TransitionModelSolver

class TransitionModelSolver

Bases: GenericSolverSettings

TransitionModelSolver class for setting up transition model solver. For more information on setting up the numerical parameters for the transition model solver, refer to the transition model solver knowledge base.

Warning

N_crit and turbulence_intensity_percent cannot be specified at the same time.

Example

>>> fl.TransitionModelSolver(
...     linear_solver=fl.LinearSolver(max_iterations=50),
...     absolute_tolerance=1e-8,
...     update_jacobian_frequency=1,
...     equation_evaluation_frequency=1,
...     turbulence_intensity_percent=0.04,
... )

Attributes

absolute_tolerance: float

Tolerance for the transition model residual, below which the solver progresses to the next physical step (unsteady) or completes the simulation (steady).

Default:

1e-07

relative_tolerance: float

Tolerance to the relative residual, below which the solver goes to the next physical step. Relative residual is defined as the ratio of the current pseudoStep’s residual to the maximum residual present in the first 10 pseudoSteps within the current physicalStep. NOTE: relativeTolerance is ignored in steady simulations and only absoluteTolerance is used as the convergence criterion.

Default:

0

equation_evaluation_frequency: int

Frequency at which to update the transition equation.

Default:

4

linear_solver: LinearSolver

Linear solver settings, see LinearSolver documentation.

Default:

LinearSolver()

CFL_multiplier: float

Factor to the CFL definitions defined in the Time Stepping section.

Default:

2.0

turbulence_intensity_percent: float, optional

Turbulence Intensity, Range from [0.03-2.5]. Only valid when N_crit is not specified.

Default:

None

N_crit: float, optional

Critical Amplification Factor, Range from [1-11]. Only valid when turbulence_intensity_percent is not specified.

Default:

None

update_jacobian_frequency: int

Frequency at which the jacobian is updated.

Default:

4

max_force_jac_update_physical_steps: int

For physical steps less than the input value, the jacobian matrix is updated every pseudo step overriding the update_jacobian_frequency value.

Default:

0

reconstruction_gradient_limiter: float, optional

The strength of gradient limiter used in reconstruction of solution variables at the faces (specified in the range [0.0, 2.0]). 0.0 corresponds to setting the gradient equal to zero, and 2.0 means no limiting.

Default:

1.0

trip_regions: EntityList[Box], optional

A list of Box entities defining the trip zones.

Default:

None

Additional Constructors

classmethod from_file(filename)

Loads a Flow360BaseModel from .json, or .yaml file.

Parameters:

filename (str) – Full path to the .yaml or .json file to load the Flow360BaseModel from.

Returns:

An instance of the component class calling load.

Return type:

Flow360BaseModel

Example

>>> params = Flow360BaseModel.from_file(filename='folder/sim.json') 

Methods

help(methods=False)

Prints message describing the fields and methods of a Flow360BaseModel.

Parameters:

methods (bool = False) – Whether to also print out information about object’s methods.

Return type:

None

Example

>>> params.help(methods=True) 

to_file(filename, **kwargs)

Exports Flow360BaseModel instance to .json or .yaml file

Parameters:

filename (str) – Full path to the .json or .yaml or file to save the Flow360BaseModel to.

Return type:

None

Example

>>> params.to_file(filename='folder/flow360.json')