rmgpy.solver.LiquidReactor¶
- class rmgpy.solver.LiquidReactor(T, initial_concentrations, n_sims=1, termination=None, sensitive_species=None, sensitivity_threshold=0.001, sens_conditions=None, const_spc_names=None)¶
A reaction system consisting of a homogeneous, isothermal, constant volume batch reactor. These assumptions allow for a number of optimizations that enable this solver to complete very rapidly, even for large kinetic models.
- Keq¶
numpy.ndarray
- Type:
Keq
- P¶
rmgpy.quantity.ScalarQuantity
- Type:
P
- T¶
rmgpy.quantity.ScalarQuantity
- Type:
T
- Trange¶
list
- Type:
Trange
- V¶
‘double’
- Type:
V
- add_reactions_to_surface(self, list new_surface_reactions, list new_surface_reaction_inds, list surface_species, list surface_reactions, list edge_species)¶
moves new surface reactions to the surface done after the while loop before the simulate call ends
- advance()¶
Simulate from the current value of the independent variable to a specified value tout, taking as many steps as necessary. The resulting values of \(t\), \(\mathbf{y}\), and \(\frac{d \mathbf{y}}{dt}\) can then be accessed via the t, y, and dydt attributes.
- atol_array¶
numpy.ndarray
- Type:
atol_array
- bimolecular_threshold¶
numpy.ndarray
- Type:
bimolecular_threshold
- compute_network_variables(self, pdep_networks=None)¶
Initialize the arrays containing network information:
- NetworkLeakCoefficients is a n x 1 array with
n the number of pressure-dependent networks.
- NetworkIndices is a n x 3 matrix with
n the number of pressure-dependent networks and 3 the maximum number of molecules allowed in either the reactant or product side of a reaction.
- compute_rate_derivative(self)¶
Returns derivative vector df/dk_j where dy/dt = f(y, t, k) and k_j is the rate parameter for the jth core reaction.
- const_spc_indices¶
list
- Type:
const_spc_indices
- const_spc_names¶
list
- Type:
const_spc_names
- constant_volume¶
‘bool’
- Type:
constant_volume
- convert_initial_keys_to_species_objects(self, species_dict)¶
Convert the initial_concentrations dictionary from species names into species objects, using the given dictionary of species.
- core_reaction_rates¶
numpy.ndarray
- Type:
core_reaction_rates
- core_species_concentrations¶
numpy.ndarray
- Type:
core_species_concentrations
- core_species_consumption_rates¶
numpy.ndarray
- Type:
core_species_consumption_rates
- core_species_production_rates¶
numpy.ndarray
- Type:
core_species_production_rates
- core_species_rates¶
numpy.ndarray
- Type:
core_species_rates
- dydt0¶
numpy.ndarray
- Type:
dydt0
- edge_reaction_rates¶
numpy.ndarray
- Type:
edge_reaction_rates
- edge_species_rates¶
numpy.ndarray
- Type:
edge_species_rates
- generate_rate_coefficients(self, core_reactions, edge_reactions)¶
Populates the forwardRateCoefficients, reverseRateCoefficients and equilibriumConstants arrays with the values computed at the temperature and (effective) pressure of the reacion system.
- generate_reactant_product_indices(self, core_reactions, edge_reactions)¶
Creates a matrix for the reactants and products.
- generate_reaction_indices(self, core_reactions, edge_reactions)¶
Assign an index to each reaction (core first, then edge) and store the (reaction, index) pair in a dictionary.
- generate_species_indices(self, core_species, edge_species)¶
Assign an index to each species (core first, then edge) and store the (species, index) pair in a dictionary.
- get_const_spc_indices(self, core_species)¶
Allow to identify constant Species position in solver
- get_layering_indices(self)¶
determines the edge reaction indices that indicate reactions that are valid for movement from edge to surface based on the layering constraint
- get_species_index(self, spc)¶
Retrieves the index that is associated with the parameter species from the species index dictionary.
- get_threshold_rate_constants(self, model_settings)¶
Get the threshold rate constants for reaction filtering.
model_settings is not used here, but is needed so that the method matches the one in simpleReactor.
- initial_concentrations¶
dict
- Type:
initial_concentrations
- initialize()¶
Initialize the DASPK solver by setting the initial values of the independent variable t0, dependent variables y0, and first derivatives dydt0. If provided, the derivatives must be consistent with the other initial conditions; if not provided, DASPK will attempt to estimate a consistent set of initial values for the derivatives. You can also set the absolute and relative tolerances atol and rtol, respectively, either as single values for all dependent variables or individual values for each dependent variable.
- initialize_model(self, list core_species, list core_reactions, list edge_species, list edge_reactions, list surface_species=None, list surface_reactions=None, list pdep_networks=None, atol=1e-16, rtol=1e-8, sensitivity=False, sens_atol=1e-6, sens_rtol=1e-4, filter_reactions=False, dict conditions=None)¶
Initialize a simulation of the liquid reactor using the provided kinetic model.
- initialize_solver(self)¶
- initialize_surface(self, list core_species, list core_reactions, list surface_species, list surface_reactions)¶
- removes surface_species and surface_reactions from until they are self consistent:
every reaction has one species in the surface
every species participates in a surface reaction
- initiate_tolerances(self, atol=1e-16, rtol=1e-08, sensitivity=False, sens_atol=1e-06, sens_rtol=0.0001)¶
Computes the number of differential equations and initializes the tolerance arrays.
