from CoolProp.CoolProp import PropsSI
import pylab, numpy as np
from ACHP.Correlations import ShahEvaporation_Average
x = np.linspace(0, 1, 1000)
h = np.zeros_like(x)
TsatL, TsatV = 300., 300.
p = PropsSI('P', 'T', TsatL, 'Q', 0, 'R134a')
for i in range(len(x)):
h[i] = ShahEvaporation_Average(x[i], x[i], 'R134a', 300, 0.01, p, 200,
TsatL, TsatV)
havg = np.trapz(h, x=x)
pylab.figure(figsize=(7, 5))
pylab.axhline(havg, ls='--')
pylab.text(0.2, havg, r'$\alpha_{avg}$', ha='center', va='bottom')
pylab.text(
0.7, 1300,
'R134a\nG=300 kg/m$^2$\nD=0.01 m\nq\"=200 W/m$^2$\np=%0.1f kPa' %
(p / 1000))
pylab.gca().set_xlabel('x [-]')
pylab.gca().set_ylabel(r'$\alpha$ [W/m$^2$/K]')
pylab.plot(x, h)
pylab.title('Shah Evaporation HTC as a function of quality')
pylab.show()
def updateHeatFlux(): # double tube system (outer is downward/innner is upward)
# Local Reynolds number and Prandtl numbers
for k in range(0,NZ):
Redtube[k] = UDmean * dD / mutube[k]
for k in range(NZ,2*NZ):
Redtube[k] = UUmean * dU / mutube[k]
#print(UDmean, UUmean, dD, dU, mutube[1], np.ndarray.max(Redtube))
# update boundary heat transfer coeffcients
for k in range(0,NZ):
htctube[k,0] = htc_DB(Redtube[2*NZ-1-k], Prtube[2*NZ-1-k], tktube[2*NZ-1-k], dU)
htctube[k,1] = htc_DB(Redtube[k] , Prtube[k] , tktube[k] , dD)
htctube[k,2] = htc_DB(Redtube[k] , Prtube[k] , tktube[k] , dD)
htctube[k,3] = htc_OUT(Z[k])
# insulation factors
tkPipe_inner_insFactor = np.ones(NZ,dtype=float)
for k in range(NZ,2*NZ):
if Ztube[k] <= 500.0:
kk = 2*NZ-1-k
tkPipe_inner_insFactor[kk] = 0.1
tkPipe_outer_insFactor = np.ones(NZ,dtype=float)
for k in range(0,NZ):
if Ztube[k] <= 150.0:
tkPipe_outer_insFactor[k] = 0.1
# update input heat flux, W
## outer tube heat budget downward, W
for k in range(0,NZ):
# CV in-flux
if k == 0:
hf_in = UDmean * (Dtube[k]*cptube[k]*Tin) * AD
else:
hf_in = UDmean * (Dtube[k-1]*cptube[k-1]*Ttube[k-1]) * AD
# CV radial in-flux
Regist = 1./(htctube[k,0]*Ri1)+math.log(Ro1/Ri1)/(tkPipe_inner*tkPipe_inner_insFactor[k]) + 1./(htctube[k,1]*Ro1)
hf_ri = 2 * math.pi * DZtube[k] / Regist * (Ttube[2*NZ-1-k] - Ttube[k])
# CV radial out-flux
hf_ro = 0.0
Registo = 1./(htctube[k,2]*Ri2)+math.log(Ro2/Ri2)/(tkPipe*tkPipe_outer_insFactor[k])+ 1./(htctube[k,3]*Ro2)
sumArea = 0.0
for j in range(NT):
iadj = kj2iadj[k,j,0]
jadj = kj2iadj[k,j,1]
sumArea = sumArea + faceArea[iadj,jadj]
for j in range(NT):
iadj = kj2iadj[k,j,0]
jadj = kj2iadj[k,j,1]
areaWeight = faceArea[iadj,jadj]/sumArea
fluxExt[iadj,jadj] = 2 * math.pi * DZtube[k] / Registo * (Ttube[k] - t[iadj]) * areaWeight # W
hf_ro = hf_ro + fluxExt[iadj,jadj]
# CV out-flux
hf_out = UDmean * (Dtube[k]*cptube[k]*Ttube[k]) * AD
# net flux
netHeattube[k] = hf_in - hf_out + hf_ri - hf_ro
## inner tube heat budget upward, W
for k in range(NZ,2*NZ):
kk = 2*NZ-1-k
# CV in-flux
if kk == NZ-1:
hf_in = UUmean * (Dtube[kk]*cptube[kk]*Ttube[kk]) * AU
else:
hf_in = UUmean * (Dtube[k-1]*cptube[k-1]*Ttube[k-1]) * AU
# CV radial out-flux
Registi = 1./(htctube[kk,0]*Ri1)+math.log(Ro1/Ri1)/(tkPipe_inner*tkPipe_inner_insFactor[kk]) + 1./(htctube[kk,1]*Ro1)
hf_ro = 2 * math.pi * DZtube[k] / Registi * (Ttube[k] - Ttube[2*NZ-1-k])
# CV out-flux
hf_out = UUmean * (Dtube[k]*cptube[k]*Ttube[k]) * AU
# net flux
netHeattube[k] = hf_in - hf_ro - hf_out
# update WF state (temperature (Euler) and pressure, etc.)
for k in range(2*NZ):
Ttuben[k] = Ttube[k] + netHeattube[k]/(Dtube[k]*cptube[k]*Vtube[k]) * dtime
Ptube[k] = Pin + Dtube[k]*cg*Ztube[k]
#Ptube[k] = PropsSI('P','T',Ttube[k],'Q',Qtube[k],'Water')
Dtube[k] = PropsSI('D','T',Ttube[k],'P',Ptube[k],'Water')
htube[k] = PropsSI('H','T',Ttube[k],'P',Ptube[k],'Water')
mutube[k] = PropsSI('V','T',Ttube[k],'P',Ptube[k],'Water')/Dtube[k] # m2/s
Prtube[k] = PropsSI('PRANDTL','T',Ttube[k],'P',Ptube[k],'Water')
tktube[k] = PropsSI('CONDUCTIVITY','T',Ttube[k],'P',Ptube[k],'Water')
cptube[k] = PropsSI('C','T',Ttube[k],'P',Ptube[k],'Water')
Ttube[:] = Ttuben[:]
# calc. thermal budget
TotalWatt = 0.0
for k in range(NZ):
for j in range(NT):
iadj = kj2iadj[k,j,0]
jadj = kj2iadj[k,j,1]
