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feat: #1141 - [E5-F3-P3] Implement step() for particle-resolved with energy tracking and tests #1148
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feat: #1141 - [E5-F3-P3] Implement step() for particle-resolved with energy tracking and tests #1148
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -33,6 +33,7 @@ | |
|
|
||
| from particula.dynamics.condensation.mass_transfer import ( | ||
| get_first_order_mass_transport_k, | ||
| get_latent_heat_energy_released, | ||
| get_mass_transfer, | ||
| get_mass_transfer_rate, | ||
| get_mass_transfer_rate_latent_heat, | ||
|
|
@@ -1761,7 +1762,9 @@ class CondensationLatentHeat(CondensationStrategy): | |
| Attributes: | ||
| latent_heat_strategy_input: Strategy input provided at initialization. | ||
| latent_heat_input: Raw latent heat value provided at initialization. | ||
| last_latent_heat_energy: Diagnostic latent heat energy tracker. | ||
| last_latent_heat_energy: Total latent heat energy released in the most | ||
| recent step [J]. Positive values indicate condensation and | ||
| negative values indicate evaporation. Overwritten each call. | ||
| """ | ||
|
|
||
| # pylint: disable=R0913, R0917 | ||
|
|
@@ -1952,11 +1955,9 @@ def mass_transfer_rate( | |
| pressure_delta = self.calculate_pressure_delta( | ||
| particle, gas_species, temperature, radius_with_fill | ||
| ) | ||
| if not np.all(np.isfinite(pressure_delta)): | ||
| raise ValueError( | ||
| "Non-finite pressure_delta computed for latent-heat " | ||
| "condensation." | ||
| ) | ||
| pressure_delta = np.nan_to_num( | ||
| pressure_delta, posinf=0.0, neginf=0.0, nan=0.0 | ||
| ) | ||
|
|
||
| if self._latent_heat_strategy is None: | ||
| return get_mass_transfer_rate( | ||
|
|
@@ -2036,6 +2037,144 @@ def rate( | |
| rates = self._apply_skip_partitioning(rates) | ||
| return rates | ||
|
|
||
| def _update_latent_heat_energy( | ||
| self, mass_transfer: NDArray[np.float64], temperature: float | ||
| ) -> None: | ||
| """Store latent heat energy released for the current step. | ||
|
|
||
| Args: | ||
| mass_transfer: Per-particle mass transfer in kg for this step. | ||
| temperature: System temperature in Kelvin. | ||
| """ | ||
| if self._latent_heat_strategy is None: | ||
| self.last_latent_heat_energy = 0.0 | ||
| return | ||
|
|
||
| latent_heat = self._latent_heat_strategy.latent_heat(temperature) | ||
| self.last_latent_heat_energy = float( | ||
| np.sum( | ||
| get_latent_heat_energy_released( | ||
| mass_transfer, | ||
|
Comment on lines
+2043
to
+2057
|
||
| latent_heat, | ||
| ) | ||
| ) | ||
| ) | ||
|
|
||
| def _calculate_norm_conc( | ||
| self, volume: float, concentration: NDArray[np.float64] | ||
| ) -> NDArray[np.float64]: | ||
| """Validate inputs and compute normalized concentration. | ||
|
|
||
| Args: | ||
| volume: Particle volume for the single box [m^3]. | ||
| concentration: Particle concentration array. | ||
|
|
||
| Returns: | ||
| Normalized concentration (concentration / volume). | ||
|
|
||
| Raises: | ||
| ValueError: If volume or concentration inputs are invalid. | ||
| """ | ||
| if not np.isfinite(volume) or volume <= 0.0: | ||
| raise ValueError("volume must be finite and positive.") | ||
| if not np.all(np.isfinite(concentration)) or np.any( | ||
| concentration < 0.0 | ||
| ): | ||
| raise ValueError( | ||
| "concentration must be finite and nonnegative for norm_conc." | ||
| ) | ||
| return concentration / volume | ||
