Input files specification

File format

JavaScript Object Notation (JSON) is an open–standard file format, that uses human readable text in form of attribute–value pairs and array data types, is used as an input for the solver. Graphical setting up of simulations may be implemented, but JSON format is intuitive enough to make as rapid changes as graphical interface could.

Data types used for parameters:

Note: When a default value is available for some parameter, user does not need to specify the parameter, unless they want to override it.

Note: The document is a JSON object, i.e. it must start with curly brackets ’{’ and ’}’.

Note: The last element in any list or object must not have comma after its definition.

Note: For quick testing, you can simply disable some option/parameter by adding any prefix or suffix to it. For example, change "parameter" to "parameter__" or "parameter_IGNORE" .

General parameters

Global parameters of the simulation:

Note: The modern GPU can execute simulations > 20 times faster than the modern CPU. This holds for typical GPUs optimized for 32-bit precision operations (GTX, RTX, etc.). If the double precision is needed, GPUs like Tesla, A100, H100 will perform better.

Note: 32-bit precision is usually enough when fast approximated/engineering results are needed.

Example: JSON input file with some general parameters.

   {
       "description": "Sway sloshing experiment blah blah",
       "dimensions": 3,
       "precision": "single",

   ... other parameters go here ...

   }

Relaxation

Relaxation is tightly connected to the pressure parameters. It says how strong factors dictate the simulation convergence within the time step.

“relaxation”: {

}

Example:

   "relaxation": {
       "space": 0.9,
       "walls": 0.7
   }

Pressure

Smooth and accurate pressure field is obtained by solving a Poisson equation. The equation is transformed to a system of linear equations, which is solved by using an iterative solver.

“pressure”: {

}

Example:

   "pressure": {
       "solver": "bicgstab",
       "max_iterations": 300,
       "max_error": 1e-4,
       "gradient_limiter": 1.0
   }

Velocity

Velocity is calculated from the momentum equation. For convection-dominated flows, it may be calculated directly, by explicitly approximating the diffusion operator. For diffusion-dominated flows, the velocity field should be solved implicitly using an iterative solver.

“velocity”: {

}

Example:

   "velocity": {
       "solver": "jacobi",
       "max_iterations": 300,
       "max_error": 1e-4
   }

Resolution

This category specifies the spacing between nearest neighbours, and the interaction radius. Each point can be connected to only first ring of its neighbours (fast, less diffusive), but better stability may be achieved by enlarging the radius to reach second ring of its neighbours (slower, more diffusive).

“resolution”: {

}

Note: Currently the point cloud resolution is constant in space and time, adaptive refinement is work in progress.

Example:

   "resolution": {
       "spacing": 0.02,
       "truncation": 1.9
   }

Reordering

Each time step points perform Lagrangian advection, i.e. they move along solved streamlines. It can lead to distortion of the point distribution, and therefore mass conservation errors (imagine a rotating disc where points move in the tangential direction and increase the volume of the disc). During the movement, points try to keep equidistant neighbours to optimally conserve mass at all times.

“reordering”: {

}

External acceleration

Here we use term gravity as constant acceleration imposed to whole fluid in the domain, at all times.

The harmonic oscillator object is created as follows:

Note: Setting domain rotation through key-frames is work-in-progress.

Time control

If the user likes to impose duration of the simulation and the time-stepping control from the input file, use the following options. Otherwise, the user can control the simulation using GUI and console parameters.

“time”: {

}

Domain

The domain is an axis-aligned bounding box (or AABB), defined by the starting and ending coordinates of its diagonal. It specifies the space where fluid flow is allowed. By default the domain automatically encompasses all objects, and dynamically resizes during the simulation.
The user may impose variable domain movement, which is then applied by imposing variable domain acceleration in time and space. This may be achieved by setting movement key-frames, or by analytically defining a harmonic oscillator.

“domain”: {

}

Note: Points leaving the domain boundaries are removed from the simulation.

Note: Performance will suffer if user specifies too large domain compared to the space of the fluid body.

Example:

   "domain": {
       "min": [0, 0, 1],
       "max": [5, 1, 3.2]

       "impose_motion": {
           "impose_position": [[0, [0, 0, 0]], [5.0, [0, 0, 9.8]]
       }

       "impose_oscillation": {
           "frequency": 3.0,
           "axis": [0.0, 1.0, 0.0]
       }
   }

Patches

The simulation input file does not incorporate any volumetric mesh, but only bounding surfaces (patches) of the domain and objects in the scene. These surfaces can be defined using primitives (list of connected line–segments, quadrilaterals) or imported from the commonly used mesh file formats. Patches can be movable, i.e. their motions can be imposed similarly as domain motions.

Note: The input is an object patches containing any number of named boundary surfaces.

“patches”: {

“name_of_patch”: {

},

“another_patch”: { … }

}

The oscillation object can be defined as follows:

“impose_oscillation”: {

}

Note: Generally, it’s not wise to use STL meshes (anywhere!) as they do not incorporate triangle connectivity information. If you still wish to use this format, solver will automatically connect triangles using default tolerance 1e-8. After merging, bad topology triangles will get removed.

