def test_condensing_equil(pypropep):
kno3 = pypropep.PROPELLANTS['POTASSIUM NITRATE']
sugar = pypropep.PROPELLANTS['SUCROSE (TABLE SUGAR)']
p = pypropep.Equilibrium()
p.add_propellants([(kno3, 0.65 / kno3.mw), (sugar, 0.35 / sugar.mw)])
p.set_state(P=30)
assert len(p.composition_condensed) > 0
def test_simp_equil(pypropep):
e = pypropep.Equilibrium()
o2 = pypropep.PROPELLANTS['OXYGEN (GAS)']
ch4 = pypropep.PROPELLANTS['METHANE']
e.add_propellants([(o2, 1.), (ch4, 1.)])
e.set_state(P=1.0, T=3000., type='TP')
assert e.equilibrated is True
assert e.properties_computed is True
def test_equil_modes(pypropep):
e = pypropep.Equilibrium()
with pytest.raises(ValueError):
e.set_state(P=1., type='TP')
with pytest.raises(ValueError):
e.set_state(P=1., T=300., type='HP')
with pytest.raises(ValueError):
e.set_state(P=1., T=300., type='SP')
def test_TP_composition(pypropep):
e = pypropep.Equilibrium()
n2 = pypropep.PROPELLANTS['NITROGEN (GASEOUS)']
e.add_propellant(n2, 1.0)
with pytest.raises(RuntimeError):
print(e._compute_product_composition())
# Compostion should be None prior to equilibration
assert e.composition is None
assert e.composition_sorted is None
assert e.composition_condensed is None
# equilibrate
e.set_state(P=1.0, T=273., type='TP')
assert e.equilibrated is True
assert e.properties_computed is True
assert 'N2' in e.composition
for k, v in list(e.composition.items()):
if k == 'N2':
assert v == pytest.approx(1.0, 1e-6)
else:
assert v == pytest.approx(0.0, 1e-6)
def test_properties(pypropep):
p = pypropep.FrozenPerformance()
ps = pypropep.ShiftingPerformance()
e = pypropep.Equilibrium()
lh2 = pypropep.PROPELLANTS['RP-1 (RPL)']
lox = pypropep.PROPELLANTS['OXYGEN (LIQUID)']
OF = 0.13
p.add_propellants_by_mass([(lh2, 1.0), (lox, OF)])
p.set_state(P=30, Ae_At=25.)
ps.add_propellants_by_mass([(lh2, 1.0), (lox, OF)])
ps.set_state(P=30, Ae_At=25.)
e.add_propellants_by_mass([(lh2, 1.0), (lox, OF)])
e.set_state(P=30, type='HP')
assert p.properties[0].T == pytest.approx(ps.properties[0].T, 1e-2)
assert p.properties[0].Cp == pytest.approx(ps.properties[0].Cp, 1e-2)
assert p.properties[0].Isex == pytest.approx(ps.properties[0].Isex, 1e-2)
assert p.properties[0].Cv == pytest.approx(ps.properties[0].Cv, 1e-2)
assert p.properties[0].T == pytest.approx(e.properties.T, 1e-2)
assert p.properties[0].Cp == pytest.approx(e.properties.Cp, 1e-2)
assert p.properties[0].Isex == pytest.approx(e.properties.Isex, 1e-2)
assert p.properties[0].Cv == pytest.approx(e.properties.Cv, 1e-2)
R = 8.314
Tref = 298.15
Pref = 1e5
Rref = Pref / R / Tref
T = np.linspace(500, 6000, 30)
# O2 <-> 2O
N_O = 2
N_O2 = 1
log_K_p = (N_O * f_T(o_tbl, T, 'log Kf') + N_O2 * f_T(o2_tbl, T, 'log Kf'))
K_p = 10**log_K_p
n_o = 0.5 * (np.sqrt(K_p) * np.sqrt(K_p + 4) - K_p)
n_o2 = 1. - n_o
equil = ppp.Equilibrium()
equil.add_propellants([(ppp.PROPELLANTS['OXYGEN (GAS)'], N_O2)])
comp = {'O2': [], 'O': []}
for i, Ti in enumerate(T):
equil.set_state(P=1, T=Ti, type='TP')
for k in comp:
comp[k].append(equil.composition[k])
f = plt.figure()
for k in comp:
plt.plot(T, comp[k], label=k)
plt.legend()
f = plt.figure()
plt.plot(T, n_o, label='O')
plt.plot(T, n_o2, label='O2')
def test_add_propellants_by_mass(pypropep):
e = pypropep.Equilibrium()
o2 = pypropep.PROPELLANTS['OXYGEN (GAS)']
ch4 = pypropep.PROPELLANTS['METHANE']
e.add_propellants_by_mass([(o2, 1.), (ch4, 1.)])
