Source code for thermo.heat_capacity

'''Chemical Engineering Design Library (ChEDL). Utilities for process modeling.
Copyright (C) 2016, 2017, 2018, 2019, 2020 Caleb Bell <Caleb.Andrew.Bell@gmail.com>

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SOFTWARE.

This module contains implementations of :obj:`TDependentProperty <thermo.utils.TDependentProperty>`
representing liquid, vapor, and solid heat capacity. A variety of estimation
and data methods are available as included in the `chemicals` library.
Additionally liquid, vapor, and solid mixture heat capacity predictor objects
are implemented subclassing  :obj:`MixtureProperty <thermo.utils.MixtureProperty>`.

For reporting bugs, adding feature requests, or submitting pull requests,
please use the `GitHub issue tracker <https://github.com/CalebBell/thermo/>`_.


.. contents:: :local:

Pure Liquid Heat Capacity
=========================
.. autoclass:: HeatCapacityLiquid
    :members: calculate, test_method_validity,
              name, property_max, property_min,
              units, ranked_methods
    :undoc-members:
    :show-inheritance:
    :exclude-members:

.. autodata:: heat_capacity_liquid_methods

Pure Gas Heat Capacity
======================
.. autoclass:: HeatCapacityGas
    :members: calculate, test_method_validity,
              name, property_max, property_min,
              units, ranked_methods
    :undoc-members:
    :show-inheritance:
    :exclude-members:

.. autodata:: heat_capacity_gas_methods

Pure Solid Heat Capacity
========================
.. autoclass:: HeatCapacitySolid
    :members: calculate, test_method_validity,
              name, property_max, property_min,
              units, ranked_methods
    :undoc-members:
    :show-inheritance:
    :exclude-members:

.. autodata:: heat_capacity_solid_methods

Mixture Liquid Heat Capacity
============================
.. autoclass:: HeatCapacityLiquidMixture
    :members: calculate, test_method_validity,
              name, property_max, property_min,
              units, Tmin, Tmax, ranked_methods
    :undoc-members:
    :show-inheritance:
    :exclude-members:

.. autodata:: heat_capacity_liquid_mixture_methods


Mixture Gas Heat Capacity
=========================
.. autoclass:: HeatCapacityGasMixture
    :members: calculate, test_method_validity,
              name, property_max, property_min,
              units, Tmin, Tmax, ranked_methods
    :undoc-members:
    :show-inheritance:
    :exclude-members:

.. autodata:: heat_capacity_gas_mixture_methods

Mixture Solid Heat Capacity
===========================
.. autoclass:: HeatCapacitySolidMixture
    :members: calculate, test_method_validity,
              name, property_max, property_min,
              units, Tmin, Tmax, ranked_methods
    :undoc-members:
    :show-inheritance:
    :exclude-members:

.. autodata:: heat_capacity_solid_mixture_methods

'''


__all__ = ['heat_capacity_gas_methods',
           'HeatCapacityGas',
           'heat_capacity_liquid_methods',
           'HeatCapacityLiquid',
           'heat_capacity_solid_methods',
           'HeatCapacitySolid', 'HeatCapacitySolidMixture',
           'HeatCapacityGasMixture', 'HeatCapacityLiquidMixture']
from chemicals import heat_capacity, miscdata
from chemicals.heat_capacity import (
    Dadgostar_Shaw,
    Dadgostar_Shaw_integral,
    Dadgostar_Shaw_integral_over_T,
    Lastovka_Shaw,
    Lastovka_Shaw_integral,
    Lastovka_Shaw_integral_over_T,
    Lastovka_Shaw_term_A,
    Lastovka_solid,
    Lastovka_solid_integral,
    Lastovka_solid_integral_over_T,
    Rowlinson_Bondi,
    Rowlinson_Poling,
    TRCCp,
    TRCCp_integral,
    TRCCp_integral_over_T,
)
from chemicals.identifiers import CAS_to_int
from chemicals.miscdata import JOBACK, lookup_VDI_tabular_data
from chemicals.utils import mixing_simple, property_mass_to_molar
from fluids.constants import R, calorie
from fluids.numerics import horner, isnan, log, quad

from thermo import electrochem
from thermo.coolprop import (
    CoolProp_T_dependent_property,
    Cp_ideal_gas_Helmholtz,
    H_ideal_gas_Helmholtz,
    Helmholtz_A0_data,
    coolprop_dict,
    coolprop_fluids,
    has_CoolProp,
)
from thermo.electrochem import Laliberte_heat_capacity
from thermo.utils import COOLPROP, HEOS_FIT, LINEAR, UNARY, JANAF_FIT, VDI_TABULAR, MixtureProperty, TDependentProperty

TRCIG = 'TRCIG'
POLING_POLY = 'POLING_POLY'
POLING_CONST = 'POLING_CONST'
CRCSTD = 'CRCSTD'
LASTOVKA_SHAW = 'LASTOVKA_SHAW'
WEBBOOK_SHOMATE = 'WEBBOOK_SHOMATE'
heat_capacity_gas_methods = [HEOS_FIT, COOLPROP, TRCIG, WEBBOOK_SHOMATE, POLING_POLY, LASTOVKA_SHAW, CRCSTD,
                             POLING_CONST, JOBACK, VDI_TABULAR]
"""Holds all methods available for the :obj:`HeatCapacityGas` class, for use in
iterating over them."""


