Unit operations

Documentation for the class objects creation are presented in this section [Highlighted in blue]. Documentation for methods called internally and not requiring user definition are ignored.

Reactors

class PharmaPy.Reactors.BatchReactor(mask_params=None, base_units='concentration', temp_ref=298.15, isothermal=True, reset_states=False, controls=None, h_conv=1000, ht_mode='jacket', return_sens=True, state_events=None)

Bases: _BaseReactor

Inherited constructor for the Batch reactor class.

Parameters:

partic_species (list of str) – Names of the species participating in the reaction. Names correspond to species names in the physical properties .json file.
mask_params (list of bool (optional, default = None)) – Binary list of which parameters to exclude from the kinetics computations.
base_units (str (optional, default = 'concentration')) – Basis used for material units in the reactor.
temp_ref (float (optional, default = 298.15)) – Reference temperature for enthalpy calculations.
isothermal (bool (optional, default = True)) – Boolean value indicating whether the energy balance is considered. (i.e. dT/dt = 0 when isothermal is True)
reset_states (bool (optional, default = False)) – Boolean value indicating whether the states should be reset before simulation.
controls (dict of functions (optional, default = None)) – Dictionary with keys representing the state which is controlled and the value indicating the function to use while computing the variable. Functions are of the form f(time) = state_value
h_conv (float (optional, default = 1000)) – Convective heat transfer coefficient for the liquid phase in the reactor (W m^-2 K^-1).
ht_mode (str (optional, default = 'jacket')) – What method is used for heat transfer. Options: [‘jacket’, ‘coil’, ‘bath’]
return_sens (bool (optional, default = True)) – whether or not the paramest_wrapper method should return the sensitivity system along with the concentratio profiles. Use False if you want the parameter estimation platform to estimate the sensitivity system using finite differences

energy_balances(time, mole_conc, vol, temp, temp_ht, inputs, heat_prof=False)

material_balances(time, mole_conc, vol, temp, temp_ht, inputs)

nomenclature()

retrieve_results(time, states)

solve_unit(runtime=None, time_grid=None, eval_sens=False, params_control=None, verbose=True, sundials_opts=None)

Batch reactor method for solving the individual unit directly. runtime : float (default = None)

Value for total unit runtime.

time_gridlist of float (optional, default = None): Optional list of time values for the integrator to use during simulation.
eval_sensbool (optional, default = False): Boolean value indicating whether the parametric sensitivity system will be included during simulation. Must be true to access sensitivity information.
verbosebool (optional, default = True): Boolean value indicating whether the simulator will output run statistics after simulation is complete. Use true if you want to see the number of function evaluations and wall-clock runtime for the unit.
timesim_limitfloat (optional, default = 0): Float value of the maximum wall-clock time for the simulator to use before aborting the simulation.
returndefault 2 arrays (3 if eval_sens is True): Returns 2 or 3 indexed data structures. First, the integrator time points. Second, the state values corresponding to those integrator time points. And if eval_sens is True, third is the parametric sensitivity information of the simulation.

class PharmaPy.Reactors.CSTR(mask_params=None, base_units='concentration', temp_ref=298.15, isothermal=True, reset_states=False, controls=None, h_conv=1000, ht_mode='jacket', return_sens=True, state_events=None)

Bases: _BaseReactor

Inherited constructor for the continuous stirred-tank reactor (CSTR) class.