# minus means outward flux (e.g.,inward ground) "fluxExt" is positive.
# note that fluxExt is in [W]
TotalWatt = TotalWatt - fluxExt[iadj,jadj]
return TotalWatt
def TwoStage(Ref,
Q,
Te,
Tc,
DTsh,
DTsc,
eta_oi,
f_p,
Tsat_ic,
DTsh_ic,
Ts_Ph='Ph',
prints=False,
skipPlot=False,
axis=None,
**kwargs):
"""
This function plots a two-stage cycle, on the current axis, or that given by the optional parameter *axis*
Required parameters:
* Ref : Refrigerant [string]
* Q : Cooling capacity [W]
* Te : Evap Temperature [K]
* Tc : Condensing Temperature [K]
* DTsh : Evaporator outlet superheat [K]
* DTsc : Condenser outlet subcooling [K]
* eta_oi : Adiabatic efficiency of compressor (no units) in range [0,1]
* f_p : fraction of compressor power lost as ambient heat transfer in range [0,1]
* Tsat_ic : Saturation temperature corresponding to intermediate pressure [K]
* DTsh_ic : Superheating at outlet of intermediate stage [K]
Optional parameters:
* Ts_Ph : 'Ts' for a Temperature-Entropy plot, 'Ph' for a Pressure-Enthalpy
* prints : True to print out some values
* axis : An axis to use instead of the active axis
* skipPlot : If True, won't actually plot anything, just print COP
"""
warnings.warn(
"This function has been deprecated. PLease consider converting it to an object inheriting from \"BaseCycle\".",
DeprecationWarning)
T = np.zeros((8))
h = np.zeros_like(T)
p = np.zeros_like(T)
s = np.zeros_like(T)
rho = np.zeros_like(T)
T[0] = np.NAN
s[0] = np.NAN
T[1] = Te + DTsh
pe = PropsSI('P', 'T', Te, 'Q', 1.0, Ref)
pc = PropsSI('P', 'T', Tc, 'Q', 1.0, Ref)
pic = PropsSI('P', 'T', Tsat_ic, 'Q', 1.0, Ref)
Tbubble_c = PropsSI('T', 'P', pc, 'Q', 0, Ref)
Tbubble_e = PropsSI('T', 'P', pe, 'Q', 0, Ref)
h[1] = PropsSI('H', 'T', T[1], 'P', pe, Ref)
s[1] = PropsSI('S', 'T', T[1], 'P', pe, Ref)
rho[1] = PropsSI('D', 'T', T[1], 'P', pe, Ref)
T[5] = Tbubble_c - DTsc
h[5] = PropsSI('H', 'T', T[5], 'P', pc, Ref)
s[5] = PropsSI('S', 'T', T[5], 'P', pc, Ref)
rho[5] = PropsSI('D', 'T', T[5], 'P', pc, Ref)
mdot = Q / (h[1] - h[5])
rho1 = PropsSI('D', 'T', T[1], 'P', pe, Ref)
h2s = PropsSI('H', 'S', s[1], 'P', pic, Ref)
Wdot1 = mdot * (h2s - h[1]) / eta_oi
h[2] = h[1] + (1 - f_p) * Wdot1 / mdot
T[2] = PropsSI('T', 'H', h[2], 'P', pic, Ref)
s[2] = PropsSI('S', 'T', T[2], 'P', pic, Ref)
rho[2] = PropsSI('D', 'T', T[2], 'P', pic, Ref)
T[3] = 288
p[3] = pic
h[3] = PropsSI('H', 'T', T[3], 'P', pic, Ref)
s[3] = PropsSI('S', 'T', T[3], 'P', pic, Ref)
rho[3] = PropsSI('D', 'T', T[3], 'P', pic, Ref)
rho3 = PropsSI('D', 'T', T[3], 'P', pic, Ref)
h4s = PropsSI('H', 'T', s[3], 'P', pc, Ref)
Wdot2 = mdot * (h4s - h[3]) / eta_oi
h[4] = h[3] + (1 - f_p) * Wdot2 / mdot
T[4] = PropsSI('T', 'H', h[4], 'P', pc, Ref)
s[4] = PropsSI('S', 'T', T[4], 'P', pc, Ref)
rho[4] = PropsSI('D', 'T', T[4], 'P', pc, Ref)
sbubble_e = PropsSI('S', 'T', Tbubble_e, 'Q', 0, Ref)
sbubble_c = PropsSI('S', 'T', Tbubble_c, 'Q', 0, Ref)
sdew_e = PropsSI('S', 'T', Te, 'Q', 1, Ref)
sdew_c = PropsSI('S', 'T', Tc, 'Q', 1, Ref)
hsatL = PropsSI('H', 'T', Tbubble_e, 'Q', 0, Ref)
hsatV = PropsSI('H', 'T', Te, 'Q', 1, Ref)
ssatL = PropsSI('S', 'T', Tbubble_e, 'Q', 0, Ref)
ssatV = PropsSI('S', 'T', Te, 'Q', 1, Ref)
vsatL = 1 / PropsSI('D', 'T', Tbubble_e, 'Q', 0, Ref)
vsatV = 1 / PropsSI('D', 'T', Te, 'Q', 1, Ref)
x = (h[5] - hsatL) / (hsatV - hsatL)
s[6] = x * ssatV + (1 - x) * ssatL
T[6] = x * Te + (1 - x) * Tbubble_e
rho[6] = 1.0 / (x * vsatV + (1 - x) * vsatL)
h[6] = h[5]
h[7] = h[1]
s[7] = s[1]
T[7] = T[1]
p = [np.nan, pe, pic, pic, pc, pc, pe, pe]
COP = Q / (Wdot1 + Wdot2)
RE = h[1] - h[6]
if prints == True:
print('x5:', x)
print('COP:', COP)
print('COPH', (Q + Wdot1 + Wdot2) / (Wdot1 + Wdot2))
print(T[2] - 273.15, T[4] - 273.15, p[2] / p[1], p[4] / p[3])
print(mdot, mdot * (h[4] - h[5]), pic)
print('Vdot1', mdot / rho1, 'Vdisp',
mdot / rho1 / (3500 / 60.) * 1e6 / 0.7)
print('Vdot2', mdot / rho3, 'Vdisp',
mdot / rho3 / (3500 / 60.) * 1e6 / 0.7)
print(mdot * (h[4] - h[5]), Tc - 273.15)
for i in range(1, len(T) - 1):
print('%d & %g & %g & %g & %g & %g \\\\' %
(i, T[i] - 273.15, p[i], h[i], s[i], rho[i]))
else:
print(Tsat_ic, COP)
if skipPlot == False:
if axis == None:
ax = matplotlib.pyplot.gca()
else:
ax = axis
if Ts_Ph in ['ph', 'Ph']:
ax.plot(h, p)
elif Ts_Ph in ['Ts', 'ts']:
s_copy = s.copy()
T_copy = T.copy()
for i in range(1, len(s) - 1):
ax.plot(s[i], T[i], 'bo', mfc='b', mec='b')
dT = [0, -5, 5, -20, 5, 5, 5]
ds = [0, 0.05, 0, 0, 0, 0, 0]
ax.text(s[i] + ds[i], T[i] + dT[i], str(i))
s = list(s)
T = list(T)
s.insert(7, sdew_e)
T.insert(7, Te)
s.insert(5, sbubble_c)
T.insert(5, Tbubble_c)
s.insert(5, sdew_c)
T.insert(5, Tc)
ax.plot(s, T)
s = s_copy
T = T_copy
else:
raise TypeError('Type of Ts_Ph invalid')
return COP
def sg(self, T: Iterable):
return [
PropsSI('S', 'T', t, 'Q', 1, self.eos + "::" + self.name) if
(self.Tmin < t < self.Tmax) else None for t in T
]
def create_Hs_diagram(H, S, H1, H01, S1, H2, H02, S2, H2s, S2s, H3, H03, S3,
H3s, S3s, H4, H04, S4, P1, P2, P3, P4, dome1h, dome2h,
dome1, dome2, criticalisobar):
#creating isobars
stator_inlet = PropsSI("H", "P", P1, "S", S, 'Toluene') * 1e-3
stator_outlet = PropsSI("H", "P", P2, "S", S, 'Toluene') * 1e-3
rotor_outlet = PropsSI("H", "P", P3, "S", S, 'Toluene') * 1e-3
condenser_inlet = PropsSI("H", "P", P4, "S", S, 'Toluene') * 1e-3
#creating contour
dftemp = pd.DataFrame(H, columns=['H'])
dfentr = pd.DataFrame(S, columns=['S'])
dftemp['key'] = 1
dfentr['key'] = 1
df = dftemp.merge(dfentr, how='outer')[['S', 'H']]
df['Z'] = df.apply(
lambda x: PropsSI('Z', 'H', x['H'], 'S', x['S'], 'Toluene'), axis=1)
