Add jet-fuels shock tube ignition data from 10.1016/j.fuel.2016.09.047

[skyreflectedinmirrors]

Add a ChemKED file for shock tube ignition data from:

"Ignition delay time correlations for distillate fuels"

https://www.sciencedirect.com/science/article/pii/S0016236116309048#s0065

The datapoints in this file were generated using this simple script:

from string import Template
import pandas as pd
import cantera as ct
import re

ct.suppress_thermo_warnings()

# create mapping of fuel names, models, and species names
nice_fuel_name = {
    'A1': 'JP-8',
    'A2': 'Jet A',
    'A3': 'JP-5'
}

model_name = {
    'A1': 'hychem_A1_highT.cti',
    'A2': 'hychem_A2_highT.cti',
    'A3': 'hychem_A3_highT.cti'
}

for name, model in model_name.items():
    model_name[name] = ct.Solution(model)

fuel_model_name = {
    'A1': 'POSF10264',
    'A2': 'POSF10325',
    'A3': 'POSF10289'
}


skeleton = Template("""
- composition:
    kind: mole fraction
    species:
      - InChI: no InChI
        amount: [${Xfuel}]
        species-name: ${fuel_name}
      - InChI: 1S/O2/c1-2
        amount: [${XO2}]
        species-name: O2
      - InChI: ${DChi}
        amount: [${XD}]
        species-name: ${Dilutant}
  equivalence-ratio: ${phi}
  ignition-type:
    target: OH*
    type: d/dt max
  ignition-delay:
    - ${tau} us
    - uncertainty-type: relative
      uncertainty: 0.15
  pressure:
    - ${pressure} atm
    - uncertainty-type: relative
      uncertainty: 0.01
  temperature:
    - ${temperature} K
    - uncertainty-type: relative
      uncertainty: 0.01
""".strip())


# get argon data -- skip empty rows
ar = pd.read_excel('davidson.xlsx', sheet_name='Argon Data New',
                   header=[2]).dropna(thresh=1)


for i, row in ar.iterrows():
    if 'Mixture' in row['Fuel']:
        # parse mixture
        mixture = row['Fuel']
        oxy_percent = float(re.compile(r'(\d+)%O2').search(
            mixture).groups()[0]) / 100.
        continue
    fuel = row['Fuel']
    # get gas
    try:
        gas = model_name[fuel]
    except KeyError:
        # not one of the model's were converting
        continue

    # get composition
    phi = float(row['Phi'])
    fuel_species = fuel_model_name[fuel]
    gas.set_equivalence_ratio(phi, fuel_species, 'O2')
    moles = gas.mole_fraction_dict()
    moles[fuel_species] *= oxy_percent
    moles['O2'] = oxy_percent
    moles['AR'] = 1 - sum(moles.values())
    gas.X = moles

    tau = float(row['tign (us)'])
    temp = float(row['T (K)'])
    pressure = float(row['P (atm)'])

    moles = gas.mole_fraction_dict()
    print(skeleton.substitute(
        Xfuel=moles[fuel_species],
        fuel_name=nice_fuel_name[fuel],
        XO2=moles["O2"],
        Dilutant="Ar",
        DChi="1S/Ar",
        XD=moles["AR"],
        tau=tau,
        temperature=temp,
        pressure=pressure,
        phi=phi))


# get air data -- skip empty rows
n2 = pd.read_excel('davidson.xlsx', sheet_name='N2 Data New',
                   header=[2]).dropna(thresh=1)


for i, row in n2.iterrows():
    fuel = row['Fuel']
    # get gas
    try:
        gas = model_name[fuel]
    except KeyError:
        # not one of the model's were converting
        continue

    # get composition
    phi = float(row['Phi'])
    fuel_species = fuel_model_name[fuel]
    gas.set_equivalence_ratio(phi, fuel_species, 'O2:1, N2:3.76')
    moles = gas.mole_fraction_dict()

    tau = float(row['tign (us)'])
    temp = float(row['T (K)'])
    pressure = float(row['P (atm)'])

    print(skeleton.substitute(
        Xfuel=moles[fuel_species],
        fuel_name=nice_fuel_name[fuel],
        XO2=moles["O2"],
        Dilutant="N2",
        DChi="1S/N2",
        XD=moles["N2"],
        tau=tau,
        temperature=temp,
        pressure=pressure,
        phi=phi))

Which can be run on the supplemental excel datasheet for that work (which I named 'davidson.xlsx').
The mechanisms used were the hychem high-temperature models for the various jet-fuels -- specifically, I only really used them for convenience of getting the state via the equivalence ratio. I can link the converted models on Slack if needed

A couple of things I'd love if someone looked over:

• When they say in the paper "fuel data measured in 4% O2/balance argon", this means that the composition was 4% O2, Fuel determined by phi (w/ pure O2), and Argon as the remaining 1 - (XO2 - XFuel), w/ XO2=0.04 ...? This is what I assumed in the script.
• Does this sentence in the paper:

Non-reactive pressure profiles in these experiments (using N2 instead of O2 in the mixture) were adjusted using driver inserts to limit pressure (and hence also temperature) variations to less than 1% over the required test times

imply that the relative uncertainty of the given pressure and temperature values are 1%? This is what I assumed in the file, but I'm not sure it's correct.

• is it possible to have a common-properties that is generally correct, but needs an override for a specific value or keyword? For example here I have a lot of uncertainties of the form:

    pressure:
      - 16.1 atm
      - uncertainty-type: relative
        uncertainty: 0.01

I don't know if I can apply a common uncertainty inside that map?