fuellib.fuel.Fuel

class fuellib.fuel.Fuel(name, decompName=None, fuelDataDir=None)

Bases: object

Class for handling group contribution calculations of thermodynamic and mixture properties.

Initialize Fuel object and pre-compute GCM properties.

Parameters:

name (str) – Name of the mixture as it appears in its gcData file.
decompName (str | None) – Name of the groupDecomposition file if different from name. Defaults to None.
fuelDataDir (str | None) – Directory where the fuel data is stored. If None, uses built-in embedded data.

Raises:

ValueError – If a GCM property cannot be found.

Attributes

`name`	Name of the fuel/mixture.
`fuelDataDir`	Directory containing the fuel data.
`fuelDataGcDir`	Directory containing the gas chromatography data.
`fuelDataDecompDir`	Directory containing the group decomposition data.
`fuelDataPropsDir`	Directory containing the fuel properties data.
`groupDecompFile`	File containing the group decomposition data for this fuel.
`gcxgcFile`	File containing the GCxGC compositional data for this fuel.
`gcmTableFile`	File containing the GCM table data.
`Nij`	Array containing the group decomposition data for each compound.
`num_compounds`	Number of compounds in the fuel mixture.
`num_groups`	Number of functional groups considered in the decomposition.
`fam`	Hydrocarbon family codes for thermal conductivity.
`hc_type`	Hydrocarbon types for each compound:
`nC`	Number of carbon atoms in each compound.
`nH`	Number of hydrogen atoms in each compound.
`compounds`	List of compound names.
`formulas`	Molecular formulas of the fuel components, if available.
`pelephysics_keys`	PelePhysics keys for the fuel components, if available.
`MW`	Molecular weights in kg/mol.
`Tc`	Critical temperature in K.
`Pc`	Critical pressure in Pa.
`Vc`	Critical volume in m^3/mol.
`Tb`	Boiling temperature in K.
`Tm`	Melting temperature in K.
`Hf`	Enthalpy of formation in J/mol.
`Gf`	Gibbs free energy in J/mol.
`Hv_stp`	Enthalpy of vaporization at 298 K in J/mol.
`omega`	Accentric factor (dimensionless).
`Vm_stp`	Molar liquid volume at 298 K in m^3/mol.
`Cp_stp`	Molar specific heat at 298 K in J/(mol*K).
`Cp_B`	Temperature-corrected specific heat (B) in J/(mol*K).
`Cp_C`	Temperature-corrected specific heat (C) in J/(mol*K).
`Lv_stp`	Latent heat of vaporization at 298 K in J/kg.
`epsilonByKB`	Lennard-Jones well depth over Boltzmann constant in K.
`sigma`	Lennard-Jones collision diameter in m.

Methods

`Cl`	Compute liquid mass specific heat capacity in J/kg/K at a given temperature.
`Cp`	Compute molar specific heat capacity at a given temperature.
`X2Y`	Calculate the mass fractions from the mole fractions of each component.
`Y2X`	Calculate the mole fractions from the mass fractions of each component.
`density`	Calculate the density of each component at temperature T.
`diffusion_coeff`	Compute diffusion coefficients using Lennard-Jones parameters.
`latent_heat_vaporization`	Calculate latent heat of vaporization adjusted for temperature.
`mass2X`	Calculate the mole fractions from the mass of each component.
`mass2Y`	Calculate the mass fractions from the mass of each component.
`mean_molecular_weight`	Calculate the mean molecular weight of the mixture.
`mixture_density`	Calculate mixture density at a given temperature.
`mixture_dynamic_viscosity`	Calculate dynamic viscosity of the mixture.
`mixture_kinematic_viscosity`	Calculate kinematic viscosity of the mixture.
`mixture_surface_tension`	Calculate surface tension of the mixture.
`mixture_thermal_conductivity`	Calculate thermal conductivity of the mixture.
`mixture_vapor_pressure`	Calculate vapor pressure of the mixture.
`mixture_vapor_pressure_antoine_coeffs`	Estimate Antoine coefficients for vapor pressure of the mixture.
`molar_liquid_vol`	Compute molar liquid volume with temperature correction.
`psat`	Compute saturated vapor pressure.
`psat_antoine_coeffs`	Estimate Antoine coefficients for vapor pressure of an individual compound.
`surface_tension`	Calculate surface tension of each compound at a given temperature.
`thermal_conductivity`	Calculate thermal conductivity at a given temperature.
`viscosity_dynamic`	Calculate liquid dynamic viscosity based on droplet temperature and density.
`viscosity_kinematic`	Calculate the viscosity using Dutt's equation.

