pycontrails.models.ps_model.PSGrid¶

class pycontrails.models.ps_model.PSGrid(met=None, params=None, **params_kwargs)¶

Bases: AircraftPerformanceGrid

Compute nominal Poll-Schumann aircraft performance over a grid.

For a given aircraft type, altitude, aircraft mass, air temperature, and mach number, the PS model computes a theoretical engine efficiency and fuel flow rate for an aircraft under cruise conditions. Letting the aircraft mass vary and fixing the other parameters, the engine efficiency curve attains a single maximum at a particular aircraft mass. By solving this implicit equation, the PS model can be used to compute the aircraft mass that maximizes engine efficiency for a given set of parameters. This is the “nominal” aircraft mass computed by this model.

This nominal aircraft mass is not always realizable. For example, the maximum engine efficiency may be attained at an aircraft mass that is less than the operating empty mass of the aircraft. This model determines the minimum and maximum possible aircraft mass for a given set of parameters using a simple heuristic. The nominal aircraft mass is then clipped to this range.

__init__(met=None, params=None, **params_kwargs)¶

Methods

`__init__`([met, params])
`downselect_met`()	Downselect `met` domain to the max/min bounds of `source`.
`eval`([source])	Evaluate the PS model over a `MetDataset` or `GeoVectorDataset`.
`get_source_param`(key[, default, set_attr])	Get source data with default set by parameter key.
`require_met`()	Ensure that `met` is a MetDataset.
`require_source_type`(type_)	Ensure that `source` is `type_`.
`set_source`([source])	Attach original or copy of input `source` to `source`.
`set_source_met`([optional, variable])	Ensure or interpolate each required `met_variables` on `source` .
`transfer_met_source_attrs`([source])	Transfer met source metadata from `met` to `source`.
`update_params`([params])	Update model parameters on `params`.

Attributes

`params`	Instantiated model parameters, in dictionary form
`met`	Meteorology data
`source`	Data evaluated in model
`hash`	Generate a unique hash for model instance.
`interp_kwargs`	Shortcut to create interpolation arguments from `params`.
`long_name`
`met_required`	Require meteorology is not None on __init__()
`met_variables`	Required meteorology pressure level variables.
`name`
`processed_met_variables`	Set of required parameters if processing already complete on `met` input.
`optional_met_variables`	Optional meteorology variables

default_params¶: alias of PSGridParams

eval(source=None, **params)¶

Evaluate the PS model over a MetDataset or GeoVectorDataset.

Parameters:

source (GeoVectorDataset | MetDataset | None, optional) – The source data to use for the evaluation. If None, the source is taken from the met attribute of the PSGrid instance. The aircraft type is taken from source.attrs["aircraft_type"]. If this field is not present, params["aircraft_type"] is used instead. See the static CSV file ps-aircraft-params-20231117.csv for a list of supported aircraft types.
**params (Any) – Override the default parameters of the PSGrid instance.

Returns:

GeoVectorDataset | MetDataset –

The source data with the following variables added:

aircraft_mass

fuel_flow

engine_efficiency

Raises:

NotImplementedError – If “true_airspeed” or “aircraft_mass” fields are included in source.