}{m_a} \sum_b \left(V_a^2 + V_b^2 \right) \left[ -\tilde{p}_{ab} \nabla_a W_{ab} + \frac{1}{2} \left(\bm{A}_a + \bm{A}_b \right) \cdot \nabla_a W_{ab} \right].\]

Here, $\tilde{p}_{ab}$ is the density-weighted pressure

\[\tilde{p}_{ab} = \frac{\rho_b p_a + \rho_a p_b}{\rho_a + \rho_b},\]

with the density $\rho_a$, $\rho_b$ and the pressure $p_a$, $p_b$ of particles $a$ and $b$ respectively. $\bm{A}_a$ and $\bm{A}_b$ are the convection tensors for particle $a$ and $b$ respectively and are given, e.g. for particle $a$, as $\bm{A}_a = \rho v_a\left(\tilde{v}_a-v_a\right)^T$.

TrixiParticles.TransportVelocityAdamiType
TransportVelocityAdami(background_pressure::Real)

Transport Velocity Formulation (TVF) to suppress pairing and tensile instability. See TVF for more details of the method.

Arguments

  • background_pressure: Background pressure. Suggested is a background pressure which is on the order of the reference pressure.
Note

There is no need for an artificial viscosity to suppress tensile instability when using TransportVelocityAdami. Thus, it is highly recommended to use ViscosityAdami as viscosity model, since ArtificialViscosityMonaghan leads to bad results.

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