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modified CO2 concentration when ventilation is close to 0. (RR)

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This commit is contained in:
Luis Aleixo 2023-07-25 14:56:13 +02:00
parent 2ddff9cbba
commit c8f2b32fef
2 changed files with 15 additions and 15 deletions
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20
caimira/models.py
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@ -1132,23 +1132,21 @@ class _ConcentrationModelBase:
return self.min_background_concentration()/self.normalization_factor()
next_state_change_time = self._next_state_change(time)
RR = self.removal_rate(next_state_change_time)
# If RR is 0, conc_limit does not play a role but its computation
# would raise an error -> we set it to zero.
try:
conc_limit = self._normed_concentration_limit(next_state_change_time)
except ZeroDivisionError:
conc_limit = 0.
t_last_state_change = self.last_state_change(time)
conc_at_last_state_change = self._normed_concentration_cached(t_last_state_change)
delta_time = time - t_last_state_change
fac = np.exp(-RR * delta_time)
return conc_limit * (1 - fac) + conc_at_last_state_change * fac
if isinstance(RR, float) and RR == 0:
curr_conc_state = delta_time * self.population.people_present(time) / self.room.volume
else:
curr_conc_state = self._normed_concentration_limit(next_state_change_time) * (1 - fac)
return curr_conc_state + conc_at_last_state_change * fac
def concentration(self, time: float) -> _VectorisedFloat:
"""
Total concentration as a function of time. The normalization
@ -1260,9 +1258,7 @@ class CO2ConcentrationModel(_ConcentrationModelBase):
return self.CO2_emitters
def removal_rate(self, time: float) -> _VectorisedFloat:
# Setting minimum air exchange rate to 1e-6 to avoid divisions by
# zero when computing the CO2 concentration.
return np.maximum(1e-6,self.ventilation.air_exchange(self.room, time))
return self.ventilation.air_exchange(self.room, time)
def min_background_concentration(self) -> _VectorisedFloat:
"""

10
caimira/tests/models/test_concentration_model.py
View file

@ -252,8 +252,11 @@ def test_normed_integrated_concentration_vectorisation(
"known_min_background_concentration",
"expected_concentration"],
[
[0., 240., 240.],
[0., np.array([240., 240.]), np.array([240., 240.])]
[0., 240., 240. + 0.5/75],
[0.0001, 240.0, 240. + 0.5/75],
[1e-6, 240.0, 240 + 0.5/75],
[0., np.array([240., 240.]), np.array([240. + 0.5/75, 240. + 0.5/75])],
[np.array([0.0001, 1e-6]), np.array([240., 240.]), np.array([240. + 0.5/75, 240. + 0.5/75])],
]
)
def test_zero_ventilation_rate(
@ -272,4 +275,5 @@ def test_zero_ventilation_rate(
known_min_background_concentration = known_min_background_concentration)
normed_concentration = known_conc_model.concentration(1)
npt.assert_almost_equal(normed_concentration, expected_concentration)
assert normed_concentration == pytest.approx(expected_concentration, abs=1e-6)