def main():
fluid_ref = 'n-Pentane'
for plot_type in ['Ts']: #['pt', 'ph', 'ps', 'ts', 'pt', 'prho', 'trho']:
plt = PropertyPlot(fluid_ref, plot_type)
plt.set_axis_limits([-0.5 * 1e3, 1.5 * 1e3, 300, 530])
plt.draw_isolines('Q', [0.1, 0.9])
plt.draw_isolines('P', [100 * 1e3, 2000 * 1e3])
plt.draw_isolines('D', [2, 600])
plt.show()
def plot_Ts():
pp = PropertyPlot('HEOS::R134a', 'TS', unit_system='EUR', tp_limits='ACHP')
pp.calc_isolines()
cycle = SimpleCompressionCycle('HEOS::R134a', 'TS', unit_system='EUR', tp_limits='ACHP')
cycle.simple_solve_dt(Te=T_K_sat_evaporating ,Tc=T_K_sat_condensing, dT_sh=superheat, dT_sc=subcooling, eta_com= Isentropic_Efficiency/100, SI=True)
cycle.steps = 50
sc = cycle.get_state_changes()
plt.close(cycle.figure)
pp.draw_process(sc)
pp.savefig('T-s.svg')
pp.show()
def SimpleRankineCycle(T3, p3, p1, epsilon_e, epsilon_p, fluid='water'):
h1 = PropsSI('H', 'P', p1, 'Q', 0., fluid)
s1 = PropsSI('S', 'P', p1, 'Q', 0., fluid)
T1 = PropsSI('T', 'P', p1, 'Q', 0., fluid)
p2 = p3
h2 = h1 + (PropsSI('H', 'P', p2, 'S', s1, fluid) - h1) / epsilon_p
s2 = PropsSI('S', 'H', h2, 'P', p2, fluid)
T2 = PropsSI('T', 'H', h2, 'P', p2, fluid)
h3 = PropsSI('H', 'P', p3, 'T', T3, fluid)
s3 = PropsSI('S', 'H', h3, 'P', p3, fluid)
p4 = p1
h4 = h3 - epsilon_e * (h3 - PropsSI('H', 'P', p4, 'S', s3, fluid))
s4 = PropsSI('S', 'H', h4, 'P', p4, fluid)
T4 = PropsSI('T', 'H', h4, 'P', p4, fluid)
w_net = h3 - h4
q_boiler = h3 - h2
eta_c = w_net / q_boiler
Ts = PropertyPlot(fluid, 'Ts', 'KSI')
Ts.set_axis_limits([0., 12., 200., 900.])
Ts.calc_isolines(CoolProp.iP, [Ts.system.P.from_SI(p1), Ts.system.P.from_SI(p3)], num=10)
Ts.calc_isolines(CoolProp.iQ, [Ts.system.Q.from_SI(0.), Ts.system.Q.from_SI(1.)], num=11)
Ts.draw_isolines()
states = zip(Ts.system.S.from_SI(array([s1,s2,s3,s4,s1])),Ts.system.T.from_SI(array([T1,T2,T3,T4,T1])))
Ts.draw_process(states, iso_types=None, line_opts={'color':'red', 'lw':1.5})
isot = [
None, # non-isentropic pumping from 1 to 2
CoolProp.iP, # p2=p3
None,
CoolProp.iP, # p4=p1
]
Ts.draw_process(states, iso_types=isot, line_opts={'color':'green', 'lw':1.5})
ax = Ts.axis
ax.text(Ts.system.S.from_SI(s1), Ts.system.T.from_SI(T1), ' 1', fontsize=10, rotation=0, color='r')
ax.text(Ts.system.S.from_SI(s2), Ts.system.T.from_SI(T2), ' 2', fontsize=10, rotation=0, color='r')
ax.text(Ts.system.S.from_SI(s3), Ts.system.T.from_SI(T3), ' 3', fontsize=10, rotation=0, color='r')
ax.text(Ts.system.S.from_SI(s4), Ts.system.T.from_SI(T4), ' 4', fontsize=10, rotation=0, color='r')
ax.text(Ts.system.S.from_SI(8e3),Ts.system.T.from_SI(850),"Efficiency: %.1f%%" %(eta_c*100.))
