flow360.TransitionModelSolver

class TransitionModelSolver

Bases: GenericFlowSolverSettings

TransitionModelSolver class for setting up transition model solver

Parameters:

• absolute_tolerance (Optional[PositiveFloat] = 1e-07) – relative_tolerance : Optional[NonNegativeFloat] = 0 order_of_accuracy : Optional[Literal[1, 2]] = 2 CFL_multiplier : Optional[PositiveFloat] = 2.0 update_jacobian_frequency : Optional[PositiveInt] = 4 max_force_jac_update_physical_steps : Optional[NonNegativeInt] = 0 model_type : Literal[‘AmplificationFactorTransport’] = AmplificationFactorTransport equation_eval_frequency : Optional[PositiveInt] = 4 turbulence_intensity_percent : Optional[ConstrainedFloatValue] = None N_crit : Optional[ConstrainedFloatValue] = None reconstruction_gradient_limiter : Optional[ConstrainedFloatValue] = 1.0 linear_solver : Optional[LinearSolver] = LinearSolver(max_iterations=20, absolute_tolerance=None, relative_tolerance=None, _type=’LinearSolver’)

• (...)

Returns:

An instance of the component class TransitionModelSolver.

Return type:

TransitionModelSolver

Example

>>> ts = TransitionModelSolver(absolute_tolerance=1e-10)

Attributes

Methods

__init__([filename])	Create a new model by parsing and validating input data from keyword arguments.
add_type_field()	Automatically place "type" field with model name in the model field dictionary.
allow_but_remove(values)	root validator for allow_but_remove, e.g., legacy properties that are no longer in use
append(params[, overwrite])	append parametrs to the model
construct([_fields_set])	Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
copy([update])	Copy a Flow360BaseModel.
dict(*args[, exclude])	Returns dict representation of the model.
dict_from_file(filename)	Loads a dictionary containing the model from a .json or .yaml file.
flow360_schema()	Generate a schema json string for the flow360 model
flow360_ui_schema()	Generate a UI schema json string for the flow360 model
from_file(filename)	Loads a Flow360BaseModel from .json, or .yaml file.
from_json(filename, **parse_obj_kwargs)	Load a Flow360BaseModel from .json file.
from_orm(obj)
from_yaml(filename, **parse_obj_kwargs)	Loads Flow360BaseModel from .yaml file.
generate_docstring()	Generates a docstring for a Flow360 model and saves it to the __doc__ of the class.
handle_conflicting_fields(values)	root validator to handle deprecated aliases
handle_deprecated_aliases(values)	root validator to handle deprecated aliases
help([methods])	Prints message describing the fields and methods of a Flow360BaseModel.
json(*args[, exclude])	Returns json representation of the model.
one_of(values)	root validator for require one of
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
set_will_export_to_flow360(flag)	Recursivly sets flag will_export_to_flow360
to_file(filename)	Exports Flow360BaseModel instance to .json or .yaml file
to_json(filename)	Exports Flow360BaseModel instance to .json file
to_solver(params, **kwargs)	Convert turbulenceIntensityPercent to Ncrit
to_yaml(filename)	Exports Flow360BaseModel instance to .yaml file.
update_forward_refs(**localns)	Try to update ForwardRefs on fields based on this Model, globalns and localns.
validate(value)

Inherited Common Usage

model_type

absolute_tolerance

equation_eval_frequency

turbulence_intensity_percent

N_crit

reconstruction_gradient_limiter

linear_solver

to_solver(params, **kwargs)

Convert turbulenceIntensityPercent to Ncrit