bluemira.fuel_cycle.cycle

Full fuel cycle model object

Classes

`EUDEMOFuelCycleModel`	Tritium fuel cycle object.
`EDFCMParams`	Parameters required to run `EUDEMOFuelCycleModel`.

Module Contents

class bluemira.fuel_cycle.cycle.EUDEMOFuelCycleModel(params: EDFCMParams | dict[str, float] | None = None, build_config: dict[str, Any] | None = None)

Tritium fuel cycle object.

Takes a lifecycle timeline and interprets it to reach tritium start-up inventory and inventory doubling time estimates.

Parameters:

params (EDFCMParams | dict[str, float] | None) – The parameters for the model. See EDFCMParams for list of available parameters.
build_config (dict[str, Any] | None) –
Configuration options for the model. Options are:
- verbose: bool (False)
  Print debugging information.
- timestep: float (1200.0)
  The time step in the cycle [s].
- conv_thresh: float (2e-4)
  The convergence threshold in the cycle.
- n: int (length of timeline[‘time’])
  The no. of time steps to use from the the timeline.

verbose

timestep

conv_thresh

n

_constructors()

run(timeline: bluemira.fuel_cycle.timeline.Timeline)

Run the fuel cycle model.

Parameters:: timeline (bluemira.fuel_cycle.timeline.Timeline) – Timeline with which to run the model

finalise(): Perform clean-up fudge to ensure all tritium returns to stores after the end of the reactor life.

initialise_arrays(timeline: bluemira.fuel_cycle.timeline.Timeline, n: int)

Initialise timeline arrays for TFV model.

Notes

Gas puff timeline mapped to burn signal.

Parameters:

timeline (bluemira.fuel_cycle.timeline.Timeline)
n (int)

seed_t(): Seed an initial value to the model.

tbreed(TBR: float, m_T_0: float) → numpy.ndarray

Ideal system without T sequestration. Used for plotting and sanity.

Returns:

Tritium breeding

Parameters:

TBR (float)
m_T_0 (float)

Return type:

numpy.ndarray

plasma(eta_iv: float, max_inventory: float, flows: list[numpy.ndarray] | None = None) → numpy.ndarray

In-vessel environment

Parameters:

eta_iv (float) – In-vessel accumulation efficiency 0 <= float <= 1
max_inventory (float) – T inventory limit of in-vessel environment [kg] (e.g. 0.7 kg in ITER in-vessel)
flows (list[numpy.ndarray] | None) – Additional flows to add into plasma

Returns:

Flow-rate out of the system [kg/s]

Return type:

numpy.ndarray

blanket(eta_b: float, max_inventory: float) → numpy.ndarray

The tritium breeding system. Dumps stored inventory at blanket change.

Parameters:

eta_b (float) – The retention efficiency parameter for the blanket
max_inventory (float) – The maximum inventory in the blanket

Return type:

Flow-rate out of the system [kg/s]

tfv(eta_tfv: float, flows: list[numpy.ndarray]) → numpy.ndarray

The TFV system where the tritium flows from the BB and plasma are combined.

Parameters:

eta_tfv (float) – Detritiation factor of the system
flows (list[numpy.ndarray]) – The flows to be added to the TFV block

Return type:

Flow-rate out of the system [kg/s]

stack(flows: list[numpy.ndarray])

Exhaust to environment

Parameters:: flows (list[numpy.ndarray])

injector(flows: list[numpy.ndarray]) → numpy.ndarray

Pellet injection system assumed

Returns:: injector mass out
Parameters:: flows (list[numpy.ndarray])
Return type:: numpy.ndarray

recycle(): The main loop of the fuel cycle, which is called recursively until the convergence criterion is met.

plot(): Plot the results of the fuel cycle model.

plot_m_T(**kwargs)

Plot the evolution of the tritium masses over time.

Returns:: The plot axis

plot_inventory(**kwargs): Plot the evolution of the tritium inventories (including sequestered) over time.

static _adjust_inv_plot(t, inventory, thresh=0.2)

Plot correction for compressed time inventories

Returns:: inventory

calc_t_d() → float

Calculate the doubling time of a fuel cycle timeline, assuming that a future tokamak requires the same start-up inventory as the present one.

Returns:

arg_t_d – index of doubling time in time array
Doubling time of the tritium fuel cycle [y]

\(t_{d} = t[\text{max}(\text{argmin}\lvert m_{T_{store}}-I_{TFV_{min}}-m_{T_{start}}\rvert))]\)

Return type:

float

calc_t_infl() → tuple[int, float]

Calculate the inflection time of the reactor tritium inventory

Returns:

arg_t_infl – index of inflection time in time array
inflection time

Return type:

tuple[int, float]

_plot_t_d(**kwargs)

_plot_t_infl(arg, **kwargs)

calc_m_release() → float

Calculate the tritium release rate from the entire system to the environment.

Returns:: Tritium release rate [kg/yr]
Return type:: float

sanity(): Check that no tritium is lost (graphically).

class bluemira.fuel_cycle.cycle.EDFCMParams

Parameters required to run EUDEMOFuelCycleModel.

TBR: float = 1.05: Tritium breeding ratio [dimensionless].

f_b: float = 0.015: Burn-up fraction [dimensionless].

m_gas: float = 50: Gas puff flow rate [Pa m^3/s]. To maintain detachment - no chance of fusion from gas injection.

A_global: float = 0.3: Load factor [dimensionless].

r_learn: float = 1: Learning rate [dimensionless].

t_pump: float = 100: Time in DIR loop [s]. Time between exit from plasma and entry into plasma through DIR loop.

t_exh: float = 3600: Time in INDIR loop [s]. Time between exit from plasma and entry into TFV systems INDIR.

t_ters: float = 18000: Time from BB exit to TFV system [s].

t_freeze: float = 1800: Time taken to freeze pellets [s].

f_dir: float = 0.9: Fraction of flow through DIR loop [dimensionless].

t_detrit: float = 36000: Time in detritiation system [s].

f_detrit_split: float = 0.9999: Fraction of detritiation line tritium extracted [dimensionless].

f_exh_split: float = 0.99: Fraction of exhaust tritium extracted [dimensionless].

eta_fuel_pump: float = 0.9: Efficiency of fuel line pump [dimensionless]. Pump which pumps down the fuelling lines.

eta_f: float = 0.5: Fuelling efficiency [dimensionless]. Efficiency of the fuelling lines prior to entry into the VV chamber.

I_miv: float = 0.3: Maximum in-vessel T inventory [kg].

I_tfv_min: float = 2: Minimum TFV inventory [kg]. Without which e.g. cryodistillation columns are not effective.

I_tfv_max: float = 2.2: Maximum TFV inventory [kg]. Account for T sequestration inside the T plant.

I_mbb: float = 0.055: Maximum BB T inventory [kg].

eta_iv: float = 0.9995: In-vessel bathtub parameter [dimensionless].

eta_bb: float = 0.995: BB bathtub parameter [dimensionless].

eta_tfv: float = 0.998: TFV bathtub parameter [dimensionless].

f_terscwps: float = 0.9999: TERS and CWPS cumulated factor [dimensionless].