One-dimensional Reacting Flows#

Composite Domains #

FreeFlame #

class cantera.FreeFlame(gas, grid=None, width=None)#

Bases: FlameBase

A freely-propagating flat flame.

A domain of type FreeFlow named ‘flame’ will be created to represent the flame. The three domains comprising the stack are stored as self.inlet, self.flame, and self.outlet.

Parameters:

grid – A list of points to be used as the initial grid. Not recommended unless solving only on a fixed grid; Use the width parameter instead.
width – Defines a grid on the interval [0, width] with internal points determined automatically by the solver.

flame#: FreeFlow domain representing the flame

get_flame_speed_reaction_sensitivities()#: Compute the normalized sensitivities of the laminar flame speed \(S_u\) with respect to the reaction rate constants \(k_i\):

\[s_i = \frac{k_i}{S_u} \frac{dS_u}{dk_i}\]

inlet#: Inlet1D at the left of the domain representing premixed reactants

outlet#: Outlet1D at the right of the domain representing the burned products

set_initial_guess(locs=[0.0, 0.3, 0.5, 1.0], data=None, group=None)#

Set the initial guess for the solution. By default, the adiabatic flame temperature and equilibrium composition are computed for the inlet gas composition. Alternatively, a previously calculated result can be supplied as an initial guess via ‘data’ and ‘key’ inputs (see FlameBase.set_initial_guess).

Parameters:: locs – A list of four locations to define the temperature and mass fraction profiles. Profiles rise linearly between the second and third location. Locations are given as a fraction of the entire domain

solve(loglevel=1, refine_grid=True, auto=False, stage=1)#

Solve the problem.

Parameters:

loglevel – integer flag controlling the amount of diagnostic output. Zero suppresses all output, and 5 produces very verbose output.
refine_grid – if True, enable grid refinement.
auto – if True, sequentially execute the different solution stages and attempt to automatically recover from errors. Attempts to first solve on the initial grid with energy enabled. If that does not succeed, a fixed-temperature solution will be tried followed by enabling the energy equation, and then with grid refinement enabled. If non-default tolerances have been specified or multicomponent transport is enabled, an additional solution using these options will be calculated.
stage – solution stage; only used when transport model is ionized-gas.

BurnerFlame #

class cantera.BurnerFlame(gas, grid=None, width=None)#

Bases: FlameBase

A burner-stabilized flat flame.

Parameters:

gas – Solution (using the IdealGas thermodynamic model) used to evaluate all gas properties and reaction rates.
grid – A list of points to be used as the initial grid. Not recommended unless solving only on a fixed grid; Use the width parameter instead.
width – Defines a grid on the interval [0, width] with internal points determined automatically by the solver.

A domain of class UnstrainedFlow named flame will be created to represent the flame. The three domains comprising the stack are stored as self.burner, self.flame, and self.outlet.

burner#: Inlet1D at the left of the domain representing the burner surface through which reactants flow

flame#: UnstrainedFlow domain representing the flame

outlet#: Outlet1D at the right of the domain representing the burned gas

set_initial_guess(data=None, group=None)#: Set the initial guess for the solution. By default, the adiabatic flame temperature and equilibrium composition are computed for the burner gas composition. The temperature profile rises linearly in the first 20% of the flame to Tad, then is flat. The mass fraction profiles are set similarly. Alternatively, a previously calculated result can be supplied as an initial guess via ‘data’ and ‘key’ inputs (see FlameBase.set_initial_guess).

solve(loglevel=1, refine_grid=True, auto=False, stage=1)#

Solve the problem.

Parameters:

loglevel – integer flag controlling the amount of diagnostic output. Zero suppresses all output, and 5 produces very verbose output.
refine_grid – if True, enable grid refinement.
auto – if True, sequentially execute the different solution stages and attempt to automatically recover from errors. Attempts to first solve on the initial grid with energy enabled. If that does not succeed, a fixed-temperature solution will be tried followed by enabling the energy equation, and then with grid refinement enabled. If non-default tolerances have been specified or multicomponent transport is enabled, an additional solution using these options will be calculated.
stage – solution stage; only used when transport model is ionized-gas.

CounterflowDiffusionFlame #

class cantera.CounterflowDiffusionFlame(gas, grid=None, width=None)#

Bases: FlameBase

A counterflow diffusion flame

Parameters:

gas – Solution (using the IdealGas thermodynamic model) used to evaluate all gas properties and reaction rates.
grid – A list of points to be used as the initial grid. Not recommended unless solving only on a fixed grid; Use the width parameter instead.
width – Defines a grid on the interval [0, width] with internal points determined automatically by the solver.

A domain of class AxisymmetricFlow named flame will be created to represent the flame. The three domains comprising the stack are stored as self.fuel_inlet, self.flame, and self.oxidizer_inlet.

property equivalence_ratio#

extinct()#: Method overloaded for some flame types to indicate if the flame has been extinguished. Base class method always returns ‘False’

flame#: AxisymmetricFlow domain representing the flame

fuel_inlet#: Inlet1D at the left of the domain representing the fuel mixture

mixture_fraction(m)#

Compute the mixture fraction based on element m or from the Bilger mixture fraction by setting m="Bilger"

The mixture fraction is computed from the elemental mass fraction of element m, normalized by its values on the fuel and oxidizer inlets:

\[Z = \frac{Z_{\mathrm{mass},m}(z) - Z_{\mathrm{mass},m}(z_\mathrm{oxidizer})} {Z_{\mathrm{mass},m}(z_\mathrm{fuel}) - Z_{\mathrm{mass},m}(z_\mathrm{oxidizer})}\]

or from the Bilger mixture fraction:

\[Z = \frac{\beta-\beta_{\mathrm{oxidizer}}} {\beta_{\mathrm{fuel}}-\beta_{\mathrm{oxidizer}}}\]

with

\[\beta = 2\frac{Z_C}{M_C}+2\frac{Z_S}{M_S} +\frac{1}{2}\frac{Z_H}{M_H}-\frac{Z_O}{M_O}\]

Parameters:: m – The element based on which the mixture fraction is computed, may be specified by name or by index, or “Bilger” for the Bilger mixture fraction, which considers the elements C, H, S, and O

>>> f.mixture_fraction('H')
>>> f.mixture_fraction('Bilger')

oxidizer_inlet#: Inlet1D at the right of the domain representing the oxidizer mixture

set_initial_guess(data=None, group=None)#: Set the initial guess for the solution. By default, the initial guess is generated by assuming infinitely-fast chemistry. Alternatively, a previously calculated result can be supplied as an initial guess via ‘data’ and ‘key’ inputs (see FlameBase.set_initial_guess).

solve(loglevel=1, refine_grid=True, auto=False, stage=1)#

Solve the problem.

