2528df0f75
These changes make it unnecessary to copy header files around during the build process, which tends to confuse IDEs and debuggers. The headers which comprise Cantera's external C++ interface are now in the 'include' directory. All of the samples and demos are now in the 'samples' subdirectory.
97 lines
3.5 KiB
Python
97 lines
3.5 KiB
Python
########################################################################
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#### NOTE: with the changes made to the ChemEquil solver in version 1.7,
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#### it now converges, and the Multiphase solver is no longer invoked
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#### in this demo
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########################################################################
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# Equilibrium of a (nearly) stoichiometric hydrogen/oxygen mixture at
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# fixed temperature.
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# Cantera has 3 different equilibrium solvers. The 'ChemEquil' solver
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# uses the element potential method for homogeneous equilibrium in gas
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# mixtures. It is fast, but sometimes doesn't converge. The
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# 'MultiPhaseEquil' solver uses the VCS algorithm (Gibbs
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# minimization), which is slower but more robust. As the name
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# suggests, it can also handle multiple phases. Here we'll solve a
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# problem for which the ChemEquil solver fails, but the
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# MultiPhaseEquil solver has no problem.
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from Cantera import *
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# create an object representing the gas phase
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gas = importPhase("h2o2.cti")
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temp = 400.0
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# make the composition very close to stoichiometric
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comp = "H2:1.00000001, O2:0.5"
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# set the initial state
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gas.set(T = temp, P = OneAtm, X = comp)
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# equilibrate the gas holding T and P fixed. First try the default
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# (ChemEquil) solver... (This will fail, throwing an exception that
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# will be caught in the 'except' block, where we will try the other
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# solver.)
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####################################################################
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# Note: We are setting solver = 0 here to demonstrate the difference
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# between the two solvers. If you do not set 'solver', or set it to a
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# negative value, then ChemEquil will be tried first, and if it fails
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# the MultiPhaseEquil solver will be tried. In most cases this will
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# give the best results.
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####################################################################
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try:
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gas.equilibrate("TP", solver = 0) # use the ChemEquil (0) solver
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except:
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print "ChemEquil solver failed! Try the MultiPhaseEquil solver..."
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# Try again. Reset the gas to the initial state
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gas.set(T = temp, P = OneAtm, X = comp)
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# The MultiPhaseEquil solver is used to equilibrate 'Mixture'
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# objects, since these may have more than one phase. Here we'll
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# create a Mixture object containing only the gas. Some other
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# useful parameters are rtol (relative error tolerance, default =
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# 1.0e-9), max_steps (default = 1000), loglevel (default = 0).
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mix = Mixture([(gas,1.0)])
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mix.equilibrate("TP", loglevel=4)
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# Note: another way to do this is:
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# gas.equilibrate("TP", solver = 1, loglevel = 4)
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# print a summary of the results
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print gas
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# To check that this is an equilibrium state, verify that the chemical
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# potentials may be computed by summing the element potentials for each atom.
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# (The element potentials are the chemical potentials of the atomic vapors.)
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mu_H2, mu_OH, mu_H2O, mu_O2, lambda_H, lambda_O = gas.chemPotentials(
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["H2", "OH", "H2O", "O2", "H", "O"])
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print
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print " Comparison between Chem potentials and element potentials:"
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print
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s_mu_H2 = "%11.4e" % mu_H2
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s_lam_mu_H2 = "%11.4e" % (2.0*lambda_H)
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print "mu_H2 : ", s_mu_H2, ", ", s_lam_mu_H2
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s_mu_O2 = "%11.4e" % mu_O2
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s_lam_mu_O2 = "%11.4e" % (2.0*lambda_O)
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print "mu_O2 : ", s_mu_O2, ", ", s_lam_mu_O2
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s_mu_OH = "%11.4e" % mu_OH
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s_lam_mu_OH = "%11.4e" % (lambda_H + lambda_O)
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print "mu_OH : ", s_mu_OH, ", ", s_lam_mu_OH
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s_mu_H2O = "%11.4e" % mu_H2O
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s_lam_mu_H2O = "%11.4e" % (2.0 * lambda_H + lambda_O)
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print "mu_H2O : ", s_mu_H2O, ", ", s_lam_mu_H2O
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