Parameters:

partic_species (list of str) – Names of the species participating in the reaction. Names correspond to species names in the physical properties .json file.
mask_params (list of bool (optional, default = None)) – Binary list of which parameters to exclude from the kinetics computations.
base_units (str (optional, default = 'concentration')) – Basis used for material units in the reactor.
temp_ref (float (optional, default = 298.15)) – Reference temperature for enthalpy calculations.
isothermal (bool (optional, default = True)) – Boolean value indicating whether the energy balance is considered. (i.e. dT/dt = 0 when isothermal is True)
reset_states (bool (optional, default = False)) – Boolean value indicating whether the states should be reset before simulation.
controls (dict of functions (optional, default = None)) – Dictionary with keys representing the state which is controlled and the value indicating the function to use while computing the variable. Functions are of the form f(time) = state_value
h_conv (float (optional, default = 1000)) – Convective heat transfer coefficient for the liquid phase in the reactor (W m^-2 K^-1).
ht_mode (str (optional, default = 'jacket')) – What method is used for heat transfer. Options: [‘jacket’, ‘coil’, ‘bath’]
return_sens (bool (optional, default = True)) – whether or not the paramest_wrapper method should return the sensitivity system along with the concentratio profiles. Use False if you want the parameter estimation platform to estimate the sensitivity system using finite differences

property Inlet

energy_balances(time, mole_conc, vol, temp, temp_ht, inputs, heat_prof=False)

material_balances(time, mole_conc, vol, temp, temp_ht, inputs)

nomenclature()

retrieve_results(time, states)

solve_unit(runtime=None, time_grid=None, eval_sens=False, params_control=None, verbose=True, sundials_opts=None)

class PharmaPy.Reactors.PlugFlowReactor(diam_in, num_discr, mask_params=None, base_units='concentration', temp_ref=298.15, isothermal=False, adiabatic=False, reset_states=False, controls=None, h_conv=1000, ht_mode='bath', return_sens=True, state_events=None)

Bases: _BaseReactor

Inherited constructor for the plug-flow (PFR) reactor class.

Parameters:

diam_in (float) – Diameter of the tubular reactor in meters.
num_discr (int) – number of finite volumes to use to discretize the volume coordinate
mask_params (list of bool (optional, default = None)) – Binary list of which parameters to exclude from the kinetics computations.
base_units (str (optional, default = 'concentration')) – Basis used for material units in the reactor.
temp_ref (float (optional, default = 298.15)) – Reference temperature for enthalpy calculations.
isothermal (bool (optional, default = True)) – Boolean value indicating whether the energy balance is considered. (i.e. dT/dt = 0 when isothermal is True)
adiabatic (bool (optional, default = False)) – Boolean value indication whether the reactor is considered to be adiabatic. Temperature change will not be zero but heat transfer will be zero in this case.
reset_states (bool (optional, default = False)) – Boolean value indicating whether the states should be reset before simulation.
controls (dict of functions (optional, default = None)) – Dictionary with keys representing the state which is controlled and the value indicating the function to use while computing the variable. Functions are of the form f(time) = state_value
h_conv (float (optional, default = 1000)) – Convective heat transfer coefficient for the liquid phase in the reactor (W m^-2 K^-1).
ht_mode (str (optional, default = 'bath')) – What method is used for heat transfer. Options: [‘jacket’, ‘coil’, ‘bath’]
return_sens (bool (optional, default = True)) – whether or not the paramest_wrapper method should return the sensitivity system along with the concentratio profiles. Use False if you want the parameter estimation platform to estimate the sensitivity system using finite differences

property Inlet

animate_reactor(filename=None, step_data=2, fps=5, pick_idx=None, title=None)

energy_balances(time, mole_conc, vol_diff, temp, flow_in, rate_i, heat_profile=False)

energy_steady(conc, temp)

get_inputs(time)

material_balances(time, mole_conc, vol_diff, temp, flow_in, rate_j)

material_steady(conc, temp)

nomenclature()

plot_profiles(times=None, vol=None, pick_comp=None, **fig_kw)

Plot representative profiles for tank reactors. For a more flexible plotting interface, see plot_function in th PharmaPy.Plotting module

Parameters:

pick_comp (list of str/int, optional) – list of components to be plotted. Each element of the list can be either the name of a species (str) or the index of the species (int). The default is None.
**fig_kwargs (keyword arguments to plt.subplots()) – named arguments passed to the plotting functions. A yypical field is ‘figsize’, passed as a (width, height) tuple.

