Coagulation Basic 1: PMF (Builder + Coagulation)¶

This notebook demonstrates Brownian coagulation for a discrete/PMF representation using the public par.dynamics API:

1. Build a Brownian coagulation strategy with distribution_type="discrete".
2. Wrap it in par.dynamics.Coagulation.
3. Run a short, lightweight step on a PMF aerosol and visualize the change.

The setup mirrors the pattern notebooks (see Coagulation_1_PMF_Pattern) but keeps grids small so it runs quickly (<120 s).

In [ ]:

# In Colab uncomment the following command to install particula:
#!pip install particula[extra] --quiet
import matplotlib.pyplot as plt
import numpy as np
import particula as par

# In Colab uncomment the following command to install particula: #!pip install particula[extra] --quiet import matplotlib.pyplot as plt import numpy as np import particula as par

Build a PMF aerosol¶

We create a lognormal PMF on a modest grid and attach it to a simple atmosphere. The PMF uses number concentration (m⁻³) per bin.

In [ ]:

# Radius bins (log-spaced, modest resolution for speed)
radius_bins = np.logspace(-8, -6, 120)  # m

# Lognormal PMF (concentration per bin)
concentration_pmf = par.particles.get_lognormal_pmf_distribution(
    x_values=radius_bins,
    mode=np.array([80e-9]),
    geometric_standard_deviation=np.array([1.5]),
    number_of_particles=np.array([5e8]),  # m^-3 total
)

# Atmosphere (ambient, non-condensing)
atmosphere = (
    par.gas.AtmosphereBuilder()
    .set_temperature(25, "degC")
    .set_pressure(1, "atm")
    .build()
)

# PMF particle representation
particles_pmf = (
    par.particles.PresetParticleRadiusBuilder()
    .set_distribution_type("pmf")
    .set_radius_bins(radius_bins, radius_bins_units="m")
    .set_concentration(concentration_pmf, concentration_units="m^-3")
    .set_density(np.array([1_000.0]), density_units="kg/m^3")
    .set_charge(np.zeros_like(radius_bins))
    .build()
)

# Aerosol object
pmf_aerosol = par.Aerosol(atmosphere=atmosphere, particles=particles_pmf)

# Radius bins (log-spaced, modest resolution for speed) radius_bins = np.logspace(-8, -6, 120) # m # Lognormal PMF (concentration per bin) concentration_pmf = par.particles.get_lognormal_pmf_distribution( x_values=radius_bins, mode=np.array([80e-9]), geometric_standard_deviation=np.array([1.5]), number_of_particles=np.array([5e8]), # m^-3 total ) # Atmosphere (ambient, non-condensing) atmosphere = ( par.gas.AtmosphereBuilder() .set_temperature(25, "degC") .set_pressure(1, "atm") .build() ) # PMF particle representation particles_pmf = ( par.particles.PresetParticleRadiusBuilder() .set_distribution_type("pmf") .set_radius_bins(radius_bins, radius_bins_units="m") .set_concentration(concentration_pmf, concentration_units="m^-3") .set_density(np.array([1_000.0]), density_units="kg/m^3") .set_charge(np.zeros_like(radius_bins)) .build() ) # Aerosol object pmf_aerosol = par.Aerosol(atmosphere=atmosphere, particles=particles_pmf)

Configure coagulation (discrete)¶

Use the Brownian builder with distribution_type="discrete", then wrap in the public Coagulation runnable.

In [ ]:

coagulation_strategy = (
    par.dynamics.BrownianCoagulationBuilder()
    .set_distribution_type("discrete")
    .build()
)
coagulation_process = par.dynamics.Coagulation(
    coagulation_strategy=coagulation_strategy
)

print(coagulation_process)

coagulation_strategy = ( par.dynamics.BrownianCoagulationBuilder() .set_distribution_type("discrete") .build() ) coagulation_process = par.dynamics.Coagulation( coagulation_strategy=coagulation_strategy ) print(coagulation_process)

Execute a short coagulation step¶

We keep the time step and sub-steps small for quick execution. The Coagulation runnable updates the aerosol in-place and returns it.

In [ ]:

time_step = 200  # seconds
time_substeps = 10

pmf_before = pmf_aerosol.particles.get_concentration()
radii = pmf_aerosol.particles.get_radius()

pmf_after_aerosol = coagulation_process.execute(
    pmf_aerosol, time_step=time_step, sub_steps=time_substeps
)
pmf_after = pmf_after_aerosol.particles.get_concentration()

time_step = 200 # seconds time_substeps = 10 pmf_before = pmf_aerosol.particles.get_concentration() radii = pmf_aerosol.particles.get_radius() pmf_after_aerosol = coagulation_process.execute( pmf_aerosol, time_step=time_step, sub_steps=time_substeps ) pmf_after = pmf_after_aerosol.particles.get_concentration()

Plot: concentration before/after¶

In [ ]:

fig, ax = plt.subplots(figsize=(8, 5))
ax.plot(radii, pmf_before, label="Before", color="tab:blue")
ax.plot(radii, pmf_after, label="After", color="tab:orange")
ax.set_xscale("log")
ax.set_xlabel("Particle radius (m)")
ax.set_ylabel(r"Number concentration ($m^{-3}$)")
ax.set_title("PMF coagulation (Brownian, discrete)")
ax.legend()
ax.grid(alpha=0.3)
plt.show()

fig, ax = plt.subplots(figsize=(8, 5)) ax.plot(radii, pmf_before, label="Before", color="tab:blue") ax.plot(radii, pmf_after, label="After", color="tab:orange") ax.set_xscale("log") ax.set_xlabel("Particle radius (m)") ax.set_ylabel(r"Number concentration ($m^{-3}$)") ax.set_title("PMF coagulation (Brownian, discrete)") ax.legend() ax.grid(alpha=0.3) plt.show()

Summary¶

• Strategy: BrownianCoagulationBuilder().set_distribution_type( "discrete").build()
• Runnable: par.dynamics.Coagulation
• Representation: PMF (bin-based number concentration)
• Runtime guardrails: small grid, short horizon for fast execution