"""
Generate functions for time-dependent power histories. The preferred
output is a simple list of power levels and time at that power level using
the conventional power in MW/MTIHM and time in days.
A time generation function shall always receive the :code:`state` along with
any other parameters inside the input :code:`time` section.
"""
from pydantic import BaseModel, Field, validate_call
from typing import List, Literal, Annotated
import scale.olm.internal as internal
__all__ = ["constpower_burndata"]
# Data model definitions.
class StateWithSpecificPower(BaseModel):
specific_power: Annotated[float, Field(gt=0)]
_TYPE_CONSTPOWER_BURNDATA = "scale.olm.generate.time:constpower_burndata"
def _schema_constpower_burndata(with_state: bool = False):
_schema = internal._infer_schema(_TYPE_CONSTPOWER_BURNDATA, with_state=with_state)
return _schema
def _test_args_constpower_burndata(with_state: bool = False):
args = {
"_type": _TYPE_CONSTPOWER_BURNDATA,
"state": {"specific_power": 40.0},
"gwd_burnups": [0, 10, 30, 60],
}
if not with_state:
args.pop("state")
return args
[docs]
@validate_call
def constpower_burndata(
state: StateWithSpecificPower,
gwd_burnups: Annotated[List[float], Field(min_length=1)],
final_burnup_padding_gwd: Annotated[float, Field(ge=0.0)] = 0.0,
_type: Literal[_TYPE_CONSTPOWER_BURNDATA] = None,
):
"""Return a list of powers and times assuming constant burnup.
TODO: Instead of returning burndata dictionary, just return the list. Make
this look less like a TRITON burndata specification.
Args:
state: state point data--only the "specific_power" key in MW/MTIHM units is
used
gwd_burnups: list of cumulative burnups in GWd/MTIHM
final_burnup_padding_gwd: final burnup increment in GWd/MTIHM added
only to generated high-order libraries
Returns:
dictionary with "burndata" values as TRITON would expect for its
burndata block. If "final_burnup_padding_gwd" is positive, the final
burndata row is padding for high-order library generation only.
Examples:
>>> import scale.olm as olm
>>> data = olm.generate.time.constpower_burndata(
... state={"specific_power": 40},
... gwd_burnups=[0,10,20]
... )
>>> data["burndata"]
[{'power': 40.0, 'burn': 250.0}, {'power': 40.0, 'burn': 250.0}]
>>> data["final_burnup_padding_gwd"]
0.0
"""
# Calculate cumulative time to achieve each burnup.
gwd_burnups = sorted(gwd_burnups)
burnups = [float(x) * 1e3 for x in gwd_burnups]
days = [burnup / state.specific_power for burnup in burnups]
# Check warnings and errors.
if burnups[0] > 0:
raise ValueError("Burnup step 0.0 GWd/MTHM must be included.")
# Create the burndata block.
burndata = []
if len(days) > 1:
for i in range(len(days) - 1):
burndata.append(
{"power": state.specific_power, "burn": (days[i + 1] - days[i])}
)
else:
burndata.append({"power": state.specific_power, "burn": 0})
if final_burnup_padding_gwd > 0.0:
burndata.append(
{
"power": state.specific_power,
"burn": final_burnup_padding_gwd * 1e3 / state.specific_power,
}
)
return {
"burndata": burndata,
"final_burnup_padding_gwd": final_burnup_padding_gwd,
}