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CoolProp/wrappers/Python/CoolProp5/Plots/SimpleCycles.py

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import matplotlib,numpy
from CoolProp.CoolProp import Props
from scipy.optimize import newton
def SimpleCycle(Ref,Te,Tc,DTsh,DTsc,eta_a,Ts_Ph='Ph',skipPlot=False,axis=None):
"""
This function plots a simple four-component cycle, on the current axis, or that given by the optional parameter *axis*
Required parameters:
* Ref : A string for the refrigerant
* Te : Evap Temperature in K
* Tc : Condensing Temperature in K
* DTsh : Evaporator outlet superheat in K
* DTsc : Condenser outlet subcooling in K
* eta_a : Adiabatic efficiency of compressor (no units) in range [0,1]
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
"""
T=numpy.zeros((6))
h=numpy.zeros_like(T)
p=numpy.zeros_like(T)
s=numpy.zeros_like(T)
T[1]=Te+DTsh
pe=Props('P','T',Te,'Q',1.0,Ref)
pc=Props('P','T',Tc,'Q',1.0,Ref)
h[1]=Props('H','T',T[1],'P',pe,Ref)
s[1]=Props('S','T',T[1],'P',pe,Ref)
T2s=newton(lambda T: Props('S','T',T,'P',pc,Ref)-s[1],T[1]+30)
h2s=Props('H','T',T2s,'P',pc,Ref)
h[2]=(h2s-h[1])/eta_a+h[1]
T[2]=Props('T','H',h[2],'P',pc,Ref)
s[2]=Props('S','T',T[2],'P',pc,Ref)
sbubble_c=Props('S','P',pc,'Q',0,Ref)
sdew_c=Props('S','P',pc,'Q',1,Ref)
sbubble_e=Props('S','P',pe,'Q',0,Ref)
sdew_e=Props('S','P',pe,'Q',1,Ref)
T[3]=Tc-DTsc
h[3]=Props('H','T',T[3],'P',pc,Ref)
s[3]=Props('S','T',T[3],'P',pc,Ref)
h[4]=h[3]
h[5]=h[1]
s[5]=s[1]
T[5]=T[1]
p=[numpy.nan,pe,pc,pc,pe,pe]
COP=(h[1]-h[4])/(h[2]-h[1])
COPH=(h[2]-h[3])/(h[2]-h[1])
hsatL=Props('H','T',Te,'Q',0,Ref)
hsatV=Props('H','T',Te,'Q',1,Ref)
ssatL=Props('S','T',Te,'Q',0,Ref)
ssatV=Props('S','T',Te,'Q',1,Ref)
vsatL=1/Props('D','T',Te,'Q',0,Ref)
vsatV=1/Props('D','T',Te,'Q',1,Ref)
x=(h[4]-hsatL)/(hsatV-hsatL)
s[4]=x*ssatV+(1-x)*ssatL
T[4]=x*Te+(1-x)*Te
print(COP,COPH)
if skipPlot==False:
if axis==None:
ax=matplotlib.pyplot.gca()
if Ts_Ph in ['ph','Ph']:
ax.plot(h,p)
elif Ts_Ph in ['Ts','ts']:
s=list(s)
T=list(T)
s.insert(5,sdew_e)
T.insert(5,Te)
s.insert(3,sbubble_c)
T.insert(3,Tc)
s.insert(3,sdew_c)
T.insert(3,Tc)
ax.plot(s[1::],T[1::],'b')
else:
raise TypeError('Type of Ts_Ph invalid')
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
"""
T=numpy.zeros((8))
h=numpy.zeros_like(T)
p=numpy.zeros_like(T)
s=numpy.zeros_like(T)
rho=numpy.zeros_like(T)
T[0]=numpy.NAN
s[0]=numpy.NAN
T[1]=Te+DTsh
pe=Props('P','T',Te,'Q',1.0,Ref)
pc=Props('P','T',Tc,'Q',1.0,Ref)
pic=Props('P','T',Tsat_ic,'Q',1.0,Ref)
Tbubble_c=Props('T','P',pc,'Q',0,Ref)
Tbubble_e=Props('T','P',pe,'Q',0,Ref)
h[1]=Props('H','T',T[1],'P',pe,Ref)
s[1]=Props('S','T',T[1],'P',pe,Ref)
rho[1]=Props('D','T',T[1],'P',pe,Ref)
T[5]=Tbubble_c-DTsc
h[5]=Props('H','T',T[5],'P',pc,Ref)
s[5]=Props('S','T',T[5],'P',pc,Ref)
rho[5]=Props('D','T',T[5],'P',pc,Ref)
mdot=Q/(h[1]-h[5])
rho1=Props('D','T',T[1],'P',pe,Ref)
h2s=Props('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]=Props('T','H',h[2],'P',pic,Ref)
s[2]=Props('S','T',T[2],'P',pic,Ref)
rho[2]=Props('D','T',T[2],'P',pic,Ref)
T[3]=288
p[3]=pic
h[3]=Props('H','T',T[3],'P',pic,Ref)
s[3]=Props('S','T',T[3],'P',pic,Ref)
rho[3]=Props('D','T',T[3],'P',pic,Ref)
rho3=Props('D','T',T[3],'P',pic,Ref)
h4s=Props('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]=Props('T','H',h[4],'P',pc,Ref)
