Equilibrium Example

This example uses ctwrap for equilibrium calculations defined by the simulation module equilibrium (ctwrap.modules.equilibrium).

Function/Class Definitions

import matplotlib.pyplot as plt
import matplotlib as mpl
import pandas as pd
col = mpl.rcParams['axes.prop_cycle'].by_key()['color']

import ctwrap as cw
cw.__version__

'0.3.3'

Simulations

Uses a module in the modules folder. Modules do not have to depend on ctwrap.

sim = cw.Simulation.from_module(cw.modules.equilibrium)
sim

<ctwrap.wrapper.Equilibrium at 0x7f829f535290>

Single Phase

Use YAML configuration defining a single phase

# create variation object
fname = 'equilibrium.yaml'
sh_single = cw.SimulationHandler.from_yaml(fname, verbosity=1)
sh_single

Simulations for entry `initial.phi` with values: [0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4,
2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5]

<ctwrap.handler.SimulationHandler at 0x7f82a4faaf10>

%%time
# Run parallel simulation
sh_single.run_parallel(sim)

 * Starting parallel batch simulation using 1 cores
 * running `case_00` (Process-1)
Tad =  1066.25
 * running `case_01` (Process-1)
Tad =  1280.77
 * running `case_02` (Process-1)
Tad =  1480.18
 * running `case_03` (Process-1)
Tad =  1665.95
 * running `case_04` (Process-1)
Tad =  1838.62
 * running `case_05` (Process-1)
Tad =  1996.89
 * running `case_06` (Process-1)
Tad =  2134.24
 * running `case_07` (Process-1)
Tad =  2225.52
 * running `case_08` (Process-1)
Tad =  2210.38
 * running `case_09` (Process-1)
Tad =  2136.52
 * running `case_10` (Process-1)
Tad =  2057.30
 * running `case_11` (Process-1)
Tad =  1979.78
 * running `case_12` (Process-1)
Tad =  1904.80
 * running `case_13` (Process-1)
Tad =  1832.34
 * running `case_14` (Process-1)
Tad =  1762.27
 * running `case_15` (Process-1)
Tad =  1694.42
 * running `case_16` (Process-1)
Tad =  1628.67
 * running `case_17` (Process-1)
Tad =  1564.89
 * running `case_18` (Process-1)
Tad =  1502.98
 * running `case_19` (Process-1)
Tad =  1442.83
 * running `case_20` (Process-1)
Tad =  1384.35
 * running `case_21` (Process-1)
Tad =  1327.46
 * running `case_22` (Process-1)
Tad =  1272.09
 * running `case_23` (Process-1)
Tad =  1218.20
 * running `case_24` (Process-1)
Tad =  1165.83
 * running `case_25` (Process-1)
Tad =  1115.42
 * running `case_26` (Process-1)
Tad =  1068.79
 * running `case_27` (Process-1)
Tad =  1030.42
 * running `case_28` (Process-1)
Tad =  1003.44
 * running `case_29` (Process-1)
Tad =   985.30
 * running `case_30` (Process-1)
Tad =   972.42
 * running `case_31` (Process-1)
Tad =   962.61
 * running `case_32` (Process-1)
Tad =   954.72
CPU times: user 42.4 ms, sys: 44.8 ms, total: 87.2 ms
Wall time: 3.41 s

True

sh_single.output_name

'equilibrium.csv'

Multiple Phases

Use YAML configuration defining two phases (gas and graphite)

# create variation object
fname = 'equilibrium_multi.yaml'
sh_multi = cw.SimulationHandler.from_yaml(fname, verbosity=1)
sh_multi

Simulations for entry `initial.phi` with values: [0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4,
2.5, 2.6, 2.7, 2.8, 2.9, 3.0, 3.1, 3.2, 3.3, 3.4, 3.5]

<ctwrap.handler.SimulationHandler at 0x7f829f563d90>

%%time
# Run parallel simulation
sh_multi.run_parallel(sim)

 * Starting parallel batch simulation using 1 cores
 * running `case_00` (Process-2)
Tad =  1066.25
 * running `case_01` (Process-2)
Tad =  1280.77
 * running `case_02` (Process-2)
Tad =  1480.18
 * running `case_03` (Process-2)
Tad =  1665.95
 * running `case_04` (Process-2)
Tad =  1838.62
 * running `case_05` (Process-2)
Tad =  1996.89
 * running `case_06` (Process-2)
Tad =  2134.24
 * running `case_07` (Process-2)
Tad =  2225.52
 * running `case_08` (Process-2)
Tad =  2210.38
 * running `case_09` (Process-2)
Tad =  2136.52
 * running `case_10` (Process-2)
Tad =  2057.30
 * running `case_11` (Process-2)
Tad =  1979.78
 * running `case_12` (Process-2)
Tad =  1904.80
 * running `case_13` (Process-2)
Tad =  1832.34
 * running `case_14` (Process-2)
Tad =  1762.27
 * running `case_15` (Process-2)
Tad =  1694.42
 * running `case_16` (Process-2)
Tad =  1628.67
 * running `case_17` (Process-2)
Tad =  1564.89
 * running `case_18` (Process-2)
Tad =  1502.98
 * running `case_19` (Process-2)
Tad =  1442.83
 * running `case_20` (Process-2)
Tad =  1384.35
 * running `case_21` (Process-2)
Tad =  1327.46
 * running `case_22` (Process-2)
Tad =  1272.09
 * running `case_23` (Process-2)
Tad =  1218.20
 * running `case_24` (Process-2)
Tad =  1165.83
 * running `case_25` (Process-2)
Tad =  1115.42
 * running `case_26` (Process-2)
Tad =  1068.79
 * running `case_27` (Process-2)
Tad =  1030.42
 * running `case_28` (Process-2)
Tad =  1003.44
 * running `case_29` (Process-2)
Tad =   985.30
 * running `case_30` (Process-2)
Tad =   973.13
 * running `case_31` (Process-2)
Tad =   968.47
 * running `case_32` (Process-2)
Tad =   963.98
CPU times: user 34.5 ms, sys: 46.3 ms, total: 80.9 ms
Wall time: 4.46 s

True

sh_multi.output_name

'equilibrium_multi.csv'

Create graphical output

Load data from files

df_single = pd.read_csv(sh_single.output_name)
df_single
df_multi = pd.read_csv(sh_multi.output_name)

Generate Plot

Display adiabatic equilibrium temperature as function of equivalence ratio.

# create figure and adjust size
fig, ax = plt.subplots(1)
fig.set_size_inches(8.,6.)

ax.plot(df_single.initial_phi.values, df_single['T'].values, 'x', markersize=10, label='Gas phase only')
ax.plot(df_multi.initial_phi.values, df_multi['T'].values, 'o', label='Gas and solid carbon')

# add title/axis labels
ax.set_title(r'Thermodynamic equilibrium')
ax.set_xlabel(r'Equivalence ratio - $\phi$ (-)')
ax.set_ylabel('Temperature (K)')

# add legend
leg = ax.legend(loc='upper right', title='Assumptions')
leg.draw_frame(False)