ax.text(Ts.system.S.from_SI(8e3),Ts.system.T.from_SI(800),"Net work: %d kJ/kg" %(w_net/1000))
ax.text(Ts.system.S.from_SI(8e3),Ts.system.T.from_SI(750),"Heat input: %d kJ/kg" %(q_boiler/1000))
return Ts
def plot_cycle(s, T):
# End calculation
# Plotting T-S
label = ('1', '2', '3a', '3b', '4a', '4b', '5', '6', '7', '8', 'cab')
_, ax = plt.subplots()
ax.plot(s, T, 'b-s', linewidth=.8)
for idx, (s_, T_) in enumerate(zip(s, T)):
ax.annotate(' ' + label[idx], (s_, T_))
ax.set_xlabel('s')
ax.set_ylabel('T')
plot = PropertyPlot('Air', 'TS', unit_system='KSI', tp_limits='ACHP', axis=ax)
plot.calc_isolines(CoolProp.iP, iso_range=s, num=(len(s) - 4))
ax.set_xlim([np.min(s) * 0.97, np.max(s) * 1.03])
ax.set_ylim([np.min(T) * 0.97, np.max(T) * 1.03])
plot.show()
def create_ts_plot(states: list, fluid: str):
cycle_states = StateContainer()
# plot only displays a dot for the state if it occurs twice
merged_states = []
for state in states:
merged_states.append(state['data'])
if state['marker']:
merged_states.append(state['data'])
states = merged_states
i = 0
for state in states:
cycle_states[i, 'P'] = state['P']
cycle_states[i]['T'] = state['T']
cycle_states[i]['S'] = state['S']
cycle_states[i]['H'] = state['H']
i += 1
plot = PropertyPlot(fluid, 'TS', tp_limits='ORC')
plot.calc_isolines(CP.iQ, num=2)
plot.calc_isolines(CP.iP)
style = {}
'''
style = {
'marker': 'o',
'markerfacecolor': 'blue',
'markeredgecolor': 'blue',
'color': matplotlib.colors.to_rgba('#ff0000'),
}
'''
plot.draw_process(cycle_states, line_opts=style)
return plot
def getPHdata(self):
ncurves = 10
with warnings.catch_warnings():
warnings.simplefilter("ignore")
plot = PropertyPlot('R134a', 'ph')
plot.calc_isolines(num=ncurves)
#plot.show()
#extract the isolines from coolprop, and plot them with pyplot
for i in range(0, 10):
xi = (plot.isolines[21])[i].x / 1000
yi = (plot.isolines[21])[i].y / 1000
if self.xPH is None:
self.xPH = np.array(xi)
self.yPH = np.array(yi)
else:
self.xPH = np.vstack((self.xPH, xi))
self.yPH = np.vstack((self.yPH, yi))
xi = (plot.isolines[19])[i].x / 1000
yi = (plot.isolines[19])[i].y / 1000
self.xPH = np.vstack((self.xPH, xi))
self.yPH = np.vstack((self.yPH, yi))
xi = (plot.isolines[34])[i].x / 1000
yi = (plot.isolines[34])[i].y / 1000
self.xPH = np.vstack((self.xPH, xi))
self.yPH = np.vstack((self.yPH, yi))
xi = (plot.isolines[36])[i].x / 1000
yi = (plot.isolines[36])[i].y / 1000
self.xPH = np.vstack((self.xPH, xi))
self.yPH = np.vstack((self.yPH, yi))
#next i
#end with
return
cycle_states[4, 'H'] = h4
cycle_states[4]['S'] = s4
cycle_states[4][CoolProp.iP] = P4
cycle_states[4, CoolProp.iT] = T4
cycle_states[5, 'H'] = h5
cycle_states[5]['S'] = s5
cycle_states[5][CoolProp.iP] = P5
cycle_states[5, CoolProp.iT] = T5
cycle_states[6, 'H'] = h6
cycle_states[6]['S'] = s6
cycle_states[6][CoolProp.iP] = P6
cycle_states[6, CoolProp.iT] = T6
cycle_states[7, 'H'] = h1
cycle_states[7]['S'] = s1
cycle_states[7][CoolProp.iP] = P1
cycle_states[7, CoolProp.iT] = T1
print(cycle_states)
pp = PropertyPlot(gas, 'PH', unit_system='EUR', tp_limits='ACHP')
pp.calc_isolines()
pp.draw_process(cycle_states)
pp.show()
#plot = PropertyPlot('R290', 'ph')
#plot.calc_isolines()
#plot.show()
label='Temperature',
symbol=u'T',
