def test_region4_2():
drop = droplet.Droplet(pressure=0.1)
assert drop.region == 'Region 4'
assert (drop.temperature - 0.372755919e3) <= TOL
drop = droplet(pressure=1)
assert drop.region == 'Region 4'
assert (drop.temperature - 0.453035632e3) <= TOL
drop = droplet(pressure=10)
assert drop.region == 'Region 4'
assert (drop.temperature - 0.584149488e3) <= TOL
def test_region4_1():
drop = droplet.Droplet(temperature=300)
assert drop.region == 'Region 4'
assert (drop.pressure - 0.353658941e-2) <= TOL
drop = droplet(temperature=500)
assert drop.region == 'Region 4'
assert (drop.pressure - 0.263889776e1) <= TOL
drop = droplet(temperature=600)
assert drop.region == 'Region 4'
assert (drop.pressure - 0.123443146e2) <= TOL
def entrainer(T, mdot):
#assume everytime the kernel entrains 10 droplets, based on the fuel mass flow rate
m10 = mdot * 1e-6
m = m10 / 10.0
fuel = 'A2'
drop_tempo = droplet(1, fuel, T, 1) #a "useless" droplet to get fuel info
#calculate r based on mass put into the the kernel, right now, no statistically distribution of r
r = np.power(3.0 / 4.0 / drop_tempo.rho / np.pi * m, 1.0 / 3.0)
print(r)
frac = 1
num = 10
d_arr = []
#create 10 droplets of the same size that give the proper mass flow rate
for i in range(0, num):
d_arr.append(droplet(r, fuel, T, frac))
return d_arr
droplet.m = droplet.m - 4.0*np.pi*droplet.k*droplet.r/droplet.cp*np.log(1.0+B)*dt
if droplet.m < 0:
pass
else:
mdot += 4.0*np.pi*droplet.k*droplet.r/droplet.cp*np.log(1.0+B)
qdot += mdot*droplet.hfg
droplet.r = (droplet.m*3.0/4.0/np.pi/droplet.rho)**(1.0/3.0)
pass
return mdot, qdot
d_array = []
for i in range(1,100):
rad = np.random.random()*100*1e-6
d_array.append(droplet(radius=rad))
dt = 1e-6
time = []
m_dot = []
q_dot = []
for i in range(1,700):
print('In iteration:' + str(i))
mdot, qdot = vaporize(1600, d_array, dt)
# d_array.append(droplet(radius=i*100e-6))
time.append(i*dt)
m_dot.append(mdot)
q_dot.append(qdot)
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
pass
else:
droplet.r = (droplet.m * 3.0 / 4.0 / np.pi /
droplet.rho)**(1.0 / 3.0)
mdot += qdot / droplet.hfg
pass
if droplet.m < 0:
d_array.remove(droplet)
pass
return mdot, qdot
d_array = []
d_array.append(droplet(radius=50e-6))
dt = 1e-6
time = []
m_dot = []
q_dot = []
r = []
m = []
Temperature = []
for i in range(1, 600):
# print('In iteration:' + str(i))
mdot, qdot = vaporize(500, d_array, dt)
# d_array.append(droplet(radius=i*100e-6))
time.append(i * dt)
m_dot.append(mdot)
def execute():
#==============================================================================
# set up the cantera gases and reactors
#==============================================================================
drop = droplet(50e-6, 'A2', 300, 1) #drop is defined only to use the drop properties
#environment air
gas_env = ct.Solution('a2.cti')
gas_env.TPX = 300, ct.one_atm, 'O2:29,N2:71'
gas_fuel = ct.Solution('a2.cti')
gas_fuel.TPX = drop.ABP, ct.one_atm, 'POSF10325:1' #gaseous fuel at average boiling temperature
gas_kernel = ct.Solution('a2.cti')
gas_kernel.TPX = 4000, ct.one_atm, 'O2:29,N2:71'
gas_kernel.equilibrate('HP')
res_air = ct.Reservoir(gas_env)
res_fuel = ct.Reservoir(gas_fuel)
kernel = ct.IdealGasConstPressureReactor(gas_kernel)
kernel.volume = 2.4e-8 #m^3
mfc1 = ct.MassFlowController(res_air, kernel) #connect air reservoir to kernel
mfc2 = ct.MassFlowController(res_fuel, kernel) #connect fuel reservoir to kernel
mfc1.set_mass_flow_rate(6e-5)
mfc2.set_mass_flow_rate(0)
w = ct.Wall(kernel, res_fuel)
w.set_heat_flux(0)
w.expansion_rate_coeff = 1e8
net = ct.ReactorNet({kernel})
net.atol = 1e-10 #absolute tolerance
net.rtol = 1e-10 #relative tolerance
#==============================================================================
# endtime, time steps, and data to be stored
#==============================================================================
dt = 1e-6 #change time step for advancing the reactor
endtime = 1000e-6
mdot_fuel = 1.98e-6 #this number should be calculated based on equivalence ratio, kg/s
droplets = []
T = []
time = []
m = []
m_dot = []