Parameters:

loglevel – integer flag controlling the amount of diagnostic output. Zero suppresses all output, and 5 produces very verbose output.
refine_grid – if True, enable grid refinement.
auto – if True, sequentially execute the different solution stages and attempt to automatically recover from errors. Attempts to first solve on the initial grid with energy enabled. If that does not succeed, a fixed-temperature solution will be tried followed by enabling the energy equation, and then with grid refinement enabled. If non-default tolerances have been specified or multicomponent transport is enabled, an additional solution using these options will be calculated.
stage – solution stage; only used when transport model is ionized-gas.

strain_rate(definition, fuel=None, oxidizer='O2', stoich=None)#

Return the axial strain rate of the counterflow diffusion flame in 1/s.

Parameters:

definition – The definition of the strain rate to be calculated. Options are: mean, max, stoichiometric, potential_flow_fuel, and potential_flow_oxidizer.
fuel – The fuel species. Used only if definition is stoichiometric.
oxidizer – The oxidizer species, default O2. Used only if definition is stoichiometric.
stoich – The molar stoichiometric oxidizer-to-fuel ratio. Can be omitted if the oxidizer is O2. Used only if definition is stoichiometric.

The parameter definition sets the method to compute the strain rate. Possible options are:

mean:

The mean axial velocity gradient in the entire domain

\[a_{mean} = \left| \frac{\Delta u}{\Delta z} \right|\]

max:

The maximum axial velocity gradient

\[a_{max} = \max \left( \left| \frac{du}{dz} \right| \right)\]

stoichiometric:

The axial velocity gradient at the stoichiometric surface.

\[a_{stoichiometric} = \left| \left. \frac{du}{dz} \right|_{\phi=1} \right|\]

This method uses the additional keyword arguments fuel, oxidizer, and stoich.

>>> f.strain_rate('stoichiometric', fuel='H2', oxidizer='O2',
                  stoich=0.5)

potential_flow_fuel:

The corresponding axial strain rate for a potential flow boundary condition at the fuel inlet.

\[a_{f} = \sqrt{-\frac{\Lambda}{\rho_{f}}}\]

potential_flow_oxidizer:

The corresponding axial strain rate for a potential flow boundary condition at the oxidizer inlet.

\[a_{o} = \sqrt{-\frac{\Lambda}{\rho_{o}}}\]

CounterflowPremixedFlame #

class cantera.CounterflowPremixedFlame(gas, grid=None, width=None)#

Bases: FlameBase

A premixed counterflow flame

Parameters:

gas – Solution (using the IdealGas thermodynamic model) used to evaluate all gas properties and reaction rates.
grid – Array of initial grid points. Not recommended unless solving only on a fixed grid; Use the width parameter instead.
width – Defines a grid on the interval [0, width] with internal points determined automatically by the solver.

A domain of class AxisymmetricFlow named flame will be created to represent the flame. The three domains comprising the stack are stored as self.reactants, self.flame, and self.products.

flame#: AxisymmetricFlow domain representing the flame

products#: Inlet1D at the right of the domain representing burned products

reactants#: Inlet1D at the left of the domain representing premixed reactants

set_initial_guess(equilibrate=True, data=None, group=None)#

Set the initial guess for the solution.

If equilibrate is True, then the products composition and temperature will be set to the equilibrium state of the reactants mixture. Alternatively, a previously calculated result can be supplied as an initial guess via ‘data’ and ‘key’ inputs (see FlameBase.set_initial_guess).

CounterflowTwinPremixedFlame #

class cantera.CounterflowTwinPremixedFlame(gas, grid=None, width=None)#

Bases: FlameBase

A twin premixed counterflow flame. Two opposed jets of the same composition shooting into each other.

Parameters:

gas – Solution (using the IdealGas thermodynamic model) used to evaluate all gas properties and reaction rates.
grid – Array of initial grid points. Not recommended unless solving only on a fixed grid; Use the width parameter instead.
width – Defines a grid on the interval [0, width] with internal points determined automatically by the solver.

A domain of class AxisymmetricFlow named flame will be created to represent the flame. The three domains comprising the stack are stored as self.reactants, self.flame, and self.products.

flame#: AxisymmetricFlow domain representing the flame

products#

reactants#

set_initial_guess(data=None, group=None)#: Set the initial guess for the solution based on an equilibrium solution. Alternatively, a previously calculated result can be supplied as an initial guess via ‘data’ and ‘key’ inputs (see FlameBase.set_initial_guess).

ImpingingJet #

class cantera.ImpingingJet(gas, grid=None, width=None, surface=None)#

Bases: FlameBase

An axisymmetric flow impinging on a surface at normal incidence.

Parameters:

gas – Solution (using the IdealGas thermodynamic model) used to evaluate all gas properties and reaction rates.
grid – A list of points to be used as the initial grid. Not recommended unless solving only on the initial grid; Use the width parameter instead.
width – Defines a grid on the interval [0, width] with internal points determined automatically by the solver.
surface – A Kinetics object used to compute any surface reactions.

