pycontrails.ext.bada.BADA4¶

class pycontrails.ext.bada.BADA4(bada_path=None)¶

Bases: BADA

BADA 4.2 Support.

Base of Aircraft Data (BADA) provides a set of ASCII files containing performance and operating procedure coefficients.`

Parameters:: bada_path (str | pathlib.Path, optional) – Path to BADA 4.2 Model files Default path set to /bada/bada4 in the parent directory of the pycontrails repository.

References

Eurocontrol. User Manual for the Base of Aircraft Data (BADA) Family 4.
Vol EEC Techni. Eurocontrol Experimental Centre; 2016.

__init__(bada_path=None)¶

Methods

`__init__`([bada_path])
`assumed_aircraft_engine_type_bada4`(...)	Get the assumed aircraft type for BADA4.
`calculate_aircraft_performance`(*, ...)	Calculate aircraft performance along a trajectory.
`check_aircraft_type_availability`(aircraft_type)	Check if aircraft type designator is available in BADA database.
`clip_fuel_flow_by_ptf_bounds`(atyp_icao, ...)	Clip array of fuel flow by the BADA PTF-defined thresholds.
`correct_fuel_flow`(atyp_icao, fuel_flow, ...)	Correct unrealistic fuel mass flow rate by clipping to PTF nominals.
`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])	Evaluate the aircraft performance model.
`get_aircraft_engine_properties`(atyp_icao[, ...])	Extract the aircraft performance and engine properties from the BADA database.
`get_aircraft_params`(aircraft_type)	Get aircraft params associated to aircraft type.
`get_ptf_params`(aircraft_type)	Get PTF params associated to aircraft type.
`get_source_param`(key[, default, set_attr])	Get source data with default set by parameter key.
`is_within_thrust_limits`(*, atyp_bada, ...)	Determine whether thrust required at each waypoint is within bounds of BADA model.
`nominal_cruising_speed`(aircraft_type, alt_ft)	Compute nominal cruising speed at altitude by interpolating over PTF data.
`nominal_fuel_flow`(aircraft_type, alt_ft, phase)	Compute nominal fuel flow depending on phase based on PTF data.
`nominal_fuel_flow_from_flight_phase`(...)	Call `nominal_fuel_flow()` for each phase according to `flight_phase`.
`nominal_roc`(aircraft_type, alt_ft)	Compute nominal rate of climb at altitude by interpolating over PTF data.
`nominal_rod`(aircraft_type, alt_ft)	Compute nominal rate of descent at altitude by interpolating over PTF data.
`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

`path`	Path to BADA data directory
`synonym_dict`	Aircraft type synonyms
`aircraft_engine_dataframe`	Available/assumed aircraft-engine combinations
`ptf_params_dict`
`aircraft_param_dict`	Engine and aircraft properties common to BADA3 and BADA4
`default_path`	Default path to BADA data directories
`version`	BADA version.
`hash`	Generate a unique hash for model instance.
`interp_kwargs`	Shortcut to create interpolation arguments from `params`.
`long_name`
`met`	Meteorology data
`met_required`	Require meteorology is not None on __init__()
`name`
`params`	Instantiated model parameters, in dictionary form
`source`	Data evaluated in model
`aircraft_engine_options`
`ptf_param_dict`	Coefficients and properties extracted from BADA3 and BADA4 PTF files
`met_variables`	Required meteorology pressure level variables.
`processed_met_variables`	Set of required parameters if processing already complete on `met` input.
`optional_met_variables`	Optional meteorology variables

aircraft_engine_dataframe¶: Available/assumed aircraft-engine combinations

aircraft_engine_options¶

aircraft_param_dict¶: Engine and aircraft properties common to BADA3 and BADA4

assumed_aircraft_engine_type_bada4(atyp_icao, engine_uid)¶

Get the assumed aircraft type for BADA4.

Parameters:

atyp_icao (str) – ICAO aircraft type designator
engine_uid (None | str) – Engine unique identification number from the ICAO EDB. If None is provided or engine_uid is unidentified, the default aircraft-engine combination from BADA4 is used.

Returns:

pandas.Series – Assumed aircraft and engine type

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.floating]) – Altitude at each waypoint, [\(ft\)]
air_temperature (npt.NDArray[np.floating]) – 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.floating] | float | None) – True airspeed for each waypoint, [\(m s^{-1}\)]. If None, a nominal value is used.
aircraft_mass (npt.NDArray[np.floating] | float) – Aircraft mass for each waypoint, [\(kg\)].
engine_efficiency (npt.NDArray[np.floating] | float | None) – Override the engine efficiency at each waypoint.
fuel_flow (npt.NDArray[np.floating] | float | None) – Override the fuel flow at each waypoint, [\(kg s^{-1}\)].
thrust (npt.NDArray[np.floating] | 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.

check_aircraft_type_availability(aircraft_type, raise_error=True)¶

Check if aircraft type designator is available in BADA database.

Parameters:

aircraft_type (str) – ICAO aircraft type designator (BADA 3), or aircraft model (BADA 4)
raise_error (bool, optional) – Optional flag for raising an error, by default True.

Returns:

bool – Aircraft found in BADA database.

Raises:

KeyError – raises KeyError if the aircraft type is not covered by database

clip_fuel_flow_by_ptf_bounds(atyp_icao, alt_ft, fuel_flow, phase, buffer=0.1)¶

Clip array of fuel flow by the BADA PTF-defined thresholds.