print(e)
def test_simp_equilibrium(pypropep):
e = pypropep.Equilibrium()
return e.__str__()
def white_dwarf_cooling_data(water_mass_fraction):
'''Engine dimensions'''
Ac = np.pi*0.1**2 #Chamber cross-sectional area (m^2)
L_star = 1.5 #L_star = Volume_c/Area_t
wall_thickness = 2e-3
'''Chamber conditions'''
pc = 15e5 #Chamber pressure (Pa)
p_tank = 20e5 #Tank / inlet coolant stagnation pressure (Pa) - used for cooling jacket
mdot = 5.4489 #Mass flow rate (kg/s)
p_amb = 1.01325e5 #Ambient pressure (Pa). 1.01325e5 is sea level atmospheric.
OF_ratio = 3.5 #Oxidiser/fuel mass ratio
'''Coolant jacket'''
wall_material = bam.materials.CopperC700
mdot_coolant = mdot/(OF_ratio + 1)
inlet_T = 298.15 #Coolant inlet temperature
'''Get combustion properties from pypropep'''
#Initialise and get propellants
ppp.init()
e = ppp.Equilibrium()
p = ppp.ShiftingPerformance()
ipa = ppp.PROPELLANTS['ISOPROPYL ALCOHOL']
water = ppp.PROPELLANTS['WATER']
n2o = ppp.PROPELLANTS['NITROUS OXIDE']
#Add propellants by mass fractions (note the mass fractions can add up to more than 1)
e.add_propellants_by_mass([(ipa, 1),
(water, water_mass_fraction),
(n2o, OF_ratio)])
p.add_propellants_by_mass([(ipa, 1),
(water, water_mass_fraction),
(n2o, OF_ratio)])
#Adiabatic combustion
e.set_state(P = pc/p_amb, type = 'HP')
#Set chamber pressure and exit pressure in atmospheres
p.set_state(P = pc/p_amb, Pe = 1)
gamma = e.properties.Isex #I don't know why they use 'Isex' for gamma.
cp = 1000*e.properties.Cp #Cp is given in kJ/kg/K, we want J/kg/K
Tc = e.properties.T
'''Choose the models we want to use for transport properties of the coolant and exhaust gas'''
thermo_coolant = thermo.mixture.Mixture(['isopropanol', 'water'], ws = [1 - water_mass_fraction, water_mass_fraction])
thermo_gas = thermo.mixture.Mixture(['N2', 'H2O', 'CO2'], zs = [e.composition['N2'], e.composition['H2O'], e.composition['CO2']])
gas_transport = cool.TransportProperties(model = "thermo", thermo_object = thermo_gas, force_phase = 'g')
coolant_transport = cool.TransportProperties(model = "thermo", thermo_object = thermo_coolant, force_phase = 'l')
'''Create the engine object'''
perfect_gas = bam.PerfectGas(gamma = gamma, cp = cp) #Gas for frozen flow
chamber_conditions = bam.ChamberConditions(pc, Tc, mdot)
nozzle = bam.Nozzle.from_engine_components(perfect_gas, chamber_conditions, p_amb, type = "rao", length_fraction = 0.8)
white_dwarf = bam.Engine(perfect_gas, chamber_conditions, nozzle)
chamber_length = L_star*nozzle.At/Ac
'''Add the cooling system to the engine'''
white_dwarf.add_geometry(chamber_length, Ac, wall_thickness)
white_dwarf.add_exhaust_transport(gas_transport)
#Spiral channels
#white_dwarf.add_cooling_jacket(wall_material, inlet_T, p_tank, coolant_transport, mdot_coolant,
# configuration = "spiral", channel_shape = "semi-circle", channel_width = 0.020)
#Or vertical channels
white_dwarf.add_cooling_jacket(wall_material, inlet_T, p_tank, coolant_transport, mdot_coolant, configuration = "vertical", channel_height = 0.001)
'''Run the heating analysis'''
cooling_data = white_dwarf.steady_heating_analysis(number_of_points = 250, to_json = False)
return cooling_data, white_dwarf.isp(p_amb)