[docs]class HeatCapacityGas(TDependentProperty): r'''Class for dealing with gas heat capacity as a function of temperature. Consists of three coefficient-based methods, two constant methods, one tabular source, one simple estimator, one group-contribution estimator, one component specific method, and the external library CoolProp. Parameters ---------- CASRN : str, optional The CAS number of the chemical MW : float, optional Molecular weight, [g/mol] similarity_variable : float, optional similarity variable, n_atoms/MW, [mol/g] load_data : bool, optional If False, do not load property coefficients from data sources in files [-] extrapolation : str or None None to not extrapolate; see :obj:`TDependentProperty <thermo.utils.TDependentProperty>` for a full list of all options, [-] method : str or None, optional If specified, use this method by default and do not use the ranked sorting; an exception is raised if this is not a valid method for the provided inputs, [-] Notes ----- A string holding each method's name is assigned to the following variables in this module, intended as the most convenient way to refer to a method. To iterate over all methods, use the list stored in :obj:`heat_capacity_gas_methods`. **TRCIG**: A rigorous expression derived in [1]_ for modeling gas heat capacity. Coefficients for 1961 chemicals are available. **POLING_POLY**: Simple polynomials in [2]_ not suitable for extrapolation. Data is available for 308 chemicals. **COOLPROP**: CoolProp external library; with select fluids from its library. Range is limited to that of the equations of state it uses, as described in [3]_. The heat capacity and enthalpy are implemented analytically and fairly fast; the entropy integral has no analytical integral and so is numerical. CoolProp's amazing coefficient collection is used directly in Python. **LASTOVKA_SHAW**: A basic estimation method using the `similarity variable` concept; requires only molecular structure, so is very convenient. See :obj:`Lastovka_Shaw <chemicals.heat_capacity.Lastovka_Shaw>` for details. **CRCSTD**: Constant values tabulated in [4]_ at 298.15 K; data is available for 533 gases. **POLING_CONST**: Constant values in [2]_ at 298.15 K; available for 348 gases. **VDI_TABULAR**: Tabular data up to the critical point available in [5]_. Note that this data is along the saturation curve. **WEBBOOK_SHOMATE**: Shomate form coefficients from [6]_ for ~700 compounds. **JOBACK**: An estimation method for organic substances in [7]_ **HEOS_FIT**: A series of higher-order polynomial fits to the calculated results from fundamental helmholtz equations of state as calculated with REFPROP See Also -------- chemicals.heat_capacity.TRCCp chemicals.heat_capacity.Shomate chemicals.heat_capacity.Lastovka_Shaw chemicals.heat_capacity.Rowlinson_Poling chemicals.heat_capacity.Rowlinson_Bondi thermo.joback.Joback Examples -------- >>> CpGas = HeatCapacityGas(CASRN='142-82-5', MW=100.2, similarity_variable=0.2295) >>> CpGas(700) 317.305 References ---------- .. [1] Kabo, G. J., and G. N. Roganov. Thermodynamics of Organic Compounds in the Gas State, Volume II: V. 2. College Station, Tex: CRC Press, 1994. .. [2] Poling, Bruce E. The Properties of Gases and Liquids. 5th edition. New York: McGraw-Hill Professional, 2000. .. [3] Bell, Ian H., Jorrit Wronski, Sylvain Quoilin, and Vincent Lemort. "Pure and Pseudo-Pure Fluid Thermophysical Property Evaluation and the Open-Source Thermophysical Property Library CoolProp." Industrial & Engineering Chemistry Research 53, no. 6 (February 12, 2014): 2498-2508. doi:10.1021/ie4033999. http://www.coolprop.org/ .. [4] Haynes, W.M., Thomas J. Bruno, and David R. Lide. CRC Handbook of Chemistry and Physics. [Boca Raton, FL]: CRC press, 2014. .. [5] Gesellschaft, V. D. I., ed. VDI Heat Atlas. 2nd edition. Berlin; New York:: Springer, 2010. .. [6] Shen, V.K., Siderius, D.W., Krekelberg, W.P., and Hatch, H.W., Eds., NIST WebBook, NIST, http://doi.org/10.18434/T4M88Q .. [7] Joback, K.G., and R.C. Reid. "Estimation of Pure-Component Properties from Group-Contributions." Chemical Engineering Communications 57, no. 1-6 (July 1, 1987): 233-43. doi:10.1080/00986448708960487. ''' name = 'gas heat capacity' units = 'J/mol/K' interpolation_T = None """No interpolation transformation by default.""" interpolation_property = None """No interpolation transformation by default.""" interpolation_property_inv = None """No interpolation transformation by default.""" tabular_extrapolation_permitted = True """Allow tabular extrapolation by default; gases are fairly linear in heat capacity at high temperatures even if not low temperatures.""" property_min = 0 """Heat capacities have a minimum value of 0 at 0 K.""" property_max = 1E4 """Maximum valid of Heat capacity; arbitrarily set. For fluids very near the critical point, this value can be obscenely high.""" ranked_methods = [HEOS_FIT, TRCIG, WEBBOOK_SHOMATE, miscdata.JANAF, POLING_POLY, COOLPROP, JOBACK, LASTOVKA_SHAW, CRCSTD, POLING_CONST, VDI_TABULAR] """Default rankings of the available methods.""" _fit_force_n = {} """Dictionary containing method: fit_n, for use in methods which should only ever be fit to a specific `n` value""" _fit_force_n[CRCSTD] = 1 _fit_force_n[POLING_CONST] = 1 custom_args = ('MW', 'similarity_variable') _json_obj_by_CAS = ('webbook_shomate', 'CP_f') @classmethod def _load_json_CAS_references(cls, d): CASRN = d['CASRN'] if CASRN in heat_capacity.WebBook_Shomate_gases: d['webbook_shomate'] = heat_capacity.WebBook_Shomate_gases[CASRN] if 'CP_f' in d: d['CP_f'] = coolprop_fluids[CASRN] def __init__(self, CASRN='', MW=None, similarity_variable=None, extrapolation='linear', iscyclic_aliphatic=False, **kwargs): self.CASRN, self.MW, self.similarity_variable, self.iscyclic_aliphatic = CASRN, MW, similarity_variable, iscyclic_aliphatic super().__init__(extrapolation, **kwargs) def load_all_methods(self, load_data=True): r'''Method which picks out coefficients for the specified chemical from the various dictionaries and DataFrames storing it. All data is stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`, and :obj:`all_methods` as a set of methods for which the data exists for. Called on initialization only. See the source code for the variables at which the coefficients are stored. The coefficients can safely be altered once the class is initialized. This method can be called again to reset the parameters. ''' methods = [] self.all_methods = set() self.T_limits = T_limits = {} CASRN = self.CASRN if load_data and CASRN: CASRN_int = None if not CASRN else CAS_to_int(CASRN) jb_df = miscdata.joback_predictions if CASRN_int in jb_df.index: Cpg3 = float(jb_df.at[CASRN_int, 'Cpg3']) if not isnan(Cpg3): methods.append(JOBACK) self.joback_coeffs = [Cpg3, float(jb_df.at[CASRN_int, 'Cpg2']), float(jb_df.at[CASRN_int, 'Cpg1']), float(jb_df.at[CASRN_int, 'Cpg0'])] Tmin_jb, Tmax_jb = float(jb_df.at[CASRN_int, 'Tm']),float(jb_df.at[CASRN_int, 'Tc'])*2.5 # if isnan(Tmin_jb): Tmin_jb = 100.0 # The same groups are defined for Tm as for Cp, should never be a nan if isnan(Tmax_jb): Tmax_jb = 10000.0 T_limits[JOBACK] = (Tmin_jb, Tmax_jb) if CASRN in heat_capacity.WebBook_Shomate_gases: methods.append(WEBBOOK_SHOMATE) self.webbook_shomate = webbook_shomate = heat_capacity.WebBook_Shomate_gases[CASRN] T_limits[WEBBOOK_SHOMATE] = (webbook_shomate.Tmin, webbook_shomate.Tmax) if CASRN in heat_capacity.TRC_gas_data.index: methods.append(TRCIG) self.TRCIG_Tmin, self.TRCIG_Tmax, a0, a1, a2, a3, a4, a5, a6, a7, _, _, _ = heat_capacity.TRC_gas_values[heat_capacity.TRC_gas_data.index.get_loc(CASRN)].tolist() self.TRCIG_coefs = [a0, a1, a2, a3, a4, a5, a6, a7] T_limits[TRCIG] = (self.TRCIG_Tmin, self.TRCIG_Tmax) if CASRN in heat_capacity.Cp_data_Poling.index and not isnan(heat_capacity.Cp_data_Poling.at[CASRN, 'a0']): POLING_Tmin, POLING_Tmax, a0, a1, a2, a3, a4, Cpg, Cpl = heat_capacity.Cp_values_Poling[heat_capacity.Cp_data_Poling.index.get_loc(CASRN)].tolist() methods.append(POLING_POLY) if isnan(POLING_Tmin): POLING_Tmin = 50.0 if isnan(POLING_Tmax): POLING_Tmax = 1000.0 self.POLING_Tmin = POLING_Tmin self.POLING_Tmax = POLING_Tmax self.POLING_coefs = [a0, a1, a2, a3, a4] T_limits[POLING_POLY] = (POLING_Tmin, POLING_Tmax) if CASRN in heat_capacity.Cp_data_Poling.index and not isnan(heat_capacity.Cp_data_Poling.at[CASRN, 'Cpg']): methods.append(POLING_CONST) self.POLING_T = 298.15 self.POLING_constant = float(heat_capacity.Cp_data_Poling.at[CASRN, 'Cpg']) T_limits[POLING_CONST] = (self.POLING_T-50.0, self.POLING_T+50.0) if CASRN in heat_capacity.CRC_standard_data.index and not isnan(heat_capacity.CRC_standard_data.at[CASRN, 'Cpg']): methods.append(CRCSTD) self.CRCSTD_T = 298.15 self.CRCSTD_constant = float(heat_capacity.CRC_standard_data.at[CASRN, 