T_high=800.,
statmech_model=ethane_ref.statmech_model,
elements=ethane_ref.elements,
references=refs)
propane_nasa = Nasa.from_statmech(name='propane',
phase='G',
T_low=298.,
T_high=800.,
statmech_model=propane_ref.statmech_model,
elements=propane_ref.elements,
references=refs)
nasa_species = [ethane_nasa, propane_nasa, butane_nasa]
# Determine the output path and write the thermdat file
thermdat_path = os.path.join(notebook_folder, 'thermdat')
write_thermdat(filename=thermdat_path, nasa_species=nasa_species)
THERMO ALL
100 500 1500
ethane 20190122C 2H 6 G298.0 800.0 502.9 1
-6.84729317E-01 2.54150584E-02-1.02900193E-05-1.15304090E-09 1.73800327E-12 2
-1.08866341E+04 2.42655635E+01 6.77655563E+00-3.31037518E-02 1.63456769E-04 3
-2.32569163E-07 1.18361103E-10-1.16548936E+04-6.74224205E+00 4
propane 20190122C 3H 8 G298.0 800.0 502.9 1
-2.54716915E+00 4.36640749E-02-2.65978975E-05 6.89956646E-09 7.68567634E-14 2
-1.35353831E+04 3.50227651E+01 8.09253651E+00-4.01657054E-02 2.23439464E-04 3
-3.27632587E-07 1.69405578E-10-1.46259783E+04-9.14554121E+00 4
butane 20190122C 4H 10 G298.0 800.0 502.9 1
-1.98482876E+00 5.99910769E-02-4.67983727E-05 2.14853318E-08-4.31005098E-12 2
-8.15415828E+05 3.48691129E+01 9.98107805E+00-3.50556935E-02 2.38938732E-04 3
-3.63709779E-07 1.92062158E-10-8.16632302E+05-1.47065846E+01 4
G = single_nasa_species.get_G(units='kcal/mol', T=298.)
print('{:12} {:10.1f} {:15.1f} {:15.1f}'.format(
name, H, S, G))
# <a id='section_9_2'></a>
# ## 9.2. Output via Thermdat
# The thermdat format uses NASA polynomials to represent several species. It has a very particular format so doing it manually is error-prone. You can write a list of ``Nasa`` objects to thermdat format using [``pmutt.io.thermdat.write_thermdat``](https://vlachosgroup.github.io/pmutt/io.html#pmutt.io.thermdat.write_thermdat).
#
# Below, we write a thermdat file using the species imported from the spreadsheet.
# In[13]:
from pmutt.io.thermdat import write_thermdat
write_thermdat(filename='./output/thermdat', nasa_species=nasa_species)
# Similarly, a list of ``Nasa`` objects can be read from a thermdat using [``pmutt.io.thermdat.read_thermdat``](https://vlachosgroup.github.io/pMuTT/io.html#pmutt.io.thermdat.read_thermdat).
# In[14]:
from pmutt.io.thermdat import read_thermdat
nasa_species = read_thermdat('./output/thermdat')
# <a id='section_10'></a>
# # 10. Reactions
#
# <img src="images/reaction.png" width=800>
#
reaction = ChemkinReaction.from_string(species=species_dict, **reaction_data)
reactions_list.append(reaction)
reactions = Reactions(reactions=reactions_list)
# ## Writing Chemkin files
# Now that we have all the required objects, we can write the output files. All outputs can be found in the [./outputs folder](https://github.com/VlachosGroup/pmutt/blob/master/docs/source/examples_jupyter/chemkin_io/outputs).
# ### Writing thermdat
# In[11]:
from pmutt.io.thermdat import write_thermdat
write_thermdat(filename='./outputs/thermdat', nasa_species=species)
# The thermdat file can be return as a string by omitting ``filename``.
# In[12]:
thermdat_str = write_thermdat(nasa_species=species)
print(thermdat_str)
# ### Writing gas.inp and surf.inp
# In[13]:
G = single_nasa_species.get_G(units='kcal/mol', T=298.)
print('{:12} {:10.1f} {:15.1f} {:15.1f}'.format(
name, H, S, G))
# <a id='section_9_2'></a>
# ## 9.2. Output via Thermdat
# The thermdat format uses NASA polynomials to represent several species. It has a very particular format so doing it manually is error-prone. You can write a list of ``Nasa`` objects to thermdat format using [``pmutt.io.thermdat.write_thermdat``](https://vlachosgroup.github.io/pmutt/io.html#pmutt.io.thermdat.write_thermdat).
#
# Below, we write a thermdat file using the species imported from the spreadsheet.
# In[13]:
from pmutt.io.thermdat import write_thermdat
write_thermdat('./output/thermdat', nasa_species)
# Similarly, a list of ``Nasa`` objects can be read from a thermdat using [``pmutt.io.thermdat.read_thermdat``](https://vlachosgroup.github.io/pMuTT/io.html#pmutt.io.thermdat.read_thermdat).
# In[14]:
from pmutt.io.thermdat import read_thermdat
nasa_species = read_thermdat('./output/thermdat')
# <a id='section_10'></a>
# # 10. Reactions
#
# <img src="images/reaction.png" width=800>
#
T_high = 1100. # K
species = [Nasa.from_statmech(references=refs, T_low=T_low, T_high=T_high,
**specie_data) for specie_data in species_data]
# Printing an example of a Nasa species
print(species[0])
# ## Writing Nasa objects to a Thermdat file
# In[5]:
from pmutt.io.thermdat import write_thermdat
write_thermdat(nasa_species=species, filename='thermdat',
write_date=True)
# ```
# THERMO ALL
# 100 500 1500
# H2_cus(S) 20181106H 2 S300.0 1100.0 610.2 1
# -1.32355622E-01 1.17210568E-02-1.21067695E-05 6.77414609E-09-1.56703390E-12 2
# -1.96714519E+03-1.13778416E+00-2.37252750E+00 2.60714871E-02-4.73583826E-05 3
# 4.61096590E-08-1.83624246E-11-1.68126562E+03 8.63949434E+00 4
# H2Obr(S) 20181106H 2O 1 S300.0 1100.0 561.2 1
# 3.33914632E+00 8.65676156E-03-1.03441245E-05 7.11690970E-09-1.91112739E-12 2
# -3.65073462E+04-1.59589792E+01 3.68293150E-01 3.06585581E-02-7.30019576E-05 3
# 8.80731362E-08-4.17597362E-11-3.61771342E+04-3.41520582E+00 4
# H2Ocus(S) 20181106H 2O 1 S300.0 1100.0 561.2 1
# 3.33914632E+00 8.65676156E-03-1.03441245E-05 7.11690970E-09-1.91112739E-12 2