Cl(T, comp_idx=None)

Compute liquid mass specific heat capacity in J/kg/K at a given temperature.

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.

Returns:

Mass specific heat capacity in J/kg/K.

Return type:

Quantity[ndarray[tuple[int]]]

Cp(T, comp_idx=None)

Compute molar specific heat capacity at a given temperature.

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.

Returns:

Molar specific heat capacity in J/mol/K.

Return type:

Quantity[ndarray[tuple[int]]]

Cp_B: Quantity[ndarray[tuple[int]]]: Temperature-corrected specific heat (B) in J/(mol*K).

Cp_C: Quantity[ndarray[tuple[int]]]: Temperature-corrected specific heat (C) in J/(mol*K).

Cp_stp: Quantity[ndarray[tuple[int]]]: Molar specific heat at 298 K in J/(mol*K).

Gf: Quantity[ndarray[tuple[int]]]: Gibbs free energy in J/mol.

Hf: Quantity[ndarray[tuple[int]]]: Enthalpy of formation in J/mol.

Hv_stp: Quantity[ndarray[tuple[int]]]: Enthalpy of vaporization at 298 K in J/mol.

Lv_stp: Quantity[ndarray[tuple[int]]]: Latent heat of vaporization at 298 K in J/kg.

MW: Quantity[ndarray[tuple[int]]]: Molecular weights in kg/mol.

Nij: ndarray[tuple[int, int]]: Array containing the group decomposition data for each compound.

Pc: Quantity[ndarray[tuple[int]]]: Critical pressure in Pa.

Tb: Quantity[ndarray[tuple[int]]]: Boiling temperature in K.

Tc: Quantity[ndarray[tuple[int]]]: Critical temperature in K.

Tm: Quantity[ndarray[tuple[int]]]: Melting temperature in K.

Vc: Quantity[ndarray[tuple[int]]]: Critical volume in m^3/mol.

Vm_stp: Quantity[ndarray[tuple[int]]]: Molar liquid volume at 298 K in m^3/mol.

X2Y(Xi)

Calculate the mass fractions from the mole fractions of each component.

Parameters:: Xi (Quantity[ndarray[tuple[int]]]) – Mole fractions of each compound.
Returns:: num_compounds,).
Return type:: Mass fractions of the compounds (shape

Y2X(Yi)

Calculate the mole fractions from the mass fractions of each component.

Parameters:: Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound.
Returns:: num_compounds,).
Return type:: Mole fractions of the compounds (shape

__init__(name, decompName=None, fuelDataDir=None)

Initialize Fuel object and pre-compute GCM properties.

Parameters:

name (str) – Name of the mixture as it appears in its gcData file.
decompName (str | None) – Name of the groupDecomposition file if different from name. Defaults to None.
fuelDataDir (str | None) – Directory where the fuel data is stored. If None, uses built-in embedded data.

Raises:

ValueError – If a GCM property cannot be found.

Return type:

None

compounds: list[str]: List of compound names.

density(T, comp_idx=None)

Calculate the density of each component at temperature T.

Parameters:

T (Quantity[float]) – Temperature of the mixture in Kelvin.
comp_idx (int | None) – Index of compound to calculate property for.

Returns:

Density of each compound in kg/m^3.

Return type:

Quantity[ndarray[tuple[int]]]

diffusion_coeff(p, T, sigma_gas=Quantity(3.62, 'angstrom'), epsilonByKB_gas=Quantity(97.0, 'kelvin'), MW_gas=Quantity(0.02897, 'kilogram / mole'), correlation='Tee')

Compute diffusion coefficients using Lennard-Jones parameters.

Uses Wilke and Lee method (Poling, equation 11-4.1). Ambient gas defaults to air parameters.

Parameters:

p (Quantity[float]) – Pressure in Pa.
T (Quantity[float]) – Temperature to compute property.
sigma_gas (Quantity[float]) – Collision diameter in m.
epsilonByKB_gas (Quantity[float]) – Well depth over Boltzmann constant, in K.
MW_gas (Quantity[float]) – Mean molecular weight of ambient gas in kg/mol.
correlation (Literal['Tee', 'Wilke']) – Method to calculate sigma and epsilon (“Tee” or “Wilke”).

Returns:

Diffusion coefficient.

Return type:

Quantity[ndarray[tuple[int]]]

epsilonByKB: Quantity[ndarray[tuple[int]]]: Lennard-Jones well depth over Boltzmann constant in K.

fam: ndarray[tuple[int]]

Hydrocarbon family codes for thermal conductivity.

