fastoad.models.performances.mission.segments.registered.mass_input module

Class for specifying input mass at “any” point in the mission.

class fastoad.models.performances.mission.segments.registered.mass_input.MassTargetSegment(name: str = '', target: ~fastoad.model_base.flight_point.FlightPoint = <object object>, isa_offset: float = 0.0)[source]

Bases: AbstractFlightSegment

Class that simply sets a target mass.

compute_from() returns a 1-row dataframe that is the start point with mass set to provided target mass.

class:~fastoad.models.performances.mission.base.FlightSequence ensures that mass is consistent for segments prior to this one.

compute_from_start_to_target(start: FlightPoint, target: FlightPoint) → DataFrame[source]

Here should come the implementation for computing flight points between start and target flight points.

Parameters:

  • start –

  • target – Definition of segment target

Returns:

a pandas DataFrame where column names match fields of FlightPoint

CONSTANT_VALUE = 'constant'

Using this value will tell to keep the associated parameter constant.

complete_flight_point(flight_point: FlightPoint)

Computes data for provided flight point.

Assumes that it is already defined for time, altitude, mass, ground distance and speed (TAS, EAS, or Mach).

Parameters:

flight_point – the flight point that will be completed in-place

static complete_flight_point_from(flight_point: FlightPoint, source: FlightPoint)

Sets undefined values in flight_point using the ones from source.

The particular case of speeds is taken into account: if at least one speed parameter is defined, all other speed parameters are considered defined, because they will be deduced when needed.

Parameters:

  • flight_point –

  • source –

compute_from(start: FlightPoint) → DataFrame

Computes the flight path segment from provided start point.

Computation ends when target is attained, or if the computation stops getting closer to target. For instance, a climb computation with too low thrust will only return one flight point, that is the provided start point.

Important

When subclasssing, if you need to overload compute_from(), you should consider overriding compute_from_start_to_target() instead. Therefore, you will take benefit of the preprocessing of start and target flight points that is done in compute_from().

Parameters:

start – the initial flight point, defined for altitude, mass and speed (true_airspeed, equivalent_airspeed or mach). Can also be defined for time and/or ground_distance.

Returns:

a pandas DataFrame where column names match fields of FlightPoint

static consume_fuel(flight_point: FlightPoint, previous: FlightPoint, fuel_consumption: float = None, mass_ratio: float = None)

This method should be used whenever fuel consumption has to be stored.

It ensures that “mass” and “consumed_fuel” fields will be kept consistent.

Mass can be modified using the ‘fuel_consumption” argument, or the ‘mass_ratio’ argument. One of them should be provided.

Parameters:

  • flight_point – the FlightPoint instance where “mass” and “consumed_fuel” fields will get new values

  • previous – FlightPoint instance that will be the base for the computation

  • fuel_consumption – consumed fuel, in kg, between ‘previous’ and ‘flight_point’. Positive when fuel is consumed.

  • mass_ratio – the ratio flight_point.mass/previous.mass

isa_offset: float = 0.0

The temperature offset for ISA atmosphere model.

name: str = ''
property target: FlightPoint

The base class of the class hierarchy.

When called, it accepts no arguments and returns a new featureless instance that has no instance attributes and cannot be given any.