Returns:

fig (TYPE) – fig object.
ax (numpy array or array) – ax object or array of objects.

plot_steady(fig_size=None, title=None)

retrieve_results(time, states)

solve_steady(vol_rxn, adiabatic=False)

solve_unit(runtime=None, time_grid=None, verbose=True, any_event=True, sundials_opts=None)

unit_model(time, states, sw=None, params=None, enrgy_bce=False)

unit_steady(time, states, params=None)

class PharmaPy.Reactors.SemibatchReactor(vol_tank, mask_params=None, base_units='concentration', temp_ref=298.15, isothermal=True, reset_states=False, controls=None, h_conv=1000, ht_mode='jacket', return_sens=True, state_events=None)

Bases: CSTR

Inherited constructor for the semibatch stirred-tank reactor class. This method inherits from the CSTR constructor.

Parameters:

partic_species (list of str) – Names of the species participating in the reaction. Names correspond to species names in the physical properties .json file.
vol_tank (float) – Volume of the vessel in m**3. Required to ensure that the vessel does not overflow
mask_params (list of bool (optional, default = None)) – Binary list of which parameters to exclude from the kinetics computations.
base_units (str (optional, default = 'concentration')) – Basis used for material units in the reactor.
temp_ref (float (optional, default = 298.15)) – Reference temperature for enthalpy calculations.
isothermal (bool (optional, default = True)) – Boolean value indicating whether the energy balance is considered. (i.e. dT/dt = 0 when isothermal is True)
reset_states (bool (optional, default = False)) – Boolean value indicating whether the states should be reset before simulation.
controls (dict of functions (optional, default = None)) – Dictionary with keys representing the state which is controlled and the value indicating the function to use while computing the variable. Functions are of the form f(time) = state_value
h_conv (float (optional, default = 1000)) – Convective heat transfer coefficient for the liquid phase in the reactor (W m^-2 K^-1).
ht_mode (str (optional, default = 'jacket')) – What method is used for heat transfer. Options: [‘jacket’, ‘coil’, ‘bath’]
return_sens (bool (optional, default = True)) – whether or not the paramest_wrapper method should return the sensitivity system along with the concentratio profiles. Use False if you want the parameter estimation platform to estimate the sensitivity system using finite differences

material_balances(time, inputs, **kwargs)

nomenclature()

solve_unit(runtime=None, time_grid=None, eval_sens=False, params_control=None, verbose=True, sundials_opts=None)

PharmaPy.Reactors.check_stoichiometry(stoich, mws)

PharmaPy.Reactors.get_sundials_callable(events, eval_sens, param_vals, unit_model, get_jac)

PharmaPy.Reactors.order_state_names(names)

Crystallizers

class PharmaPy.Crystallizers.BatchCryst(target_comp, mask_params=None, method='1D-FVM', scale=1, vol_tank=None, controls=None, adiabatic=False, rad_zero=0, reset_states=False, h_conv=1000, vol_ht=None, basis='mass_conc', jac_type=None, state_events=None, param_wrapper=None)

Bases: _BaseCryst

Construct a Batch Crystallizer object

Parameters:

target_comp (str, list of strings) – Name of the crystallizing compound(s) from .json file.
mask_params (list of bool (optional, default = None)) – Binary list of which parameters to exclude from the kinetics computation
method (str) – Choice of the numerical method. Options are: ‘moments’, ‘1D-FVM’
scale (float) – Scaling factor by which crystal size distribution will be multiplied.
controls (dict of dicts (funcs) (optional, default = None)) – Dictionary with keys representing the state (e.g.’Temp’) which is controlled and the value indicating the function to use while computing the varible. Functions are of the form f(time) = state_value
cfun_solub (callable) – User defined function for the solubility function : func(conc)
adiabatic (bool (optional, default =True)) – Boolean value indicating whether the heat transfer of the crystallization is considered.
rad_zero (float (optional)) – size of the first bin of the CSD discretization [m]
reset_states (bool (optional, default = False)) – Boolean value indicating whether the states should be reset before simulation
basis (str (optional, default = 'mass_conc')) – Options : ‘massfrac’, ‘massconc’
state_events (lsit of dict(s)) – list of dictionaries, each one containing the specification of a state event