Code	Hydrocarbon Family
0	saturated
1	aromatics
2	cycloparaffins
3	olefins

formulas: ndarray[tuple[int]] | None: Molecular formulas of the fuel components, if available.

fuelDataDecompDir: str: Directory containing the group decomposition data.

fuelDataDir: str: Directory containing the fuel data.

fuelDataGcDir: str: Directory containing the gas chromatography data.

fuelDataPropsDir: str: Directory containing the fuel properties data.

gcmTableFile: str: File containing the GCM table data.

gcxgcFile: str: File containing the GCxGC compositional data for this fuel.

groupDecompFile: str: File containing the group decomposition data for this fuel.

hc_type: ndarray[tuple[int]]

Hydrocarbon types for each compound:

“n-alkane”
“iso-alkane”
“alkene”
“cyclo-alkane”
“aromatic”

latent_heat_vaporization(T, comp_idx=None)

Calculate latent heat of vaporization adjusted for temperature.

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.

Returns:

Latent heat of vaporization in J/kg.

Return type:

Quantity[ndarray[tuple[int]]]

mass2X(mass)

Calculate the mole fractions from the mass of each component.

Parameters:: mass (Quantity[ndarray[tuple[int]]]) – Mass of each compound.
Returns:: num_compounds,).
Return type:: Mole fractions of the compounds (shape

mass2Y(mass)

Calculate the mass fractions from the mass of each component.

Parameters:: mass (Quantity[ndarray[tuple[int]]]) – Mass of each compound.
Returns:: num_compounds,).
Return type:: Mass fractions of the compounds (shape

mean_molecular_weight(Yi)

Calculate the mean molecular weight of the mixture.

Parameters:: Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound.
Returns:: Mean molecular weight of the mixture in kg/mol.
Return type:: Quantity[float]

mixture_density(Yi, T)

Calculate mixture density at a given temperature.

Parameters:

Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound.
T (Quantity[float]) – Temperature to compute property.

Returns:

Mixture density in kg/m^3.

Return type:

Quantity[ndarray[tuple[int]]]

mixture_dynamic_viscosity(Yi, T, correlation='Kendall-Monroe')

Calculate dynamic viscosity of the mixture.

Parameters:

Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound.
T (Quantity[float]) – Temperature to compute property.
correlation (Literal['Kendall-Monroe', 'Arrhenius']) – Mixing model (“Kendall-Monroe” or “Arrhenius”).

Returns:

Mixture dynamic viscosity in Pa*s.

Return type:

Quantity[float]

mixture_kinematic_viscosity(Yi, T, correlation='Kendall-Monroe')

Calculate kinematic viscosity of the mixture.

Uses Kendall-Monroe (default) or Arrhenius mixing correlations.

Parameters:

Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound.
T (Quantity[float]) – Temperature to compute property.
correlation (Literal['Kendall-Monroe', 'Arrhenius']) – Mixing model (“Kendall-Monroe” or “Arrhenius”).

Returns:

Mixture kinematic viscosity in m^2/s.

Return type:

Quantity[float]

mixture_surface_tension(Yi, T, correlation='Brock-Bird')

Calculate surface tension of the mixture.

Uses arithmetic pseudo-property method recommended by Hugill and van Welsenes (1986).

Parameters:

Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound in the mixture.
T (Quantity[float]) – Temperature to compute property.
correlation (Literal['Pitzer', 'Brock-Bird']) – Correlation method (“Pitzer” or “Brock-Bird”).

Returns:

Mixture surface tension in N/m.

Return type:

Quantity[float]

mixture_thermal_conductivity(Yi, T)

Calculate thermal conductivity of the mixture.

Parameters:

Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound in the mixture.
T (Quantity[float]) – Temperature to compute property.

Returns:

Thermal conductivity in W/m/K.

Return type:

Quantity[float]

mixture_vapor_pressure(Yi, T, correlation='Lee-Kesler')

Calculate vapor pressure of the mixture.

Parameters:

Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound in the mixture.
T (Quantity[float]) – Temperature to compute property.
correlation (Literal['Ambrose-Walton', 'Lee-Kesler']) – Correlation method (“Ambrose-Walton” or “Lee-Kesler”).

Returns:

Mixture vapor pressure in Pa.

Return type:

Quantity[float]

mixture_vapor_pressure_antoine_coeffs(Yi, Tvals=None, units='mks', correlation='Lee-Kesler')

Estimate Antoine coefficients for vapor pressure of the mixture.

