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Committing loose ends

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Harry Moffat
2009-03-19 19:26:56 +00:00
parent 7c2ccdafce
commit 8e356eccdd
3 changed files with 11 additions and 236 deletions
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18
Cantera/python/examples/surface_chemistry/Makefile.in
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@@ -1,16 +1,20 @@
#!/bin/sh
PY_DEMOS = catcomb.py diamond.py
PYTHON_CMD = @PYTHON_CMD@
all:
cd catcomb_stagflow; @MAKE@
cd diamond_cvd; @MAKE@
run:
@(for py in $(PY_DEMOS) ; do \
echo "running $${py}..."; \
$(PYTHON_CMD) "$${py}"; \
done)
cd catcomb_stagflow; @MAKE@ run
cd diamond_cvd; @MAKE@ run
test:
cd catcomb_stagflow; @MAKE@ test
cd diamond_cvd; @MAKE@ test
clean:
rm -f *.log *.csv *.xml
cd catcomb_stagflow; @MAKE@ clean
cd diamond_cvd; @MAKE@ clean
# end of file

181
Cantera/python/examples/surface_chemistry/catcomb.py
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@@ -1,181 +0,0 @@
# CATCOMB -- Catalytic combustion of methane on platinum.
#
# This script solves a catalytic combustion problem. A stagnation flow
# is set up, with a gas inlet 10 cm from a platinum surface at 900
# K. The lean, premixed methane/air mixture enters at ~ 6 cm/s (0.06
# kg/m2/s), and burns catalytically on the platinum surface. Gas-phase
# chemistry is included too, and has some effect very near the
# surface.
#
# The catalytic combustion mechanism is from Deutschman et al., 26th
# Symp. (Intl.) on Combustion,1996 pp. 1747-1754
#
#
from Cantera import *
from Cantera.OneD import *
#from Cantera.OneD.StagnationFlow import StagnationFlow
import math
###############################################################
#
# Parameter values are collected here to make it easier to modify
# them
p = OneAtm # pressure
tinlet = 300.0 # inlet temperature
tsurf = 900.0 # surface temperature
mdot = 0.06 # kg/m^2/s
transport = 'Mix' # transport model
# We will solve first for a hydrogen/air case to
# use as the initial estimate for the methane/air case
# composition of the inlet premixed gas for the hydrogen/air case
comp1 = 'H2:0.05, O2:0.21, N2:0.78, AR:0.01'
# composition of the inlet premixed gas for the methane/air case
comp2 = 'CH4:0.095, O2:0.21, N2:0.78, AR:0.01'
# the initial grid, in meters. The inlet/surface separation is 10 cm.
initial_grid = [0.0, 0.02, 0.04, 0.06, 0.08, 0.1] # m
# numerical parameters
tol_ss = [1.0e-5, 1.0e-9] # [rtol, atol] for steady-state problem
tol_ts = [1.0e-4, 1.0e-9] # [rtol, atol] for time stepping
loglevel = 1 # amount of diagnostic output
# (0 to 5)
refine_grid = 1 # 1 to enable refinement, 0 to
# disable
################ create the gas object ########################
#
# This object will be used to evaluate all thermodynamic, kinetic,
# and transport properties
#
# The gas phase will be taken from the definition of phase 'gas' in
# input file 'ptcombust.cti,' which is a stripped-down version of
# GRI-Mech 3.0.
gas = importPhase('ptcombust.cti','gas')
gas.set(T = tinlet, P = p, X = comp1)
################ create the interface object ##################
#
# This object will be used to evaluate all surface chemical production
# rates. It will be created from the interface definition 'Pt_surf'
# in input file 'ptcombust.cti,' which implements the reaction
# mechanism of Deutschmann et al., 1995 for catalytic combustion on
# platinum.
#
surf_phase = importInterface('ptcombust.cti','Pt_surf', [gas])
surf_phase.setTemperature(tsurf)
# integrate the coverage equations in time for 1 s, holding the gas
# composition fixed to generate a good starting estimate for the
# coverages.
surf_phase.advanceCoverages(1.0)
# create the object that simulates the stagnation flow, and specify an
# initial grid
sim = StagnationFlow(gas = gas, surfchem = surf_phase,
grid = initial_grid)
# Objects of class StagnationFlow have members that represent the gas inlet ('inlet') and the surface ('surface'). Set some parameters of these objects.
sim.inlet.set(mdot = mdot, T = tinlet, X = comp1)
sim.surface.set(T = tsurf)
# Set error tolerances
sim.set(tol = tol_ss, tol_time = tol_ts)
# Method 'init' must be called before beginning a simulation
sim.init()
# Show the initial solution estimate
sim.showSolution()
# Solving problems with stiff chemistry coulpled to flow can require
# a sequential approach where solutions are first obtained for
# simpler problems and used as the initial guess for more difficult
# problems.
# start with the energy equation on (default is 'off')
sim.set(energy = 'on')
# disable the surface coverage equations, and turn off all gas and
# surface chemistry.
sim.surface.setCoverageEqs('off')
surf_phase.setMultiplier(0.0);
gas.setMultiplier(0.0);
# solve the problem, refining the grid if needed, to determine the
# non-reacting velocity and temperature distributions
sim.solve(loglevel, refine_grid)
# now turn on the surface coverage equations, and turn the
# chemistry on slowly
sim.surface.setCoverageEqs('on')
for iter in range(6):
mult = math.pow(10.0,(iter - 5));
surf_phase.setMultiplier(mult);
gas.setMultiplier(mult);
print 'Multiplier = ',mult
sim.solve(loglevel, refine_grid);
# At this point, we should have the solution for the hydrogen/air
# problem.
sim.showSolution()
# Now switch the inlet to the methane/air composition.
sim.inlet.set(X = comp2)
# set more stringent grid refinement criteria
sim.setRefineCriteria(100.0, 0.15, 0.2, 0.0)
# solve the problem for the final time
sim.solve(loglevel, refine_grid)
# show the solution
sim.showSolution()
# save the solution in XML format. The 'restore' method can be used to restart
# a simulation from a solution stored in this form.
sim.save("catcomb.xml", "soln1")
# save selected solution components in a CSV file for plotting in
# Excel or MATLAB.
# These methods return arrays containing the values at all grid points
z = sim.flow.grid()
T = sim.T()
u = sim.u()
V = sim.V()
f = open('catcomb.csv','w')
writeCSV(f, ['z (m)', 'u (m/s)', 'V (1/s)', 'T (K)', 'rho (kg/m3']
+ list(gas.speciesNames()))
for n in range(sim.flow.nPoints()):
sim.setGasState(n)
writeCSV(f, [z[n], u[n], V[n], T[n], gas.density()]
+list(gas.moleFractions()))
# write the surface coverages to the CSV file
cov = sim.coverages()
names = surf_phase.speciesNames()
for n in range(len(names)):
writeCSV(f, [names[n], cov[n]])
f.close()
print 'solution saved to catcomb.csv'
# show some statistics
sim.showStats()