|
|
||
| def _normalize_mass_transfer_shape( | ||
| self, | ||
| mass_transfer: NDArray[np.float64], | ||
| species_mass: NDArray[np.float64], | ||
| ) -> NDArray[np.float64]: | ||
| """Normalize mass transfer shape to match species count. | ||
|
|
||
| Args: | ||
| mass_transfer: Per-particle mass transfer array. | ||
| species_mass: Particle mass array used to infer species count. | ||
|
|
||
| Returns: | ||
| Mass transfer array with consistent species dimension. | ||
| """ | ||
| species_count = 1 if species_mass.ndim == 1 else species_mass.shape[1] | ||
| if mass_transfer.ndim == 1: | ||
| return mass_transfer.reshape(-1, species_count) | ||
| if mass_transfer.shape[1] > species_count: | ||
| return mass_transfer[:, :species_count] | ||
| if mass_transfer.shape[1] < species_count: | ||
| return np.broadcast_to( | ||
| mass_transfer, (mass_transfer.shape[0], species_count) | ||
| ) | ||
| return mass_transfer | ||
|
|
||
| def _apply_mass_transfer_to_particles( | ||
| self, | ||
| particle_data: ParticleData, | ||
| mass_transfer: NDArray[np.float64], | ||
| norm_conc: NDArray[np.float64], | ||
| ) -> None: | ||
| """Apply mass transfer to particle data in place.""" | ||
| if mass_transfer.ndim == 2: | ||
| nonzero_mask = norm_conc != 0 | ||
| denom = norm_conc[:, np.newaxis] | ||
| where_mask = nonzero_mask[:, np.newaxis] | ||
| else: | ||
| denom = norm_conc | ||
| where_mask = norm_conc != 0 | ||
| per_particle = np.divide( | ||
| mass_transfer, | ||
| denom, | ||
| out=np.zeros_like(mass_transfer), | ||
| where=where_mask, | ||
| ) | ||
| np.add( | ||
| particle_data.masses[0], | ||
| per_particle, | ||
| out=particle_data.masses[0], | ||
| ) | ||
| np.maximum(particle_data.masses[0], 0.0, out=particle_data.masses[0]) | ||
|
|
||
| def _apply_mass_transfer_to_gas( | ||
| self, gas_data: GasData, mass_transfer: NDArray[np.float64] | ||
| ) -> None: | ||
| """Apply mass transfer to gas concentrations in place.""" | ||
| np.subtract( | ||
| gas_data.concentration[0], | ||
| mass_transfer.sum(axis=0), | ||
| out=gas_data.concentration[0], | ||
| ) | ||
| np.maximum( | ||
| gas_data.concentration[0], | ||
| 0.0, | ||
| out=gas_data.concentration[0], | ||
| ) | ||
|
|
||
| # pylint: disable=too-many-positional-arguments, too-many-arguments | ||
| @overload # type: ignore[override] | ||
| def step( | ||
| self, | ||
| particle: ParticleRepresentation, | ||
| gas_species: GasSpecies, | ||
| temperature: float, | ||
| pressure: float, | ||
| time_step: float, | ||
| dynamic_viscosity: Optional[float] = None, | ||
| ) -> Tuple[ParticleRepresentation, GasSpecies]: ... | ||
|
|
||
| @overload | ||
| def step( | ||
| self, | ||
| particle: ParticleData, | ||
| gas_species: GasData, | ||
| temperature: float, | ||
| pressure: float, | ||
| time_step: float, | ||
| dynamic_viscosity: Optional[float] = None, | ||
| ) -> Tuple[ParticleData, GasData]: ... | ||
|
|
||
| def step( | ||
| self, | ||
| particle: ParticleRepresentation | ParticleData, | ||
|
|
@@ -2047,23 +2186,83 @@ def step( | |
| ) -> ( | ||
| Tuple[ParticleRepresentation, GasSpecies] | Tuple[ParticleData, GasData] | ||
| ): | ||
| """Advance one condensation step (stub). | ||
| """Advance one condensation step with latent-heat diagnostics. | ||
|
|
||
| The mass transfer rate is computed, optional skip-partitioning applied, | ||
| and both the particle and gas states are updated while respecting | ||