A domain of class AxisymmetricFlow named flame will be created to represent the flame. The three domains comprising the stack are stored as self.inlet, self.flame, and self.surface.

flame#: AxisymmetricFlow domain representing the flame

inlet#: Inlet1D at the left of the domain representing the incoming reactants

set_initial_guess(products='inlet', data=None, group=None)#: Set the initial guess for the solution. If products = ‘equil’, then the equilibrium composition at the adiabatic flame temperature will be used to form the initial guess. Otherwise the inlet composition will be used. Alternatively, a previously calculated result can be supplied as an initial guess via ‘data’ and ‘key’ inputs (see FlameBase.set_initial_guess).

surface#: Surface1D or ReactingSurface1D domain representing the surface the flow is impinging on

Flow Domains #

FreeFlow #

class cantera.FreeFlow(thermo)#

Bases: _FlowBase

A free flow domain. The equations solved are standard equations for adiabatic one-dimensional flow. The solution variables are:

velocity: axial velocity
T: temperature
Y_k: species mass fractions

AxisymmetricFlow #

class cantera.AxisymmetricFlow(thermo)#

Bases: _FlowBase

An axisymmetric flow domain. The equations solved are the similarity equations for the flow in a finite-height gap of infinite radial extent. The solution variables are:

velocity: axial velocity
spread_rate: radial velocity divided by radius
T: temperature
lambda: \((1/r)(dP/dr)\)
Y_k: species mass fractions

It may be shown that if the boundary conditions on these variables are independent of radius, then a similarity solution to the exact governing equations exists in which these variables are all independent of radius. This solution holds only in the low-Mach-number limit, in which case \((dP/dz) = 0\), and \(lambda\) is a constant. (Lambda is treated as a spatially-varying solution variable for numerical reasons, but in the final solution it is always independent of \(z\).) As implemented here, the governing equations assume an ideal gas mixture. Arbitrary chemistry is allowed, as well as arbitrary variation of the transport properties.

Boundaries #

Inlet1D #

class cantera.Inlet1D(phase, *, name=None)#

Bases: Boundary1D

A one-dimensional inlet. Note that an inlet can only be a terminal domain - it must be either the leftmost or rightmost domain in a stack.

Outlet1D #

class cantera.Outlet1D(phase, *, name=None)#

Bases: Boundary1D

A one-dimensional outlet. An outlet imposes a zero-gradient boundary condition on the flow.

OutletReservoir1D #

class cantera.OutletReservoir1D(phase, *, name=None)#

Bases: Boundary1D

A one-dimensional outlet into a reservoir.

SymmetryPlane1D #

class cantera.SymmetryPlane1D(phase, *, name=None)#

Bases: Boundary1D

A symmetry plane.

Surface1D #

class cantera.Surface1D(phase, * name=None)#

Bases: Boundary1D

A solid surface.

ReactingSurface1D #

class cantera.ReactingSurface1D(phase, *, name=None)#

Bases: Boundary1D

A reacting solid surface.

Parameters:: phase – The (surface) phase corresponding to the boundary

Changed in version 3.0: Starting in Cantera 3.0, parameter phase should reference surface instead of gas phase.

coverage_enabled#: Controls whether or not to solve the surface coverage equations.

phase#: Get the Interface object representing species and reactions on the surface

surface#

Base Classes #

Domain1D #

class cantera.Domain1D(phase, *, name=None)#

Bases: object

bounds(component)#

Return the (lower, upper) bounds for a solution component.

>>> d.bounds('T')
(200.0, 5000.0)

component_index(name)#: Index of the component with name ‘name’

component_name(n)#: Name of the nth component.

component_names#: List of the names of all components of this domain.

domain_type#: String indicating the domain implemented.

grid#: The grid for this domain

have_user_tolerances#

index#: Index of this domain in a stack. Returns -1 if this domain is not part of a stack.

n_components#: Number of solution components at each grid point.

n_points#: Number of grid points belonging to this domain.

name#: The name / id of this domain

phase#: Phase describing the domain (that is, a gas phase or surface phase).

set_bounds(*, default=None, Y=None, **kwargs)#

Set the lower and upper bounds on the solution.

The argument list should consist of keyword/value pairs, with component names as keywords and (lower bound, upper bound) tuples as the values. The keyword default may be used to specify default bounds for all unspecified components. The keyword Y can be used to stand for all species mass fractions in flow domains.

>>> d.set_bounds(default=(0, 1), Y=(-1.0e-5, 2.0))

set_default_tolerances()#: Set all tolerances to their default values

set_steady_tolerances(*, default=None, Y=None, abs=None, rel=None, **kwargs)#

Set the error tolerances for the steady-state problem.

The argument list should consist of keyword/value pairs, with component names as keywords and (relative tolerance, absolute tolerance) tuples as the values. The keyword default may be used to specify default bounds for all unspecified components. The keyword Y can be used to stand for all species mass fractions in flow domains. Alternatively, the keywords abs and rel can be used to specify arrays for the absolute and relative tolerances for each solution component.

set_transient_tolerances(*, default=None, Y=None, abs=None, rel=None, **kwargs)#

Set the error tolerances for the steady-state problem.

settings#: Return comprehensive dictionary describing type, name, and simulation settings that are specific to domain types.

Changed in version 3.0: Added missing domain-specific simulation settings and updated structure.

steady_abstol(component=None)#: Return the absolute error tolerance for the steady state problem for a specified solution component, or all components if none is specified.

steady_reltol(component=None)#: Return the relative error tolerance for the steady state problem for a specified solution component, or all components if none is specified.

tolerances(component)#

Return the (relative, absolute) error tolerances for a solution component.

>>> rtol, atol = d.tolerances('u')

transient_abstol(component=None)#: Return the absolute error tolerance for the transient problem for a specified solution component, or all components if none is specified.

transient_reltol(component=None)#: Return the relative error tolerance for the transient problem for a specified solution component, or all components if none is specified.

Boundary1D #

class cantera.Boundary1D(phase, *, name=None)#

Bases: Domain1D

Base class for boundary domains.

Parameters:: phase – The (gas) phase corresponding to the adjacent flow domain

T#: The temperature [K] at this boundary.

X#: Species mole fractions at this boundary. May be set as either a string or as an array.

Y#: Species mass fractions at this boundary. May be set as either a string or as an array.

mdot#: The mass flow rate per unit area [kg/s/m^2]

spread_rate#: Get/set the tangential velocity gradient [1/s] at this boundary.

Sim1D #

class cantera.Sim1D(domains)#

Bases: object

Class Sim1D is a container for one-dimensional domains. It also holds the multi-domain solution vector, and controls the process of finding the solution.