'Cpg']) T_limits[CRCSTD] = (self.CRCSTD_T-50.0, self.CRCSTD_T+50.0) if CASRN in miscdata.VDI_saturation_dict: # NOTE: VDI data is for the saturation curve, i.e. at increasing # pressure; it is normally substantially higher than the ideal gas # value Ts, props = lookup_VDI_tabular_data(CASRN, 'Cp (g)') self.add_tabular_data(Ts, props, VDI_TABULAR, check_properties=False) del self._method if self.CASRN in heat_capacity.Cp_dict_JANAF_gas: methods.append(miscdata.JANAF) Ts, props = heat_capacity.Cp_dict_JANAF_gas[self.CASRN] self.add_tabular_data(Ts, props, miscdata.JANAF, check_properties=False) del self._method if has_CoolProp() and CASRN in coolprop_dict: methods.append(COOLPROP) self.CP_f = coolprop_fluids[CASRN] if CASRN in Helmholtz_A0_data: # We can do the fast calculation in Python CoolProp_dat = Helmholtz_A0_data[CASRN] A0_dat = CoolProp_dat['alpha0'] self.CoolProp_A0_args = (CoolProp_dat['Tc'], CoolProp_dat['R'], A0_dat.get('IdealGasHelmholtzLead_a1', 0.0), A0_dat.get('IdealGasHelmholtzLead_a2', 0.0), A0_dat.get('IdealGasHelmholtzLogTau_a', 0.0), A0_dat.get('IdealGasHelmholtzPlanckEinstein_ns', None), A0_dat.get('IdealGasHelmholtzPlanckEinstein_ts', None), A0_dat.get('IdealGasHelmholtzPower_ns', None), A0_dat.get('IdealGasHelmholtzPower_ts', None), A0_dat.get('IdealGasHelmholtzPlanckEinsteinGeneralized_ns', None), A0_dat.get('IdealGasHelmholtzPlanckEinsteinGeneralized_ts', None), A0_dat.get('IdealGasHelmholtzPlanckEinsteinGeneralized_cs', None), A0_dat.get('IdealGasHelmholtzPlanckEinsteinGeneralized_ds', None), ) Tmin = min(self.CP_f.Tt, self.CP_f.Tmin) Tmax = max(self.CP_f.Tc, self.CP_f.Tmax) else: # Use the more conservative limits to try to get CoolProp to solve self.CoolProp_A0_args = None Tmin = max(self.CP_f.Tt, self.CP_f.Tmin) Tmax = min(self.CP_f.Tc, self.CP_f.Tmax) T_limits[COOLPROP] = (Tmin, Tmax) if self.MW is not None and self.similarity_variable is not None: methods.append(LASTOVKA_SHAW) T_limits[LASTOVKA_SHAW] = (1e-3, 1e5) self.Lastovka_Shaw_term_A = Lastovka_Shaw_term_A(self.similarity_variable, self.iscyclic_aliphatic) self.all_methods.update(methods) @property def T_limits_fitting(self): values = self.T_limits.copy() if LASTOVKA_SHAW in values: values[LASTOVKA_SHAW] = (150, 3000) return values @staticmethod def _method_indexes(): '''Returns a dictionary of method: index for all methods that use data files to retrieve constants. The use of this function ensures the data files are not loaded until they are needed. ''' return {TRCIG: heat_capacity.TRC_gas_data.index, POLING_POLY: [i for i in heat_capacity.Cp_data_Poling.index if not isnan(heat_capacity.Cp_data_Poling.at[i, 'a0'])], POLING_CONST: [i for i in heat_capacity.Cp_data_Poling.index if not isnan(heat_capacity.Cp_data_Poling.at[i, 'Cpg'])], CRCSTD: [i for i in heat_capacity.CRC_standard_data.index if not isnan(heat_capacity.CRC_standard_data.at[i, 'Cpg'])], COOLPROP: coolprop_dict, VDI_TABULAR: list(miscdata.VDI_saturation_dict.keys()), }
[docs] def calculate(self, T, method): r'''Method to calculate surface tension of a liquid at temperature `T` with a given method. This method has no exception handling; see :obj:`T_dependent_property <thermo.utils.TDependentProperty.T_dependent_property>` for that. Parameters ---------- T : float Temperature at which to calculate heat capacity, [K] method : str Method name to use Returns ------- Cp : float Calculated heat capacity, [J/mol/K] ''' if method == TRCIG: Cp = TRCCp(T, *self.TRCIG_coefs) elif method == WEBBOOK_SHOMATE: Cp = self.webbook_shomate.force_calculate(T) elif method == JOBACK: Cp = horner(self.joback_coeffs, T) elif method == COOLPROP: if self.CoolProp_A0_args is not None: Cp = Cp_ideal_gas_Helmholtz(T, *self.CoolProp_A0_args) else: return CoolProp_T_dependent_property(T, self.CASRN, 'CP0MOLAR', 'g') elif method == POLING_POLY: Cp = R*(self.POLING_coefs[0] + self.POLING_coefs[1]*T + self.POLING_coefs[2]*T**2 + self.POLING_coefs[3]*T**3 + self.POLING_coefs[4]*T**4) elif method == POLING_CONST: Cp = self.POLING_constant elif method == CRCSTD: Cp = self.CRCSTD_constant elif method == LASTOVKA_SHAW: Cp = Lastovka_Shaw(T, self.similarity_variable, self.iscyclic_aliphatic, self.MW) else: return self._base_calculate(T, method) return Cp
[docs] def test_method_validity(self, T, method): r'''Method to test the validity of a specified method for a given temperature. 'TRC' and 'Poling' both have minimum and maimum temperatures. The constant temperatures in POLING_CONST and CRCSTD are considered valid for 50 degrees around their specified temperatures. :obj:`Lastovka_Shaw <chemicals.heat_capacity.Lastovka_Shaw>` is considered valid for the whole range of temperatures. It is not guaranteed that a method will work or give an accurate prediction simply because this method considers the method valid. Parameters ---------- T : float Temperature at which to determine the validity of the method, [K] method : str Name of the method to test Returns ------- validity : bool Whether or not a specifid method is valid ''' validity = True if method == POLING_CONST: if T > self.POLING_T + 50.0 or T < self.POLING_T - 50.0: return False elif method == CRCSTD: if T > self.CRCSTD_T + 50.0 or T < self.CRCSTD_T - 50.0: return False elif method == LASTOVKA_SHAW: pass # Valid everywhere elif method == COOLPROP: if T <= self.CP_f.Tmin or T >= self.CP_f.Tmax: return False else: return super().test_method_validity(T, method) return validity
def calculate_integral(self, T1, T2, method): r'''Method to calculate the integral of a property with respect to temperature, using a specified method. Implements the analytical integrals of all available methods except for tabular data. Parameters ---------- T1 : float Lower limit of integration, [K] T2 : float Upper limit of integration, [K] method : str Method for which to find the integral Returns ------- integral : float Calculated integral of the property over the given range, [`units*K`] ''' if method == TRCIG: H2 = TRCCp_integral(T2, *self.TRCIG_coefs) H1 = TRCCp_integral(T1, *self.TRCIG_coefs) return H2 - H1 elif method == WEBBOOK_SHOMATE: return self.webbook_shomate.force_calculate_integral(T1, T2) elif method == POLING_POLY: A, B, C, D, E = self.POLING_coefs H2 = (((((0.2*E)*T2 + 0.25*D)*T2 + C/3.)*T2 + 0.5*B)*T2 + A)*T2 H1 = (((((0.2*E)*T1 + 0.25*D)*T1 + C/3.)*T1 + 0.5*B)*T1 + A)*T1 return R*(H2 - H1) elif method == POLING_CONST: return (T2 - T1)*self.POLING_constant elif method == CRCSTD: return (T2 - T1)*self.CRCSTD_constant elif method == LASTOVKA_SHAW: similarity_variable = self.similarity_variable iscyclic_aliphatic = self.iscyclic_aliphatic MW = self.MW term_A = self.Lastovka_Shaw_term_A return ( Lastovka_Shaw_integral(T2, similarity_variable, iscyclic_aliphatic, MW, term_A) - Lastovka_Shaw_integral(T1, similarity_variable, iscyclic_aliphatic, MW, term_A) ) elif method == COOLPROP and self.CoolProp_A0_args is not None: return (H_ideal_gas_Helmholtz(T2, *self.CoolProp_A0_args) -H_ideal_gas_Helmholtz(T1, *self.CoolProp_A0_args)) else: return super().calculate_integral(T1, T2, method) def calculate_integral_over_T(self, T1, T2, method): r'''Method to calculate the integral of a property over temperature with respect to temperature, using a specified method. Implements the analytical integrals of all available methods except for tabular data. Parameters ---------- T1 : float Lower limit of integration, [K] T2 : float Upper limit of integration, [K] method : str Method for which to find the integral Returns ------- integral : float Calculated integral of the property over the given range, [`units`] ''' if method == TRCIG: S2 = TRCCp_integral_over_T(T2, *self.TRCIG_coefs) S1 = TRCCp_integral_over_T(T1, *self.TRCIG_coefs) return S2 - S1 elif method == WEBBOOK_SHOMATE: return self.webbook_shomate.force_calculate_integral_over_T(T1, T2) elif method == CRCSTD: return self.CRCSTD_constant*log(T2/T1) elif method == POLING_CONST: return self.POLING_constant*log(T2/T1) elif method == POLING_POLY: A, B, C, D, E = self.POLING_coefs S2 = ((((0.25*E)*T2 + D/3.)*T2 + 0.5*C)*T2 + B)*T2 S1 = ((((0.25*E)*T1 + D/3.)*T1 + 0.5*C)*T1 + B)*T1 return R*(S2-S1 + A*log(T2/T1)) elif method == LASTOVKA_SHAW: similarity_variable = self.similarity_variable iscyclic_aliphatic = self.iscyclic_aliphatic MW = self.MW term_A = self.Lastovka_Shaw_term_A return ( Lastovka_Shaw_integral_over_T(T2, similarity_variable, iscyclic_aliphatic, MW, term_A) - Lastovka_Shaw_integral_over_T(T1, similarity_variable, iscyclic_aliphatic, MW, term_A) ) return super().calculate_integral_over_T(T1, T2, method)
