pmutt.empirical.nasa.SingleNasa9

class pmutt.empirical.nasa.SingleNasa9(T_low, T_high, a)

Bases: EmpiricalBase

Stores the NASA9 polynomial for a defined interval. Inherits from EmpiricalBase

T_low

Lower temperature bound (in K)

Type:: float

T_high

High temperature bound (in K)

Type:: float

a

NASA9 polynomial to use between T_low and T_high

Type:: (9,) numpy.ndarray

__init__(T_low, T_high, a)

Methods

`__init__`(T_low, T_high, a)
`compare_CpoR`([T])	Compares the dimensionless heat capacity of the statistical model and the empirical model
`compare_GoRT`([T])	Compares the dimensionless Gibbs energy of the statistical model and the empirical model
`compare_HoRT`([T])	Compares the dimensionless enthalpy of the statistical model and the empirical model
`compare_SoR`([T])	Compares the dimensionless entropy of the statistical model and the empirical model
`from_dict`(json_obj)	Recreate an object from the JSON representation.
`get_Cp`(units, **kwargs)	Calculate the heat capacity (constant P)
`get_CpoR`(T)	Calculate the dimensionless heat capacity
`get_Cv`(units, **kwargs)	Calculate the heat capacity (constant V)
`get_CvoR`()	Default method to calculate the dimensionless heat capacity at constant volume.
`get_F`(units[, T])	Calculate the Helmholtz energy
`get_FoRT`(**kwargs)	Calculates the dimensionless Helmholtz energy
`get_G`(units[, T])	Calculate the Gibbs energy
`get_GoRT`(**kwargs)	Calculates the dimensionless Gibbs free energy
`get_H`(units[, T])	Calculate the enthalpy
`get_HoRT`(T)	Calculate the dimensionless enthalpy
`get_S`(units, **kwargs)	Calculate the entropy
`get_SoR`(T)	Calculate the dimensionless heat capacity
`get_U`(units[, T])	Calculate the internal energy
`get_UoRT`()	Default method to calculate the dimensionless internal energy.
`get_q`()	Default method to calculate the partition coefficient.
`plot_empirical`([T_low, T_high, Cp_units, ...])	Plots the thermodynamic profiles between `T_low` and `T_high` using empirical relationship
`plot_statmech`([T_low, T_high, Cp_units, ...])	Plots the thermodynamic profiles between `T_low` and `T_high` using empirical relationship
`plot_statmech_and_empirical`([T_low, T_high, ...])	Plots the thermodynamic profiles between `T_low` and `T_high` using empirical relationship
`to_cti`([line_indent])	Writes the object in Cantera's CTI format.
`to_dict`()	Represents object as dictionary with JSON-accepted datatypes

compare_CpoR(T=None)

Compares the dimensionless heat capacity of the statistical model and the empirical model

Parameters:

T ((N,) numpy.ndarray or float, optional) – Temperatures (in K) to calculate CpoR. If None, generates a list of temperatures between self.T_low and self.T_high

Returns:

T ((N,) numpy.ndarray or float) – Temperatures in K
CpoR_model ((N,) numpy.ndarray or float) – Dimensionless heat capacity of original model
CpoR_empirical (((N,) numpy.ndarray or float) – Dimensionless heat capacity of empirical model

compare_GoRT(T=None)

Compares the dimensionless Gibbs energy of the statistical model and the empirical model

Parameters:

T ((N,) numpy.ndarray or float, optional) – Temperatures (in K) to calculate CpoR. If None, generates a list of temperatures between self.T_low and self.T_high

Returns:

T ((N,) numpy.ndarray or float) – Temperatures in K
CpoR_model ((N,) numpy.ndarray or float) – Dimensionless heat capacity of original model
CpoR_empirical ((N,) numpy.ndarray or float) – Dimensionless heat capacity of empirical model

compare_HoRT(T=None)

Compares the dimensionless enthalpy of the statistical model and the empirical model

Parameters:

T ((N,) numpy.ndarray or float, optional) – Temperatures (in K) to calculate CpoR. If None, generates a list of temperatures between self.T_low and self.T_high

Returns:

T ((N,) numpy.ndarray or float) – Temperatures in K
CpoR_model ((N,) numpy.ndarray or float) – Dimensionless heat capacity of original model
CpoR_empirical (((N,) numpy.ndarray or float) – Dimensionless heat capacity of empirical model

compare_SoR(T=None)

