fastoad.models.performances.mission.openmdao.mission module

FAST-OAD model for mission computation.

class fastoad.models.performances.mission.openmdao.mission.OMMission(**kwargs)

Bases: openmdao.core.group.Group, fastoad.models.performances.mission.openmdao.base.BaseMissionComp, fastoad.models.performances.mission.openmdao.base.NeedsOWE

Computes a mission as specified in mission input file.

Set the solvers to nonlinear and linear block Gauss–Seidel by default.

initialize()

Perform any one-time initialization run at instantiation.

setup()

Build this group.

This method should be overidden by your Group’s method. The reason for using this method to add subsystem is to save memory and setup time when using your Group while running under MPI. This avoids the creation of systems that will not be used in the current process.

You may call ‘add_subsystem’ to add systems to this group. You may also issue connections, and set the linear and nonlinear solvers for this group level. You cannot safely change anything on children systems; use the ‘configure’ method instead.

Available attributes:

name pathname comm options

property flight_points: pandas.core.frame.DataFrame

Dataframe that lists all computed flight point data.

class fastoad.models.performances.mission.openmdao.mission.SpecificBurnedFuelComputation(**kwargs)

Bases: openmdao.core.explicitcomponent.ExplicitComponent

Computation of specific burned fuel (mission fuel / payload / mission range).

Store some bound methods so we can detect runtime overrides.

initialize()

Perform any one-time initialization run at instantiation.

property range_variable

Name of range variable.

property burned_fuel_variable

Name of burned fuel variable.

property specific_burned_fuel_variable

Name of specific burned fuel variable (mission fuel / payload / mission range).

property payload_variable

Name of payload variable.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

compute(inputs, outputs, discrete_inputs=None, discrete_outputs=None)

Compute outputs given inputs. The model is assumed to be in an unscaled state.

Parameters

• inputs (Vector) – Unscaled, dimensional input variables read via inputs[key].

• outputs (Vector) – Unscaled, dimensional output variables read via outputs[key].

• discrete_inputs (dict or None) – If not None, dict containing discrete input values.

• discrete_outputs (dict or None) – If not None, dict containing discrete output values.