ZABRANSKY_SPLINE = 'ZABRANSKY_SPLINE' ZABRANSKY_QUASIPOLYNOMIAL = 'ZABRANSKY_QUASIPOLYNOMIAL' ZABRANSKY_SPLINE_C = 'ZABRANSKY_SPLINE_C' ZABRANSKY_QUASIPOLYNOMIAL_C = 'ZABRANSKY_QUASIPOLYNOMIAL_C' ZABRANSKY_SPLINE_SAT = 'ZABRANSKY_SPLINE_SAT' ZABRANSKY_QUASIPOLYNOMIAL_SAT = 'ZABRANSKY_QUASIPOLYNOMIAL_SAT' ROWLINSON_POLING = 'ROWLINSON_POLING' ROWLINSON_BONDI = 'ROWLINSON_BONDI' DADGOSTAR_SHAW = 'DADGOSTAR_SHAW' heat_capacity_liquid_methods = [HEOS_FIT, ZABRANSKY_SPLINE, ZABRANSKY_QUASIPOLYNOMIAL, ZABRANSKY_SPLINE_C, ZABRANSKY_QUASIPOLYNOMIAL_C, ZABRANSKY_SPLINE_SAT, ZABRANSKY_QUASIPOLYNOMIAL_SAT, WEBBOOK_SHOMATE, VDI_TABULAR, UNARY, ROWLINSON_POLING, ROWLINSON_BONDI, COOLPROP, DADGOSTAR_SHAW, POLING_CONST, CRCSTD] """Holds all methods available for the :obj:`HeatCapacityLiquid class`, for use in iterating over them."""
[docs]class HeatCapacityLiquid(TDependentProperty): r'''Class for dealing with liquid heat capacity as a function of temperature. Consists of seven coefficient-based methods, two constant methods, one tabular source, two CSP methods based on gas heat capacity, one simple estimator, and the external library CoolProp. Parameters ---------- CASRN : str, optional The CAS number of the chemical MW : float, optional Molecular weight, [g/mol] similarity_variable : float, optional similarity variable, n_atoms/MW, [mol/g] Tc : float, optional Critical temperature, [K] omega : float, optional Acentric factor, [-] Cpgm : float or callable, optional Idea-gas molar heat capacity at T or callable for the same, [J/mol/K] load_data : bool, optional If False, do not load property coefficients from data sources in files [-] extrapolation : str or None None to not extrapolate; see :obj:`TDependentProperty <thermo.utils.TDependentProperty>` for a full list of all options, [-] method : str or None, optional If specified, use this method by default and do not use the ranked sorting; an exception is raised if this is not a valid method for the provided inputs, [-] Notes ----- A string holding each method's name is assigned to the following variables in this module, intended as the most convenient way to refer to a method. To iterate over all methods, use the list stored in :obj:`heat_capacity_liquid_methods`. **ZABRANSKY_SPLINE, ZABRANSKY_QUASIPOLYNOMIAL, ZABRANSKY_SPLINE_C, and ZABRANSKY_QUASIPOLYNOMIAL_C**: Rigorous expressions developed in [1]_ following critical evaluation of the available data. The spline methods use the form described in :obj:`Zabransky_cubic <chemicals.heat_capacity.Zabransky_cubic>` over short ranges with varying coefficients to obtain a wider range. The quasi-polynomial methods use the form described in :obj:`Zabransky_quasi_polynomial <chemicals.heat_capacity.Zabransky_quasi_polynomial>`, more suitable for extrapolation, and over then entire range. Respectively, there is data available for 588, 146, 51, and 26 chemicals. 'C' denotes constant- pressure data available from more precise experiments. The others are heat capacity values averaged over a temperature changed. **ZABRANSKY_SPLINE_SAT and ZABRANSKY_QUASIPOLYNOMIAL_SAT**: Rigorous expressions developed in [1]_ following critical evaluation of the available data. The spline method use the form described in :obj:`Zabransky_cubic <chemicals.heat_capacity.Zabransky_cubic>` over short ranges with varying coefficients to obtain a wider range. The quasi-polynomial method use the form described in :obj:`Zabransky_quasi_polynomial <chemicals.heat_capacity.Zabransky_quasi_polynomial>`, more suitable for extrapolation, and over their entire range. Respectively, there is data available for 203, and 16 chemicals. Note that these methods are for the saturation curve! **VDI_TABULAR**: Tabular data up to the critical point available in [5]_. Note that this data is along the saturation curve. **ROWLINSON_POLING**: CSP method described in :obj:`Rowlinson_Poling <chemicals.heat_capacity.Rowlinson_Poling>`. Requires a ideal gas heat capacity value at the same temperature as it is to be calculated. **ROWLINSON_BONDI**: CSP method described in :obj:`Rowlinson_Bondi <chemicals.heat_capacity.Rowlinson_Bondi>`. Requires a ideal gas heat capacity value at the same temperature as it is to be calculated. **COOLPROP**: CoolProp external library; with select fluids from its library. Range is limited to that of the equations of state it uses, as described in [3]_. Very slow. **DADGOSTAR_SHAW**: A basic estimation method using the `similarity variable` concept; requires only molecular structure, so is very convenient. See :obj:`Dadgostar_Shaw <chemicals.heat_capacity.Dadgostar_Shaw>` for details. **POLING_CONST**: Constant values in [2]_ at 298.15 K; available for 245 liquids. **CRCSTD**: Constant values tabulated in [4]_ at 298.15 K; data is available for 433 liquids. **WEBBOOK_SHOMATE**: Shomate form coefficients from [6]_ for ~200 compounds. **HEOS_FIT**: A series of higher-order polynomial fits to the calculated results from fundamental helmholtz equations of state as calculated with REFPROP See Also -------- chemicals.heat_capacity.Zabransky_quasi_polynomial chemicals.heat_capacity.Zabransky_cubic chemicals.heat_capacity.Rowlinson_Poling chemicals.heat_capacity.Rowlinson_Bondi chemicals.heat_capacity.Dadgostar_Shaw chemicals.heat_capacity.Shomate Examples -------- >>> CpLiquid = HeatCapacityLiquid(CASRN='142-82-5', MW=100.2, similarity_variable=0.2295, Tc=540.2, omega=0.3457, Cpgm=165.2) References ---------- .. [1] Zabransky, M., V. Ruzicka Jr, V. Majer, and Eugene S. Domalski. Heat Capacity of Liquids: Critical Review and Recommended Values. 2 Volume Set. Washington, D.C.: Amer Inst of Physics, 1996. .. [2] Poling, Bruce E. The Properties of Gases and Liquids. 5th edition. New York: McGraw-Hill Professional, 2000. .. [3] Bell, Ian H., Jorrit Wronski, Sylvain Quoilin, and Vincent Lemort. "Pure and Pseudo-Pure Fluid Thermophysical Property Evaluation and the Open-Source Thermophysical Property Library CoolProp." Industrial & Engineering Chemistry Research 53, no. 6 (February 12, 2014): 2498-2508. doi:10.1021/ie4033999. http://www.coolprop.org/ .. [4] Haynes, W.M., Thomas J. Bruno, and David R. Lide. CRC Handbook of Chemistry and Physics. [Boca Raton, FL]: CRC press, 2014. .. [5] Gesellschaft, V. D. I., ed. VDI Heat Atlas. 2nd edition. Berlin; New York:: Springer, 2010. .. [6] Shen, V.K., Siderius, D.W., Krekelberg, W.P., and Hatch, H.W., Eds., NIST WebBook, NIST, http://doi.org/10.18434/T4M88Q ''' name = 'Liquid heat capacity' units = 'J/mol/K' interpolation_T = None """No interpolation transformation by default.""" interpolation_property = None """No interpolation transformation by default.""" interpolation_property_inv = None """No interpolation transformation by default.""" tabular_extrapolation_permitted = False """Disallow tabular extrapolation by default; higher-temeprature behavior is not well predicted by most extrapolation.""" property_min = 1 """Allow very low heat capacities; arbitrarily set; liquid heat capacity should always be somewhat substantial.""" property_max = 1E4 # Originally 1E4 """Maximum valid of Heat capacity; arbitrarily set. For fluids very near the critical point, this value can be obscenely high.""" ranked_methods = [HEOS_FIT, ZABRANSKY_SPLINE, ZABRANSKY_QUASIPOLYNOMIAL, ZABRANSKY_SPLINE_C, ZABRANSKY_QUASIPOLYNOMIAL_C, ZABRANSKY_SPLINE_SAT, ZABRANSKY_QUASIPOLYNOMIAL_SAT, WEBBOOK_SHOMATE, miscdata.JANAF, UNARY, VDI_TABULAR, COOLPROP, DADGOSTAR_SHAW, ROWLINSON_POLING, ROWLINSON_BONDI, POLING_CONST, CRCSTD] """Default rankings of the available methods.""" _fit_force_n = {} """Dictionary containing method: fit_n, for use in methods which should only ever be fit to a specific `n` value""" _fit_force_n[CRCSTD] = 1 _fit_force_n[POLING_CONST] = 1 _json_obj_by_CAS = ('Zabransky_spline', 'Zabransky_spline_iso', 'Zabransky_spline_sat', 'Zabransky_quasipolynomial', 'Zabransky_quasipolynomial_iso', 'Zabransky_quasipolynomial_sat', 'CP_f', 'webbook_shomate') obj_references = pure_references = ('Cpgm',) obj_references_types = pure_reference_types = (HeatCapacityGas,) custom_args = ('MW', 'similarity_variable', 'Tc', 'omega', 'Cpgm') def __init__(self, CASRN='', MW=None, similarity_variable=None, Tc=None, omega=None, Cpgm=None, extrapolation='linear', **kwargs): self.CASRN = CASRN self.MW = MW self.Tc = Tc self.omega = omega self.Cpgm = Cpgm self.similarity_variable = similarity_variable super().