unit=u'R')
self._U = BaseDimension(add_SI=0.0,
mul_SI=0.000429923,
off_SI=0.0,
label='Specific Internal Energy',
symbol=u'u',
unit=u'BTU/lbm')
self._Q = BaseDimension(add_SI=0.0,
mul_SI=1.0,
off_SI=0.0,
label='Vapour Quality',
symbol=u'x',
unit=u'')
BasePlot.UNIT_SYSTEMS['ENG'] = ENGunits() # ['EUR','KSI','SI']
ec = EC_Fluid(symbol)
ec.printCriticalProps()
# Plot Types: 'PS', 'PT', 'HS', 'TS', 'PD', 'TD', 'PH'
# tp_limits: 'NONE', 'DEF','ACHP','ORC'
plot = PropertyPlot(symbol, 'TD', unit_system='ENG', tp_limits='DEF')
plot.calc_isolines(CP.iHmass, num=11)
plot.calc_isolines(CP.iQ, num=11)
plot.title('%s (%s)' % (ec.name, ec.symbol))
plot.grid()
plot.show()
import CoolProp
from CoolProp.Plots import PropertyPlot
fluids = CoolProp.CoolProp.FluidsList()
for i, fluid in enumerate(fluids):
plot = PropertyPlot(fluid, 'ph')
plot.calc_isolines()
plot.show()
if i > 3:
break
from CoolProp.Plots import PropertyPlot
from CoolProp.Plots.SimpleCycles import StateContainer
import pickle
import os
cache_plot = False
if cache_plot:
filename = fluid + '.p'
if os.path.isfile(filename): # Load previously saved plot
pp = pickle.load(open( filename, "rb" ) )
else:
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot('HEOS::'+fluid, 'TS')
with NoStdStreams():
pp.calc_isolines()
with open(filename, 'wb') as f:
pickle.dump(pp, f)
else:
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot('HEOS::'+fluid, 'TS')
with NoStdStreams():
pp.calc_isolines()
for i in range(3):
states[i,'T'] = T[i]
from CoolProp.Plots.Common import process_fluid_state, get_critical_point
state = process_fluid_state(
"HEOS::R32[0.381109419953993]&R125[0.179558888662016]&R134A[0.439331691383991]"
)
cstate = get_critical_point(state)
print(cstate.T())
import matplotlib.pyplot as plt
from CoolProp.Plots import PropertyPlot
fluid = "R407C"
fluid = "R32[0.381109419953993]&R125[0.179558888662016]&R134A[0.439331691383991]"
#fluid = "R32[0.40]&R125[0.15]&R134A[0.45]"
plot_RP = PropertyPlot("REFPROP::" + fluid,
'PH',
unit_system='EUR',
tp_limits='ACHP')
plot_RP.calc_isolines()
plot_RP.draw()
plot_CP = PropertyPlot("HEOS::" + fluid,
'PH',
unit_system='EUR',
tp_limits='ACHP')
plot_CP.calc_isolines()
plot_CP.draw()
plt.show(block=True)
print MCE.OutputList(), '\n', '=' * 20
csv_file = "Evaporator_MCE.csv"
print "\n demonstrating write to csv", csv_file, '\n'
Write2CSV(MCE, open(csv_file, 'w'), append=False)
print "check MCE capacity summation", MCE.hin_r * MCE.mdot_r[-1],
print np.sum([
MCE.Evaps[i].hin_r * MCE.Evaps[i].mdot_r
for i in range(MCE.Fins.Tubes.Ncircuits)
])
# plot maldistribution
h = np.array([MCE.Evaps[i].hout_r for i in range(len(MCE.Evaps))])
p = MCE.psat_r * (1 + 0 * h)
plot = PropertyPlot('HEOS::R410A', 'PH', unit_system='KSI')
plot.calc_isolines(CoolProp.iQ, num=2)
plot.axis.plot(MCE.hin_r / 1000, MCE.psat_r / 1000, '>', label='Inlet')
plot.axis.plot(h / 1000, p / 1000, 'x', label='Individual circuit exits')
plot.axis.plot(MCE.hout_r / 1000,
MCE.psat_r / 1000,
'o',
label='Overall exit')
plt.legend(loc='best', numpoints=1)
plot.savefig('MultiCircuitEvaporator_py_example.pdf')
#plot.figure.show()
plt.close(plot.figure)
print "outlet enthalpies", [
MCE.Evaps[i].hout_r for i in range(len(MCE.Evaps))