Domains are ordered left-to-right, with domain number 0 at the left.

clear_stats()#: Clear solver statistics.

domain_index(dom)#: Get the index of a domain, specified either by name or as a Domain1D object.

domains#

eval(rdt=0.0)#

Evaluate the governing equations using the current solution estimate, storing the residual in the array which is accessible with the work_value function.

Parameters:: rdt – Reciprocal of the time-step

eval_count_stats#: Return number of non-Jacobian function evaluations made in each call to solve()

eval_time_stats#: Return CPU time spent on non-Jacobian function evaluations in each call to solve()

extinct()#: Method overloaded for some flame types to indicate if the flame has been extinguished. Base class method always returns ‘False’

fixed_temperature#: Set the temperature used to fix the spatial location of a freely propagating flame.

fixed_temperature_location#: Return the location of the point where temperature is fixed for a freely propagating flame.

get_max_grid_points(domain)#: Get the maximum number of grid points in the specified domain.

get_refine_criteria(domain)#

Get a dictionary of the criteria used to refine one domain. The items in the dictionary are the ratio, slope, curve, and prune, as defined in set_refine_criteria.

Parameters:: domain – domain object, index, or name

>>> s.set_refine_criteria(d, ratio=5.0, slope=0.2, curve=0.3, prune=0.03)
>>> s.get_refine_criteria(d)
{'ratio': 5.0, 'slope': 0.2, 'curve': 0.3, 'prune': 0.03}

grid_size_stats#: Return total grid size in each call to solve()

jacobian_count_stats#: Return number of Jacobian evaluations made in each call to solve()

jacobian_time_stats#: Return CPU time spent evaluating Jacobians in each call to solve()

max_time_step_count#: Get/Set the maximum number of time steps allowed before reaching the steady-state solution

phase(domain=None)#

Return phase describing a domain (that is, a gas phase or surface phase).

Parameters:: domain – Index of domain within Sim1D.domains list; the default is to return the phase of the parent Sim1D object.

profile(domain, component)#

Spatial profile of one component in one domain.

Parameters:

domain – Domain1D object, name, or index
component – component name or index

>>> T = s.profile(flow, 'T')

refine(loglevel=1)#: Refine the grid, adding points where solution is not adequately resolved.

restore(filename='soln.yaml', name='solution', loglevel=None)#

Retrieve data and settings from a previously saved simulation.

This method restores a simulation object from YAML or HDF data previously saved using the save method.

Parameters:

filename – Name of container file (YAML or HDF)
name – Identifier of location within the container file; this node/group contains header information and subgroups with domain-specific SolutionArray data
loglevel – Amount of logging information to display while restoring, from 0 (disabled) to 2 (most verbose).

Returns:

Dictionary containing header information

>>> s.restore(filename='save.yaml', name='energy_off')

Changed in version 3.0: Implemented return value for meta data; loglevel is no longer supported

restore_steady_solution()#: Set the current solution vector to the last successful steady-state solution. This can be used to examine the solver progress after a failure during grid refinement.

restore_time_stepping_solution()#: Set the current solution vector to the last successful time-stepping solution. This can be used to examine the solver progress after a failed integration.

save(filename='soln.yaml', name='solution', description=None, loglevel=None, *, overwrite=False, compression=0, basis=None)#

Save current simulation data to a data file (CSV, YAML or HDF).

In order to save the content of the current object, individual domains are converted to SolutionArray objects and saved using the save method. For HDF and YAML output, all domains are written to a single container file with shared header information. Simulation settings of individual domains are preserved as meta data of the corresponding SolutionArray objects. For CSV files, only state and auxiliary data of the main 1D domain are saved.

The complete state of the current object can be restored from HDF and YAML container files using the restore method, while individual domains can be loaded using SolutionArray.restore for further analysis. While CSV files do not contain complete information, they can be used for setting initial states of individual simulation objects (example: set_initial_guess).

Parameters:

filename – Name of output file (CSV, YAML or HDF)
name – Identifier of storage location within the container file; this node/group contains header information and multiple subgroups holding domain-specific SolutionArray data (YAML/HDF only).
description – Custom comment describing the dataset to be stored (YAML/HDF only).
overwrite – Force overwrite if file and/or data entry exists; optional (default=`False`)
compression – Compression level (0-9); optional (default=0; HDF only)
basis – Output mass (Y/mass) or mole (Y/mass) fractions; if not specified (None), the native basis of the underlying ThermoPhase manager is used.

>>> s.save(filename='save.yaml', name='energy_off',
...        description='solution with energy eqn. disabled')

Changed in version 3.0: Argument loglevel is no longer supported

set_flat_profile(domain, component, value)#

Set a flat profile for one component in one domain.

Parameters:

domain – Domain1D object, name, or index
component – component name or index
v – value

>>> s.set_flat_profile(d, 'u', -3.0)

set_grid_min(dz, domain=None)#: Set the minimum grid spacing on domain. If domain is None, then set the grid spacing for all domains.

set_initial_guess(*args, **kwargs)#: Store arguments for initial guess and prepare storage for solution.

set_interrupt(f)#: Set an interrupt function to be called each time that OneDim::eval() is called. The signature of f is float f(float). The default interrupt function is used to trap KeyboardInterrupt exceptions so that ctrl-c can be used to break out of the C++ solver loop.

set_max_grid_points(domain, npmax)#: Set the maximum number of grid points in the specified domain.

set_max_jac_age(ss_age, ts_age)#

Set the maximum number of times the Jacobian will be used before it must be re-evaluated.

Parameters:

ss_age – age criterion during steady-state mode
ts_age – age criterion during time-stepping mode

set_max_time_step(tsmax)#: Set the maximum time step.

set_min_time_step(tsmin)#: Set the minimum time step.

set_profile(domain, component, positions, values)#

Set an initial estimate for a profile of one component in one domain.

Parameters:

domain – Domain1D object, name, or index
component – component name or index
positions – sequence of relative positions, from 0 on the left to 1 on the right
values – sequence of values at the relative positions specified in positions

>>> s.set_profile(d, 'T', [0.0, 0.2, 1.0], [400.0, 800.0, 1500.0])

set_refine_criteria(domain, ratio=10.0, slope=0.8, curve=0.8, prune=0.05)#

Set the criteria used to refine one domain.