q_dot = []
droplet_count = []
X_fuel = []
X_O = []
X_CO2 = []
num_d = []
#==============================================================================
# advance reaction
#==============================================================================
print("Running simulation")
for i in range(1,int(endtime/dt)):
print (int(endtime/dt) - i)
#entrain droplets every 1 microsecond
droplets.extend(entrainer(400, 5.*mdot_fuel))
mdot, qdot = vaporize(gas_kernel.T, droplets, dt)
# print(gas_kernel.T, mdot, qdot, len(droplets))
# print(str(mdot) + str(qdot) + str(gas_kernel.T)+' '+str(len(droplets)))
mfc2.set_mass_flow_rate(mdot)
w.set_heat_flux(qdot) #heat required to heat up the droplets during that time step
net.advance(i*dt)
num_d.append(len(droplets))
#storing variables
T.append(gas_kernel.T)
time.append(net.time)
m.append(kernel.mass)
m_dot.append(mdot)
q_dot.append(qdot)
droplet_count.append(len(droplets))
if gas_kernel.X[0] < 0:
gas_kernel.X[0] = 0
X_fuel.append(gas_kernel.X[gas_kernel.species_index("POSF10325")])
X_O.append(gas_kernel.X[gas_kernel.species_index("O")])
X_CO2.append(gas_kernel.X[gas_kernel.species_index("CO2")])
#==============================================================================
# plotting important information
#==============================================================================
plt.plot([t*1e3 for t in time],T, linewidth=3)
plt.xlabel('time(ms)', FontSize=15)
plt.ylabel('Temperature (K)', FontSize=15)
plt.show()
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
ax1.plot([t*1e3 for t in time], X_fuel, color = 'red', linewidth = 3)
ax1.set_xlabel('time (ms)', FontSize=15)
ax1.set_ylabel('X_fuel', color='red', FontSize=15)
# ax2.plot([t*1e3 for t in time], X_O, color = 'green', linewidth = 3)
ax2.set_ylabel('X_CO2', color='green', FontSize=15)
ax2.plot([t*1e3 for t in time], X_CO2, color = 'blue', linewidth = 3)
plt.show()
fig, ax1 = plt.subplots()
ax2 = ax1.twinx()
ax1.plot([t*1e3 for t in time], m_dot, color = 'red', linewidth = 3)
ax1.set_xlabel('time (ms)', FontSize=15)
ax1.set_ylabel('m_dot', color='red', FontSize=15)
ax2.plot([t*1e3 for t in time], q_dot, color = 'green', linewidth = 3)
ax2.set_ylabel('q_dot', color='green', FontSize=15)
plt.show()
fig,ax1 = plt.subplots()
ax1.plot([t*1e3 for t in time], num_d, linewidth=3)
ax1.set_xlabel('time(ms)', FontSize=15)
ax1.set_ylabel('#droplets', FontSize=15)
plt.show()
import cantera as ct
import numpy as np
import matplotlib.pyplot as plt
from droplet import *
from entrainer import *
from vaporize import *
ct.suppress_thermo_warnings()
if __name__ == '__main__':
d_vec = [] # this vector is going to store all droplets
dt_vap = 1e-6 #time step to call vaporizer
dt_r = 1e-8 #time step to call reactor
drop = droplet(50e-6, 'A2', 300,
1) #drop is defined only to use the drop properties
end_time = 300e-6
#environment air
gas_env = ct.Solution('a2.cti')
gas_env.TPX = 300, ct.one_atm, 'O2:29,N2:71'
gas_fuel = ct.Solution('a2.cti')
gas_fuel.TPX = drop.ABP, ct.one_atm, 'POSF10325:1' #gaseous fuel at average boiling temperature
gas_kernel = ct.Solution('a2.cti')
gas_kernel.TPX = 4000, ct.one_atm, 'O2:29,N2:71'
gas_kernel.equilibrate('HP')
res_air = ct.Reservoir(gas_env)
res_fuel = ct.Reservoir(gas_fuel)
kernel = ct.IdealGasConstPressureReactor(gas_kernel)
kernel.volume = 2.4e-8 #m^3
Gr = L**3*rho**2*g*del_T*beta/nu**2
#Rayleigh # based on Grashof and Prandtl #'s
Ra = Gr*Pr
#Nusselt #, -- T.Yuge
try:
Nu = 2 + 0.43*Ra**0.25
except:
print('error occured at finding nusselt number')
#convective heat transfer coefficient
k = 91e-3 #thermal conductivity for air at ?1600K?
h = Nu*k/L
#establish the ordinary differential equation
A = 4.0*np.pi*droplet.r**2.0
V = 4.0/3.0*np.pi*droplet.r**3.0
dTdt = (h*A*(Tenv - droplet.T) - mdot*droplet.hfg)/(droplet.rho*V*droplet.cp)
return dTdt
r = float(input('droplet diameter(m):'))
endtime = float(input('endtime(s):'))
d = droplet(radius=r)
ts = np.linspace(0,endtime,100)
T = 300
Ts = odeint(dT_dt, T, ts, args=(d, 1600))
plt.plot(ts, Ts)
plt.xlim([0,0.0001])
plt.show()