Frequently Asked Questions#

Hint

If your question isn’t answered here, consider asking us on the Cantera Users’ Group.

Installation#

How do I determine the cause of the error “DLL load failed while importing _cantera: The specified module can not be found.”?

  1. Install the Dependencies tool.

  2. If you are using Conda: Run this tool from a terminal where your Cantera Conda environment is active. That is, run the command:

    start "C:\Program Files\Dependencies\DependenciesGUI.exe"

    from that terminal, replacing the path with the path to DependenciesGUI.exe on your computer. This step is necessary to have the PATH environment variable set correctly.

  3. Use Dependencies to open the Cantera Python extension module. If you installed Mambaforge at C:\mambaforge and Cantera in an environment named ct-env, then this file would be named something like C:\mambaforge\envs\ct-env\Lib\site-packages\cantera\_cantera.cp312-win_amd64.pyd.

  4. Identify any DLLs that the tool is unable to find, or if there are methods that are not being resolved. One thing to keep an eye out for is if there are any libraries that are being loaded from unexpected locations (for example, other than from your conda installation and the Windows system directories).

Input Files#

Where can I find chemical mechanisms to use with Cantera?

There are a few sites that distribute mechanisms in the Cantera YAML format:

Many research groups maintain pages with mechanisms they developed, provided in the Chemkin format. These mechanisms can be converted to the Cantera YAML format using the ck2yaml tool. The following is an incomplete list:

Caution

The inclusion of a site in the above lists does not constitute an endorsement of the chemical mechanisms provided there. You must use your own judgement to determine if a mechanism is appropriate for any particular scientific or engineering purpose.

How do I fix errors converting Chemkin input files to Cantera’s format?

See our documentation on Debugging common errors in CK files. If you’re encountering an issue not described there, please post a question on the Cantera Users’ Group.

Thermodynamics & Equilibrium#

Why don’t the enthalpy and internal energy values calculated by Cantera match data from other sources (CoolProp / NIST / steam tables)? Why does my mixture have a negative enthalpy?

Reference states in thermodynamics are arbitrary, since the observable quantities of interest (work done, heat transferred) do not depend on absolute quantities but on differences between states. Different data sources use different conventions for the reference state. Cantera uses the convention commonly used in reaction thermodynamics, where pure elements in their natural state (for example, oxygen as O₂ gas and carbon as graphite) have zero enthalpy at a temperature of 298.15 K and a pressure of 1 atm. This convention provides a consistent treatment for the change in enthalpy associated with chemical reactions. In contrast, it is common for tabulated data for a single pure substance to use a different reference state, such as CO₂ where the enthalpy may be referenced to the saturated liquid at 273.15 K.

Why doesn’t the heat capacity calculated by Cantera match what I get from CEA?

Cantera’s definition of \(c_p\) is the partial derivative of enthalpy with respect to temperature, with pressure and composition held constant. The value returned by CEA is the derivative while holding the system at chemical equilibrium. The former definition is the one that appears in governing equations for multi-species systems, such as well-stirred reactors. While the latter property is of interest in certain physical situations, it is of somewhat limited use computationally, since it is only defined for mixtures at equilibrium.

You can use Cantera to compute a value like what’s returned by CEA by computing \(dh/dT\) using a finite difference method where the mixture is equilibrated at constant \(T\) and \(P\) at each point before calculating the enthalpy. sound_speed.py presents a related example.

CEA provides a value consistent with Cantera’s definition which it calls the \(c_p\) “with frozen reactions.”

Why doesn’t changing reactions affect the equilibrium state calculated by Cantera? How does Cantera find the equilibrium state even when no reactions are defined?

Chemical equilibrium is not defined in terms of reactions. For whatever set of species are allowed in a phase or multi-phase mixture, it is defined as the composition that minimizes a particular thermodynamic state variable while holding two others constant (for example, for equilibrium at constant temperature and pressure, the Gibbs free energy is minimized). This optimization is independent of any reactions that are defined, and the resulting composition may be different from what you would get, for example, from integrating a reactor network using a set of irreversible chemical reactions or a set of reactions that does not form a complete basis set for the defined species.

Reactor Networks#

How do I set the residence time for a reactor?