Parameters:

domain – domain object, index, or name
ratio – additional points will be added if the ratio of the spacing on either side of a grid point exceeds this value
slope – maximum difference in value between two adjacent points, scaled by the maximum difference in the profile (0.0 < slope < 1.0). Adds points in regions of high slope.
curve – maximum difference in slope between two adjacent intervals, scaled by the maximum difference in the profile (0.0 < curve < 1.0). Adds points in regions of high curvature.
prune – if the slope or curve criteria are satisfied to the level of ‘prune’, the grid point is assumed not to be needed and is removed. Set prune significantly smaller than ‘slope’ and ‘curve’. Set to zero to disable pruning the grid.

>>> s.set_refine_criteria(d, ratio=5.0, slope=0.2, curve=0.3, prune=0.03)

set_steady_callback(f)#: Set a callback function to be called after each successful steady-state solve, before regridding. The signature of f is float f(float). The argument passed to f is 0.0 and the output is ignored.

set_time_step(stepsize, n_steps)#

Set the sequence of time steps to try when Newton fails.

Parameters:

stepsize – initial time step size [s]
n_steps – sequence of integer step numbers

>>> s.set_time_step(1.0e-5, [1, 2, 5, 10])

set_time_step_callback(f)#: Set a callback function to be called after each successful timestep. The signature of f is float f(float). The argument passed to f is the size of the timestep. The output is ignored.

set_time_step_factor(tfactor)#: Set the factor by which the time step will be increased after a successful step, or decreased after an unsuccessful one.

set_value(domain, component, point, value)#

Set the value of one component in one domain at one point to ‘value’.

Parameters:

domain – Domain1D object, name, or index
component – component name or index
point – grid point number within domain starting with 0 on the left
value – numerical value

>>> s.set(d, 3, 5, 6.7)
>>> s.set(1, 0, 5, 6.7)
>>> s.set('flow', 'T', 5, 500)

show()#: print the current solution.

show_stats(print_time=True)#

Show the statistics for the last solution.

If invoked with no arguments or with a non-zero argument, the timing statistics will be printed. Otherwise, the timing will not be printed.

solve(loglevel=1, refine_grid=True, auto=False)#

Solve the problem.

Parameters:

loglevel – integer flag controlling the amount of diagnostic output. Zero suppresses all output, and 5 produces very verbose output.
refine_grid – if True, enable grid refinement.
auto – if True, sequentially execute the different solution stages and attempt to automatically recover from errors. Attempts to first solve on the initial grid with energy enabled. If that does not succeed, a fixed-temperature solution will be tried followed by enabling the energy equation, and then with grid refinement enabled. If non-default tolerances have been specified or multicomponent transport is enabled, an additional solution using these options will be calculated.

solve_adjoint(perturb, n_params, dgdx, g=None, dp=1e-05)#

Find the sensitivities of an objective function using an adjoint method.

For an objective function \(g(x, p)\) where \(x\) is the state vector of the system and \(p\) is a vector of parameters, this computes the vector of sensitivities \(dg/dp\). This assumes that the system of equations has already been solved to find \(x\).

Parameters:

perturb –
A function with the signature perturb(sim, i, dp) which perturbs parameter i by a relative factor of dp. To perturb a reaction rate constant, this function could be defined as:
```
def perturb(sim, i, dp):
    sim.gas.set_multiplier(1+dp, i)
```
Calling perturb(sim, i, 0) should restore that parameter to its default value.
n_params – The length of the vector of sensitivity parameters
dgdx – The vector of partial derivatives of the function \(g(x, p)\) with respect to the system state \(x\).
g – A function with the signature value = g(sim) which computes the value of \(g(x,p)\) at the current system state. This is used to compute \(\partial g/\partial p\). If this is identically zero (that is, \(g\) is independent of \(p\)) then this argument may be omitted.
dp – A relative value by which to perturb each parameter

time_step_stats#: Return number of time steps taken in each call to solve()

value(domain, component, point)#

Solution value at one point

Parameters:

domain – Domain1D object, name, or index
component – component name or index
point – grid point number within domain starting with 0 on the left

>>> t = s.value('flow', 'T', 6)

work_value(domain, component, point)#

Internal work array value at one point. After calling eval, this array contains the values of the residual function.

Parameters:

domain – Domain1D object, name, or index
component – component name or index
point – grid point number in the domain, starting with zero at the left

>>> t = s.value(flow, 'T', 6)

FlameBase #

class cantera.FlameBase(domains, gas, grid=None)#

Bases: Sim1D

Base class for flames with a single flow domain

Parameters:

gas – object to use to evaluate all gas properties and reaction rates
grid – array of initial grid points

property E#: Array containing the electric field strength at each point.

property L#: Array containing the radial pressure gradient (1/r)(dP/dr) [N/m^4] at each point. Note: This value is named ‘lambda’ in the C++ code.

property P#: Get/Set the pressure of the flame [Pa]

property T#: Array containing the temperature [K] at each grid point.

property X#: Array of mole fractions of size n_species x n_points

property Y#: Array of mass fractions of size n_species x n_points

property activities#

Array of nondimensional activities. Returns either molar or molal activities depending on the convention of the thermodynamic model.

Returns an array of size n_species x n_points.

property activity_coefficients#

Array of nondimensional, molar activity coefficients.

Returns an array of size n_species x n_points.

property boundary_emissivities#: Set/get boundary emissivities.

property chemical_potentials#

Array of species chemical potentials [J/kmol].

Returns an array of size n_species x n_points.

property concentrations#: Array of species concentrations [kmol/m^3] of size n_species x n_points

property cp#

Heat capacity at constant pressure [J/kg/K or J/kmol/K] depending on basis.

Returns an array of length n_points.

property cp_mass#

Specific heat capacity at constant pressure [J/kg/K].

Returns an array of length n_points.

property cp_mole#

Molar heat capacity at constant pressure [J/kmol/K].