__init__(extrapolation, **kwargs) @staticmethod def _method_indexes(): '''Returns a dictionary of method: index for all methods that use data files to retrieve constants. The use of this function ensures the data files are not loaded until they are needed. ''' return {ZABRANSKY_SPLINE: list(heat_capacity.zabransky_dict_const_s), ZABRANSKY_QUASIPOLYNOMIAL: list(heat_capacity.zabransky_dict_const_p), ZABRANSKY_SPLINE_C: list(heat_capacity.zabransky_dict_iso_s), ZABRANSKY_QUASIPOLYNOMIAL_C: list(heat_capacity.zabransky_dict_iso_p), ZABRANSKY_SPLINE_SAT: list(heat_capacity.zabransky_dict_sat_s), ZABRANSKY_QUASIPOLYNOMIAL_SAT: list(heat_capacity.zabransky_dict_sat_p), POLING_CONST: [i for i in heat_capacity.Cp_data_Poling.index if not isnan(heat_capacity.Cp_data_Poling.at[i, 'Cpl'])], CRCSTD: [i for i in heat_capacity.CRC_standard_data.index if not isnan(heat_capacity.CRC_standard_data.at[i, 'Cpl'])], COOLPROP: coolprop_dict, VDI_TABULAR: list(miscdata.VDI_saturation_dict.keys()), } @classmethod def _load_json_CAS_references(cls, d): CASRN = d['CASRN'] if CASRN in heat_capacity.zabransky_dict_const_s: d['Zabransky_spline'] = heat_capacity.zabransky_dict_const_s[CASRN] if CASRN in heat_capacity.zabransky_dict_const_p: d['Zabransky_quasipolynomial'] = heat_capacity.zabransky_dict_const_p[CASRN] if CASRN in heat_capacity.zabransky_dict_iso_s: d['Zabransky_spline_iso'] = heat_capacity.zabransky_dict_iso_s[CASRN] if CASRN in heat_capacity.zabransky_dict_iso_p: d['Zabransky_quasipolynomial_iso'] = heat_capacity.zabransky_dict_iso_p[CASRN] if CASRN in heat_capacity.zabransky_dict_sat_s: d['Zabransky_spline_sat'] = heat_capacity.zabransky_dict_sat_s[CASRN] if CASRN in heat_capacity.zabransky_dict_sat_p: d['Zabransky_quasipolynomial_sat'] = heat_capacity.zabransky_dict_sat_p[CASRN] if 'CP_f' in d: d['CP_f'] = coolprop_fluids[CASRN] if CASRN in heat_capacity.WebBook_Shomate_liquids: d['webbook_shomate'] = heat_capacity.WebBook_Shomate_liquids[CASRN] def load_all_methods(self, load_data=True): r'''Method which picks out coefficients for the specified chemical from the various dictionaries and DataFrames storing it. All data is stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`, and :obj:`all_methods` as a set of methods for which the data exists for. Called on initialization only. See the source code for the variables at which the coefficients are stored. The coefficients can safely be altered once the class is initialized. This method can be called again to reset the parameters. ''' methods = [] self.all_methods = set() self.T_limits = T_limits = {} CASRN = self.CASRN if load_data and CASRN: if CASRN in heat_capacity.zabransky_dict_const_s: methods.append(ZABRANSKY_SPLINE) self.Zabransky_spline = heat_capacity.zabransky_dict_const_s[CASRN] T_limits[ZABRANSKY_SPLINE] = (self.Zabransky_spline.Tmin, self.Zabransky_spline.Tmax) if CASRN in heat_capacity.WebBook_Shomate_liquids: methods.append(WEBBOOK_SHOMATE) self.webbook_shomate = webbook_shomate = heat_capacity.WebBook_Shomate_liquids[CASRN] T_limits[WEBBOOK_SHOMATE] = (webbook_shomate.Tmin, webbook_shomate.Tmax) if CASRN in heat_capacity.zabransky_dict_const_p: methods.append(ZABRANSKY_QUASIPOLYNOMIAL) self.Zabransky_quasipolynomial = heat_capacity.zabransky_dict_const_p[CASRN] T_limits[ZABRANSKY_QUASIPOLYNOMIAL] = (self.Zabransky_quasipolynomial.Tmin, self.Zabransky_quasipolynomial.Tmax) if CASRN in heat_capacity.zabransky_dict_iso_s: methods.append(ZABRANSKY_SPLINE_C) self.Zabransky_spline_iso = heat_capacity.zabransky_dict_iso_s[CASRN] T_limits[ZABRANSKY_SPLINE_C] = (self.Zabransky_spline_iso.Tmin, self.Zabransky_spline_iso.Tmax) if CASRN in heat_capacity.zabransky_dict_iso_p: methods.append(ZABRANSKY_QUASIPOLYNOMIAL_C) self.Zabransky_quasipolynomial_iso = heat_capacity.zabransky_dict_iso_p[CASRN] T_limits[ZABRANSKY_QUASIPOLYNOMIAL_C] = (self.Zabransky_quasipolynomial_iso.Tmin, self.Zabransky_quasipolynomial_iso.Tmax) if CASRN in heat_capacity.Cp_data_Poling.index and not isnan(heat_capacity.Cp_data_Poling.at[CASRN, 'Cpl']): methods.append(POLING_CONST) self.POLING_T = 298.15 self.POLING_constant = float(heat_capacity.Cp_data_Poling.at[CASRN, 'Cpl']) T_limits[POLING_CONST] = (298.15-50.0, 298.15+50.0) if CASRN in heat_capacity.CRC_standard_data.index and not isnan(heat_capacity.CRC_standard_data.at[CASRN, 'Cpl']): methods.append(CRCSTD) self.CRCSTD_T = 298.15 self.CRCSTD_constant = float(heat_capacity.CRC_standard_data.at[CASRN, 'Cpl']) T_limits[CRCSTD] = (298.15-50.0, 298.15+50.0) # Saturation functions if CASRN in heat_capacity.zabransky_dict_sat_s: methods.append(ZABRANSKY_SPLINE_SAT) self.Zabransky_spline_sat = heat_capacity.zabransky_dict_sat_s[CASRN] T_limits[ZABRANSKY_SPLINE_SAT] = (self.Zabransky_spline_sat.Tmin, self.Zabransky_spline_sat.Tmax) if CASRN in heat_capacity.zabransky_dict_sat_p: methods.append(ZABRANSKY_QUASIPOLYNOMIAL_SAT) self.Zabransky_quasipolynomial_sat = heat_capacity.zabransky_dict_sat_p[CASRN] T_limits[ZABRANSKY_QUASIPOLYNOMIAL_SAT] = (self.Zabransky_quasipolynomial_sat.Tmin, self.Zabransky_quasipolynomial_sat.Tmax) if CASRN in heat_capacity.Cp_dict_JANAF_liquid: methods.append(miscdata.JANAF) Ts, props = heat_capacity.Cp_dict_JANAF_liquid[CASRN] self.add_tabular_data(Ts, props, miscdata.JANAF, check_properties=False) del self._method if CASRN in miscdata.VDI_saturation_dict: # NOTE: VDI data is for the saturation curve, i.e. at increasing # pressure; it is normally substantially higher than the ideal gas # value Ts, props = lookup_VDI_tabular_data(CASRN, 'Cp (l)') self.add_tabular_data(Ts, props, VDI_TABULAR, check_properties=False) del self._method if has_CoolProp() and CASRN in coolprop_dict: methods.append(COOLPROP) self.CP_f = coolprop_fluids[CASRN] Tmin = max(self.CP_f.Tt, self.CP_f.Tmin) Tmax = min(self.CP_f.Tc*.9999, self.CP_f.Tmax) T_limits[COOLPROP] = (Tmin, Tmax) if self.Tc and self.omega: methods.extend([ROWLINSON_POLING, ROWLINSON_BONDI]) limits_Tc = (0.3*self.Tc, self.Tc-0.1) T_limits[ROWLINSON_POLING] = limits_Tc T_limits[ROWLINSON_BONDI] = limits_Tc if self.MW and self.similarity_variable: methods.append(DADGOSTAR_SHAW) T_limits[DADGOSTAR_SHAW] = (1e-3, 10000. if self.Tc is None else self.Tc) self.all_methods.update(methods)
[docs] def calculate(self, T, method): r'''Method to calculate heat capacity of a liquid at temperature `T` with a given method. This method has no exception handling; see :obj:`T_dependent_property <thermo.utils.TDependentProperty.T_dependent_property>` for that. Parameters ---------- T : float Temperature at which to calculate heat capacity, [K] method : str Name of the method to use Returns ------- Cp : float Heat capacity of the liquid at T, [J/mol/K] ''' if method == ZABRANSKY_SPLINE: return self.Zabransky_spline.force_calculate(T) elif method == ZABRANSKY_QUASIPOLYNOMIAL: return self.Zabransky_quasipolynomial.calculate(T) elif method == ZABRANSKY_SPLINE_C: return self.Zabransky_spline_iso.force_calculate(T) elif method == ZABRANSKY_QUASIPOLYNOMIAL_C: return self.Zabransky_quasipolynomial_iso.calculate(T) elif method == ZABRANSKY_SPLINE_SAT: return self.Zabransky_spline_sat.force_calculate(T) elif method == ZABRANSKY_QUASIPOLYNOMIAL_SAT: return self.Zabransky_quasipolynomial_sat.calculate(T) elif method == WEBBOOK_SHOMATE: return self.webbook_shomate.force_calculate(T) elif method == COOLPROP: return CoolProp_T_dependent_property(T, self.CASRN , 'CPMOLAR', 'l') elif method == POLING_CONST: return self.POLING_constant elif method == CRCSTD: return self.CRCSTD_constant elif method == ROWLINSON_POLING: Cpgm = self.Cpgm(T) if hasattr(self.Cpgm, '__call__') else self.Cpgm return Rowlinson_Poling(T, self.Tc, self.omega, Cpgm) elif method == ROWLINSON_BONDI: Cpgm = self.Cpgm(T) if hasattr(self.Cpgm, '__call__') else self.Cpgm return Rowlinson_Bondi(T, self.Tc, self.omega, Cpgm) elif method == DADGOSTAR_SHAW: Cp = Dadgostar_Shaw(T, self.similarity_variable) return property_mass_to_molar(Cp, self.MW) else: return self._base_calculate(T, method)
[docs] def test_method_validity(self, T, method): r'''Method to check the validity of a method. Follows the given ranges for all coefficient-based methods. For the CSP method :obj:`Rowlinson_Poling <chemicals.heat_capacity.Rowlinson_Poling>`, the model is considered valid for all temperatures. The simple method :obj:`Dadgostar_Shaw <chemicals.heat_capacity.Dadgostar_Shaw>` is considered valid for all temperatures. For tabular data, extrapolation outside of the range is used if :obj:`tabular_extrapolation_permitted` is set; if it is, the extrapolation is considered valid for all temperatures. It is not guaranteed that a method will work or give an accurate prediction simply because this method considers the method valid. Parameters ---------- T : float Temperature at which to test the method, [K] method : str Name of the method to test Returns ------- validity : bool Whether or not a method is valid ''' validity = True if method == ZABRANSKY_SPLINE: if T < self.Zabransky_spline.Tmin or T > self.Zabransky_spline.Tmax: return False elif method == ZABRANSKY_SPLINE_C: if T < self.Zabransky_spline_iso.Tmin or T > self.Zabransky_spline_iso.Tmax: return False elif method == ZABRANSKY_SPLINE_SAT: if T < self.Zabransky_spline_sat.Tmin or T > self.Zabransky_spline_sat.Tmax: return False elif method == ZABRANSKY_QUASIPOLYNOMIAL: if T > self.Zabransky_quasipolynomial.Tc: return False elif method == ZABRANSKY_QUASIPOLYNOMIAL_C: if T > self.Zabransky_quasipolynomial_iso.Tc: return False elif method == ZABRANSKY_QUASIPOLYNOMIAL_SAT: if T > self.Zabransky_quasipolynomial_sat.Tc: return False elif method == COOLPROP: if T <= self.CP_f.Tmin or T >= self.CP_f.Tmax: return False elif method == POLING_CONST: if T > self.POLING_T + 50 or T < self.POLING_T - 50: return False elif method == CRCSTD: if T > self.CRCSTD_T + 50 or T < self.CRCSTD_T - 50: return False elif method == DADGOSTAR_SHAW: pass # Valid everywhere elif method in [ROWLINSON_POLING, ROWLINSON_BONDI]: if self.Tc and T > self.Tc: return False else: return super().test_method_validity(T, method) return validity