df['phase'] = df.apply(
lambda x: PropsSI('Phase', 'H', x['H'], 'S', x['S'], 'Toluene'),
axis=1)
gas = df['phase'] == CP.get_phase_index('phase_gas')
supercritical_gas = df['phase'] == CP.get_phase_index(
'phase_supercritical_gas')
df_filter = df[gas | supercritical_gas][['H', "S", "Z"]]
df_filter['H'] = df_filter['H'] * 1e-3
df_filter['S'] = df_filter['S'] * 1e-3
hdfpivot = df_filter.pivot('H', 'S')
X = hdfpivot.columns.levels[1].values
Y = hdfpivot.index.values
Z = hdfpivot.values
Xi, Yi = np.meshgrid(X, Y)
fig, ax = plt.subplots(figsize=(10, 7))
# isobars
ax.plot(S * 1e-3,
H01 * np.ones(np.size(S)) * 1e-3,
color='black',
linestyle=':')
fig.text(0.15, 0.77, "$\displaystyle h_{01}$", fontsize=20)
ax.plot(S * 1e-3,
H03 * np.ones(np.size(S)) * 1e-3,
color='black',
linestyle=':')
fig.text(0.15, 0.5, "$\displaystyle h_{03}$", fontsize=20)
#isobars
ax.plot(S * 1e-3, stator_inlet, color='black', linestyle='--')
fig.text(0.3, 0.65, "{:4.2f}".format(P1 / 1e5) + ' [Bar]')
ax.plot(S * 1e-3, stator_outlet, color='black', linestyle='--')
fig.text(0.3, 0.42, "{:4.2f}".format(P2 / 1e5) + ' [Bar]')
ax.plot(S * 1e-3, rotor_outlet, color='black', linestyle='--')
fig.text(0.3, 0.29, "{:4.2f}".format(P3 / 1e5) + ' [Bar]')
ax.plot(S * 1e-3, condenser_inlet, color='black', linestyle='--')
fig.text(0.3, 0.33, "{:4.2f}".format(P4 / 1e5) + ' [Bar]')
# ax.plot(S, condenser_inlet, color='black', linestyle='--')
# dome
ax.plot(dome1 * 1e-3, dome1h * 1e-3, color='black')
ax.plot(dome2 * 1e-3, dome2h * 1e-3, color='black')
# process
ax.plot([S1 * 1e-3, S2 * 1e-3, S3 * 1e-3, S4 * 1e-3],
[H1 * 1e-3, H2 * 1e-3, H3 * 1e-3, H4 * 1e-3],
color='black',
marker="X")
#isentropic process
ax.plot([S1 * 1e-3, S2s * 1e-3], [H1 * 1e-3, H2s * 1e-3],
color='black',
marker="o")
ax.plot([S2 * 1e-3, S3s * 1e-3], [H2 * 1e-3, H3s * 1e-3],
color='black',
marker="o")
# compressibility
fig = ax.contourf(Xi, Yi, Z, 25, alpha=0.7, cmap=plt.cm.jet)
ax.set_xlim([.850, 1.5])
ax.ticklabel_format(fontsize=20)
ax.set_ylim([200, 700])
ax.set_xlabel(r'Entropy [KJ/kgK]', fontsize=15)
ax.set_ylabel(r'Enthalpy [KJ/kg]', fontsize=15)
cb = plt.colorbar(fig)
cb.set_label(r"Compressibility factor [-]", fontsize=15)
return fig, ax
def dvg_dP_saturation(self):
dP = 0.002
rho1 = PropsSI('D', 'P', self.state.p() + dP / 2, 'Q', 1, self.name)
rho0 = PropsSI('D', 'P', self.state.p() - dP / 2, 'Q', 1, self.name)
dvg = 1 / rho1 - 1 / rho0
return dvg / dP
def psat(self, T: Iterable):
return [
PropsSI('P', 'Q', 0.5, 'T', t, self.eos + "::" + self.name) if
(self.Tmin < t < self.Tmax) else None for t in T
]
# --------------
# analysis conditions - fixed
# --------------
p_in = 100.0 # [bar]
p_out = 1.01325 # [bar]
t_in = 298.15 # [K]
t_out = 298.15 # [K]
RPM = 3600 # [rpm]
# --------------
# specific work
# --------------
# air properties
fluid = 'Air.mix'
CP = PropsSI('CPMASS', "T", t_in, "P", p_in, fluid) # J/Kg-K
CV = PropsSI('CVMASS', "T", t_in, "P", p_in, fluid) # J/Kg-K
k = CP / CV
MW = PropsSI('M', fluid) * 1000.0 # kg/kmol
R_bar = PropsSI('GAS_CONSTANT', fluid) # kJ/kmol/K
R = R_bar / MW # kJ/kg-K
# polytropic work
n = k # polytropic exponent
t2 = t_in * (p_out / p_in) ** ((n - 1.0) / n) # [K]
w = 1.0 * R * (t2 - t_in) / (1.0 - n) # [kJ/kg]
# --------------
# run sweep
# --------------
pwrs = [0.5, 1.0, 5.0, 10.0, 50.0, 100.0, 500.0, 1000.0] # [MW]
pistons = [False]
def calc_temperature(self):
# Calculate temperature based on saturation curve
T = PropsSI("T", "Q", 0, "P", self.storage_pressure,
self.coolprop_name)
self.storage_temperature = T
return T
def Calculate(self):
#Update the parameters
self.Update()
#Average mass flux of refrigerant [kg/m^2-s]
self.G_r = self.mdot_r / (pi * self.ID_i**2 / 4.0)
#Average mass flux of glycol [kg/m^2-s]
self.G_g = self.mdot_g / (pi * (self.ID_o**2 - self.OD_i**2) / 4.0)
#Hydraulic diameter
self.Dh_g = self.ID_o - self.OD_i
#Evaporation hydraulic diameter [m]
self.Dh_r = self.ID_i
#Thermal conductivity of the intermediate wall pipe
self.k = self.Conductivity
#Thermal Conduction Resistance of the intermediate wall
self.Rw = log(self.OD_i / self.ID_i) / (2 * pi * self.k * self.L)
self.Tbubble_r = PropsSI('T', 'P', self.pin_r, 'Q', 0, self.Ref_r)
self.Tdew_r = PropsSI('T', 'P', self.pin_r, 'Q', 1, self.Ref_r)
self.Tsat_r = (self.Tbubble_r + self.Tdew_r) / 2.0
#Inlet enthalpy
hsatL = PropsSI('H', 'T', self.Tbubble_r, 'Q', 0, self.Ref_r) #*1000
hsatV = PropsSI('H', 'T', self.Tdew_r, 'Q', 1, self.Ref_r) #*1000
self.xin_r = (self.hin_r - hsatL) / (hsatV - hsatL)
#Change in enthalpy through two-phase region [J/kg]
self.h_fg = hsatV - hsatL
self.Tin_r = self.xin_r * self.Tdew_r + (1 -
self.xin_r) * self.Tbubble_r
#Inlet entropy
ssatL = PropsSI('S', 'T', self.Tbubble_r, 'Q', 0, self.Ref_r) #*1000
ssatV = PropsSI('S', 'T', self.Tdew_r, 'Q', 1, self.Ref_r) #*1000
self.sin_r = self.xin_r * ssatV + (1 - self.xin_r) * ssatL
#Mean values for the glycol side based on average of inlet temperatures
Tavg_g = (self.Tsat_r + self.Tin_g) / 2.0
self.f_g, self.h_g, self.Re_g = f_h_1phase_Annulus(
self.mdot_g, self.ID_o, self.OD_i, Tavg_g, self.pin_g, self.Ref_g)
self.cp_g = PropsSI('C', 'T', Tavg_g, 'P', self.pin_g,
self.Ref_g) #*1000
#Glycol pressure drop
v_g = 1 / PropsSI('D', 'T', Tavg_g, 'P', self.pin_g, self.Ref_g)
dpdz_g = -self.f_g * v_g * self.G_g**2 / (2. * self.Dh_g
) #Pressure gradient
self.DP_g = dpdz_g * self.L
def OBJECTIVE(w_superheat):
"""Nested function for driving the Brent's method solver"""
#Run the superheated portion
self._Superheat_Forward(w_superheat)
#Run the two-phase portion and return residual