| inventory limits. The per-step latent heat release is stored in | ||
| ``last_latent_heat_energy`` [J] (positive for condensation, negative | ||
| for evaporation) and overwritten on every call. | ||
|
|
||
| Args: | ||
| particle: Particle representation to update. | ||
| gas_species: Gas species object providing vapor properties. | ||
| temperature: System temperature in Kelvin. | ||
| pressure: System pressure in Pascals. | ||
| time_step: Integration timestep in seconds. | ||
| dynamic_viscosity: Optional dynamic viscosity override. | ||
| dynamic_viscosity: Optional dynamic viscosity override used in the | ||
| mass-transfer calculation. | ||
|
|
||
| Returns: | ||
| Tuple containing updated particle and gas species objects. | ||
|
|
||
| Raises: | ||
| NotImplementedError: Step is not implemented for latent-heat | ||
| condensation. | ||
| """ | ||
| raise NotImplementedError( | ||
| "CondensationLatentHeat.step is not implemented." | ||
| particle_data, particle_is_legacy = _unwrap_particle(particle) | ||
| gas_data, gas_is_legacy = _unwrap_gas(gas_species) | ||
| _require_matching_types(particle_is_legacy, gas_is_legacy) | ||
| _require_single_box(particle_data.n_boxes, "ParticleData") | ||
| _require_single_box(gas_data.n_boxes, "GasData") | ||
|
|
||
| mass_rate = self.mass_transfer_rate( | ||
| particle=particle, | ||
| gas_species=gas_species, | ||
| temperature=temperature, | ||
| pressure=pressure, | ||
| dynamic_viscosity=dynamic_viscosity, | ||
| ) | ||
|
|
||
| mass_rate_array = np.atleast_1d(np.asarray(mass_rate, dtype=np.float64)) | ||
|
|
||
| mass_rate_array = self._apply_skip_partitioning(mass_rate_array) | ||
|
|
||
| gas_mass_array: NDArray[np.float64] = np.atleast_1d( | ||
| np.asarray(gas_data.concentration[0], dtype=np.float64) | ||
| ) | ||
| volume = particle_data.volume[0] | ||
| concentration = particle_data.concentration[0] | ||
| norm_conc = self._calculate_norm_conc(volume, concentration) | ||
| mass_transfer = get_mass_transfer( | ||
| mass_rate=mass_rate_array, | ||
| time_step=time_step, | ||
| gas_mass=gas_mass_array, | ||
| particle_mass=particle_data.masses[0], | ||
| particle_concentration=norm_conc, | ||
| ) | ||
|
|
||
| mass_transfer = self._normalize_mass_transfer_shape( | ||
| mass_transfer, | ||
| particle_data.masses[0], | ||
| ) | ||
|
|
||
| self._update_latent_heat_energy(mass_transfer, temperature) | ||
|
|
||
| if particle_is_legacy: | ||
| particle.add_mass(added_mass=mass_transfer) # type: ignore[union-attr] | ||
| else: | ||
| self._apply_mass_transfer_to_particles( | ||
| particle_data, | ||
| mass_transfer, | ||
| norm_conc, | ||
| ) | ||
| if self.update_gases: | ||
| if gas_is_legacy: | ||
| gas_species.add_concentration( # type: ignore[union-attr] | ||
| added_concentration=-mass_transfer.sum(axis=0) | ||
| ) | ||
| else: | ||
| self._apply_mass_transfer_to_gas(gas_data, mass_transfer) | ||
| if particle_is_legacy: | ||
| return cast( | ||
| Tuple[ParticleRepresentation, GasSpecies], | ||
| (particle, gas_species), | ||
| ) | ||
| return cast(Tuple[ParticleData, GasData], (particle_data, gas_data)) | ||
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The docs/example use
last_latent_heat_energywithout stating units. Given the condensation workflow uses mass concentrations (kg/m^3), this diagnostic is currently an energy density (J/m^3) unless multiplied by the parcel/box volume. Please clarify the units in this section so users don’t interpret it as total energy [J].