def calculate_integral(self, T1, T2, method): r'''Method to calculate the integral of a property with respect to temperature, using a specified method. Implements the analytical integrals of all available methods except for tabular data, the case of multiple coefficient sets needed to encompass the temperature range of any of the ZABRANSKY methods, and the CSP methods using the vapor phase properties. Parameters ---------- T1 : float Lower limit of integration, [K] T2 : float Upper limit of integration, [K] method : str Method for which to find the integral Returns ------- integral : float Calculated integral of the property over the given range, [`units*K`] ''' if method == ZABRANSKY_SPLINE: return self.Zabransky_spline.calculate_integral(T1, T2) elif method == ZABRANSKY_SPLINE_C: return self.Zabransky_spline_iso.force_calculate_integral(T1, T2) elif method == ZABRANSKY_SPLINE_SAT: return self.Zabransky_spline_sat.calculate_integral(T1, T2) elif method == ZABRANSKY_QUASIPOLYNOMIAL: return self.Zabransky_quasipolynomial.calculate_integral(T1, T2) elif method == ZABRANSKY_QUASIPOLYNOMIAL_C: return self.Zabransky_quasipolynomial_iso.calculate_integral(T1, T2) elif method == ZABRANSKY_QUASIPOLYNOMIAL_SAT: return self.Zabransky_quasipolynomial_sat.calculate_integral(T1, T2) elif method == WEBBOOK_SHOMATE: return self.webbook_shomate.force_calculate_integral(T1, T2) elif method == POLING_CONST: return (T2 - T1)*self.POLING_constant elif method == CRCSTD: return (T2 - T1)*self.CRCSTD_constant elif method == DADGOSTAR_SHAW: dH = (Dadgostar_Shaw_integral(T2, self.similarity_variable) - Dadgostar_Shaw_integral(T1, self.similarity_variable)) return property_mass_to_molar(dH, self.MW) elif method in self.tabular_data or method == COOLPROP or method in [ROWLINSON_POLING, ROWLINSON_BONDI]: return float(quad(self.calculate, T1, T2, args=(method,))[0]) return super().calculate_integral(T1, T2, method) def calculate_integral_over_T(self, T1, T2, method): r'''Method to calculate the integral of a property over temperature with respect to temperature, using a specified method. Implements the analytical integrals of all available methods except for tabular data, the case of multiple coefficient sets needed to encompass the temperature range of any of the ZABRANSKY methods, and the CSP methods using the vapor phase properties. Parameters ---------- T1 : float Lower limit of integration, [K] T2 : float Upper limit of integration, [K] method : str Method for which to find the integral Returns ------- integral : float Calculated integral of the property over the given range, [`units`] ''' if method == ZABRANSKY_SPLINE: return self.Zabransky_spline.calculate_integral_over_T(T1, T2) elif method == ZABRANSKY_SPLINE_C: return self.Zabransky_spline_iso.calculate_integral_over_T(T1, T2) elif method == ZABRANSKY_SPLINE_SAT: return self.Zabransky_spline_sat.calculate_integral_over_T(T1, T2) elif method == ZABRANSKY_QUASIPOLYNOMIAL: return self.Zabransky_quasipolynomial.calculate_integral_over_T(T1, T2) elif method == ZABRANSKY_QUASIPOLYNOMIAL_C: return self.Zabransky_quasipolynomial_iso.calculate_integral_over_T(T1, T2) elif method == ZABRANSKY_QUASIPOLYNOMIAL_SAT: return self.Zabransky_quasipolynomial_sat.calculate_integral_over_T(T1, T2) elif method == WEBBOOK_SHOMATE: return self.webbook_shomate.force_calculate_integral_over_T(T1, T2) elif method == POLING_CONST: return self.POLING_constant*log(T2/T1) elif method == CRCSTD: return self.CRCSTD_constant*log(T2/T1) elif method == DADGOSTAR_SHAW: dS = (Dadgostar_Shaw_integral_over_T(T2, self.similarity_variable) - Dadgostar_Shaw_integral_over_T(T1, self.similarity_variable)) return property_mass_to_molar(dS, self.MW) elif method in self.tabular_data or method == COOLPROP or method in [ROWLINSON_POLING, ROWLINSON_BONDI]: return float(quad(lambda T: self.calculate(T, method)/T, T1, T2)[0]) return super().calculate_integral_over_T(T1, T2, method)
LASTOVKA_S = 'LASTOVKA_S' PERRY151 = """PERRY151""" heat_capacity_solid_methods = [JANAF_FIT, WEBBOOK_SHOMATE, PERRY151, CRCSTD, LASTOVKA_S] """Holds all methods available for the :obj:`HeatCapacitySolid` class, for use in iterating over them."""
[docs]class HeatCapacitySolid(TDependentProperty): r'''Class for dealing with solid heat capacity as a function of temperature. Consists of two temperature-dependent expressions, one constant value source, and one simple estimator. Parameters ---------- similarity_variable : float, optional similarity variable, n_atoms/MW, [mol/g] MW : float, optional Molecular weight, [g/mol] CASRN : str, optional The CAS number of the chemical load_data : bool, optional If False, do not load property coefficients from data sources in files [-] extrapolation : str or None None to not extrapolate; see :obj:`TDependentProperty <thermo.utils.TDependentProperty>` for a full list of all options, [-] method : str or None, optional If specified, use this method by default and do not use the ranked sorting; an exception is raised if this is not a valid method for the provided inputs, [-] Notes ----- A string holding each method's name is assigned to the following variables in this module, intended as the most convenient way to refer to a method. To iterate over all methods, use the list stored in :obj:`heat_capacity_solid_methods`. **PERRY151**: Simple polynomials with vaious exponents selected for each expression. Coefficients are in units of calories/mol/K. The full expression is: .. math:: Cp = a + bT + c/T^2 + dT^2 Data is available for 284 solids, from [2]_. **CRCSTD**: Values tabulated in [1]_ at 298.15 K; data is available for 529 solids. **LASTOVKA_S**: A basic estimation method using the `similarity variable` concept; requires only molecular structure, so is very convenient. See :obj:`Lastovka_solid <chemicals.heat_capacity.Lastovka_solid>` for details. **WEBBOOK_SHOMATE**: Shomate form coefficients from [3]_ for ~300 compounds. See Also -------- chemicals.heat_capacity.Lastovka_solid chemicals.heat_capacity.Shomate Examples -------- >>> CpSolid = HeatCapacitySolid(CASRN='142-82-5', MW=100.2, similarity_variable=0.2295) >>> CpSolid(200) 131.205824 References ---------- .. [1] Haynes, W.M., Thomas J. Bruno, and David R. Lide. CRC Handbook of Chemistry and Physics. [Boca Raton, FL]: CRC press, 2014. .. [2] Green, Don, and Robert Perry. Perry's Chemical Engineers' Handbook, Eighth Edition. McGraw-Hill Professional, 2007. .. [3] Shen, V.K., Siderius, D.W., Krekelberg, W.P., and Hatch, H.W., Eds., NIST WebBook, NIST, http://doi.org/10.18434/T4M88Q ''' name = 'solid heat capacity' units = 'J/mol/K' interpolation_T = None """No interpolation transformation by default.""" interpolation_property = None """No interpolation transformation by default.""" interpolation_property_inv = None """No interpolation transformation by default.""" tabular_extrapolation_permitted = True """Allow tabular extrapolation by default; a theoretical solid phase exists for all chemicals at sufficiently high pressures, although few chemicals could stably exist in those conditions.""" property_min = 0 """Heat capacities have a minimum value of 0 at 0 K.""" property_max = 1E4 """Maximum value of Heat capacity; arbitrarily set.""" ranked_methods = [WEBBOOK_SHOMATE, JANAF_FIT, miscdata.JANAF, UNARY, PERRY151, CRCSTD, LASTOVKA_S] """Default rankings of the available methods.""" _fit_force_n = {} """Dictionary containing method: fit_n, for use in methods which should only ever be fit to a specific `n` value""" _fit_force_n[CRCSTD] = 1 custom_args = ('MW', 'similarity_variable') _json_obj_by_CAS = ('webbook_shomate',) @classmethod def _load_json_CAS_references(cls, d): CASRN = d['CASRN'] if CASRN in heat_capacity.WebBook_Shomate_solids: d['webbook_shomate'] = heat_capacity.WebBook_Shomate_solids[CASRN] def __init__(self, CASRN='', similarity_variable=None, MW=None, extrapolation='linear', **kwargs): self.similarity_variable = similarity_variable self.MW = MW self.CASRN = CASRN super().