return self._TwoPhase_Forward(1 - w_superheat)
def OBJECTIVE_2phase(xout_2phase):
"""Nested function for finding outlet quality"""
#Need to pass in outlet quality but still maintain the full w_2phase
return self._TwoPhase_Forward(1.0, xout_2phase)
# First see if you have a superheated portion. Try to use the entire HX
# for the two-phase portion
# ---------------------
# Intermediate glycol temp between superheated and 2phase sections [K]
self.T_g_x = self.Tin_g
#Call two-phase forward method
error = self._TwoPhase_Forward(1.0)
# If HT greater than required
if error > 0:
#Too much HT if all is 2phase, there is a superheated section
existsSuperheat = True
#Solve for the break between 2phase and superheated parts
w_superheat = brentq(OBJECTIVE, 0.00001, 0.99999)
self.w_2phase = 1 - w_superheat
self.w_superheat = w_superheat
else:
existsSuperheat = False
# Solve for outlet quality in 2phase section, lowest possible outlet
# quality is the inlet quality
self.xout_2phase = brentq(OBJECTIVE_2phase, self.xin_r, 0.99999)
#Dummy variables for the superheated section which doesn't exist
self.Q_superheat = 0.0
self.Charge_r_superheat = 0.0
self.h_r_superheat = 0.0
self.DP_r_superheat = 0.0
self.w_superheat = 0.0
self.w_2phase = 1.0
self.Charge_r = self.Charge_r_2phase + self.Charge_r_superheat
self.Q = self.Q_2phase + self.Q_superheat
self.Tout_g = self.Tin_g - self.Q / (self.cp_g * self.mdot_g)
self.DP_r = self.DP_r_2phase + self.DP_r_superheat
if existsSuperheat == True:
self.hout_r = PropsSI('H', 'T', self.Tout_r, 'P', self.pin_r,
self.Ref_r) #*1000
self.sout_r = PropsSI('S', 'T', self.Tout_r, 'P', self.pin_r,
self.Ref_r) #*1000
else:
self.Tout_r = self.xout_2phase * self.Tdew_r + (
1 - self.xout_2phase) * self.Tbubble_r
self.hout_r = PropsSI('H', 'T', self.Tout_r, 'Q', self.xout_2phase,
self.Ref_r) #*1000
self.sout_r = PropsSI('S', 'T', self.Tout_r, 'Q', self.xout_2phase,
self.Ref_r) #*1000
#Dummy variables for the subcooled section which doesn't exist
self.Q_subcool = 0.0
self.DP_r_subcool = 0.0
self.h_r_subcool = 0.0
self.Re_r_subcool = 0.0
self.Charge_r_subcool = 0.0
self.w_subcool = 0.0
RPMs = np.arange(3600, 72000, 1000)
# Conditions to Vary
PRs = [2.0, 4.0, 6.0, 8.0, 10.0, 12.0, 14.0] # Pressure Ratio
RPMs = [3600, 7200, 14400] # RPM
#RPMs = [10000.,20000.,40000.,50000.] # RPM
#RPMs = [3600,7200,14400] # RPM
#===============================
# Prep
#===============================
g = 9.81 #m/s^2
g = 9.81
# Gas properties
CP = PropsSI('CPMASS', "T", T1, "P", p1, fluid) * 1000.0 # KJ/Kg
CV = PropsSI('CVMASS', "T", T1, "P", p1, fluid) * 1000.0 # KJ/Kg
kappa = CP / CV
MW = PropsSI('M', fluid) * 1000.0 # kg/kmol
R_bar = PropsSI('GAS_CONSTANT', fluid) # kJ/kmol/K
R = R_bar / MW * 1000.0 # J/kg-K
D1 = PropsSI('H', 'T', T1, 'P', p1, fluid) # Density (kg/m3)
# Results
variables = ['RPM', 'PR', 'D', 'pwr', 'pwr_real', 'm_dot', 'V1', 'T2', 'p2']
df = pd.DataFrame(columns=variables)
for RPM in RPMs:
for PR in PRs:
# Compressor Calculations
self.DP_r_2phase = DP_frict + DP_accel
if self.Verbosity > 4:
print Q_2phase_eNTU - self.Q_2phase
return Q_2phase_eNTU - self.Q_2phase
if __name__ == '__main__':
TT = []
QQ = []
Q1 = []
for Tdew_evap in np.linspace(270, 290.4):
Tdew_cond = 317.73
# Tdew_evap=285.42
pdew_cond = PropsSI('P', 'T', Tdew_cond, 'Q', 1.0, 'R290')
h = PropsSI('H', 'T', Tdew_cond - 7, 'P', pdew_cond, 'R290') #*1000
params = {
'ID_i': 0.0278, #inner tube, Internal Diameter (ID)
'OD_i': 0.03415, #inner tube, Outer Diameter (OD)
'ID_o': 0.045, #outer tube (annulus), Internal Diameter (ID)
'L': 50,
'mdot_r': 0.040,
'mdot_g': 0.38,
'hin_r': h,
'pin_r': PropsSI('P', 'T', Tdew_evap, 'Q', 1.0, 'R290'),
'pin_g': 300000, #pin_g in Pa
'Tin_g': 290.52,
'Ref_r': 'R290',
'Ref_g': 'Water',
'Verbosity': 0,
FinsTubes.Air.RH = 0.51
FinsTubes.Air.RHmean = 0.51
FinsTubes.Air.FanPower = 438
#Abstract State
Ref = 'R410A'
Backend = 'HEOS' #choose between: 'HEOS','TTSE&HEOS','BICUBIC&HEOS','REFPROP','SRK','PR'
AS = CP.AbstractState(Backend, Ref)
kwargs = {
'AS':
AS,
'mdot_r':
0.0708,
'psat_r':
PropsSI('P', 'T', T_dews[0], 'Q', 1.0, Ref),
'Fins':
FinsTubes,
'FinsType':
'WavyLouveredFins', #Choose fin Type: 'WavyLouveredFins' or 'HerringboneFins'or 'PlainFins'
'hin_r':
PropsSI('H', 'P', PropsSI('P', 'T', 282, 'Q', 1.0, Ref), 'Q', 0.15,
Ref),
'Verbosity':
0,
'h_a_tuning':
1,
'h_tp_tuning':
1,
'DP_tuning':
1,
T_clr = 150 + 273.15 # K
# Tank
V = 1E6 # m3
p_min = 2.0 * p_amb
p_max = 10.0 * p_amb
# Simulation
dt = 60.0 # s
pwr = 10E6 # W = 1 MW
# ----------
# Pre-processing calculations
# ----------
# Ambient
T1 = T_amb
p1 = p_amb
h1 = PropsSI('H', 'T', T1, 'P', p1, fluid)
s1 = PropsSI('S', 'T', T1, 'P', p1, fluid)
# Air Tank
T_tnk = T_amb
p_tnk = p_min
m_tnk = V * PropsSI('D', 'T', T_tnk, 'P', p_tnk, fluid)
u_tnk = PropsSI('U', 'T', T_tnk, 'P', p_tnk, fluid)
MW = PropsSI('MOLEMASS', fluid) # kg/mol
R = PropsSI('GAS_CONSTANT', fluid) # J/mol-K
# Track energy and heat stored
E_stor = 0.0
Q_stor = 0.0
#-------------------------------------
# Charge
#-------------------------------------
def getPr(self, P, T):
self.Pr = PropsSI('Prandtl', 'T', T, 'P', P, self.name)
return self.Pr
def __init__(
self,
num_samples=100, # Have this many chromos in the sample group
num_selected=20, # Have this many chromos in the selected group
mutation_factor=2, # Randomly mutate 1/n of the chromosomes
num_powers=5, # How many powers in the fit
Ref='R407C',
value='rhoV',
addTr=True,
values=None,
Tlims=None):
self.num_samples = num_samples
self.num_selected = num_selected
self.mutation_factor = mutation_factor
