pycontrails.ext.bada.BADAFlight

class pycontrails.ext.bada.BADAFlight(met=None, params=None, **params_kwargs)

Bases: AircraftPerformance

Compute aircraft properties and fuel consumption.

Parameters:

• met (MetDataset | None, optional) – Dataset containing “air_temperature”, “eastward_wind”, and “northward_wind” variables. Only used if these variables are not already found on parameter source in eval(). By default None.

• params (dict[str, Any], optional) – Override model parameters with dictionary. See BADAFlightParams for model parameters.

• **params_kwargs – Override model parameters with keyword arguments. See BADAFlightParams for model parameters.

See also

-

meth:eval

-

class:BADAFlightParams

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

Methods

__init__([met, params])
calculate_aircraft_performance(*, ...)	Calculate aircraft performance along a trajectory.
downselect_met()	Downselect met domain to the max/min bounds of source.
ensure_true_airspeed_on_source()	Add true_airspeed field to source data if not already present.
eval([source])	Extract aircraft properties and calculate the fuel consumption.
get_bada(aircraft_type)	Check BADA databases for aircraft_type.
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(*args, **kwargs)	Ensure or interpolate each required met_variables on source .
simulate_fuel_and_performance(*, ...)	Calculate aircraft mass, fuel mass flow rate, and overall propulsion efficiency.
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
optional_met_variables	Optional meteorology variables
processed_met_variables	Set of required parameters if processing already complete on met input.

calculate_aircraft_performance(*, aircraft_type, altitude_ft, air_temperature, time, true_airspeed, aircraft_mass, engine_efficiency, fuel_flow, thrust, q_fuel, **kwargs)

Calculate aircraft performance along a trajectory.

When time is not None, this method should be used for a single flight trajectory. Waypoints are coupled via the time parameter.

This method computes the rate of climb and descent (ROCD) to determine flight phases: “cruise”, “climb”, and “descent”. Performance metrics depend on this phase.

When time is None, this method can be used to simulate flight performance over an arbitrary sequence of flight waypoints by assuming nominal flight characteristics. In this case, each point is treated independently and all points are assumed to be in a “cruise” phase of the flight.

Parameters:

• aircraft_type (str) – Used to query the underlying model database for aircraft engine parameters.

• altitude_ft (npt.NDArray[np.float64]) – Altitude at each waypoint, [\(ft\)]

• air_temperature (npt.NDArray[np.float64]) – Ambient temperature for each waypoint, [\(K\)]

• time (npt.NDArray[np.datetime64] | None) – Waypoint time in np.datetime64 format. If None, only drag force will is used in thrust calculations (ie, no vertical change and constant horizontal change). In addition, aircraft is assumed to be in cruise.

• true_airspeed (npt.NDArray[np.float64] | float | None) – True airspeed for each waypoint, [\(m s^{-1}\)]. If None, a nominal value is used.

• aircraft_mass (npt.NDArray[np.float64] | float) – Aircraft mass for each waypoint, [\(kg\)].

• engine_efficiency (npt.NDArray[np.float64] | float | None) – Override the engine efficiency at each waypoint.

• fuel_flow (npt.NDArray[np.float64] | float | None) – Override the fuel flow at each waypoint, [\(kg s^{-1}\)].

• thrust (npt.NDArray[np.float64] | float | None) – Override the thrust setting at each waypoint, [:math: N].

• q_fuel (float) – Lower calorific value (LCV) of fuel, [\(J \ kg_{fuel}^{-1}\)].

• **kwargs (Any) – Additional keyword arguments to pass to the model.

Returns:

AircraftPerformanceData – Derived performance metrics at each waypoint.

default_params

alias of BADAFlightParams

eval(source=None, **params)

Extract aircraft properties and calculate the fuel consumption.

Input source must contain a valid aircraft_type in its source.attrs["aircraft_type"].

If met data is not passed into instance constructor, parameter source must contain the following data variables. - true_airspeed - air_temperature

If the following variables are not provided in the flight attribute, the default aircraft-engine assignment and aircraft mass properties from BADA will be assumed: - engine_uid - max_takeoff_weight - operating_empty_weight - max_payload

If ‘load_factor’ (ranging between 0 and 1) is not provided in the flight attribute, the aircraft mass at the first waypoint will be set to the reference mass for the specific aircraft type from the BADA database.

This method extracts the following aircraft properties from the BADA database.

• aircraft_type_bada

• wingspan

• max_mach

• max_altitude

• engine_name

• n_engine

From these BADA derived quantities, each of the following is computed.

• fuel_flow: fuel mass flow rate, [\(kg s^{-1}\)]

• fuel_burn: total fuel burn between two waypoints, [\(kg\)]

• aircraft_mass

• engine_efficiency

• thrust

Parameters:

• source (Flight) – Flight to evaluate

• **params (Any) – Overwrite model parameters before eval

Returns:

Flight – Flight with additional properties and fuel consumption variables listed above.

get_bada(aircraft_type)

Check BADA databases for aircraft_type.

Parameters:

aircraft_type (str) – Aircraft type to check for.

Returns:

BADA – BADA database object.

long_name = 'Base of aircraft data flight model'

met

Meteorology data

met_variables = (MetVariable(short_name='t', standard_name='air_temperature', long_name='Air Temperature', level_type='isobaricInhPa', ecmwf_id=130, grib1_id=11, grib2_id=(0, 0, 0), units='K', amip='ta', description='Air temperature is the bulk temperature of the air, not the surface (skin) temperature.'),)

Required meteorology pressure level variables. Each element in the list is a MetVariable or a tuple[MetVariable]. If element is a tuple[MetVariable], the variable depends on the data source. Only one variable in the tuple is required.

name = 'bada'

optional_met_variables = (MetVariable(short_name='u', standard_name='eastward_wind', long_name='Eastward Wind', level_type='isobaricInhPa', ecmwf_id=131, grib1_id=33, grib2_id=(0, 2, 2), units='m s**-1', amip='ua', description='"Eastward" indicates a vector component which is positive when directed eastward (negative westward). Wind is defined as a two-dimensional (horizontal) air velocity vector, with no vertical component.'), MetVariable(short_name='v', standard_name='northward_wind', long_name='Northward Wind', level_type='isobaricInhPa', ecmwf_id=132, grib1_id=34, grib2_id=(0, 2, 3), units='m s**-1', amip='va', description='"Northward" indicates a vector component which is positive when directed northward (negative southward). Wind is defined as a two-dimensional (horizontal) air velocity vector, with no vertical component.'))

Optional meteorology variables

params

Instantiated model parameters, in dictionary form

source

Data evaluated in model