s[4]=Props('S','T',T[4],'P',pc,Ref)
rho[4]=Props('D','T',T[4],'P',pc,Ref)
sbubble_e=Props('S','T',Tbubble_e,'Q',0,Ref)
sbubble_c=Props('S','T',Tbubble_c,'Q',0,Ref)
sdew_e=Props('S','T',Te,'Q',1,Ref)
sdew_c=Props('S','T',Tc,'Q',1,Ref)
hsatL=Props('H','T',Tbubble_e,'Q',0,Ref)
hsatV=Props('H','T',Te,'Q',1,Ref)
ssatL=Props('S','T',Tbubble_e,'Q',0,Ref)
ssatV=Props('S','T',Te,'Q',1,Ref)
vsatL=1/Props('D','T',Tbubble_e,'Q',0,Ref)
vsatV=1/Props('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=[numpy.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 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
"""
m=1
T=numpy.zeros((11))
h=numpy.zeros_like(T)
p=numpy.zeros_like(T)
s=numpy.zeros_like(T)
rho=numpy.zeros_like(T)
T[0]=numpy.NAN
s[0]=numpy.NAN
T[1]=Te+DTsh
pe=Props('P','T',Te,'Q',1.0,Ref)
pc=Props('P','T',Tc,'Q',1.0,Ref)
pi=Props('P','T',Ti,'Q',1.0,Ref)
p[1]=pe
h[1]=Props('H','T',T[1],'P',pe,Ref)
s[1]=Props('S','T',T[1],'P',pe,Ref)
rho[1]=Props('D','T',T[1],'P',pe,Ref)
h2s=Props('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)
s[2]=Props('S','T',T[2],'P',pi,Ref)
rho[2]=Props('D','T',T[2],'P',pi,Ref)
T[5]=Tc-DTsc
h[5]=Props('H','T',T[5],'P',pc,Ref)
s[5]=Props('S','T',T[5],'P',pc,Ref)
rho[5]=Props('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]=Props('H','T',Ti,'Q',1,Ref)
s[7]=Props('S','T',Ti,'Q',1,Ref)
rho[7]=Props('D','T',Ti,'Q',1,Ref)
T[8]=Ti
h[8]=Props('H','T',Ti,'Q',0,Ref)
s[8]=Props('S','T',Ti,'Q',0,Ref)
rho[8]=Props('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])
s[3]=Props('S','T',T[3],'P',pi,Ref)
rho[3]=Props('D','T',T[3],'P',pi,Ref)
T4s=newton(lambda T: Props('S','T',T,'P',pc,Ref)-s[3],T[2]+30)
h4s=Props('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)
s[4]=Props('S','T',T[4],'P',pc,Ref)
rho[4]=Props('D','T',T[4],'P',pc,Ref)
p[9]=pe
h[9]=h[8]
T[9]=Te
hsatL_e=Props('H','T',Te,'Q',0,Ref)
hsatV_e=Props('H','T',Te,'Q',1,Ref)
ssatL_e=Props('S','T',Te,'Q',0,Ref)
ssatV_e=Props('S','T',Te,'Q',1,Ref)
vsatL_e=1/Props('D','T',Te,'Q',0,Ref)
vsatV_e=1/Props('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=Props('S','T',Tbubble_e,'Q',0,Ref)
sbubble_c=Props('S','T',Tbubble_c,'Q',0,Ref)
sdew_e=Props('S','T',Te,'Q',1,Ref)
sdew_c=Props('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(numpy.r_[s[7],s[3]],numpy.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
if __name__=='__main__':
from CoolProp.Plots import Ph,Ts
Ref='R290'
fig=matplotlib.pyplot.figure(figsize=(4,3))
ax=fig.add_axes((0.15,0.15,0.8,0.8))
Ph(Ref,Tmin=273.15-30,hbounds=[0,600],axis=ax)
COP=TwoStage('Propane',10000,273.15-5,273.15+43.3,5,7,0.7,0.3,15+273.15,3,prints = True)
matplotlib.pyplot.show()
Ref='R290'
fig=matplotlib.pyplot.figure(figsize=(4,3))
ax=fig.add_axes((0.15,0.15,0.8,0.8))
Ph(Ref,Tmin=273.15-30,hbounds=[0,600],axis=ax)
COP=SimpleCycle(Ref,273.15-5,273.15+45,5,7,0.7,Ts_Ph='Ph')
matplotlib.pyplot.show()
Ref='R410A'
fig=matplotlib.pyplot.figure(figsize=(4,3))
ax=fig.add_axes((0.15,0.15,0.8,0.8))
Ts(Ref,Tmin=273.15-100,sbounds=[0,600],axis=ax)
COP=SimpleCycle(Ref,273.15-5,273.15+45,5,7,0.7,Ts_Ph='Ts')
matplotlib.pyplot.show()
## for x in numpy.linspace(0,1):
## Ref='REFPROP-MIX:R152A[%g]&R32[%g]' %(x,1-x)
## COP=SimpleCycle(273.15+8,273.15+44,5,7,0.7,skipPlot=True,Ts_Ph='Ph')
## matplotlib.pyplot.show()
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