self.num_powers = num_powers
self.addTr = addTr
self.value = value
self.Ref = Ref
#Thermodynamics
from CoolProp.CoolProp import PropsSI
if values is None:
self.Tc = PropsSI(Ref, 'Tcrit')
self.pc = PropsSI(Ref, 'pcrit')
self.rhoc = PropsSI(Ref, 'rhocrit')
self.Tmin = PropsSI(Ref, 'Tmin')
if Tlims is None:
self.T = np.append(
np.linspace(self.Tmin + 1e-14, self.Tc - 1, 150),
np.logspace(np.log10(self.Tc - 1),
np.log10(self.Tc) - 1e-15, 40))
else:
self.T = np.linspace(Tlims[0], Tlims[1])
self.pL = np.array(
PropsSI('P', 'T', self.T, 'Q', [0] * len(self.T), Ref))
self.pV = np.array(
PropsSI('P', 'T', self.T, 'Q', [1] * len(self.T), Ref))
self.rhoL = PropsSI('D', 'T', self.T, 'Q', [0] * len(self.T), Ref)
self.rhoV = PropsSI('D', 'T', self.T, 'Q', [1] * len(self.T), Ref)
else:
self.Tc = values['Tcrit']
self.pc = values['pcrit']
self.rhoc = values['rhocrit']
self.Tmin = values['Tmin']
self.T = values['T']
self.p = values['p']
self.rhoL = values['rhoL']
self.rhoV = values['rhoV']
self.logpLpc = (np.log(self.pL) - np.log(self.pc))
self.logpVpc = (np.log(self.pV) - np.log(self.pc))
self.rhoLrhoc = np.array(self.rhoL) / self.rhoc
self.rhoVrhoc = np.array(self.rhoV) / self.rhoc
self.logrhoLrhoc = np.log(self.rhoL) - np.log(self.rhoc)
self.logrhoVrhoc = np.log(self.rhoV) - np.log(self.rhoc)
self.x = 1.0 - self.T / self.Tc
MM = PropsSI(Ref, 'molemass')
self.T_r = self.Tc
if self.value == 'pL':
self.LHS = self.logpLpc.copy()
self.EOS_value = self.pL.copy()
if self.addTr == False:
self.description = "p' = pc*exp(sum(n_i*theta^t_i))"
else:
self.description = "p' = pc*exp(Tc/T*sum(n_i*theta^t_i))"
self.reducing_value = self.pc
elif self.value == 'pV':
self.LHS = self.logpVpc.copy()
self.EOS_value = self.pV.copy()
if self.addTr == False:
self.description = "p'' = pc*exp(sum(n_i*theta^t_i))"
else:
self.description = "p'' = pc*exp(Tc/T*sum(n_i*theta^t_i))"
self.reducing_value = self.pc
elif self.value == 'rhoL':
self.LHS = self.logrhoLrhoc.copy()
self.EOS_value = self.rhoL
if self.addTr == False:
self.description = "rho' = rhoc*exp(sum(n_i*theta^t_i))"
else:
self.description = "rho' = rhoc*exp(Tc/T*sum(n_i*theta^t_i))"
self.reducing_value = self.rhoc / MM
elif self.value == 'rhoV':
self.LHS = self.logrhoVrhoc.copy()
self.EOS_value = self.rhoV
if self.addTr == False:
self.description = "rho'' = rhoc*exp(sum(n_i*theta^t_i))"
else:
self.description = "rho'' = rhoc*exp(Tc/T*sum(n_i*theta^t_i))"
self.reducing_value = self.rhoc / MM
elif self.value == 'rhoLnoexp':
self.LHS = (self.rhoLrhoc - 1).copy()
self.EOS_value = self.rhoL
self.description = "rho' = rhoc*(1+sum(n_i*theta^t_i))"
self.reducing_value = self.rhoc / MM
else:
raise ValueError
if self.value == 'rhoLnoexp' and self.addTr:
raise ValueError('Invalid combination')
if self.addTr:
self.LHS *= self.T / self.Tc
Fins.Air.Vdot_ha = 1.7934 #rated volumetric flowrate
Fins.Air.Tdb = 308.15 #Dry Bulb Temperature
Fins.Air.p = 101325 #Air pressure in Pa
Fins.Air.RH = 0.51 #Relative Humidity
Fins.Air.FanPower = 160
Ref = 'R410A'
Backend = 'TTSE&HEOS' #choose between: 'HEOS','TTSE&HEOS','BICUBIC&HEOS','REFPROP','SRK','PR'
AS = CP.AbstractState(Backend, Ref)
params = {
'AS': AS,
'mdot_r': 0.0708,
'Tin_r': 333.15,
'psat_r': PropsSI('P', 'T', 323.15, 'Q', 1.0, Ref),
'Fins': Fins,
'FinsType':
'WavyLouveredFins', #WavyLouveredFins, HerringboneFins, PlainFins
'Verbosity': 0,
}
Cond = CondenserClass(**params)
Cond.Calculate()
print('Heat transfer rate in condenser is', Cond.Q, 'W')
print('Heat transfer rate in condenser (superheat section) is',
Cond.Q_superheat, 'W')
print('Heat transfer rate in condenser (twophase section) is', Cond.Q_2phase,
'W')
print('Heat transfer rate in condenser (subcooled section) is', Cond.Q_subcool,
@author: TrungNguyen
"""
import CoolProp.CoolProp as CP
from CoolProp.CoolProp import PropsSI
from CoolProp.Plots import PropertyPlot
from CoolProp.Plots import StateContainer
#Evaporator chracteristics
HEOS = CP.AbstractState('HEOS', 'Propane&IsoButane')
HEOS.set_mole_fractions([0.3, 0.7])
isentropic_eff = 0.7
evaporation_temp = 0 + 273.15 # R290
condensation_temp = 55 + 273.15 # Estimation from Aeronamic
superheat = 5 # ambient temperature
subcooling = 3.1 # estimation from Aeronamic (how to know or calculate the value)
#Compressor characteristics
compressor_power = 4300 #
massflow = 0.04506 #
#Aeronamic calculated values
Qdot_condensor_expected = 14.3e3
Expected_COP = 3.17
#after evaporator, not superheated
T1 = evaporation_temp
P1 = PropsSI('P', 'T', T1, 'Q', 1, 'Propane&IsoButane')
h1 = PropsSI('H', 'T', T1, 'Q', 1, 'Propane&IsoButane')
s1 = PropsSI('S', 'T', T1, 'Q', 1, 'Propane&IsoButane')
def rhog(self, T: Iterable):
return [
PropsSI('D', 'T', t, 'Q', 1, self.eos + "::" + self.name)
for t in T
]
def pentanes():
# from doi 10.1021/je0202174 | J. Chem. Eng. Data 2003, 48, 1418-1421
# T (K), rhoL (kg/m^3), rhoV (kg/m^3), eta (mPa-s)
data_cyclopentane = """253.15 258.15 263.15 268.15 273.15 278.15 283.15 288.15 293.15 298.15 303.15 308.15 313.15 318.15 323.15 328.15 333.15 338.15 343.15 348.15 353.15
784.64 779.53 774.59 769.77 765.12 760.20 755.32 750.27 745.02 738.63 731.97 725.15 718.32 711.59 705.11 699.08 693.40 688.44 684.25 680.96 678.71
0.0881 0.1127 0.1443 0.1848 0.2368 0.3036 0.3894 0.4999 0.6421 0.8255 1.062 1.368 1.764 2.279 2.950 3.827 4.980 6.509 8.554 11.33 15.20
0.7268 0.6786 0.6347 0.5930 0.5567 0.5224 0.4922 0.4646 0.4382 0.4148 0.3923 0.3714 0.3521 0.3350 0.3190 0.3048 0.2912 0.2793 0.2690 0.2590 0.2502"""