], MCE.hout_r, PropsSI('H', 'T', MCE.Evaps[-1].Tdew_r, 'Q', 1,
def plot_TS(fluid, rrange, prange):
############### TS
fig_x, fig_y = 14, 9
fig = plt.figure(figsize=(fig_x, fig_y))
ax = fig.gca()
ax.set_ylim(240, 400)
ax.set_xlim(800, 2000)
qrange = np.linspace(0, 1, 10).tolist()
ts = PropertyPlot(fluid, 'TS', unit_system='SI', tp_limits='ORC',
axis=ax) #,reciprocal_density=True)
ts.calc_isolines(CP.iQ, iso_range=qrange, num=10)
ts.props[CP.iDmass]['color'] = 'red'
ts.props[CP.iDmass]['lw'] = '0.5'
ts.calc_isolines(CP.iDmass,
iso_range=rrange,
num=len(rrange),
rounding=False)
## isobaric
ts.props[CP.iP]['color'] = 'green'
ts.props[CP.iP]['lw'] = '0.5'
ts.calc_isolines(CP.iP, iso_range=prange, num=len(prange), rounding=False)
ts.draw()
axL = ts.get_axis_limits()
ax.text(axL[0] + 20, axL[3] - 7, fluid, size=20)
t1 = axL[3] - 25
t0 = t1 - 5
for p in prange:
s1 = CP.PropsSI("Smass", "T", t1, "P", p, fluid)
s0 = CP.PropsSI("Smass", "T", t0, "P", p, fluid)
pA = np.array([s0, t0])
pB = np.array([s1, t1])
# Calculate the angle of the line
dx, dy = pA - pB
x_min, x_max = axL[0:2]
y_min, y_max = axL[2:4]
Dx = dx * fig_x / (x_max - x_min)
Dy = dy * fig_y / (y_max - y_min)
angle = (180 / np.pi) * np.arctan(Dy / Dx)
ax.text(s0,
t0,
str(format(p / 1E5, '.0f')) + 'bar',
rotation=angle,
horizontalalignment='left',
verticalalignment='bottom',
rotation_mode='anchor',
color='green')
t1 = axL[3] - 10
t0 = t1 - 5
for r in rrange:
s1 = CP.PropsSI("Smass", "T", t1, "Dmass", r, fluid)
s0 = CP.PropsSI("Smass", "T", t0, "Dmass", r, fluid)
pA = np.array([s0, t0])
pB = np.array([s1, t1])
# Calculate the angle of the line
dx, dy = pA - pB
x_min, x_max = axL[0:2]
y_min, y_max = axL[2:4]
Dx = dx * fig_x / (x_max - x_min)
Dy = dy * fig_y / (y_max - y_min)
angle = (180 / np.pi) * np.arctan(Dy / Dx)
ax.text(s0,
t0,
str(format(r, '.0f')) + 'kg/m3',
rotation=angle,
horizontalalignment='left',
verticalalignment='bottom',
rotation_mode='anchor',
color='red')
t1 = axL[2]
t0 = t1 + 8
for q in qrange:
s1 = CP.PropsSI("Smass", "T", t1, "Q", q, fluid)
s0 = CP.PropsSI("Smass", "T", t0, "Q", q, fluid)
pA = np.array([s0, t0])
pB = np.array([s1, t1])
# Calculate the angle of the line
dx, dy = pA - pB
x_min, x_max = axL[0:2]
y_min, y_max = axL[2:4]
Dx = dx * fig_x / (x_max - x_min)
Dy = dy * fig_y / (y_max - y_min)
angle = (180 / np.pi) * np.arctan(Dy / Dx)
ax.text(s0,
t0,
str(format(q, '.1f')),
rotation=angle,
horizontalalignment='left',
verticalalignment='bottom',
rotation_mode='anchor',
color='gray')
#fig.plot([s0,s1],[t0,t1],'ro')
## isobaric
ax.grid()
pgf_with_pdflatex = {
"pgf.texsystem":
"pdflatex",
"pgf.preamble": [
r"\usepackage[utf8x]{inputenc}",
r"\usepackage[T1]{fontenc}",
]
}
mpl.rcParams.update(pgf_with_pdflatex)
fig.savefig('TS.eps')
fig.savefig("TS.pgf", bbox_inches="tight")
#%%
from CoolProp.Plots import PropertyPlot
from CoolProp.Plots.SimpleCycles import StateContainer
# for the property plot, the composition needs to be embedded in the fluid name:
if '&' in fluid:
fluid_full = library+'::'+fluid1 + '[' + str(x_molar) + ']&' + fluid2 + '[' + str(1-x_molar) + ']'
else:
fluid_full = library+'::'+fluid
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot(fluid_full, 'TS')
if len(limits)>0:
pp.set_axis_limits(limits)