energy_balances(time, params, cryst_rate, u_inputs, rhos, mu_n, distrib, mass_conc, temp, temp_ht, vol, h_in=None, heat_prof=False)

get_heat_duty(time, states)

jac_params(time, states, params)

jac_states(time, states, params, return_only=True)

material_balances(time, params, u_inputs, rhos, mu_n, distrib, mass_conc, temp, temp_ht, vol, phi_in=None)

retrieve_results(time, states)

class PharmaPy.Crystallizers.MSMPR(target_comp, mask_params=None, method='1D-FVM', scale=1, vol_tank=None, controls=None, adiabatic=False, rad_zero=0, reset_states=False, h_conv=1000, vol_ht=None, basis='mass_conc', jac_type=None, num_interp_points=3, state_events=None, param_wrapper=None)

Bases: _BaseCryst

Construct a MSMPR object.

Parameters:

target_comp (str, list of strings) – Name of the crystallizing compound(s) from .json file.
mask_params (list of bool (optional, default = None)) – Binary list of which parameters to exclude from the kinetics computation
method (str) – Choice of the numerical method. Options are: ‘moments’, ‘1D-FVM’
scale (float) – Scaling factor by which crystal size distribution will be multiplied.
controls (dict of dicts (funcs) (optional, default = None)) – Dictionary with keys representing the state (e.g.’Temp’) which is controlled and the value indicating the function to use while computing the varible. Functions are of the form f(time) = state_value
cfun_solub (callable) – User defined function for the solubility function : func(conc)
adiabatic (bool (optional, default =True)) – Boolean value indicating whether the heat transfer of the crystallization is considered.
reset_states (bool (optional, default = False)) – Boolean value indicating whether the states should be reset before simulation
basis (str (optional, default = 'mass_conc')) – Options : ‘massfrac’, ‘massconc’
state_events (lsit of dict(s)) – list of dictionaries, each one containing the specification of a state event

property Inlet

energy_balances(time, params, cryst_rate, u_inputs, rhos, mu_n, distrib, mass_conc, temp, temp_ht, vol, h_in, heat_prof=False)

get_heat_duty(time, states)

material_balances(time, params, u_inputs, rhos, mu_n, distrib, mass_conc, temp, temp_ht, vol, phi_in)

retrieve_results(time, states)

solve_steady_state(frac_seed, temp)

class PharmaPy.Crystallizers.SemibatchCryst(target_comp, vol_tank=None, mask_params=None, method='1D-FVM', scale=1, controls=None, adiabatic=False, rad_zero=0, reset_states=False, h_conv=1000, vol_ht=None, basis='mass_conc', jac_type=None, num_interp_points=3, state_events=None, param_wrapper=None)

Bases: MSMPR

Construct a Semi-batch Crystallizer object

Parameters:

target_comp (str, list of strings) – Name of the crystallizing compound(s) from .json file.
mask_params (list of bool (optional, default = None)) – Binary list of which parameters to exclude from the kinetics computation
method (str) – Choice of the numerical method. Options are: ‘moments’, ‘1D-FVM’
scale (float) – Scaling factor by which crystal size distribution will be multiplied.
controls (dict of dicts (funcs) (optional, default = None)) – Dictionary with keys representing the state (e.g.’Temp’) which is controlled and the value indicating the function to use while computing the varible. Functions are of the form f(time) = state_value
adiabatic (bool (optional, default =True)) – Boolean value indicating whether the heat transfer of the crystallization is considered.
reset_states (bool (optional, default = False)) – Boolean value indicating whether the states should be reset before simulation
basis (str (optional, default = 'mass_conc')) – Options : ‘massfrac’, ‘massconc’
state_events (lsit of dict(s)) – list of dictionaries, each one containing the specification of a state event

energy_balances(time, params, cryst_rate, u_inputs, rhos, distrib, mass_conc, temp, temp_ht, vol, mu_n, h_in)

material_balances(time, params, u_inputs, rhos, mu_n, distrib, mass_conc, temp, temp_ht, vol, phi_in)