# from doi 10.1021/je0202174 | J. Chem. Eng. Data 2003, 48, 1418-1421
# T (K), rhoL (kg/m^3), rhoV (kg/m^3), eta (mPa-s)
data_isopentane = """253.15 258.15 263.15 268.15 273.15 278.15 283.15 288.15 293.15 298.15 303.15 308.15 313.15 318.15 323.15 328.15 333.15 338.15 343.15 348.15 353.15
658.32 653.55 648.73 643.87 639.01 634.15 629.35 624.63 620.05 615.69 610.87 605.63 600.05 594.23 588.24 582.18 576.13 570.18 564.41 558.92 553.79
0.4655 0.5889 0.7372 0.9137 1.122 1.366 1.650 1.979 2.356 2.788 3.278 3.833 4.459 5.162 5.949 6.827 7.803 8.886 10.09 11.41 12.87
0.3893 0.3661 0.3439 0.3201 0.3023 0.2859 0.2703 0.2547 0.2399 0.2289 0.2144 0.2023 0.1910 0.1813 0.1724 0.1611 0.1543 0.1480 0.1411 0.1332 0.1287"""
fluid = ''
def undelimit(args, delim=''):
return [
np.array([float(_) for _ in a.strip().split(delim)]) for a in args
]
from CoolProp.CoolProp import PropsSI
for fluid, e_k, sigma_nm in zip(['CycloPentane', 'Isopentane'],
[406.33, 341.06], [0.518, 0.56232]):
xx, yy, RHO, ETA, ETACP, ETARP = [], [], [], [], [], []
for _T, _rhoLmass, _rhoVmass, _eta_mPas in zip(
*undelimit(data_cyclopentane.split('\n'), delim=' ')):
MM = PropsSI('molemass', fluid)
rhomolar = _rhoLmass / MM
eta = _eta_mPas / 1000
psi = get_psi(fluid, 'Propane', eta, _T, rhomolar, e_k, sigma_nm)
xx.append(_T)
yy.append(psi)
RHO.append(rhomolar)
try:
ETACP.append(
CoolProp.CoolProp.PropsSI('V', 'T', _T, 'Q', 0, fluid))
except:
ETACP.append(np.nan)
ETA.append(eta)
ETARP.append(
CoolProp.CoolProp.PropsSI(
'V', 'T', _T, 'Q', 0,
'REFPROP::' + CoolProp.CoolProp.get_fluid_param_string(
fluid, 'REFPROP_name')))
xx, yy, ETACP, ETARP, RHO, = arrayize(xx, yy, ETACP, ETARP, RHO)
rhored = CoolProp.CoolProp.PropsSI(fluid, 'rhomolar_critical')
print('rhored', rhored)
rhor = np.array(RHO) / rhored
plt.title(fluid)
plt.plot(rhor, yy, 'o-', label='from experimental data')
p = np.polyfit(rhor, yy, 2)
print(p[::-1])
plt.plot(rhor, np.polyval(p, rhor), 'o-', label='from correlation')
plt.xlabel(r'$\rho_r$')
plt.ylabel('$\psi$')
plt.legend(loc='best')
plt.show()
plt.title(fluid)
plt.plot(xx, (ETACP / ETA - 1) * 100, '^', label='CoolProp')
plt.plot(xx, (ETARP / ETA - 1) * 100, 'o', label='REFPROP')
plt.xlabel('Temperature (K)')
plt.ylabel('$100\\times(\eta_{calc}/\eta_{exp}-1)$ (%)')
plt.legend(loc='best')
plt.savefig(fluid + '_deviation.pdf')
plt.show()
def tsat(self, P: Iterable):
return [
PropsSI('T', 'P', P, 'Q', 0.5, self.eos + "::" + self.name) if
(self.pmin < p < self.pmax) else None for p in P
]
def __init__(self, symbol="N2", T=530.0, P=1000.0, child=1):
'''Init generic Fluid'''
self.symbol = symbol.upper()
# http://www.coolprop.org/_static/doxygen/html/class_cool_prop_1_1_abstract_state.html
AS = AbstractState("HEOS", self.symbol)
self.AS = AS
self.name = AS.name()
self.T = T
self.P = P
self.child = child
Tsi = TSI_fromEng(T)
Psi = PSI_fromEng(P)
AS.update(CP.PT_INPUTS, Psi, Tsi)
self.WtMol = AS.molar_mass() * 1000.0
self.Tc = Teng_fromSI(AS.T_critical())
self.Pc = Peng_fromSI(AS.p_critical())
self.Dc = Deng_fromSI(AS.rhomass_critical())
self.Ttriple = Teng_fromSI(AS.Ttriple())
try:
self.Tfreeze = Teng_fromSI(AS.T_freeze())
except:
self.Tfreeze = self.Ttriple
self.Tmin = Teng_fromSI(AS.Tmin())
self.Tmax = Teng_fromSI(AS.Tmax())
#self.Pmin = Peng_fromSI( AS.pmin() ) # missing from AbstractState
self.Pmax = Peng_fromSI(AS.pmax())
dcIdeal = self.Pc * self.WtMol / self.Tc / 10.729
self.Zc = dcIdeal / self.Dc
try:
TnbpSI = PropsSI("T", "P", 101325, "Q", Q_LIQUID, self.symbol)
self.good_nbp = True
self.Tnbp = Teng_fromSI(TnbpSI)
except:
#print('WARNING... "%s" failed Normal Boiling Point Calculation.'%self.symbol)
Ttriple = PropsSI(self.symbol, 'Ttriple')
#print(' Using Triple Point = %g degK as Tref'%Ttriple)
self.good_nbp = False
self.Tnbp = 'N/A'
if self.good_nbp:
if self.Tnbp < 536.67:
self.Tref = self.Tnbp # if NBP is low, use NBP as ref
else:
self.Tref = 536.67 # 536.67R = (SATP, Standard Ambient T P) = 77F, 25C
else:
self.Tref = Teng_fromSI(Ttriple) + 0.1
self.Pref = 14.7
#print( 'About to call setTP #1 with Tref, Pref=',self.Tref,self.Pref )
self.setTP(self.Tref, self.Pref)
#print( 'Back from call setTP')
self.Href = self.H
#print( 'About to call setTP #2')
self.setTP(T, P)
#print( 'Back from call setTP')
if child == 1:
self.dup = EC_Fluid(symbol=self.symbol,
T=self.T,
P=self.P,
child=0)
self.calcdFreezePt = 0
Tmax = 650
T = np.linspace(Tmin, Tmax, nT)
nS = 100
Smin = 850
Smax = 1500
S = np.linspace(Smin, Smax, nS)
nH = nT
Hmin = 200 * 1e3 #PropsSI("H", "T", Tmin, "S", Smin, 'Toluene')
Hmax = 700 * 1e3 #psSI("H", "T", Tmax, "S", Smax, 'Toluene')
H = np.linspace(Hmin, Hmax, nH)
print(Hmin, Hmax)
condenser_inlet = PropsSI("T", "P", P4, "S", S, 'Toluene')
# diagram bars
criticalisobar = PropsSI("T", "P", CP.PropsSI("Pcrit", "Toluene"), "S", S,
'Toluene')
dome1 = PropsSI("S", "T", T, "Q", 1., 'Toluene')
dome2 = PropsSI("S", "T", T, "Q", 0., 'Toluene')
dome1 = PropsSI("S", "T", T, "Q", 1., 'Toluene')
dome2 = PropsSI("S", "T", T, "Q", 0., 'Toluene')
dome1h = []
dome2h = []
for index, element in enumerate(dome1):
try:
dome1h.append(PropsSI("H", "T", T[index], "S", element, 'Toluene'))
def getRho(self, P, T):
self.rho = PropsSI('D', 'T', T, 'P', P, self.name)
return self.rho
Tg = np.zeros(NZ)
for i in range(NZ):
if Z[i] < Z2:
Tg[i] = 273.2 + 20.0+(100.0/350.0)*Z[i]
else:
Tg[i] = 273.2 + 120.0
# initilize in tube
Qtube[:] = 1.0
Ttube[:] = Tin
Ttuben[:] = Tin
for i in range(2*NZ):
Ptube[i] = Pin + Rhoin * cg * (Ztube[i]) # PropsSI('P','T',Ttube[i],'Q',Qtube[i],'Water')
Dtube[i] = PropsSI('D','T',Ttube[i],'P',Ptube[i],'Water')
htube[i] = PropsSI('H','T',Ttube[i],'P',Ptube[i],'Water')
mutube[i] = PropsSI('V','T',Ttube[i],'P',Ptube[i],'Water')/Dtube[i] # m2/s