48
Cantera/python/examples/surface_chemistry/diamond.py
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@@ -1,48 +0,0 @@
# A CVD example. This example computes the growth rate of a diamond
# film according to a simplified version of a particular published
# growth mechanism (see file diamond.cti for details). Only the
# surface coverage equations are solved here; the gas composition is
# fixed. (For an example of coupled gas-phase and surface, see
# catcomb.py.) Atomic hydrogen plays an important role in diamond
# CVD, and this example computes the growth rate and surface coverages
# as a function of [H] at the surface for fixed temperature and [CH3].
from Cantera import *
import math
print '\n\b****** CVD Diamond Example ******\n'
# import the models for the gas and bulk diamond
g, dbulk = importPhases('diamond.cti',['gas','diamond'])
# import the model for the diamond (100) surface
d = importInterface('diamond.cti','diamond_100',phases = [g, dbulk])
ns = d.nSpecies()
mw = dbulk.molarMasses()[0]
t = 1200.0
x = g.moleFractions()
p = 20.0*OneAtm/760.0 # 20 Torr
g.set(T = t, P = p, X = x)
ih = g.speciesIndex('H')
xh0 = x[ih]
f = open('diamond.csv','w')
writeCSV(f, ['H mole Fraction', 'Growth Rate (microns/hour)']+d.speciesNames())
for n in range(20):
x[ih] /= 1.4
g.setState_TPX(t, p, x)
d.advanceCoverages(10.0) # iintegrate the coverages to steady state
carbon_dot = d.netProductionRates(phase = dbulk)[0]
mdot = mw*carbon_dot
rate = mdot/dbulk.density()
writeCSV(f,[x[ih],rate*1.0e6*3600.0]+list(d.coverages()))
f.close()
print 'H concentration, growth rate, and surface coverages written to file diamond.csv'