Evaporators

class PharmaPy.Evaporators.AdiabaticFlash(pres_drum, div_energybce=1000.0, gamma_method='ideal', mult_midfun=1, seed_basedon_input=False)

Bases: object

Create an adiabatic flash object.

Parameters:

pres_drum (float) – tank pressure [Pa].
div_energybce (float, optional) – Constant by which the energy balance equation is divided. It helps improving the conditioning of the numerical solver. The default is 1e3.
gamma_method (str, optional) – one of ‘ideal’, ‘UNIFAC’ or ‘UNIQUAC’. If ‘UNIFAC’ or ‘UNIQUAC’ is passed, the pure-component .json property file must have required parameters for the activity coefficient model.
mult_midfun (TYPE, optional) – DESCRIPTION. The default is 1.
seed_basedon_input (TYPE, optional) – DESCRIPTION. The default is False.

Return type:

None.

property Inlet

energy_balance(liq, vap, x_i, y_i, z_i, temp)

material_balances(liq, vap, x_i, y_i, z_i, temp)

solve_unit(v_seed=0.5)

Solve AdiabaticFlash unit

Parameters:: v_seed (float, optional) – A seed for output fraction of vapor with respect to feed material to the flash. It must be in the range 0-1. The default is 0.5.
Returns:: solution – solution of the root finding algorithm.
Return type:: SciPy OptimizerResult object

unit_model(states)

class PharmaPy.Evaporators.ContinuousEvaporator(vol_drum, adiabatic=False, pressure=101325, diam_out=0.0254, frac_liq=0.5, k_liq=100, k_vap=1, cv_gas=0.8, h_conv=1000, activity_model='ideal', num_interp_points=3, mult_flash=1, state_events=None, reflux_ratio=0)

Bases: object

Create a continuous evaporator object

Parameters:

vol_drum (float) – total drum volume [m**3].
adiabatic (bool, optional) – if True, heat transfer will be disregarded from the energy balance. The default is False.
pressure (TYPE, optional) – pressure setpoint [Pa] (actual pressure is computed by the evaporator model). The default is 101325.
diam_out (float, optional) – diameter of the vapor outlet pipe [m]. The default is 2.54e-2.
frac_liq (float, optional) – setpoint for the fraction of the total tank volume occupied by the liquid phase. The default is 0.5.
k_liq (float, optional) – proportional control constant for liquid level control, which dictates output liquid mole flow (F_L), with F_L = k_liq * (v_drum * frac_liq - V_L(t)), being V_L(t) the liquid volume computed by the DAE system. The default is 100.
k_vap (float, optional) – proportional control constant for pressure, which actual pressure (P) by changing output vapor molar flow (F_V), with F_V = k_vap * f(pressure - P). The default is 1.
h_conv (float, optional) – convective heat transfer coefficient for the liquid phase [W/m**2/K]. The default is 1000.
activity_model (str, optional) – model to be used for calculation activity coefficient in vapor-liquid equilibria. Choose one of ‘ideal’, ‘UNIFAC’ and ‘UNIQUAC’ The default is ‘ideal’.
num_interp_points (int, optional) – Number of interpolation points to be used by the Interpolation module of PharmaPy to calculate inputs if the evaporator receives material from a dynamic upstream unit operation. The default is 3.
state_events (list of dicts, optional) – list of dictionaries containing the specification of a state event. To learn about the structure of a state event, see the PharmaPy.Commons.eval_state_events documentation. The default is None.
reflux_ratio (float, optional) – reflux ratio ranging from (0 - 1), which dictates the fraction of the vapor flow which is sent back to the unit, assuming total condensation. The default is 0.