__init__(extrapolation, **kwargs) def _method_indexes(): '''Returns a dictionary of method: index for all methods that use data files to retrieve constants. The use of this function ensures the data files are not loaded until they are needed. ''' return {PERRY151: [i for i in heat_capacity.Cp_dict_PerryI.keys() if 'c' in heat_capacity.Cp_dict_PerryI[i]], CRCSTD: [i for i in heat_capacity.CRC_standard_data.index if not isnan(heat_capacity.CRC_standard_data.at[i, 'Cps'])], } def load_all_methods(self, load_data): r'''Method which picks out coefficients for the specified chemical from the various dictionaries and DataFrames storing it. All data is stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`, and :obj:`all_methods` as a set of methods for which the data exists for. Called on initialization only. See the source code for the variables at which the coefficients are stored. The coefficients can safely be altered once the class is initialized. This method can be called again to reset the parameters. ''' methods = [] self.T_limits = T_limits = {} self.all_methods = set() CASRN = self.CASRN if load_data and CASRN: if CASRN in heat_capacity.WebBook_Shomate_solids: methods.append(WEBBOOK_SHOMATE) self.webbook_shomate = webbook_shomate = heat_capacity.WebBook_Shomate_solids[CASRN] T_limits[WEBBOOK_SHOMATE] = (webbook_shomate.Tmin, webbook_shomate.Tmax) if CASRN in heat_capacity.Cp_dict_JANAF_solid: methods.append(miscdata.JANAF) Ts, props = heat_capacity.Cp_dict_JANAF_solid[CASRN] self.add_tabular_data(Ts, props, miscdata.JANAF, check_properties=False) del self._method if CASRN and CASRN in heat_capacity.Cp_dict_PerryI and 'c' in heat_capacity.Cp_dict_PerryI[CASRN]: self.PERRY151_Tmin = heat_capacity.Cp_dict_PerryI[CASRN]['c']['Tmin'] if heat_capacity.Cp_dict_PerryI[CASRN]['c']['Tmin'] else 0 self.PERRY151_Tmax = heat_capacity.Cp_dict_PerryI[CASRN]['c']['Tmax'] if heat_capacity.Cp_dict_PerryI[CASRN]['c']['Tmax'] else 2000 self.PERRY151_const = heat_capacity.Cp_dict_PerryI[CASRN]['c']['Const'] self.PERRY151_lin = heat_capacity.Cp_dict_PerryI[CASRN]['c']['Lin'] self.PERRY151_quad = heat_capacity.Cp_dict_PerryI[CASRN]['c']['Quad'] self.PERRY151_quadinv = heat_capacity.Cp_dict_PerryI[CASRN]['c']['Quadinv'] methods.append(PERRY151) T_limits[PERRY151] = (self.PERRY151_Tmin, self.PERRY151_Tmax) if CASRN in heat_capacity.CRC_standard_data.index and not isnan(heat_capacity.CRC_standard_data.at[CASRN, 'Cps']): self.CRCSTD_Cp = float(heat_capacity.CRC_standard_data.at[CASRN, 'Cps']) methods.append(CRCSTD) T_limits[CRCSTD] = (298.15, 298.15) if self.MW and self.similarity_variable: methods.append(LASTOVKA_S) T_limits[LASTOVKA_S] = (1.0, 1e4) # Works above roughly 1 K up to 10K. self.all_methods.update(methods)
[docs] def calculate(self, T, method): r'''Method to calculate heat capacity of a solid at temperature `T` with a given method. This method has no exception handling; see :obj:`T_dependent_property <thermo.utils.TDependentProperty.T_dependent_property>` for that. Parameters ---------- T : float Temperature at which to calculate heat capacity, [K] method : str Name of the method to use Returns ------- Cp : float Heat capacity of the solid at T, [J/mol/K] ''' if method == PERRY151: Cp = (self.PERRY151_const + self.PERRY151_lin*T + self.PERRY151_quadinv/T**2 + self.PERRY151_quad*T**2)*calorie elif method == CRCSTD: Cp = self.CRCSTD_Cp elif method == LASTOVKA_S: Cp = Lastovka_solid(T, self.similarity_variable) Cp = property_mass_to_molar(Cp, self.MW) elif method == WEBBOOK_SHOMATE: Cp = self.webbook_shomate.force_calculate(T) else: return self._base_calculate(T, method) return Cp
[docs] def test_method_validity(self, T, method): r'''Method to check the validity of a method. Follows the given ranges for all coefficient-based methods. For tabular data, extrapolation outside of the range is used if :obj:`tabular_extrapolation_permitted` is set; if it is, the extrapolation is considered valid for all temperatures. For the :obj:`Lastovka_solid <chemicals.heat_capacity.Lastovka_solid>` method, it is considered valid under 10000K. It is not guaranteed that a method will work or give an accurate prediction simply because this method considers the method valid. Parameters ---------- T : float Temperature at which to test the method, [K] method : str Name of the method to test Returns ------- validity : bool Whether or not a method is valid ''' validity = True if method == PERRY151: if T < self.PERRY151_Tmin or T > self.PERRY151_Tmax: validity = False elif method == CRCSTD: if T < 298.15-50 or T > 298.15+50: validity = False elif method == LASTOVKA_S: if T > 10000 or T < 0: validity = False else: return super().test_method_validity(T, method) return validity
def calculate_integral(self, T1, T2, method): r'''Method to calculate the integral of a property with respect to temperature, using a specified method. Implements the analytical integrals of all available methods except for tabular data. Parameters ---------- T1 : float Lower limit of integration, [K] T2 : float Upper limit of integration, [K] method : str Method for which to find the integral Returns ------- integral : float Calculated integral of the property over the given range, [`units*K`] ''' if method == PERRY151: H2 = (self.PERRY151_const*T2 + 0.5*self.PERRY151_lin*T2**2 - self.PERRY151_quadinv/T2 + self.PERRY151_quad*T2**3/3.) H1 = (self.PERRY151_const*T1 + 0.5*self.PERRY151_lin*T1**2 - self.PERRY151_quadinv/T1 + self.PERRY151_quad*T1**3/3.) return (H2-H1)*calorie elif method == CRCSTD: return (T2-T1)*self.CRCSTD_Cp elif method == WEBBOOK_SHOMATE: return self.webbook_shomate.force_calculate_integral(T1, T2) elif method == LASTOVKA_S: dH = (Lastovka_solid_integral(T2, self.similarity_variable) - Lastovka_solid_integral(T1, self.similarity_variable)) return property_mass_to_molar(dH, self.MW) else: return super().calculate_integral(T1, T2, method) def calculate_integral_over_T(self, T1, T2, method): r'''Method to calculate the integral of a property over temperature with respect to temperature, using a specified method. Implements the analytical integrals of all available methods except for tabular data. Parameters ---------- T1 : float Lower limit of integration, [K] T2 : float Upper limit of integration, [K] method : str Method for which to find the integral Returns ------- integral : float Calculated integral of the property over the given range, [`units`] ''' if method == PERRY151: S2 = (self.PERRY151_const*log(T2) + self.PERRY151_lin*T2 - self.PERRY151_quadinv/(2.*T2**2) + 0.5*self.PERRY151_quad*T2**2) S1 = (self.PERRY151_const*log(T1) + self.PERRY151_lin*T1 - self.PERRY151_quadinv/(2.*T1**2) + 0.5*self.PERRY151_quad*T1**2) return (S2 - S1)*calorie elif method == CRCSTD: S2 = self.CRCSTD_Cp*log(T2) S1 = self.CRCSTD_Cp*log(T1) return (S2 - S1) elif method == LASTOVKA_S: dS = (Lastovka_solid_integral_over_T(T2, self.similarity_variable) - Lastovka_solid_integral_over_T(T1, self.similarity_variable)) return property_mass_to_molar(dS, self.MW) elif method == WEBBOOK_SHOMATE: return self.webbook_shomate.force_calculate_integral_over_T(T1, T2) else: return super().calculate_integral_over_T(T1, T2, method)
### Mixture heat capacities LALIBERTE = 'LALIBERTE' heat_capacity_gas_mixture_methods = [LINEAR] """Holds all methods available for the :obj:`HeatCapacityGasMixture` class, for use in iterating over them.""" heat_capacity_liquid_mixture_methods = [LALIBERTE, LINEAR] """Holds all methods available for the :obj:`HeatCapacityLiquidMixture` class, for use in iterating over them.""" heat_capacity_solid_mixture_methods = [LINEAR] """Holds all methods available for the :obj:`HeatCapacitySolidMixture` class, for use in iterating over them."""
[docs]class HeatCapacityLiquidMixture(MixtureProperty): '''Class for dealing with liquid heat capacity of a mixture as a function of temperature, pressure, and composition. Consists only of mole weighted averaging, and the Laliberte method for aqueous electrolyte solutions. Parameters ---------- MWs : list[float], optional Molecular weights of all species in the mixture, [g/mol] CASs : str, optional The CAS numbers of all species in the mixture HeatCapacityLiquids : list[HeatCapacityLiquid], optional HeatCapacityLiquid objects created for all species in the mixture [-] Notes ----- To iterate over all methods, use the list stored in :obj:`heat_capacity_liquid_mixture_methods`. **LALIBERTE**: Electrolyte model equation with coefficients; see :obj:`thermo.electrochem.Laliberte_heat_capacity` for more details. **LINEAR**: Mixing rule described in :obj:`mixing_simple <chemicals.utils.mixing_simple>`. ''' name = 'Liquid heat capacity' units = 'J/mol' property_min = 1 """Allow very low heat capacities; arbitrarily set; liquid heat capacity should always be somewhat substantial.""" property_max = 1E4 # Originally 1E4 """Maximum valid of Heat capacity; arbitrarily set. For fluids very near the critical point, this value can be obscenely high.""" ranked_methods = [LALIBERTE, LINEAR] pure_references = ('HeatCapacityLiquids',) pure_reference_types = (HeatCapacityLiquid,) pure_constants = ('MWs', ) custom_args = pure_constants def __init__(self, MWs=[], CASs=[], HeatCapacityLiquids=[], **kwargs): self.MWs = MWs self.CASs = CASs self.HeatCapacityLiquids = HeatCapacityLiquids super().