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130 lines
3.7 KiB
Python
130 lines
3.7 KiB
Python
XXX = 'XXX'
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import json
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# From McLinden, IJR, 2000
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McLinden_sigma_ek_f_data = {
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'R11': [0.5447, 363.61, 1.4000e-3],
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'R12': [0.5186, 297.24, 1.3440e-3],
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'R13': [0.4909, 233.36, 1.3200e-3],
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'R22': [0.4666, 284.72, 7.7817e-4, +1.2536e-6],
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'R23': [0.4430, 230.83, 6.0570e-4, +1.8604e-6],
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'R32': [0.4098, 289.65, 8.1980e-4, +2.2352e-7],
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'R114': [0.5770, 323.26, 1.3200e-3],
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'R115': [0.5476, 272.53, 1.3200e-3],
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'R125': [0.5101, 261.39, 1.2565e-3, +2.2296e-6],
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'R142b': [0.5320, 316.64, 1.3200e-3],
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'R143a': [0.5025, 267.10, 1.0066e-3, +1.3729e-6]
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}
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# From McLinden, IJR, 2000
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McLinden_psi_cond_data = {
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'R11': [1.0724, -0.0226720],
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'R12': [0.9910, 0.0029509],
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'R13': [1.4078, -0.2634600, 0.037978],
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'R22': [1.0750, -0.0385740],
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'R23': [1.3801, -0.2797500, 0.048798],
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'R32': [1.2325, -0.0883940],
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'R114': [1.0961, -0.0348990],
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'R115': [1.0338, -0.0020661],
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'R125': [1.0369, -0.0030368],
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'R142b': [1.6808, -0.8395440, 0.321957, -0.039706],
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'R143a': [1.1779, -0.2054100, 0.064870, -0.006473]}
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# From Klein, 1997
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Klein_psi_visc_data = {
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'R11': [1.171, -0.0592],
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'R12': [1.087, -0.0379],
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'R113': [1.212, -0.0569],
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'R22': [1.106, -0.0491],
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'R32': [0.898, +0.0099],
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'R123': [1.155, -0.0513],
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'R125': [1.110, -0.0332],
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'R143a': [1.134, -0.0801],
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'R152a': [0.807, +0.0496]}
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template = {
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"conductivity": {
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"BibTeX": "McLinden-IJR-2000",
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"f_int": {
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"T_reducing": 1.0,
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"T_reducing_units": "K",
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"a": [
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XXX
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],
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"t": [
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XXX
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]
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},
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"psi": {
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"a": [
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XXX
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],
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"rhomolar_reducing": XXX,
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"rhomolar_reducing_units": "mol/m^3",
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"t": [
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XXX
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]
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},
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"q_D": 1999999999.9999998,
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"q_D_units": "m",
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"reference_fluid": "R134a",
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"type": "ECS"
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},
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"viscosity": {
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"BibTeX": "Klein-IJR-1997",
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"epsilon_over_k": XXX,
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"epsilon_over_k_units": "K",
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"psi": {
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"a": [
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XXX
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],
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"rhomolar_reducing": XXX,
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"rhomolar_reducing_units": "mol/m^3",
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"t": [
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XXX
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]
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},
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"reference_fluid": "R134a",
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"sigma_eta": XXX,
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"sigma_eta_units": "m",
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"type": "ECS"
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}
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}
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import CoolProp
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# Find all fluids with both a viscosity and conductivity curve
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fluids = set(('R11,R12,R113,R22,R32,R123,R125,R143a,R152a'.split(','))).intersection(('R11,R12,R13,R22,R23,R32,R114,R115,R125,R142b,R143a'.split(',')))
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for fluid in fluids:
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try:
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v = CoolProp.CoolProp.PropsSI('V', 'T', 300, 'Q', 0, fluid)
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l = CoolProp.CoolProp.PropsSI('L', 'T', 300, 'Q', 0, fluid)
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# print 'GOOD', fluid, v, l
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except ValueError:
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print('BAD %s' % fluid)
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new = template.copy()
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new['viscosity']['sigma_eta'] = McLinden_sigma_ek_f_data[fluid][0] / 1e9
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new['viscosity']['epsilon_over_k'] = McLinden_sigma_ek_f_data[fluid][1]
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a = Klein_psi_visc_data[fluid]
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new['viscosity']['psi']['a'] = a
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new['viscosity']['psi']['t'] = range(len(a))
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new['viscosity']['psi']['rhomolar_reducing'] = CoolProp.CoolProp.PropsSI(fluid, 'rhomolar_reducing')
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a = McLinden_sigma_ek_f_data[fluid][2::]
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new['conductivity']['f_int']['a'] = a
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new['conductivity']['f_int']['t'] = range(len(a))
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a = McLinden_psi_cond_data[fluid]
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new['conductivity']['psi']['a'] = a
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new['conductivity']['psi']['t'] = range(len(a))
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new['conductivity']['psi']['rhomolar_reducing'] = CoolProp.CoolProp.PropsSI(fluid, 'rhomolar_reducing')
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fname = '../fluids/' + fluid + '.json'
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with open(fname, 'r') as fp:
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jj = json.load(fp)
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jj['TRANSPORT'] = new
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with open(fname, 'w') as fp:
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fp.write(json.dumps(jj))
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