Returns an array of length n_points.

property creation_rates#

Creation rates for each species. [kmol/m^3/s] for bulk phases or [kmol/m^2/s] for surface phases.

Returns an array of size n_species x n_points.

property creation_rates_ddC#

Calculate derivatives of species creation rates with respect to molar concentration at constant temperature, pressure and mole fractions.

Warning

This property is an experimental part of the Cantera API and may be changed or removed without notice.

Returns an array of size n_species x n_points.

property creation_rates_ddP#

Calculate derivatives of species creation rates with respect to pressure at constant temperature, molar concentration and mole fractions.

Returns an array of size n_species x n_points.

property creation_rates_ddT#

Calculate derivatives of species creation rates with respect to temperature at constant pressure, molar concentration and mole fractions.

Returns an array of size n_species x n_points.

property cv#

Heat capacity at constant volume [J/kg/K or J/kmol/K] depending on basis.

Returns an array of length n_points.

property cv_mass#

Specific heat capacity at constant volume [J/kg/K].

Returns an array of length n_points.

property cv_mole#

Molar heat capacity at constant volume [J/kmol/K].

Returns an array of length n_points.

property delta_enthalpy#

Change in enthalpy for each reaction [J/kmol].

Returns an array of size n_reactions x n_points.

property delta_entropy#

Change in entropy for each reaction [J/kmol/K].

Returns an array of size n_reactions x n_points.

property delta_gibbs#

Change in Gibbs free energy for each reaction [J/kmol].

Returns an array of size n_reactions x n_points.

property delta_standard_enthalpy#

Change in standard-state enthalpy (independent of composition) for each reaction [J/kmol].

Returns an array of size n_reactions x n_points.

property delta_standard_entropy#

Change in standard-state entropy (independent of composition) for each reaction [J/kmol/K].

Returns an array of size n_reactions x n_points.

property delta_standard_gibbs#

Change in standard-state Gibbs free energy (independent of composition) for each reaction [J/kmol].

Returns an array of size n_reactions x n_points.

property density#

Density [kg/m^3 or kmol/m^3] depending on basis.

Returns an array of length n_points.

property density_mass#

(Mass) density [kg/m^3].

Returns an array of length n_points.

property density_mole#

Molar density [kmol/m^3].

Returns an array of length n_points.

property destruction_rates#

Destruction rates for each species. [kmol/m^3/s] for bulk phases or [kmol/m^2/s] for surface phases.

Returns an array of size n_species x n_points.

property destruction_rates_ddC#

Calculate derivatives of species destruction rates with respect to molar concentration at constant temperature, pressure and mole fractions.

Warning

This property is an experimental part of the Cantera API and may be changed or removed without notice.

Returns an array of size n_species x n_points.

property destruction_rates_ddP#

Calculate derivatives of species destruction rates with respect to pressure at constant temperature, molar concentration and mole fractions.

Returns an array of size n_species x n_points.

property destruction_rates_ddT#

Calculate derivatives of species destruction rates with respect to temperature at constant pressure, molar concentration and mole fractions.

Returns an array of size n_species x n_points.

property electric_field_enabled#: Get/Set whether or not to solve the Poisson’s equation.

property electrochemical_potentials#

Array of species electrochemical potentials [J/kmol].

Returns an array of size n_species x n_points.

elemental_mass_fraction(m)#

Get the elemental mass fraction \(Z_{\mathrm{mass},m}\) of element \(m\) at each grid point, which is defined as:

\[Z_{\mathrm{mass},m} = \sum_k \frac{a_{m,k} M_m}{M_k} Y_k\]

with \(a_{m,k}\) being the number of atoms of element \(m\) in species \(k\), \(M_m\) the atomic weight of element \(m\), \(M_k\) the molecular weight of species \(k\), and \(Y_k\) the mass fraction of species \(k\).

Parameters:: m – Base element, may be specified by name or by index.

>>> phase.elemental_mass_fraction('H')
[1.0, ..., 0.0]

elemental_mole_fraction(m)#

Get the elemental mole fraction \(Z_{\mathrm{mole},m}\) of element \(m\) at each grid point, which is defined as:

\[Z_{\mathrm{mole},m} = \sum_k \frac{a_{m,k}}{\sum_j a_{j,k}} X_k\]

with \(a_{m,k}\) being the number of atoms of element \(m\) in species \(k\) and \(X_k\) the mole fraction of species \(k\).

Parameters:: m – Base element, may be specified by name or by index.

>>> phase.elemental_mole_fraction('H')
[1.0, ..., 0.0]

property energy_enabled#: Get/Set whether or not to solve the energy equation.

property enthalpy_mass#

Specific enthalpy [J/kg].

Returns an array of length n_points.

property enthalpy_mole#

Molar enthalpy [J/kmol].

Returns an array of length n_points.

property entropy_mass#

Specific entropy [J/kg/K].

Returns an array of length n_points.

property entropy_mole#

Molar entropy [J/kmol/K].

Returns an array of length n_points.

property equilibrium_constants#

Equilibrium constants in concentration units for all reactions.

Returns an array of size n_reactions x n_points.

property flux_gradient_basis#: Get/Set whether or not species diffusive fluxes are computed with respect to their mass fraction gradients (‘mass’) or mole fraction gradients (‘molar’, default) when using the mixture-averaged transport model.

property forward_rate_constants#

Forward rate constants for all reactions.

The computed values include all temperature-dependent and pressure-dependent contributions. By default, third-body concentrations are only considered if they are part of the reaction rate definition; for a legacy implementation that includes third-body concentrations, see use_legacy_rate_constants.

Returns an array of size n_reactions x n_points.

property forward_rate_constants_ddC#

Calculate derivatives for forward rate constants with respect to molar concentration at constant temperature, pressure and mole fractions.

Warning

This property is an experimental part of the Cantera API and may be changed or removed without notice.

Returns an array of size n_reactions x n_points.

property forward_rate_constants_ddP#

Calculate derivatives for forward rate constants with respect to pressure at constant temperature, molar concentration and mole fractions.

Returns an array of size n_reactions x n_points.

property forward_rate_constants_ddT#

Calculate derivatives for forward rate constants with respect to temperature at constant pressure, molar concentration and mole fractions.