with NoStdStreams():
pass
pp.calc_isolines()
for i in range(3):
states[i,'T'] = T[i]
states[i,"S"] = s[i]
for i,Tx in enumerate(T_cd):
states.append({'T':Tx,'S':s_cd[i]})
for i in range(5,len(T)):
from CoolProp.Plots import PropertyPlot
#plot = PropertyPlot("HEOS::ISOBUTAN[0.8]&PROPANE[0.2]", 'PH', unit_system='EUR', tp_limits='ACHP')
# plot.calc_isolines()
# plot.show()
#plot = PropertyPlot("HEOS::ISOBUTAN[0.8]&PROPANE[0.2]", 'TS', unit_system='EUR', tp_limits='ORC')
# plot.calc_isolines()
# plot.show()
plot = PropertyPlot("REFPROP::ISOBUTAN[0.8]&PROPANE[0.2]", 'PH', unit_system='EUR', tp_limits='ACHP')
plot.calc_isolines()
plot.show()
#plot = PropertyPlot("REFPROP::ISOBUTAN[0.8]&PROPANE[0.2]", 'TS', unit_system='EUR', tp_limits='ORC')
# plot.calc_isolines()
# plot.show()
plot = PropertyPlot("HEOS::R134a", 'PH', unit_system='EUR', tp_limits='ACHP')
plot.calc_isolines()
plot.show()
h = HAPropsSI('H', 'T', 298.15, 'P', 101325, 'R', 0.5)
print(h)
# Temperature of saturated air at the previous enthalpy
T = HAPropsSI('T', 'P', 101325, 'H', h, 'R', 1.0)
print(T)
# Temperature of saturated air - order of inputs doesn't matter
T = HAPropsSI('T', 'H', h, 'R', 1.0, 'P', 101325)
print(T)
#%%
import CoolProp
from CoolProp.Plots import PropertyPlot
plot = PropertyPlot('R290', 'ph')
plot.calc_isolines()
plot.show()
#%%
import CoolProp
from CoolProp.Plots import PropertyPlot
ts_plot = PropertyPlot('R290', 'Ts', tp_limits='ORC')
ts_plot.calc_isolines(CoolProp.iQ, num=6)
ts_plot.show()
#%%problem
import CoolProp
from CoolProp.Plots import PropertyPlot
plot = PropertyPlot('HEOS::R134a', 'PH', unit_system='EUR', tp_limits='ACHP')
plot.calc_isolines(CoolProp.iQ, num=11)
cycle_states[7,'H'] = h1 cycle_states[7]['S'] = s1 cycle_states[7][CoolProp.iP] = P1 cycle_states[7,CoolProp.iT] = T1 #Qdot_condensor_calculated = (h2-h4)*massflow print(cycle_states) print(Qdot_condensor_expected) #print(Qdot_condensor_calculated) print(Expected_COP) #print(Qdot_condensor_calculated/compressor_power) pp = PropertyPlot(gas, 'PH', unit_system='KSI',tp_limits='ACHP') pp.calc_isolines(CoolProp.iQ, num=11) pp.set_axis_limits([300,700,400,2500]) pp.draw_process(cycle_states) pp.show() pp = PropertyPlot(gas, 'TS', unit_system='KSI',tp_limits='ACHP') pp.calc_isolines(CoolProp.iQ, num=15) pp.set_axis_limits([1.2,2.6,250,360]) pp.draw_process(cycle_states) pp.show() pp = PropertyPlot(gas, 'PH', unit_system='KSI',tp_limits='ACHP') pp.calc_isolines(CoolProp.iQ, num=11) pp.set_axis_limits([300,700,400,2500]) pp.draw_process(cycle_states)
library = 'HEOS'
library = 'REFPROP'
limits = [0, 1.75, 250, 550] # limits for plotting
cache_plot = False
if cache_plot:
filename = fluid + '.p'
if os.path.isfile(filename): # Load previously saved plot
pp = pickle.load(open(filename, "rb"))
else:
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot(library + '::' + fluid, 'TS')
with NoStdStreams():
pp.calc_isolines()
with open(filename, 'wb') as f:
pickle.dump(pp, f)
else:
states = StateContainer()
states_hf = StateContainer()
states_cf = StateContainer()
pp = PropertyPlot(library + '::' + fluid, 'TS')
# pp.set_axis_limits(limits)
with NoStdStreams():
pp.calc_isolines()
pp.figure.set_figheight(8)
pp.figure.set_figwidth(10)