Compares the dimensionless entropy of the statistical model and the empirical model

Parameters:

T ((N,) numpy.ndarray or float, optional) – Temperatures (in K) to calculate CpoR. If None, generates a list of temperatures between self.T_low and self.T_high

Returns:

T ((N,) numpy.ndarray or float) – Temperatures in K
CpoR_model ((N,) numpy.ndarray or float) – Dimensionless heat capacity of original model
CpoR_empirical (((N,) numpy.ndarray or float) – Dimensionless heat capacity of empirical model

classmethod from_dict(json_obj)

Recreate an object from the JSON representation.

Parameters:: json_obj (dict) – JSON representation
Returns:: Nasa
Return type:: Nasa object

get_Cp(units, **kwargs)

Calculate the heat capacity (constant P)

Parameters:

units (str) – Units as string. See R() for accepted units.
kwargs (keyword arguments) – Parameters needed by get_CpoR

Returns:

Cp – Heat capacity (constant P) in appropriate units

Return type:

float

get_CpoR(T)

Calculate the dimensionless heat capacity

Parameters:: T (float or (N,) numpy.ndarray) – Temperature(s) in K
Returns:: CpoR – Dimensionless heat capacity
Return type:: float or (N,) numpy.ndarray

get_Cv(units, **kwargs)

Calculate the heat capacity (constant V)

Parameters:

units (str) – Units as string. See R() for accepted units.
kwargs (keyword arguments) – Parameters needed by get_CvoR

Returns:

Cv – Heat capacity (constant V) in appropriate units

Return type:

float

get_CvoR()

Default method to calculate the dimensionless heat capacity at constant volume.

Returns:: CvoR – Returns 0
Return type:: float

get_F(units, T=298.15, **kwargs)

Calculate the Helmholtz energy

Parameters:

units (str) – Units as string. See R() for accepted units but omit the ‘/K’ (e.g. J/mol).
T (float, optional) – Temperature in K. Default is 298.15 K
kwargs (keyword arguments) – Parameters needed by get_FoRT

Returns:

F – Hemholtz energy in appropriate units

Return type:

float

get_FoRT(**kwargs)

Calculates the dimensionless Helmholtz energy

Parameters:: kwargs (keyword arguments) – Parameters needed by get_UoRT and get_SoR
Returns:: FoRT – Dimensionless Helmholtz energy
Return type:: float

get_G(units, T=298.15, **kwargs)

Calculate the Gibbs energy

Parameters:

units (str) – Units as string. See R() for accepted units but omit the ‘/K’ (e.g. J/mol).
T (float, optional) – Temperature in K. Default is 298.15 K
kwargs (keyword arguments) – Parameters needed by get_GoRT

Returns:

G – Gibbs energy in appropriate units

Return type:

float

get_GoRT(**kwargs)

Calculates the dimensionless Gibbs free energy

Parameters:: kwargs (keyword arguments) – Parameters needed by get_HoRT and get_SoR
Returns:: GoRT – Dimensionless Gibbs free energy
Return type:: float

get_H(units, T=298.15, **kwargs)

Calculate the enthalpy

Parameters:

units (str) – Units as string. See R() for accepted units but omit the ‘/K’ (e.g. J/mol).
T (float, optional) – Temperature in K. Default is 298.15 K
kwargs (keyword arguments) – Parameters needed by get_HoRT

Returns:

H – Enthalpy in appropriate units

Return type:

float

get_HoRT(T)

Calculate the dimensionless enthalpy

Parameters:: T (float or (N,) numpy.ndarray) – Temperature(s) in K
Returns:: HoRT – Dimensionless enthalpy
Return type:: float or (N,) numpy.ndarray

get_S(units, **kwargs)

Calculate the entropy

Parameters:

units (str) – Units as string. See R() for accepted units.
kwargs (keyword arguments) – Parameters needed by get_SoR

Returns:

S – Entropy in appropriate units

Return type:

float

get_SoR(T)

Calculate the dimensionless heat capacity

Parameters:: T (float or (N,) numpy.ndarray) – Temperature(s) in K
Returns:: CpoR – Dimensionless heat capacity
Return type:: float or (N,) numpy.ndarray

get_U(units, T=298.15, **kwargs)

Calculate the internal energy

Parameters:

units (str) – Units as string. See R() for accepted units but omit the ‘/K’ (e.g. J/mol).
T (float, optional) – Temperature in K. Default is 298.15 K
kwargs (keyword arguments) – Parameters needed by get_UoRT

Returns:

U – Internal energy in appropriate units

Return type:

float

get_UoRT()

Default method to calculate the dimensionless internal energy.