Returns an array of size n_reactions x n_points.

property forward_rates_of_progress#

Forward rates of progress for the reactions. [kmol/m^3/s] for bulk phases or [kmol/m^2/s] for surface phases.

Returns an array of size n_reactions x n_points.

property forward_rates_of_progress_ddC#

Calculate derivatives for forward rates-of-progress with respect to molar concentration at constant temperature, pressure and mole fractions.

Warning

This property is an experimental part of the Cantera API and may be changed or removed without notice.

Returns an array of size n_reactions x n_points.

property forward_rates_of_progress_ddP#

Calculate derivatives for forward rates-of-progress with respect to pressure at constant temperature, molar concentration and mole fractions.

Returns an array of size n_reactions x n_points.

property forward_rates_of_progress_ddT#

Calculate derivatives for forward rates-of-progress with respect to temperature at constant pressure, molar concentration and mole fractions.

Returns an array of size n_reactions x n_points.

from_array(arr, domain=None)#

Restore the solution vector from a SolutionArray object.

Parameters:

arr – SolutionArray containing data to be restored.
domain – Domain to be converted; by default, the method retrieves the flow domain

Added in version 3.0.

property g#

Gibbs free energy [J/kg or J/kmol] depending on basis.

Returns an array of length n_points.

gas#: The Solution object representing the species and reactions in the flame

get_refine_criteria()#

Get a dictionary of the criteria used for grid refinement. The items in the dictionary are the ratio, slope, curve, and prune, as defined in set_refine_criteria.

>>> f.set_refine_criteria(ratio=3.0, slope=0.1, curve=0.2, prune=0)
>>> f.get_refine_criteria()
{'ratio': 3.0, 'slope': 0.1, 'curve': 0.2, 'prune': 0.0}

property gibbs_mass#

Specific Gibbs free energy [J/kg].

Returns an array of length n_points.

property gibbs_mole#

Molar Gibbs free energy [J/kmol].

Returns an array of length n_points.

property grid#: Array of grid point positions along the flame.

property h#

Enthalpy [J/kg or J/kmol] depending on basis.

Returns an array of length n_points.

property heat_production_rates#

Get the volumetric heat production rates [W/m^3] on a per-reaction basis. The sum over all reactions results in the total volumetric heat release rate. Example: C. K. Law: Combustion Physics (2006), Fig. 7.8.6

>>> gas.heat_production_rates[1]  # heat production rate of the 2nd reaction

Returns an array of size n_reactions x n_points.

property heat_release_rate#

Get the total volumetric heat release rate [W/m^3].

Returns an array of length n_points.

property int_energy#

Internal energy in [J/kg or J/kmol].

Returns an array of length n_points.

property int_energy_mass#

Specific internal energy [J/kg].

Returns an array of length n_points.

property int_energy_mole#

Molar internal energy [J/kmol].

Returns an array of length n_points.

property isothermal_compressibility#

Isothermal compressibility [1/Pa].

Returns an array of length n_points.

property max_grid_points#: Get/Set the maximum number of grid points used in the solution of this flame.

property mean_molecular_weight#

The mean molecular weight (molar mass) [kg/kmol].

Returns an array of length n_points.

property mix_diff_coeffs#

Mixture-averaged diffusion coefficients [m^2/s] relating the mass-averaged diffusive fluxes (with respect to the mass averaged velocity) to gradients in the species mole fractions.

Returns an array of size n_species x n_points.

property mix_diff_coeffs_mass#

Mixture-averaged diffusion coefficients [m^2/s] relating the diffusive mass fluxes to gradients in the species mass fractions.

Returns an array of size n_species x n_points.

property mix_diff_coeffs_mole#

Mixture-averaged diffusion coefficients [m^2/s] relating the molar diffusive fluxes to gradients in the species mole fractions.

Returns an array of size n_species x n_points.

property mobilities#

Electrical mobilities of charged species [m^2/s-V]

Returns an array of size n_species x n_points.

property net_production_rates#

Net production rates for each species. [kmol/m^3/s] for bulk phases or [kmol/m^2/s] for surface phases.

Returns an array of size n_species x n_points.

property net_production_rates_ddC#

Calculate derivatives of species net production rates with respect to molar density at constant temperature, pressure and mole fractions.

Warning

This property is an experimental part of the Cantera API and may be changed or removed without notice.

Returns an array of size n_species x n_points.

property net_production_rates_ddP#

Calculate derivatives of species net production rates with respect to pressure at constant temperature, molar concentration and mole fractions.

Returns an array of size n_species x n_points.

property net_production_rates_ddT#

Calculate derivatives of species net production rates with respect to temperature at constant pressure, molar concentration and mole fractions.

Returns an array of size n_species x n_points.

property net_rates_of_progress#

Net rates of progress for the reactions. [kmol/m^3/s] for bulk phases or [kmol/m^2/s] for surface phases.

Returns an array of size n_reactions x n_points.

property net_rates_of_progress_ddC#

Calculate derivatives for net rates-of-progress with respect to molar concentration at constant temperature, pressure and mole fractions.

Warning

This property is an experimental part of the Cantera API and may be changed or removed without notice.

Returns an array of size n_reactions x n_points.

property net_rates_of_progress_ddP#

Calculate derivatives for net rates-of-progress with respect to pressure at constant temperature, molar concentration and mole fractions.

Returns an array of size n_reactions x n_points.

property net_rates_of_progress_ddT#

Calculate derivatives for net rates-of-progress with respect to temperature at constant pressure, molar concentration and mole fractions.

Returns an array of size n_reactions x n_points.

property partial_molar_cp#

Array of species partial molar specific heat capacities at constant pressure [J/kmol/K].

Returns an array of size n_species x n_points.

property partial_molar_enthalpies#

Array of species partial molar enthalpies [J/kmol].

Returns an array of size n_species x n_points.

property partial_molar_entropies#

Array of species partial molar entropies [J/kmol/K].

Returns an array of size n_species x n_points.

property partial_molar_int_energies#

Array of species partial molar internal energies [J/kmol].

Returns an array of size n_species x n_points.

property partial_molar_volumes#

Array of species partial molar volumes [m^3/kmol].