Prtube[i] = PropsSI('PRANDTL','T',Ttube[i],'P',Ptube[i],'Water')
tktube[i] = PropsSI('CONDUCTIVITY','T',Ttube[i],'P',Ptube[i],'Water')
cptube[i] = PropsSI('C','T',Ttube[i],'P',Ptube[i],'Water')
#----------------- Ground temperature as reference (real data will be required)
def Tg1(z):
Tsg1 = 20.0+273.2
dtdz = 100.0/350.0 # 100K/350m
return Tsg1+dtdz*z
def Tg2(z):
Tsg2 = 120.0+273.2
def getViscosity(self, P, T):
self.viscosity = PropsSI('viscosity', 'T', T, 'P', P, self.name)
return self.viscosity
def EconomizedCycle(Ref,
Qin,
Te,
Tc,
DTsh,
DTsc,
eta_oi,
f_p,
Ti,
Ts_Ph='Ts',
skipPlot=False,
axis=None,
**kwargs):
"""
This function plots an economized cycle, on the current axis, or that given by the optional parameter *axis*
Required parameters:
* Ref : Refrigerant [string]
* Qin : Cooling capacity [W]
* Te : Evap Temperature [K]
* Tc : Condensing Temperature [K]
* DTsh : Evaporator outlet superheat [K]
* DTsc : Condenser outlet subcooling [K]
* eta_oi : Adiabatic efficiency of compressor (no units) in range [0,1]
* f_p : fraction of compressor power lost as ambient heat transfer in range [0,1]
* Ti : Saturation temperature corresponding to intermediate pressure [K]
Optional parameters:
* Ts_Ph : 'Ts' for a Temperature-Entropy plot, 'Ph' for a Pressure-Enthalpy
* axis : An axis to use instead of the active axis
* skipPlot : If True, won't actually plot anything, just print COP
"""
warnings.warn(
"This function has been deprecated. Please consider converting it to an object inheriting from \"BaseCycle\".",
DeprecationWarning)
from scipy.optimize import newton
m = 1
T = np.zeros((11))
h = np.zeros_like(T)
p = np.zeros_like(T)
s = np.zeros_like(T)
rho = np.zeros_like(T)
T[0] = np.NAN
s[0] = np.NAN
T[1] = Te + DTsh
pe = PropsSI('P', 'T', Te, 'Q', 1.0, Ref)
pc = PropsSI('P', 'T', Tc, 'Q', 1.0, Ref)
pi = PropsSI('P', 'T', Ti, 'Q', 1.0, Ref)
p[1] = pe
h[1] = PropsSI('H', 'T', T[1], 'P', pe, Ref)
s[1] = PropsSI('S', 'T', T[1], 'P', pe, Ref)
rho[1] = PropsSI('D', 'T', T[1], 'P', pe, Ref)
h2s = PropsSI('H', 'S', s[1], 'P', pi, Ref)
wdot1 = (h2s - h[1]) / eta_oi
h[2] = h[1] + (1 - f_p[0]) * wdot1
p[2] = pi
#T[2]=T_hp(Ref,h[2],pi,T2s)
T[2] = PropsSI('T', 'H', h[2], 'P', pi, Ref)
s[2] = PropsSI('S', 'T', T[2], 'P', pi, Ref)
rho[2] = PropsSI('D', 'T', T[2], 'P', pi, Ref)
T[5] = Tc - DTsc
h[5] = PropsSI('H', 'T', T[5], 'P', pc, Ref)
s[5] = PropsSI('S', 'T', T[5], 'P', pc, Ref)
rho[5] = PropsSI('D', 'T', T[5], 'P', pc, Ref)
p[5] = pc
p[6] = pi
h[6] = h[5]
p[7] = pi
p[8] = pi
p[6] = pi
T[7] = Ti
h[7] = PropsSI('H', 'T', Ti, 'Q', 1, Ref)
s[7] = PropsSI('S', 'T', Ti, 'Q', 1, Ref)
rho[7] = PropsSI('D', 'T', Ti, 'Q', 1, Ref)
T[8] = Ti
h[8] = PropsSI('H', 'T', Ti, 'Q', 0, Ref)
s[8] = PropsSI('S', 'T', Ti, 'Q', 0, Ref)
rho[8] = PropsSI('D', 'T', Ti, 'Q', 0, Ref)
x6 = (h[6] - h[8]) / (h[7] - h[8]) #Vapor Quality
s[6] = s[7] * x6 + s[8] * (1 - x6)
rho[6] = 1.0 / (x6 / rho[7] + (1 - x6) / rho[8])
T[6] = Ti
#Injection mass flow rate
x = m * (h[6] - h[8]) / (h[7] - h[6])
p[3] = pi
h[3] = (m * h[2] + x * h[7]) / (m + x)
#T[3]=T_hp(Ref,h[3],pi,T[2])
T[3] = PropsSI('T', 'H', h[3], 'P', pi, Ref)
s[3] = PropsSI('S', 'T', T[3], 'P', pi, Ref)
rho[3] = PropsSI('D', 'T', T[3], 'P', pi, Ref)
T4s = newton(lambda T: PropsSI('S', 'T', T, 'P', pc, Ref) - s[3],
T[2] + 30)
h4s = PropsSI('H', 'T', T4s, 'P', pc, Ref)
p[4] = pc
wdot2 = (h4s - h[3]) / eta_oi
h[4] = h[3] + (1 - f_p[1]) * wdot2
#T[4]=T_hp(Ref,h[4],pc,T4s)
T[4] = PropsSI('T', 'H', h[4], 'P', pc, Ref)
s[4] = PropsSI('S', 'T', T[4], 'P', pc, Ref)
rho[4] = PropsSI('D', 'T', T[4], 'P', pc, Ref)
p[9] = pe
h[9] = h[8]
T[9] = Te
hsatL_e = PropsSI('H', 'T', Te, 'Q', 0, Ref)
hsatV_e = PropsSI('H', 'T', Te, 'Q', 1, Ref)
ssatL_e = PropsSI('S', 'T', Te, 'Q', 0, Ref)
ssatV_e = PropsSI('S', 'T', Te, 'Q', 1, Ref)
vsatL_e = 1 / PropsSI('D', 'T', Te, 'Q', 0, Ref)
vsatV_e = 1 / PropsSI('D', 'T', Te, 'Q', 1, Ref)
x9 = (h[9] - hsatL_e) / (hsatV_e - hsatL_e) #Vapor Quality
s[9] = ssatV_e * x9 + ssatL_e * (1 - x9)
rho[9] = 1.0 / (x9 * vsatV_e + (1 - x9) * vsatL_e)
s[10] = s[1]
T[10] = T[1]
h[10] = h[1]
p[10] = p[1]
Tbubble_e = Te
Tbubble_c = Tc
sbubble_e = PropsSI('S', 'T', Tbubble_e, 'Q', 0, Ref)
sbubble_c = PropsSI('S', 'T', Tbubble_c, 'Q', 0, Ref)
sdew_e = PropsSI('S', 'T', Te, 'Q', 1, Ref)
sdew_c = PropsSI('S', 'T', Tc, 'Q', 1, Ref)
Wdot1 = m * wdot1
Wdot2 = (m + x) * wdot2
if skipPlot == False:
if axis == None:
ax = matplotlib.pyplot.gca()
else:
ax = axis
if Ts_Ph in ['ph', 'Ph']:
ax.plot(h, p)
ax.set_yscale('log')
elif Ts_Ph in ['Ts', 'ts']:
ax.plot(np.r_[s[7], s[3]], np.r_[T[7], T[3]], 'b')
s_copy = s.copy()
T_copy = T.copy()
dT = [0, -5, 5, -12, 5, 12, -12, 0, 0, 0]
ds = [0, 0.05, 0.05, 0, 0.05, 0, 0.0, 0.05, -0.05, -0.05]
for i in range(1, len(s) - 1):
ax.plot(s[i], T[i], 'bo', mfc='b', mec='b')
ax.text(s[i] + ds[i],
T[i] + dT[i],
str(i),
ha='center',
va='center')
s = list(s)
T = list(T)
s.insert(10, sdew_e)
T.insert(10, Te)
s.insert(5, sbubble_c)
T.insert(5, Tbubble_c)
s.insert(5, sdew_c)
T.insert(5, Tc)
ax.plot(s, T, 'b')
s = s_copy
T = T_copy
else:
raise TypeError('Type of Ts_Ph invalid')
COP = m * (h[1] - h[9]) / (m * (h[2] - h[1]) + (m + x) * (h[4] - h[3]))
for i in range(1, len(T) - 1):
print('%d & %g & %g & %g & %g & %g \\\\' %
(i, T[i] - 273.15, p[i], h[i], s[i], rho[i]))
print(x, m * (h[1] - h[9]), (m * (h[2] - h[1]) + (m + x) * (h[4] - h[3])),
COP)
mdot = Qin / (h[1] - h[9])
mdot_inj = x * mdot
print(
'x9',
x9,
)
print('Qcond', (mdot + mdot_inj) * (h[4] - h[5]), 'T4', T[4] - 273.15)
print(mdot, mdot + mdot_inj)
f = 3500 / 60.
