rizer.thermal_plasma.fit_LTE_data#
Attributes#
Classes#
Load and process the data for thermal plasma analytical model. |
Module Contents#
- class rizer.thermal_plasma.fit_LTE_data.FitLTEData(gas_name_transport: str, gas_name_radiation: str, pressure_atm: int, source_transport: str, source_radiation: str, emission_radius_mm: int, max_temperature_fit: float | None, skip_missing_values: bool = False, fit_all: bool = True)#
Load and process the data for thermal plasma analytical model.
This class is responsible for loading and processing the data needed for the thermal plasma analytical model, including both transport and radiation data.
Methods include fitting the electrical conductivity, enthalpy, and Net Emission Coefficient (NEC) to linear functions of the integrated thermal conductivity.
- Parameters:
gas_name_transport (
str) – Gas used for the transport data.gas_name_radiation (
str) – Gas used for the radiation data. Could be different from the transport gas.pressure_atm (
int) – Pressure in atm, for the transport and radiation data.source_transport (
str) – Source used for the transport data.source_radiation (
str) – Source used for the radiation data.plasma_radius_radiation_mm (
int) – Plasma radius in mm, for the radiation data.max_temperature_fit (
float | None) – Fit parameters up to this temperature. If None, no limit is applied.skip_missing_values (
bool, optional) – If True, skip missing values in the thermo-transport data, by default False.fit_all (
bool, optional) – If True, fit all the parameters upon initialization, by default True.
Examples
Use Stine-Watson model for a DC thermal plasma in H₂.
Use Stine-Watson model for a DC thermal plasma in H₂.- thermo_transport_data#
- radiation_data#
- idx_high_temp#
- fit_electrical_conductivity(sigma_cutoff: float = 100.0, plot_fit: bool = True) tuple[float, float]#
Fit the electrical conductivity.
The electrical conductivity is fitted to a linear function for the data above the cutoff.
- Parameters:
sigma_cutoff (
float, optional) – Cutoff for the electrical conductivity, by default 100.0 S/m.plot_fit (
bool, optional) – If True, plot the fit, by default True.
- Returns:
Fitted parameters:
\(a_\sigma\) in (S/m)/(W.m^-1)
\(\theta_\sigma\) in W.m^-1
- Return type:
tuple[float,float]
Notes
The electrical conductivity \(\sigma\) is assumed to be linear above the cutoff:
\[\begin{split}\sigma(\theta)= \begin{cases} 0 & \text { for } \theta<\theta_\sigma \\ a_\sigma\left(\theta-\theta_\sigma\right) & \text { for } \theta>\theta_\sigma \end{cases}\end{split}\]where:
\(\theta\) is the thermal conductivity in W.m^-1.K^-1,
\(a_\sigma\) is the electrical conductivity coefficient in (S/m)/(W.m^-1),
\(\theta_\sigma\) is the electrical conductivity threshold in W.m^-1,
\(\sigma\) is the electrical conductivity in S/m.
- fit_enthalpy(plot_fit: bool = True) float#
Fit the enthalpy.
- Parameters:
plot_fit (
bool, optional) – If True, plot the fit, by default True.- Returns:
Fitted parameter \(a_h\) in (J/kg)/(W.m^-1).
- Return type:
float
Notes
The enthalpy \(h\) is assumed to be linear with respect to the integrated thermal conductivity:
\[h(\theta) = a_h \theta\]where:
\(\theta\) is the thermal conductivity in W.m^-1.K^-1,
\(a_h\) is the enthalpy coefficient in (J/kg)/(W.m^-1),
\(h\) is the enthalpy in J/kg.
- fit_nec(theta_sigma: float | None = None, plot_fit: bool = True) float#
Fit the Net Emission Coefficient (NEC).
- Parameters:
theta_sigma (
float | None, optional) – If provided, use this value for the cutoff in thermal conductivity. If None, use the previously fitted value from fit_electrical_conductivity.plot_fit (
bool, optional) – If True, plot the fit, by default True.
- Returns:
Fitted parameter \(a_\varepsilon\) in (W.m^-3.sr^-1)/(W.m^-1).
- Return type:
float
Notes
The NEC is assumed to be linear is assumed to be linear above the SAME cutoff as the electrical conductivity:
\[\begin{split}\varepsilon_N(\theta)= \begin{cases} 0 & \text { for } \theta<\theta_\sigma \\ a_{\varepsilon}\left(\theta-\theta_\sigma\right) & \text { for } \theta>\theta_\sigma \end{cases}\end{split}\]where:
\(\theta\) is the thermal conductivity in W.m^-1.K^-1,
\(a_\varepsilon\) is the NEC coefficient in (W.m^-3.sr^-1)/(W.m^-1),
\(\theta_\sigma\) is the electrical conductivity threshold in W.m^-1,
\(\varepsilon_N\) is the NEC in W.m^-3.sr^-1.
- fit_all(plot_fit: bool = True) tuple[float, float, float, float]#
Fit all the parameters and plot the fits.
- Parameters:
plot_fit (
bool, optional) – If True, plot the fits, by default True.- Returns:
Fitted parameters:
\(a_\sigma\) in (S/m)/(W.m^-1)
\(\theta_\sigma\) in W.m^-1
\(a_h\) in (J/kg)/(W.m^-1)
\(a_\varepsilon\) in (W.m^-3.sr^-1)/(W.m^-1)
- Return type:
tuple[float,float,float,float]
- rizer.thermal_plasma.fit_LTE_data.H2_lte_data#