Often, especially at high altitudes, the BADA “hi” and “lo” values both coincide with the “nom” values. Consequently, it is impossible for a predicted fuel flow to fall within the PTF range. To account for this, values within +/- 10% of nominal are considered in range.

Parameters:

atyp_icao (str) – ICAO aircraft type designator.
alt_ft (npt.NDArray[np.floating]) – Array of altitude values, [\(ft\)]
fuel_flow (npt.NDArray[np.floating]) – Values to clip
phase (str, optional) – One of “cruise”, “climb”, or “descent”. By default, “cruise”.
buffer (float, optional) – Custom nominal buffer, [:math: 0 - 1] Values within buffer of nominal are considered “within range”. By default, 0.1.

Returns:

npt.NDArray[np.floating] – Clipped fuel flow

correct_fuel_flow(atyp_icao, fuel_flow, altitude_ft, flight_phase)¶

Correct unrealistic fuel mass flow rate by clipping to PTF nominals.

The BADA PTF files provide “guardrails” for fuel flow values within a specified flight phase (climb, cruise, descent). Specifically, the PTF files provide a nominal, a high, and low value for fuel flows.

The high and low PTF values often fail to provide a sufficiently wide range for fuel flow. To address this, an additional buffer is applied to the nominal values. The adjust PTF ranges take the form

ptf_adjusted_low = minimum(ptf_nom - buffer, ptf_low) ptf_adjusted_high = minimum(ptf_nom + buffer, ptf_high)

This implementation hard codes distinct buffer thresholds for the climb, cruise, and descent phases of flights. These buffers were tuned on real-world flight recorder data to optimize BADA’s predictive quality. These values could be revisited with additional flight recorder data or improved BADA models.

Parameters:

atyp_icao (str) – ICAO aircraft type designator.
fuel_flow (npt.NDArray[np.floating]) – Uncorrected fuel mass flow rate, [\(kg s^{-1}\)]
altitude_ft (npt.NDArray[np.floating]) – Array of altitude values, [\(ft\)]
flight_phase (npt.NDArray[np.uint8] | flight.FlightPhase) – Phase state of each waypoint.

Returns:

npt.NDArray[np.floating] – Corrected fuel mass flow rate, [\(kg s^{-1}\)]

default_params¶: alias of AircraftPerformanceParams

default_path¶: Default path to BADA data directories

downselect_met()¶

Downselect met domain to the max/min bounds of source.

Override this method if special handling is needed in met down-selection.

source must be defined before calling downselect_met().
This method copies and re-assigns met using met.copy() to avoid side-effects.

Raises:

ValueError – Raised if source is not defined. Raised if source is not a GeoVectorDataset.
TypeError – Raised if met is not a MetDataset.

ensure_true_airspeed_on_source()¶

Add true_airspeed field to source data if not already present.

Returns:: npt.NDArray[np.floating] – True airspeed, [\(m s^{-1}\)]. If true_airspeed is already present on source, this is returned directly. Otherwise, it is calculated using Flight.segment_true_airspeed().

eval(source=None, **params)¶

Evaluate the aircraft performance model.

The implementing model adds the following fields to the source flight:

aircraft_mass: aircraft mass at each waypoint, [\(kg\)]
fuel_flow: fuel mass flow rate at each waypoint, [\(kg s^{-1}\)]
thrust: thrust at each waypoint, [\(N\)]
engine_efficiency: engine efficiency at each waypoint
rocd: rate of climb or descent at each waypoint, [\(ft min^{-1}\)]
fuel_burn: fuel burn at each waypoint, [\(kg\)]

In addition, the following attributes are added to the source flight:

n_engine: number of engines
wingspan: wingspan, [\(m\)]
max_mach: maximum Mach number
max_altitude: maximum altitude, [\(m\)]
total_fuel_burn: total fuel burn, [\(kg\)]

Parameters:

source (Flight) – Flight trajectory to evaluate.
params (Any) – Override params with keyword arguments.

Returns:

Flight – Flight trajectory with aircraft performance data.

get_aircraft_engine_properties(atyp_icao, engine_uid=None)¶

Extract the aircraft performance and engine properties from the BADA database.

Parameters:

atyp_icao (str) – ICAO aircraft type designator.
engine_uid (str) – Engine unique identification number from the ICAO EDB. If None is provided or engine_uid is unidentified, default aircraft-engine combination from BADA will be used. This parameter is unused for BADA3; it is only considered for BADA4.

Returns:

AircraftProperties

get_aircraft_params(aircraft_type)¶

Get aircraft params associated to aircraft type.

Parameters:: aircraft_type (str) – ICAO aircraft type designator, or BADA-specific aircraft type.
Returns:: AircraftParams – Value from aircraft_param_dict.

get_ptf_params(aircraft_type)¶

Get PTF params associated to aircraft type.

Parameters:: aircraft_type (str) – ICAO aircraft type designator, or BADA-specific aircraft type.
Returns:: PTFParams – Value from ptf_param_dict.

get_source_param(key, default=<object object>, *, set_attr=True)¶

Get source data with default set by parameter key.

Retrieves data with the following hierarchy:

source.data[key]. Returns np.ndarray | xr.DataArray.
source.attrs[key]
params[key]
default

In case 3., the value of params[key] is attached to source.attrs[key].

Parameters:

key (str) – Key to retrieve
default (Any, optional) – Default value if key is not found.
set_attr (bool, optional) – If True (default), set source.attrs[key] to params[key] if found. This allows for better post model evaluation tracking.

Returns:

Any – Value(s) found for key in source data, source attrs, or model params

Raises:

KeyError – Raises KeyError if key is not found in any location and default is not provided.