__init__(**kwargs) def load_all_methods(self): r'''Method to initialize the object by precomputing any values which may be used repeatedly and by retrieving mixture-specific variables. All data are stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`, and :obj:`all_methods` as a set of methods which should work to calculate the property. Called on initialization only. See the source code for the variables at which the coefficients are stored. The coefficients can safely be altered once the class is initialized. This method can be called again to reset the parameters. ''' methods = [LINEAR] if len(self.CASs) > 1 and '7732-18-5' in self.CASs: Laliberte_data = electrochem.Laliberte_data a1s, a2s, a3s, a4s, a5s, a6s = [], [], [], [], [], [] laliberte_incomplete = False for CAS in self.CASs: if CAS == '7732-18-5': continue if CAS in Laliberte_data.index: dat = Laliberte_data.loc[CAS].values if isnan(dat[22]): laliberte_incomplete = True break a1s.append(float(dat[22])) a2s.append(float(dat[23])) a3s.append(float(dat[24])) a4s.append(float(dat[25])) a5s.append(float(dat[26])) a6s.append(float(dat[27])) else: laliberte_incomplete = True break if not laliberte_incomplete: self.Laliberte_a1s = a1s self.Laliberte_a2s = a2s self.Laliberte_a3s = a3s self.Laliberte_a4s = a4s self.Laliberte_a5s = a5s self.Laliberte_a6s = a6s wCASs = [i for i in self.CASs if i != '7732-18-5'] methods.append(LALIBERTE) self.wCASs = wCASs self.index_w = self.CASs.index('7732-18-5') self.all_methods = all_methods = set(methods)
[docs] def calculate(self, T, P, zs, ws, method): r'''Method to calculate heat capacity of a liquid mixture at temperature `T`, pressure `P`, mole fractions `zs` and weight fractions `ws` with a given method. This method has no exception handling; see :obj:`mixture_property <thermo.utils.MixtureProperty.mixture_property>` for that. Parameters ---------- T : float Temperature at which to calculate the property, [K] P : float Pressure at which to calculate the property, [Pa] zs : list[float] Mole fractions of all species in the mixture, [-] ws : list[float] Weight fractions of all species in the mixture, [-] method : str Name of the method to use Returns ------- Cplm : float Molar heat capacity of the liquid mixture at the given conditions, [J/mol] ''' if method == LALIBERTE: ws = list(ws) ws.pop(self.index_w) Cpl = Laliberte_heat_capacity(T, ws, self.wCASs) MW = mixing_simple(zs, self.MWs) return property_mass_to_molar(Cpl, MW) return super().calculate(T, P, zs, ws, method)
[docs] def test_method_validity(self, T, P, zs, ws, method): if method in self.all_methods: return True return super().test_method_validity(T, P, zs, ws, method)
[docs]class HeatCapacitySolidMixture(MixtureProperty): '''Class for dealing with solid heat capacity of a mixture as a function of temperature, pressure, and composition. Consists only of mole weighted averaging. Parameters ---------- CASs : list[str], optional The CAS numbers of all species in the mixture, [-] HeatCapacitySolids : list[HeatCapacitySolid], optional HeatCapacitySolid objects created for all species in the mixture [-] MWs : list[float], optional Molecular weights of all species in the mixture, [g/mol] Notes ----- To iterate over all methods, use the list stored in :obj:`heat_capacity_solid_mixture_methods`. **LINEAR**: Mixing rule described in :obj:`mixing_simple <chemicals.utils.mixing_simple>`. ''' name = 'Solid heat capacity' units = 'J/mol' property_min = 0 """Heat capacities have a minimum value of 0 at 0 K.""" property_max = 1E4 """Maximum value of Heat capacity; arbitrarily set.""" ranked_methods = [LINEAR] pure_references = ('HeatCapacitySolids',) pure_reference_types = (HeatCapacitySolid,) pure_constants = ('MWs', ) custom_args = pure_constants def __init__(self, CASs=[], HeatCapacitySolids=[], MWs=[], **kwargs): self.CASs = CASs self.HeatCapacitySolids = HeatCapacitySolids self.MWs = MWs super().__init__(**kwargs) def load_all_methods(self): r'''Method to initialize the object by precomputing any values which may be used repeatedly and by retrieving mixture-specific variables. All data are stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`, and :obj:`all_methods` as a set of methods which should work to calculate the property. Called on initialization only. See the source code for the variables at which the coefficients are stored. The coefficients can safely be altered once the class is initialized. This method can be called again to reset the parameters. ''' methods = [LINEAR] self.all_methods = all_methods = set(methods)
[docs] def calculate(self, T, P, zs, ws, method): r'''Method to calculate heat capacity of a solid mixture at temperature `T`, pressure `P`, mole fractions `zs` and weight fractions `ws` with a given method. This method has no exception handling; see :obj:`mixture_property <thermo.utils.MixtureProperty.mixture_property>` for that. Parameters ---------- T : float Temperature at which to calculate the property, [K] P : float Pressure at which to calculate the property, [Pa] zs : list[float] Mole fractions of all species in the mixture, [-] ws : list[float] Weight fractions of all species in the mixture, [-] method : str Name of the method to use Returns ------- Cpsm : float Molar heat capacity of the solid mixture at the given conditions, [J/mol] ''' return super().calculate(T, P, zs, ws, method)
[docs] def test_method_validity(self, T, P, zs, ws, method): if method in self.all_methods: return True return super().test_method_validity(T, P, zs, ws, method)
[docs]class HeatCapacityGasMixture(MixtureProperty): '''Class for dealing with the gas heat capacity of a mixture as a function of temperature, pressure, and composition. Consists only of mole weighted averaging. Parameters ---------- CASs : list[str], optional The CAS numbers of all species in the mixture, [-] HeatCapacityGases : list[HeatCapacityGas], optional HeatCapacityGas objects created for all species in the mixture [-] MWs : list[float], optional Molecular weights of all species in the mixture, [g/mol] Notes ----- To iterate over all methods, use the list stored in :obj:`heat_capacity_gas_mixture_methods`. **LINEAR**: Mixing rule described in :obj:`mixing_simple <chemicals.utils.mixing_simple>`. ''' name = 'Gas heat capacity' units = 'J/mol' property_min = 0 """Heat capacities have a minimum value of 0 at 0 K.""" property_max = 1E4 """Maximum valid of Heat capacity; arbitrarily set. For fluids very near the critical point, this value can be obscenely high.""" ranked_methods = [LINEAR] pure_references = ('HeatCapacityGases',) pure_reference_types = (HeatCapacityGas,) pure_constants = ('MWs', ) custom_args = pure_constants def __init__(self, CASs=[], HeatCapacityGases=[], MWs=[], **kwargs): self.CASs = CASs self.HeatCapacityGases = HeatCapacityGases self.MWs = MWs super().__init__(**kwargs) def load_all_methods(self): r'''Method to initialize the object by precomputing any values which may be used repeatedly and by retrieving mixture-specific variables. All data are stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`, and :obj:`all_methods` as a set of methods which should work to calculate the property. Called on initialization only. See the source code for the variables at which the coefficients are stored. The coefficients can safely be altered once the class is initialized. This method can be called again to reset the parameters. ''' methods = [LINEAR] self.all_methods = all_methods = set(methods)
[docs] def calculate(self, T, P, zs, ws, method): r'''Method to calculate heat capacity of a gas mixture at temperature `T`, pressure `P`, mole fractions `zs` and weight fractions `ws` with a given method. This method has no exception handling; see :obj:`mixture_property <thermo.utils.MixtureProperty.mixture_property>` for that. Parameters ---------- T : float Temperature at which to calculate the property, [K] P : float Pressure at which to calculate the property, [Pa] zs : list[float] Mole fractions of all species in the mixture, [-] ws : list[float] Weight fractions of all species in the mixture, [-] method : str Name of the method to use Returns ------- Cpgm : float Molar heat capacity of the gas mixture at the given conditions, [J/mol] ''' return super().calculate(T, P, zs, ws, method)
[docs] def test_method_validity(self, T, P, zs, ws, method): if method in self.all_methods: return True return super().test_method_validity(T, P, zs, ws, method)