Returns an array of size n_species x n_points.

property radiation_enabled#: Get/Set whether or not to include radiative heat transfer

property reverse_rate_constants#

Reverse rate constants for all reactions.

Returns an array of size n_reactions x n_points.

property reverse_rates_of_progress#

Reverse rates of progress for the reactions. [kmol/m^3/s] for bulk phases or [kmol/m^2/s] for surface phases.

Returns an array of size n_reactions x n_points.

property reverse_rates_of_progress_ddC#

Calculate derivatives for reverse rates-of-progress with respect to molar concentration at constant temperature, pressure and mole fractions.

Warning

This property is an experimental part of the Cantera API and may be changed or removed without notice.

Returns an array of size n_reactions x n_points.

property reverse_rates_of_progress_ddP#

Calculate derivatives for reverse rates-of-progress with respect to pressure at constant temperature, molar concentration and mole fractions.

Returns an array of size n_reactions x n_points.

property reverse_rates_of_progress_ddT#

Calculate derivatives for reverse rates-of-progress with respect to temperature at constant pressure, molar concentration and mole fractions.

Returns an array of size n_reactions x n_points.

property s#

Entropy [J/kg/K or J/kmol/K] depending on basis.

Returns an array of length n_points.

set_gas_state(point)#: Set the state of the the Solution object used for calculations to the temperature and composition at the point with index point.

set_initial_guess(*args, data=None, group=None, **kwargs)#

Set the initial guess for the solution, and load restart data if provided. Derived classes extend this function to set approximations for the temperature and composition profiles.

Parameters:

data – Restart data, which are typically based on an earlier simulation result. Restart data may be specified using a SolutionArray, pandas.DataFrame, or previously saved CSV, YAML or HDF container files. Note that restart data do not overwrite boundary conditions. HDF input requires Cantera compiled with HDF support. DataFrame input requires a working installation of pandas, which can be installed using pip or conda (package: pandas).
group – Group identifier within a HDF container file (only used in combination with HDF restart data).

set_profile(component, positions, values)#

Set an initial estimate for a profile of one component.

Parameters:

component – component name or index
positions – sequence of relative positions, from 0 on the left to 1 on the right
values – sequence of values at the relative positions specified in positions

>>> f.set_profile('T', [0.0, 0.2, 1.0], [400.0, 800.0, 1500.0])

set_refine_criteria(ratio=10.0, slope=0.8, curve=0.8, prune=0.0)#

Set the criteria used for grid refinement.

Parameters:

ratio – additional points will be added if the ratio of the spacing on either side of a grid point exceeds this value
slope – maximum difference in value between two adjacent points, scaled by the maximum difference in the profile (0.0 < slope < 1.0). Adds points in regions of high slope.
curve – maximum difference in slope between two adjacent intervals, scaled by the maximum difference in the profile (0.0 < curve < 1.0). Adds points in regions of high curvature.
prune – if the slope or curve criteria are satisfied to the level of ‘prune’, the grid point is assumed not to be needed and is removed. Set prune significantly smaller than ‘slope’ and ‘curve’. Set to zero to disable pruning the grid.

>>> f.set_refine_criteria(ratio=3.0, slope=0.1, curve=0.2, prune=0)

property soret_enabled#: Get/Set whether or not to include diffusive mass fluxes due to the Soret effect. Enabling this option works only when using the multicomponent transport model.

property sound_speed#

Speed of sound [m/s].

Returns an array of length n_points.

property species_viscosities#

Pure species viscosities [Pa-s]

Returns an array of size n_species x n_points.

property spread_rate#: Array containing the tangential velocity gradient [1/s] (that is, radial velocity divided by radius) at each point.

property standard_cp_R#

Array of nondimensional species standard-state specific heat capacities at constant pressure at the current temperature and pressure.

Returns an array of size n_species x n_points.

property standard_enthalpies_RT#

Array of nondimensional species standard-state enthalpies at the current temperature and pressure.

Returns an array of size n_species x n_points.

property standard_entropies_R#

Array of nondimensional species standard-state entropies at the current temperature and pressure.

Returns an array of size n_species x n_points.

property standard_gibbs_RT#

Array of nondimensional species standard-state Gibbs free energies at the current temperature and pressure.

Returns an array of size n_species x n_points.

property standard_int_energies_RT#

Array of nondimensional species standard-state internal energies at the current temperature and pressure.

Returns an array of size n_species x n_points.

property thermal_conductivity#

Thermal conductivity. [W/m/K]

Returns an array of length n_points.

property thermal_diff_coeffs#

Return a one-dimensional array of the species thermal diffusion coefficients [kg/m/s].

Returns an array of size n_species x n_points.

property thermal_expansion_coeff#

Thermal expansion coefficient [1/K].

Returns an array of length n_points.

property third_body_concentrations#

Effective third-body concentrations used by individual reactions; values are only defined for reactions involving third-bodies and are set to not-a-number otherwise.

Returns an array of size n_reactions x n_points.

to_array(domain=None, normalize=False)#

Retrieve domain data as a SolutionArray object.

Parameters:

domain – Domain to be converted; by default, the method retrieves the flow domain
normalize – Boolean flag indicating whether mass/mole fractions should be normalized

Added in version 3.0.

to_pandas(species='X', normalize=True)#

Return the solution vector as a pandas.DataFrame.

Parameters:

species – Attribute to use obtaining species profiles, for example X for mole fractions or Y for mass fractions.
normalize – Boolean flag to indicate whether the mole/mass fractions should be normalized (default is True)

This method uses to_array and requires a working pandas installation. Use pip or conda to install pandas to enable this method.

property transport_model#: Get/Set the transport model used by the Solution object used for this simulation.

property velocity#: Array containing the velocity [m/s] normal to the flame at each point.

property viscosity#

Viscosity [Pa-s].

Returns an array of length n_points.

property volume#

Specific volume [m^3/kg or m^3/kmol] depending on basis.

Returns an array of length n_points.

property volume_mass#

Specific volume [m^3/kg].

Returns an array of length n_points.

property volume_mole#

Molar volume [m^3/kmol].

Returns an array of length n_points.