Example in 2D:

   "patches": {
       "tank": {
           "type": "solid",
           "geometry": "polyline",
           "points": [
               [-0.3, 0.3], [-0.3, 0.0], [ 0.3, 0.0], [ 0.3, 0.3], [-0.3, 0.3]
           ],
           "oscillation": {
               "period": 1.5,
               "direction": [0.05, 0]
           },
           "probes": [
               [-0.3, 0.1],
               [0.3, 0.1]
           ]
       },

       "water": {
           "type": "free_surface",
           "geometry": "polyline",
           "points": [ [-1, 0.12], [1, 0.12] ]
       }
   }

Example in 3D:

   "patches": {

       "tank": {
           "type": "solid",
           "geometry": "some_tank_mesh.obj"
       }

   }

Fluid

Currently a single fluid phase is supported, but soon multi-phase and variable-phase calculation will be implemented. The specified single fluid moves in the domain specified above. When the boundary surfaces are defined, user may fill the domain space with fluid.

Note: The fluid set-up follows the same as idea as bucket fill or flood fill tools in painting programs. Fluid is filled from some source point until it reaches wall and free-surface boundaries, defined above.

   "fluid": {
       "density": 998.6,
       "viscosity": 1.14e-6,
       "flood_point": [0.0, 0.05]
   }

Wall-Slip models

Currently there are four boundary condition for imposing the velocity boundary condition on the solid walls, including: no-slip, partial-slip, wall-function, and Navier-slip boundary conditions. The defaul BC is the no-slip boundary condition.

No-slip BC

In no_slip model, adjacent fluid molecule has the same velocity as the wall. This model does not need any additional input parameters.

Partial-slip BC

In partial_slip model user can manually control the slip coefficient on the boundaries.

wall-function slip model

In wall_function model, nothing else is needed as an input. This model is for the turbulent flow applying the log-law.

Navier-slip BC

navier_slip model relates the slip velocity with the velocity gradient through a non-linear equation.

Non-Newtonian models

If the fluid type is not Newtonian, but some non-Newtonian type, then the below listed parameters should be set. Currently available non-Newtonian models are: bingham, casson, power_law, cross_power_law, bird_carreau, mohr_coulomb.

Note: The viscosities of non-Newtonian models are input as dynamic, instead of kinematic. This may change in the future, or there may be a switch.

Bingham

Models a viscoplastic material that behaves as a rigid body at low stresses but flows as a viscous fluid at high stress. Once the critical shear stress (yield stress) is exceeded, the material flows in such a way that the shear rate is proportional to the amount by which the applied shear stress exceeds the yield stress.

Casson Model

Similar to the Bingham model, for simulating shear-thickening behaviour of non-Newtonian fluids, for modelling viscoplastic fluids.

Power Law

Power-law or the Ostwald–de Waele relationship, is a type of approximate generalised Newtonian fluid (time independent Non-Newtonian fluid). It yields good flow description across the range of shear rates to which the coefficients were fitted.

Cross-Power Law model

A type of generalised Newtonian fluid whose viscosity depends upon shear rate according to the following equation. The zero-shear viscosity is approached at very low shear rates, while the infinite shear viscosity is approached at very high shear rates.

Bird-Carreau Model

A model that is valid over the complete range of shear rates. For cases where there are significant variations from the Power law model, i.e. at very high and very low shear rates it becomes essential to incorporate the values of viscosity at zero shear and at infinite shear into the formulation.

Mohr-Coulomb Model

A model describing the response of brittle materials such as concrete, or rubble piles, to shear stress as well as normal stress. Generally the theory applies to materials for which the compression strength far exceeds the tensile strength.

PVC PB1335 Model

This is a relation that derived from fitting the experimental data of PB1335, which is used in sealing by many companies. It is a three-segment function. No parameters are needed for this model. It is hard-coded. This will hopefully be removed soon.

Output

The results may be written to hard drive to post-process them in some post-processing software.

“output”: {

}

Note: The folder for outputting is created where the input file is located.

Note: Along with output fields, the solver writes: log, forces & torques, pressure probes.

Note: For vtu format of output, a file named data_time.pvd will be created to collect all vtu files (into Multi-block dataset) with their time makers, which can be directly read by Paraview (the filter Extract Block should be used for obtaining results in a certain layer, e.g. to see the flow block that contains fluid particles). A python script run_dataset.py is also prepared for automatically importing data (data_time.pvd), setting up filters and zoom into proper view, but this requires python3-paraview support to be installed.

Example:

   "output": {
       "time_step": 0.2,
       "times": [0.1666, 1.53],
       "fields": ["velocity", "vorticity"]
   }

Coupling

The fluid simulation can be directly coupled to a FEM solver, using the preCICE coupling tool.

“coupling”: {

}

Note: Currently explicit type of bi-directional coupling is implemented. Implicit coupling is work-in-progress.