Parameters:

Yi (Quantity[ndarray[tuple[int]]]) – Mass fractions of each compound in the mixture.
Tvals (Quantity[ndarray[tuple[int]]] | None) – Temperature range or nodes for Antoine fit in Kelvin (default [273.15, min(Tb)]).
units (Literal['mks', 'cgs', 'dyne/cm^2', 'Pa']) – Units for pressure in fit (“mks”, “cgs”).
correlation (Literal['Ambrose-Walton', 'Lee-Kesler']) – Correlation method (“Ambrose-Walton” or “Lee-Kesler”).

Returns:

Coefficients A, B, C, D.

Raises:

ValueError – If units or Tvals are invalid.

Return type:

tuple[float, float, float, float]

molar_liquid_vol(T, comp_idx=None)

Compute molar liquid volume with temperature correction.

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.

Returns:

Molar liquid volume in m^3/mol.

Return type:

Quantity[ndarray[tuple[int]]]

nC: ndarray[tuple[int]]: Number of carbon atoms in each compound.

nH: ndarray[tuple[int]]: Number of hydrogen atoms in each compound.

name: str: Name of the fuel/mixture.

num_compounds: int: Number of compounds in the fuel mixture.

num_groups: int: Number of functional groups considered in the decomposition.

omega: Quantity[ndarray[tuple[int]]]: Accentric factor (dimensionless).

pelephysics_keys: ndarray[tuple[int]] | None: PelePhysics keys for the fuel components, if available.

psat(T, comp_idx=None, correlation='Lee-Kesler')

Compute saturated vapor pressure.

Can use Ambrose-Walton or Lee-Kesler correlations (default Lee-Kesler).

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.
correlation (Literal['Ambrose-Walton', 'Lee-Kesler']) – Correlation method (“Ambrose-Walton” or “Lee-Kesler”).

Returns:

Saturated vapor pressure in Pa.

Return type:

Quantity[ndarray[tuple[int]]]

psat_antoine_coeffs(Tvals=None, units='mks', correlation='Lee-Kesler')

Estimate Antoine coefficients for vapor pressure of an individual compound.

Parameters:

Tvals (Quantity[ndarray[tuple[int]]] | None) – Temperature range or nodes for Antoine fit in Kelvin (default [273.15, Tb_i]).
units (Literal['mks', 'cgs', 'dyne/cm^2', 'Pa']) – Units for pressure in fit (“mks”, “cgs”).
correlation (Literal['Ambrose-Walton', 'Lee-Kesler']) – Correlation method (“Ambrose-Walton” or “Lee-Kesler”).

Returns:

Coefficients A, B, C, D for each compound.

Raises:

ValueError – If units or Tvals are invalid.

Return type:

tuple[ndarray[tuple[int]], ndarray[tuple[int]], ndarray[tuple[int]], ndarray[tuple[int]]]

sigma: Quantity[ndarray[tuple[int]]]: Lennard-Jones collision diameter in m.

surface_tension(T, comp_idx=None, correlation='Brock-Bird')

Calculate surface tension of each compound at a given temperature.

Uses Brock-Bird (default) or Pitzer correlations (Poling 12-3.5, 12-3.7).

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.
correlation (Literal['Brock-Bird', 'Pitzer']) – Correlation method (“Brock-Bird” or “Pitzer”).

Returns:

Surface tension in N/m.

Return type:

Quantity[ndarray[tuple[int]]]

thermal_conductivity(T, comp_idx=None)

Calculate thermal conductivity at a given temperature.

Uses Latini et al. method (Poling equation 10-9.1).

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.

Returns:

Thermal conductivity in W/m/K.

Return type:

Quantity[ndarray[tuple[int]]]

viscosity_dynamic(T, comp_idx=None)

Calculate liquid dynamic viscosity based on droplet temperature and density.

Uses Dutt’s equation (4.23) for kinematic viscosity, combined with density.

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.

Returns:

Dynamic viscosity in Pa*s.

Return type:

Quantity[ndarray[tuple[int]]]

viscosity_kinematic(T, comp_idx=None)

Calculate the viscosity using Dutt’s equation.

Uses Dutt’s equation (4.23) from “Viscosity of Liquids”. The equation predicts viscosity in mm^2/s and is converted to SI units.

Parameters:

T (Quantity[float]) – Temperature to compute property.
comp_idx (int | None) – Index of compound to calculate property for.

Returns:

Viscosity of each component in m^2/s.

Return type:

Quantity[ndarray[tuple[int]]]