Return type:

A continuous vaporizer object.

property Inlet

property Phases

property Utility

energy_balances(time, flow_liq, flow_vap, vol_liq, u_int, temp, x_liq, y_vap, mol_i, mol_liq, mol_vap, pres, u_inputs, heat_prof=False)

flatten_states()

get_heat_duty(time, states)

get_inputs(time)

get_mole_flows(temp, pres, x_i, y_i, mol_liq, mol_vap, input_flow)

get_volumes(temp, pres, x_i, mol_liq, mol_vap)

init_unit()

material_balances(time, mol_i, x_liq, y_vap, mol_liq, mol_vap, pres, u_int, temp, u_inputs, flows_out=False)

nomenclature()

plot_profiles(pick_comp=None, vol_plot=False, **fig_kwargs)

Convenience function to plot model solution. Dynamic profiles displayed by this funcion are x_liq vs t, y_vap vs t, T/P vs t and either mol_liq-mol_vap vs t or vol_liq-vol_vap vs t.

Parameters:

pick_comp (list of int, optional) – indexes of states to be plot. If None, all the states are plotted. The default is None.
vol_plot (bool, optional) – If True, vol_liq-vol_vap vs t is plotted. Otherwise, mol_liq-mol_vap vs t is plotted.
**fig_kwargs (keyword arguments) – keyword arguments to be passed to the construction of fig and axes objects of matplotlib (plt.subplots(**kwargs)). Do not use nrows or ncols arguments, since the plot grid is already defined by PharmaPy

Returns:

fig (TYPE) – figure object.
ax (numpy array) – grid of axis objects.

retrieve_results(time, states)

solve_unit(runtime, steady_state=False, verbose=True, sundials_opts=None, any_event=True)

Solve ContinuousEvaporator model

Parameters:

runtime (float) – final time of the simulation routine.
steady_state (bool, optional) – If True, a steady-state version of the model is solved. Otherwise, a dynamic model is solved. The default is False.
verbose (bool, optional) – if True, integrator statistics will be displayed after the model is solved. The default is True.
sundials_opts (dict, optional) – options to be passed to SUNDIALS. For a list of available options, visit https://jmodelica.org/assimulo/ODE_CVode.html. The default is None.
any_event (TYPE, optional) – DESCRIPTION. The default is True.

Returns:

If steady_state, then a SciPy OptimizationResult object is returned.
Else, a tuple containing a list of times returned by the numerical
integrator and an array of solved states is returned.

unit_jacobian(c, time, states, sdot, params=None)

unit_model(time, states, states_dot, sw, params=None, enrgy_bce=False)

class PharmaPy.Evaporators.Evaporator(vol_drum, pressure=101325, diam_out=0.0254, k_vap=1, cv_gas=0.8, h_conv=1000, activity_model='ideal', state_events=None, stop_at_maxvol=True, flash_kwargs=None, include_nitrogen=False)

Bases: object

Create a batch/semibatch evaporator object

Parameters:

vol_drum (float) – total drum volume [m**3].
pressure (float, optional) – pressure setpoint [Pa] (actual pressure is computed by the evaporator model). The default is 101325.
diam_out (float, optional) – diameter of the vapor outlet pipe [m]. The default is 2.54e-2.
k_vap (float, optional) – constant for vapor flow proportional control. Vapor flow is calculated as F_v = k_vap * (P_model - P) + F_in. The default is 1.
h_conv (float, optional) – convective heat transfer coefficient for the liquid phase [W/m**2/K]. The default is 1000.
activity_model (str, optional) – model to be used for calculation activity coefficient in vapor-liquid equilibria. Choose one of ‘ideal’, ‘UNIFAC’ and ‘UNIQUAC’ The default is ‘ideal’.
state_events (list of dicts, optional) – list of dictionaries containing the specification of a state event. To learn about the structure of a state event, see the PharmaPy.Commons.eval_state_events documentation. The default is None.
stop_at_maxvol (bool, optional) – whether or not to automatically stop integration when liquid volume reaches tank volume. This can be important for semi-batch vaporization. is important for The default is True.
flash_kwargs (dict, optional) – dictionary to be passed to the solve_unit method of the PharmaPy.AdiabaticFlash instance run to initialize the vaporizer. The default is None.