eta_v = 0.7
print('Vdisp1: ', mdot / (rho[1] * f * eta_v) * 1e6, 'cm^3')
print('Vdisp2: ', (mdot + mdot_inj) / (rho[1] * f * eta_v) * 1e6, 'cm^3')
return COP
def getK(self, P, T):
self.k = PropsSI('conductivity', 'T', T, 'P', P, self.name)
return self.k
self.FilterDrierCharge = 0
#Charge in MicroMotion [kg]
self.MicroMotionCharge = 0
#Total Chnarge [kg]
self.Charge = 0
if __name__=='__main__':
#Abstract State
Ref = 'R410A'
Backend = 'HEOS' #choose between: 'HEOS','TTSE&HEOS','BICUBIC&HEOS','REFPROP','SRK','PR'
AS = CP.AbstractState(Backend, Ref)
kwargs={
'AS': AS,
'pin': 500000,
'hin': PropsSI('H','P',500000,'T',PropsSI('T','P',500000,'Q',0,Ref)-10,Ref),
'mdot': 0.03,
'ID':in2m(3.0/8.0)-mm2m(2), #pipe diameter
'h':in2m(1.370), #height of sight glass in m
'D':in2m(1.110), #diameter of sight glass in m
'n_sight':2, #number of sight glasses
'V': cubin2cubm(16), #volume of filter drier (website = 13.74in^3 calculated) (manual = 16in^3)
'D_Micro': in2m(0.21), #micromotion tube diameter
'L_Micro': in2m(14.6), #micormotion tube length
'n_Micro': 2, #micormotion number of tubes
}
SightGlassFilterDrierMicroMotionClass = SightGlassFilterDrierMicroMotionClass(**kwargs)
SightGlassFilterDrierMicroMotionClass.Calculate()
print (SightGlassFilterDrierMicroMotionClass.OutputList())
def run(self):
# ----------
# Pre-processing calculations
# ----------
# Ambient
T1 = self.T_amb
p1 = self.p_amb
h1 = PropsSI('H', 'T', T1, 'P', p1, self.fluid)
s1 = PropsSI('S', 'T', T1, 'P', p1, self.fluid)
# Cavern
p_cav = self.p_min
m_cav = self.V * PropsSI('D', 'T', self.T_cav, 'P', p_cav, self.fluid)
# u_tnk = PropsSI('U', 'T', T_tnk, 'P', p_tnk, self.fluid)
MW = PropsSI('MOLEMASS', self.fluid) # kg/mol
R = PropsSI('GAS_CONSTANT', self.fluid) # J/mol-K
# Track energy and heat stored
E_stor = 0.0
Q_stor = 0.0
#-------------------------------------
# Charge
#-------------------------------------
t = 0.
while p_cav < self.p_max:
t = t + self.dt
# Compressor
p2 = p_cav
h2s = PropsSI('H', 'P', p2, 'S', s1, self.fluid)
h2 = h1 + (h2s - h1) / self.cmp_eff
T2 = PropsSI('T', 'P', p2, 'H', h2, self.fluid)
m_dot = self.pwr / (h2 - h1)
# Cooler
p3 = p2
T3 = min(self.T_stor, T2)
h3 = PropsSI('H', 'T', T3, 'P', p3, self.fluid)
Q_clr = m_dot * (h2 - h3)
# Storage Tank
# Mass balance
m_cav = m_cav + m_dot * self.dt
n = m_cav / MW # moles
# Energy balance
# Cv = PropsSI('CVMASS', 'T', self.T_cav, 'P', p_tnk, self.fluid) # Assume small differences in Cv
# u_tnk = ((m_tnk-m_dot*self.dt)*u_tnk + m_dot*self.dt*h3)/(m_tnk)
# T_tnk = u_tnk / Cv
p_tnk = n * R * self.T_cav / self.V
# Energy/Heat Storage
Q_stor = Q_stor + Q_clr * self.dt
E_stor = E_stor + self.pwr * self.dt
# Store Data
s = pd.Series(index=variablesC)
s['t'] = t
s['pwr'] = self.pwr
s['m_dot'] = m_dot
s['p1'] = p1
s['T1'] = T1
s['p2'] = p2
s['T2'] = T2
s['p3'] = p3
s['T3'] = T3
s['p_cav'] = p_cav
s['T_cav'] = self.T_cav
s['Q_clr'] = Q_clr
s['Q_stor'] = Q_stor
s['E_stor'] = E_stor
s.name = t
self.dfC = self.dfC.append(s)
#-------------------------------------
# Mid-Analysis
#-------------------------------------
E_in = E_stor
Q_in = Q_stor
#-------------------------------------
# Discharge
#-------------------------------------
t = 0.
while p_cav > self.p_min and E_stor > 0.0:
t = t + self.dt
# Heater
T4 = self.T_cav
p4 = p_cav
h4 = PropsSI('H', 'T', T4, 'P', p4, self.fluid)
p5 = p_cav
if Q_stor > 0:
T5 = max(self.T_stor, self.T_cav)
else:
T5 = self.T_cav
h5 = PropsSI('H', 'T', T5, 'P', p5, self.fluid)
s5 = PropsSI('S', 'T', T5, 'P', p5, self.fluid)
# Turbine
p6 = self.p_amb
h6s = PropsSI('H', 'P', p6, 'S', s5, self.fluid)
h6 = h5 + (h6s - h5) * self.trb_eff
T6 = PropsSI('T', 'P', p6, 'H', h6, self.fluid)
m_dot = self.pwr / (h5 - h6)
# Revisit Heater
Q_htr = m_dot * (h5 - h4)
# Cavern
# Mass balance
m_cav = m_cav - m_dot * self.dt
n = m_cav / MW # moles
# Energy balance
# Cv = PropsSI('CVMASS', 'T', T_tnk, 'P', p_tnk, self.fluid) # Assume small differences in Cv
# u_tnk = ((m_tnk+m_dot*self.dt)*u_tnk - m_dot*self.dt*h4)/(m_tnk)
# T_tnk = u_tnk / Cv
p_tnk = n * R * self.T_cav / self.V
# Energy/Heat Storage
Q_stor = Q_stor - Q_htr * self.dt
E_stor = E_stor - self.pwr * self.dt
# Check outlet temp
if self.T_out_min == -1.0:
self.T_out_min = T6
else:
self.T_out_min = min(self.T_out_min, T6)
# Store Data
s = pd.Series(index=variablesD)
s['t'] = t
s['pwr'] = self.pwr
s['m_dot'] = m_dot
s['p4'] = p4
s['T4'] = T4
s['p5'] = p5
s['T5'] = T5
s['p6'] = p6
s['T6'] = T6
s['p_cav'] = p_cav
s['T_cav'] = self.T_cav
s['Q_htr'] = Q_htr
s['Q_stor'] = Q_stor
s['E_stor'] = E_stor
s.name = t
self.dfD = self.dfD.append(s)
#-------------------------------------
# Final-Analysis
#-------------------------------------
Q_out = Q_in - Q_stor
E_out = E_in - E_stor
self.RTE = E_out / E_in * 100.0
self.Heat_Util = Q_out / Q_in * 100.0
# Store and Convert from Ws to MWh
convert = 1.0 / 1E6 / 60. / 60.
self.E_in = E_in * convert
self.E_out = E_out * convert
self.Q_in = Q_in * convert
self.Q_out = Q_out * convert
# Convert to C
self.T_out_min = self.T_out_min - 273.15
results = pd.Series(index=[
'RTE', 'Heat_Util', 'E_in', 'E_out', 'Q_in', 'Q_out', 'T_out_min',
'Ebal', 'Qbal'
])
results['RTE'] = self.RTE
results['Heat_Util'] = self.Heat_Util
results['E_in'] = self.E_in
results['E_out'] = self.E_out
results['Q_in'] = self.Q_in
results['Q_out'] = self.Q_out
results['T_out_min'] = self.T_out_min
results['Ebal'] = self.E_in - self.E_out
results['Qbal'] = self.Q_in - self.Q_out
return results
