Particle Property¶

Particula-beta Index / Particula Beta / Lagrangian / Particle Property

Auto-generated documentation for particula_beta.lagrangian.particle_property module.

friction_factor_wrapper¶

Calculate the friction factor for a given radius, temperature, and pressure.

This function wraps several underlying calculations related to dynamic viscosity, mean free path, Knudsen number, and slip correction factor to compute the particle friction factor.

Arguments¶

radius_meter - A tensor representing the radius of the sphere(s) in meters. Can be a scalar or a vector.
temperature_kelvin - A tensor of the temperature in Kelvin.
pressure_pascal - A tensor of the pressure in Pascals.

Returns¶

torch.Tensor - A tensor of the same shape as radius_meter, representing the particle friction factor.

Signature¶

def friction_factor_wrapper(
    radius_meter: torch.Tensor, temperature_kelvin: float, pressure_pascal: float
) -> torch.Tensor: ...

generate_particle_masses¶

Show source in particle_property.py:129

Generate an array of particle masses based on a log-normal distribution of particle radii and a given density.

Arguments¶

mean_radius float - Mean radius of the particles. The units are specified by radius_input_units.
std_dev_radius float - Standard deviation of the particle radii. The units are specified by radius_input_units.
density torch.Tensor - Density of the particles in kg/m^3.
num_particles int - Number of particles to generate.
radius_input_units str, optional - Units of mean_radius and std_dev_radius. Defaults to 'nm' (nanometers).

Returns¶

torch.Tensor - A tensor of particle masses in kg, corresponding to each particle.

Raises¶

ValueError - If mean_radius or std_dev_radius are non-positive.

Signature¶

def generate_particle_masses(
    mean_radius: float,
    std_dev_radius: float,
    density: torch.Tensor,
    num_particles: int,
    radius_input_units: str = "nm",
) -> torch.Tensor: ...

mass_calculation¶

Show source in particle_property.py:51

Calculate the mass of a sphere given its radius and density using the formula for the volume of a sphere.

This function assumes a uniform density and spherical shape to compute the mass based on the mass-density relationship: Volume = Mass / Density. The volume of a sphere is given by (4/3) * pi * radius^3.

Arguments¶

radius (torch.Tensor): A tensor containing the radius of the sphere(s). Can be a scalar or a vector.
density (torch.Tensor): A tensor containing the density of the sphere(s). Can be a scalar or a vector.

Returns¶

torch.Tensor - A tensor of the same shape as radius and density representing the mass of the sphere(s).

Signature¶

def mass_calculation(radius: torch.Tensor, density: torch.Tensor) -> torch.Tensor: ...

nearest_match¶

Show source in particle_property.py:261

Perform nearest neighbor interpolation (on torch objects) to find y-values corresponding to new x-values. The function identifies the nearest x-value for each value in x_new and returns the corresponding y-value.

Arguments¶

x_values torch.Tensor - The original x-values of shape (n,).
y_values torch.Tensor - The original y-values of shape (n,). Each y-value corresponds to an x-value.
x_new torch.Tensor - The new x-values for which y-values are to be interpolated, of shape (m,).

Returns¶

torch.Tensor - The interpolated y-values of shape (m,). Each value corresponds to the nearest match from x_values.

Signature¶

def nearest_match(
    x_values: torch.Tensor, y_values: torch.Tensor, x_new: torch.Tensor
) -> torch.Tensor: ...

radius_calculation¶

Show source in particle_property.py:19

Calculate the radius of a sphere given its mass and density using the formula for the volume of a sphere.

This function assumes a uniform density and spherical shape to compute the radius based on the mass-density relationship: Volume = Mass / Density. The volume of a sphere is given by (4/3) * pi * radius^3.

Arguments¶

mass (torch.Tensor): A tensor containing the mass of the sphere(s). Can be a scalar or a vector.
density (torch.Tensor): A tensor containing the density of the sphere(s). Can be a scalar or a vector.

Returns¶

torch.Tensor - A tensor of the same shape as mass and density representing the radius of the sphere(s).

Notes¶

The function supports broadcasting, so mass and density can be of different shapes, as long as they are broadcastable to a common shape.
Units of mass and density should be consistent to obtain a radius in meaningful units.

Signature¶

def radius_calculation(mass: torch.Tensor, density: torch.Tensor) -> torch.Tensor: ...

random_thermal_velocity¶

Show source in particle_property.py:228

Generate a random thermal velocity for each particle.

Arguments¶

temperature_kelvin torch.Tensor - Temperature of the fluid in Kelvin.
mass_kg torch.Tensor - Mass of the particle in kilograms.
number_of_particles int - Number of particles.

Returns¶

torch.Tensor - Thermal speed of the particle in meters per second.

Signature¶

def random_thermal_velocity(
    temperature_kelvin: float,
    mass_kg: torch.Tensor,
    number_of_particles: int,
    t_type=torch.float,
    random_seed: int = 0,
) -> torch.Tensor: ...

speed¶

Show source in particle_property.py:213

Calculate the speed of a particle.

Arguments¶

velocity torch.Tensor - Velocity of the particle.

Returns¶

torch.Tensor - Speed of the particle.

Signature¶

def speed(velocity: torch.Tensor) -> torch.Tensor: ...

thermal_speed¶

Show source in particle_property.py:180

Calculate the thermal speed of a particle based on its temperature and mass.

The thermal speed is computed using the formula: sqrt(8 * k * T / (pi * m)) where k is the Boltzmann constant, T is the temperature in Kelvin, and m is the particle mass in kilograms.

Arguments¶

temperature_kelvin float - Temperature of the environment in Kelvin.
mass_kg torch.Tensor - Mass of the particle(s) in kilograms. Can be a scalar or a vector.

Returns¶

torch.Tensor - The thermal speed of the particle(s) in meters per second

Raises¶

ValueError - If temperature_kelvin is less than or equal to zero or if any element of mass_kg is non-positive.

Signature¶

def thermal_speed(temperature_kelvin: float, mass_kg: torch.Tensor) -> torch.Tensor: ...