Returns:: UoRT – Returns 0
Return type:: float

get_q()

Default method to calculate the partition coefficient.

Returns:: q – Returns 1
Return type:: float

plot_empirical(T_low=None, T_high=None, Cp_units=None, H_units=None, S_units=None, G_units=None)

Plots the thermodynamic profiles between T_low and T_high using empirical relationship

Parameters:

T_low (float) – Lower temperature in K. If not specified, T_low attribute used.
T_high (float) – Upper temperature in K. If not specified, T_high attribute used.
Cp_units (str) – Units to plot heat capacity. See R() for accepted units. If not specified, dimensionless units used.
H_units (str) – Units to plot enthalpy. See R() for accepted units but omit the ‘/K’ (e.g. J/mol). If not specified, dimensionless units used.
S_units (str) – Units to plot entropy. See R() for accepted units. If not specified, dimensionless units used.
G_units (str) – Units to plot Gibbs free energy. See R() for accepted units but omit the ‘/K’ (e.g. J/mol). If not specified, dimensionless units used.

Returns:

figure (matplotlib.figure.Figure) – Figure
axes (tuple of matplotlib.axes.Axes.axis) – Axes of the plots. 0. Cp 1. H 2. S 3. G

plot_statmech(T_low=None, T_high=None, Cp_units=None, H_units=None, S_units=None, G_units=None, use_references=True)

Plots the thermodynamic profiles between T_low and T_high using empirical relationship

Parameters:

T_low (float) – Lower temperature in K. If not specified, T_low attribute used
T_high (float) – Upper temperature in K. If not specified, T_high attribute used
Cp_units (str) – Units to plot heat capacity. See R() for accepted units. If not specified, dimensionless units used.
H_units (str) – Units to plot enthalpy. See R() for accepted units but omit the ‘/K’ (e.g. J/mol). If not specified, dimensionless units used.
S_units (str) – Units to plot entropy. See R() for accepted units. If not specified, dimensionless units used.
G_units (str) – Units to plot Gibbs free energy. See R() for accepted units but omit the ‘/K’ (e.g. J/mol). If not specified, dimensionless units used.

Returns:

figure (matplotlib.figure.Figure) – Figure
axes (tuple of matplotlib.axes.Axes.axis) – Axes of the plots. 0. Cp 1. H 2. S 3. G

plot_statmech_and_empirical(T_low=None, T_high=None, Cp_units=None, H_units=None, S_units=None, G_units=None, use_references=True)

Plots the thermodynamic profiles between T_low and T_high using empirical relationship

Parameters:

T_low (float) – Lower temperature in K. If not specified, T_low attribute used
T_high (float) – Upper temperature in K. If not specified, T_high attribute used
Cp_units (str) – Units to plot heat capacity. See R() for accepted units. If not specified, dimensionless units used.
H_units (str) – Units to plot enthalpy. See R() for accepted units but omit the ‘/K’ (e.g. J/mol). If not specified, dimensionless units used.
S_units (str) – Units to plot entropy. See R() for accepted units. If not specified, dimensionless units used.
G_units (str) – Units to plot Gibbs free energy. See R() for accepted units but omit the ‘/K’ (e.g. J/mol). If not specified, dimensionless units used.

Returns:

figure (matplotlib.figure.Figure) – Figure
axes (tuple of matplotlib.axes.Axes.axis) – Axes of the plots. 0. Cp 1. H 2. S 3. G

to_cti(line_indent=False)

Writes the object in Cantera’s CTI format.

Parameters:: line_indent (bool, optional) – If True, the first line is indented by 16 spaces. Default is False
Returns:: CTI_str – Object represented as a CTI string.
Return type:: str

to_dict()

Represents object as dictionary with JSON-accepted datatypes

Returns:: obj_dict
Return type:: dict