The generalized TurbOPark wake model, integrating TI over the streamline.

https://iopscience.iop.org/article/10.1088/1742-6596/2265/2/022063/pdf

Attributes¶

dx: float

The step size of the integral

A: float

The wake growth parameter A.

sbeta_factor: float

Factor multiplying sbeta

ti_var: str

The TI variable

self_wake: bool

Flag for considering only own wake in ti integral

induction: foxes.core.AxialInductionModel or str

The induction model

ipars: dict

Additional parameters for centreline integration

Public members¶

TurbOParkWakeIX(superposition, dx, A, sbeta_factor=0.25, ...)[source]

Constructor.

__repr__()[source]

Return repr(self).

sub_models()[source]

List of all sub-models

initialize(algo, verbosity=0, force=False)[source]

Initializes the model.

init_wake_deltas(algo, mdata, fdata, pdata, wake_deltas)[source]

Initialize wake delta storage.

calc_amplitude_sigma_spsel(algo, mdata, fdata, pdata, ...)[source]

Calculate the amplitude and the sigma, both depend only on x (not on r).

finalize(algo, verbosity=0)[source]

Finalizes the model.

calc_wakes_spsel_x_r(algo, mdata, fdata, pdata, ...)[source]

Calculate wake deltas.

calc_wakes_spsel_x_yz(algo, mdata, fdata, pdata, ...)[source]

Calculate wake deltas.

contribute_to_wake_deltas(algo, mdata, fdata, pdata, ...)[source]

Calculate the contribution to the wake deltas by this wake model.

finalize_wake_deltas(algo, mdata, fdata, pdata, amb_results, ...)[source]

Finalize the wake calculation.

classmethod new(wmodel_type, *args, **kwargs)[source]

Run-time wake model factory.

property model_id

Unique id based on the model type.

var(v)[source]

Creates a model specific variable name.

property initialized

Initialization flag.

load_data(algo, verbosity=0)[source]

Load and/or create all model data that is subject to chunking.

get_data(variable, target, lookup='smfp', mdata=None, ...)[source]

Getter for a data entry in the model object or provided data sources

data_to_store(name, algo, data)[source]

Adds data from mdata to the local store, intended for iterative runs.

from_data_or_store(name, algo, data, ret_dims=False, safe=False)[source]

Get data from mdata or local store