Cantera defines reactor flows in terms of inlet and outlet mass flow rates, with residence time being an output that can be calculated:

\[ t_\t{res} = \frac{m_\t{combustor}}{\dot{m}_\t{in}} \]

To achieve a specified residence time, you can define the mass flow rate to be a function of the combustor state. For example, the following approach is used in the example combustor.py:

def mdot(t):
    return combustor.mass / residence_time

inlet_mfc = ct.MassFlowController(inlet, combustor, mdot=mdot)
outlet_mfc = ct.PressureController(combustor, exhaust, primary=inlet_mfc, K=0.01)
How do I understand errors from ReactorNet that give a list of “components with largest weighted error estimates”?

Calls to ReactorNet.step or ReactorNet.advance may result in error messages like the following:

 CanteraError thrown by CVodesIntegrator::integrate:
CVodes error encountered. Error code: -4
At t = 0.151127 and h = 1.61901e-09, the corrector convergence test failed repeatedly or with |h| = hmin.

Components with largest weighted error estimates:
834: 297.28141792959997
762: -273.0999483219796
8: 1.8673611455956203
99: -0.018812031839692638
100: 0.01850247743429419
2: -0.002587710808893717
771: 0.0007865229822411536
843: -0.0007861126902119126
184: -0.0006244451494927259
231: 0.0006129536140016525

The list labeled “Components with largest weighted error estimates” provides a list of component indices followed by their corresponding error estimates. Large error estimates tend to be associated with rapidly changing variables which require very small time steps. If you are using the Python interface and the ReactorNet object is named net, you can identify the variables associated with these indices:

>>> net.component_name(834)
'ABC'
>>> net.component_name(762)
'XYZ'

It is sometimes the case that a reaction mechanism will contain one or more reactions where at some temperatures, either the forward or reverse rate constant becomes high and nonphysical, particularly if the mechanism has not been designed for use at in a particular temperature range. For this example, you can find reactions involving the species with the highest errors, assuming a Solution object named gas:

>>> for i, R in enumerate(gas.reactions()):
...     spec = R.reactants | R.products
...     if 'ABC' in spec and 'XYZ' in spec:
...         print(i, R)
244 ABC <=> XYZ

For this example, resolution of the problem would then involve investigating the rate parameterization for reaction 244 or the thermodynamic data for species ABC and XYZ, which determine the reverse rate constant.

In other cases, the time reached by the integrator (here, t = 0.151127) can provide a hint at the source of the problem. For example, if this time is near the time of a discontinuity in the inputs to a reactor network, such as a valve opening or closing, then the problem might be solved by using a smoother time function or decreasing the maximum integrator timestep.

1D Reacting Flows#

Why can’t I calculate the flame speed for a mixture with an inlet temperature of ~1000 K or higher?

Two failure modes are common under these conditions:

  1. when the auto=True option is specified to FreeFlame.solve, the solver keeps expanding the domain and never finds a solution satisfying its tolerances

  2. the solver converges but the solution is a strong function of the distance from the inlet to the flame.

The cause of both these problems is that at high inlet temperatures, reactions are already starting to occur at that inlet temperature. This violates the standard boundary conditions for the laminar flame problem, where the reaction rates need to go to zero for the inlet mixture. Here, however, finite rates at an inlet that is a finite distance from the flame mean that the mixture has changed before it even reaches the flame, and the computed flame speed becomes a function of that distance. Cantera’s solver (with the “auto” option enabled) tries to keep the inlet boundary far enough away from the flame to avoid problems with non-zero diffusive fluxes across the inlet, and that leads it to further widening the domain as the temperature continues to go up.

Considering a domain with the temperature fixed point at a distance \(d\) from the inlet, the ignition delay time \(\tau_\t{ig}\) sets a lower bound on the calculated flame speed. That is, even in the absence of any diffusion of heat or radicals into the unburned mixture, the calculated flame speed will be \(S_u \approx d / \tau_\t{ig}\) or, accounting for transport, \(S_u > d / \tau_\t{ig}\). A correct flame speed calculation can only be obtained when \(S_u\) is independent of \(d\) and \(d\) is larger than the flame thickness.

On this page
Show Source