Returns:

A vaporizer object (VO). If a PharmaPy.Stream object is aggregated to the
resulting instance (instance.Inlet = PharmaPy.Stream(…)),
the VO will be interpreted as a Semi-batch evaporator object.
Otherwise, a Batch evaporator will be run.

property Inlet

property Phases

property Utility

energy_balances(time, vol_liq, flow_vap, u_int, temp, x_liq, y_vap, mol_liq, mol_vap, pres, mol_i, u_inputs, du_dt=None)

flatten_states()

get_heat_duty(time, states)

get_inputs(time)

init_unit()

material_balances(time, mol_i, x_liq, y_vap, mol_liq, mol_vap, pres, u_int, temp, u_inputs, dmoli_dt=None)

nomenclature()

plot_profiles(pick_comp=None, **fig_kwargs)

Convenience function to plot model solution. Dynamic profiles displayed by this funcion are x_liq vs t, y_vap vs t, T/P vs t and mol_liq/mol_vap vs t.

Parameters:

pick_comp (list of int, optional) – indexes of states to be plot. If None, all the states are plotted. The default is None.
**fig_kwargs (keyword arguments) – keyword arguments to be passed to the construction of fig and axes object of matplotlib (plt.subplots(**kwargs)). Do not use nrows or ncols arguments, since the plot grid is already defined by PharmaPy

Returns:

fig (TYPE) – figure object.
ax (numpy array) – grid of axis objects.

retrieve_results(time, states)

solve_unit(runtime, verbose=True, sundials_opts=None)

Solve Evaporator model

Parameters:

runtime (float) – final time of the simulation routine.
verbose (bool, optional) – if True, integrator statistics will be displayed after the model is solved. The default is True.
sundials_opts (dict, optional) – options to be passed to SUNDIALS. For a list of available options, visit https://jmodelica.org/assimulo/DAE_IDA.html The default is None.

Returns:

time (list) – list of time steps taken by the numerical integrator.
states (numpy array) – array containing the solution of the model.

unit_jacobian(c, time, states, sdot, params=None)

unit_model(time, states, states_dot, sw, params=None)

class PharmaPy.Evaporators.IsothermalFlash(temp_drum=None, pres_drum=None, gamma_method='ideal')

Bases: object

Create an isothermal flash object. The model run by the instances of this class is steady state isothermal flash given T and P. This model is often used to determine the thermodynamic state of a given stream or phase (only liquid, vapor-liquid, only vapor)

Parameters:

temp_drum (float, optional) – equipment temperature [K]. If None, temperature will be taken from the Inlet object aggregated to the flash (from PharmaPy.Phases or PharmaPy.Streams modules). The default is None.
pres_drum (float, optional) – equipment pressure [Pa]. If None, pressure will be taken from the Inlet object aggregated to the flash (from PharmaPy.Phases or PharmaPy.Streams modules). The default is None.
gamma_method (str, optional) – one of ‘ideal’, ‘UNIFAC’ or ‘UNIQUAC’. If ‘UNIFAC’ or ‘UNIQUAC’ is passed, the pure-component .json file must have the interaction parameters of the model. The default is ‘ideal’.

Return type:

None.

property Inlet

energy_balance(liq, vap, x_i, y_i, z_i)

material_balance(liq, vap, x_i, y_i, z_i)

solve_unit()

unit_model(states, material=True)

PharmaPy.Evaporators.merge_supercritical(flags, x_liq, y_vap, z_super)