- jacobian(self, double t, ndarray y, ndarray dydt, double cj, ndarray senpar=np.zeros(1, np.float64))¶
Return the analytical Jacobian for the reaction system.
- jacobian_matrix¶
numpy.ndarray
- Type:
jacobian_matrix
- kb¶
numpy.ndarray
- Type:
kb
- kf¶
numpy.ndarray
- Type:
kf
- log_conversions(self, species_index, y0)¶
Log information about the current conversion values.
- log_rates(self, double char_rate, species, double species_rate, double max_dif_ln_accum_num, network, double network_rate)¶
Log information about the current maximum species and network rates.
- max_edge_species_rate_ratios¶
numpy.ndarray
- Type:
max_edge_species_rate_ratios
- max_network_leak_rate_ratios¶
numpy.ndarray
- Type:
max_network_leak_rate_ratios
- n_sims¶
‘int’
- Type:
n_sims
- neq¶
‘Py_ssize_t’
- Type:
neq
- network_indices¶
numpy.ndarray
- Type:
network_indices
- network_leak_coefficients¶
numpy.ndarray
- Type:
network_leak_coefficients
- network_leak_rates¶
numpy.ndarray
- Type:
network_leak_rates
- num_core_reactions¶
‘Py_ssize_t’
- Type:
num_core_reactions
- num_core_species¶
‘Py_ssize_t’
- Type:
num_core_species
- num_edge_reactions¶
‘Py_ssize_t’
- Type:
num_edge_reactions
- num_edge_species¶
‘Py_ssize_t’
- Type:
num_edge_species
- num_pdep_networks¶
‘Py_ssize_t’
- Type:
num_pdep_networks
- product_indices¶
numpy.ndarray
- Type:
product_indices
- prunable_network_indices¶
numpy.ndarray
- Type:
prunable_network_indices
- prunable_networks¶
list
- Type:
prunable_networks
- prunable_species¶
list
- Type:
prunable_species
- prunable_species_indices¶
numpy.ndarray
- Type:
prunable_species_indices
- reactant_indices¶
numpy.ndarray
- Type:
reactant_indices
- reaction_index¶
dict
- Type:
reaction_index
- reset_max_edge_species_rate_ratios(self)¶
This function sets max_edge_species_rate_ratios back to zero for pruning of ranged reactors it is important to avoid doing this every initialization
- residual(self, double t, ndarray y, ndarray dydt, ndarray senpar=np.zeros(1, np.float64))¶
Return the residual function for the governing DAE system for the liquid reaction system.
- rtol_array¶
numpy.ndarray
- Type:
rtol_array
- sens_conditions¶
dict
- Type:
sens_conditions
- sensitive_species¶
list
- Type:
sensitive_species
- sensitivity_coefficients¶
numpy.ndarray
- Type:
sensitivity_coefficients
- sensitivity_threshold¶
‘double’
- Type:
sensitivity_threshold
- set_initial_conditions(self)¶
Sets the initial conditions of the rate equations that represent the current reactor model.
The volume is set to the value in m3 required to contain one mole total of core species at start.
The core_species_concentrations array is set to the values stored in the initial concentrations dictionary.
The initial number of moles of a species j is computed and stored in the y0 instance attribute.
- set_initial_derivative(self)¶
Sets the derivative of the species moles with respect to the independent variable (time) equal to the residual.
- set_initial_reaction_thresholds(self)¶
- set_prunable_indices(self, edge_species, pdep_networks)¶
- simulate(self, list core_species, list core_reactions, list edge_species, list edge_reactions, list surface_species, list surface_reactions, list pdep_networks=None, bool prune=False, bool sensitivity=False, list sens_worksheet=None, model_settings=None, simulator_settings=None, dict conditions=None)¶
Simulate the reaction system with the provided reaction model, consisting of lists of core species, core reactions, edge species, and edge reactions. As the simulation proceeds the system is monitored for validity. If the model becomes invalid (e.g. due to an excessively large edge flux), the simulation is interrupted and the object causing the model to be invalid is returned. If the simulation completes to the desired termination criteria and the model remains valid throughout,
None
is returned.
- snapshots¶
list
- Type:
snapshots
- species_index¶
dict
- Type:
species_index
- step()¶
Perform one simulation step from the current value of the independent variable toward (but not past) a specified value tout. The resulting values of \(t\), \(\mathbf{y}\), and \(\frac{d \mathbf{y}}{dt}\) can then be accessed via the t, y, and dydt attributes.
- surface_reaction_indices¶
numpy.ndarray
- Type:
surface_reaction_indices
- surface_species_indices¶
numpy.ndarray
- Type:
surface_species_indices
- t0¶
‘float’
- Type:
t0
- termination¶
list
- Type:
termination
- trimolecular¶
‘bool’
- Type:
trimolecular
- trimolecular_threshold¶
numpy.ndarray
- Type:
trimolecular_threshold
- unimolecular_threshold¶
numpy.ndarray
- Type:
unimolecular_threshold
- valid_layering_indices¶
numpy.ndarray
- Type:
valid_layering_indices
- viscosity¶
‘double’
- Type:
viscosity
- y0¶
numpy.ndarray
- Type:
y0