noads.application.scenario_setup

noads.application.scenario_setup#

Setup model structure, default inputs and design space for optimization.

noads.application.scenario_setup.multi_scenario_setup(name, background_scenario_names, start_year=2025, end_year=2075, time_step=2.0, interp_step=5.0, technology_index=0, aggregate_constraints=False, integrate_constraints=False, demand_aversion=False, fossil_kerosene_only=False, drop_in_only=False, preferential_energy=False, plot_scenario_data=False)[source]#

Set up a decarbonization scenario robust to several background scenarios.

Same as single_scenario_setup(), but the temporal scenario is batched across the given ensemble of background scenarios with a MultiScenario: the aircraft mix variables are shared across the ensemble (fixed. prefix) while the energy mix variables are scenario-specific, and ensemble-mean outputs (mean. prefix) are exposed for the robust objective.

Parameters:

  • name (str)

  • background_scenario_names (Sequence[str])

noads.application.scenario_setup.single_scenario_setup(name, background_scenario_name, start_year=2025, end_year=2075, time_step=1.0, interp_step=2.5, technology_index=0, integrate_constraints=False, demand_aversion=False, drop_in_only=False, fossil_kerosene_only=False, preferential_energy=False, plot_scenario_data=False, compile_jit=True)[source]#

Set up a single-objective decarbonization scenario.

Builds the fleet and energy-mix objects, loads the AR6 background data of the chosen scenario, assembles everything into a TemporalScenario, fills in the default inputs (pathway efficiencies and emission indices, market shares, fair shares, demand-model constants), and creates the design space (aircraft entry-into-service and maximum market shares, energy pathway shares, and, with demand_aversion, the market supply-shift ratios) together with the optimization constraints.

Parameters:

  • name (str) – The name of the scenario.

  • background_scenario_name (str) – The AR6 background scenario (e.g. "SSP2-26").

  • start_year – The first simulated year.

  • end_year – The last simulated year.

  • time_step – The simulation time step in years.

  • interp_step – The spacing in years of the control knots.

  • technology_index – The aircraft technology scenario (0: Lower, 1: Mid, 2: Upper).

  • integrate_constraints – Whether to time-integrate constraint violations instead of imposing path-wise constraints.

  • demand_aversion – Whether to use the low-demand formulation (supply caps and discounted price-increase burden).

  • drop_in_only – Whether to restrict the fleet to drop-in (Jet-A) aircraft.

  • fossil_kerosene_only – Whether to restrict Jet-A to fossil kerosene.

  • preferential_energy – Whether to use the preferential (8.6 %) instead of the conservative (5.0 %) fair share of biomass and electricity.

  • plot_scenario_data – Whether to plot the AR6 background data.

  • compile_jit – Whether to JIT-compile the assembled discipline.

Returns:

The temporal scenario, the design space, the constraints (mapping each constraint name to its bound and sign), the energy mix, and the fleet.

Functions

multi_scenario_setup(name, ...[, ...])

Set up a decarbonization scenario robust to several background scenarios.

single_scenario_setup(name, ...[, ...])

Set up a single-objective decarbonization scenario.