def ex_S4(method, nGG=24):
import numpy as np
from cyparallel_planes import parallel_planes
#from parallel_planes import parallel_planes
from pyrad import pyrad_planck_mean as rad_planck_mean
from pyrad import pyrad_wsgg as rad_wsgg
from pyrad import pyrad_rcslw as rad_rcslw
################################################################################
#--------------------- parameters
P = 101325.0
L = 0.3
ntheta = 101
nx = 1001
Twall = 500.0
Tmax = 2500.0
H = 0.1
nGGa = nGG + 1
xco2 = 0.0
xco = 0.0
xh2o = 0.1
xch4 = 0.0
fvs = 0.0
#---------------------
xCO2 = np.full(nx, xco2, dtype=np.float64)
xCO = np.full(nx, xco, dtype=np.float64)
xH2O = np.full(nx, xh2o, dtype=np.float64)
xCH4 = np.full(nx, xch4, dtype=np.float64)
fvsoot = np.full(nx, fvs, dtype=np.float64)
x = np.zeros(nx)
T = np.full(nx, Twall, dtype=np.float64)
dx = L / (nx - 1)
x[0] = 0.0
Tavg = T[0]
for i in range(1, nx):
x[i] = x[i - 1] + dx
if x[i] <= L / 2 - H / 2 or x[i] >= L / 2 + H / 2:
T[i] = Twall
elif x[i] < L / 2:
T[i] = Twall + (Tmax -
Twall) / (L / 2 -
(L / 2 - H / 2)) * (x[i] -
(L / 2 - H / 2))
else:
T[i] = Tmax + (Twall - Tmax) / (
(L / 2 + H / 2) - L / 2) * (x[i] - L / 2)
Tavg += T[i]
Tavg /= nx
if method == 'rcslw':
#rad = rad_rcslw(nGG, P, Tmax, xh2o, xco2, xco, fvs) # CHANGE: use T=Tmax or T=Tavg for plot
rad = rad_rcslw(nGG, P, Tavg, xh2o, xco2, xco,
fvs) # CHANGE: use T=Tmax or T=Tavg for plot
elif method == 'wsgg':
rad = rad_wsgg()
elif method == 'planckmean':
rad = rad_planck_mean()
else:
raise ValueError('unknown radiation method')
#------------------- get q, Q
x, xQ, q, Q = parallel_planes(rad, L, ntheta, P, T, xH2O, xCO2, xCO, xCH4,
fvsoot)
print("# x (m), Q (kW/m3)")
for i in range(len(xQ)):
print(f'{xQ[i]:.5f} {Q[i]/1000:.5f}')
#print("# x (m), q (kW/m2)")
#for i in range(len(x)):
# print(f'{x[i]:.5f} {q[i]/1000:.5f}')
#-------------------------------------------------------------------------
print()
return xQ, Q
def ex_S5(method, nGG=24, use_Tmax=False):
import numpy as np
from cyparallel_planes import parallel_planes
#from parallel_planes import parallel_planes
from pyrad import pyrad_planck_mean as rad_planck_mean
from pyrad import pyrad_wsgg as rad_wsgg
from pyrad import pyrad_rcslw as rad_rcslw
################################################################################
#--------------------- parameters
P = 101325.0
L = 2.0
ntheta = 101
nx = 1001
T0 = 1500.0
TL = 500.0
nGGa = nGG + 1
TT = 1500
xco2 = 0.0
xco = 0.0
xh2o = 0.1
fvs = 0.0
#---------------------
xCO2 = np.full(nx, xco2, dtype=np.float64)
xCO = np.full(nx, xco, dtype=np.float64)
xH2O = np.full(nx, xh2o, dtype=np.float64)
xCH4 = np.full(nx, 0.0, dtype=np.float64)
fvsoot = np.full(nx, fvs, dtype=np.float64)
x = np.zeros(nx)
T = np.full(nx, T0, dtype=np.float64)
dx = L / (nx - 1)
x[0] = 0.0
Tavg = T[0]
for i in range(1, nx):
x[i] = x[i - 1] + dx
T[i] = 1000.0 + 500 * np.cos(np.pi * x[i] / L)
Tavg += T[i]
Tavg /= nx
if method == 'rcslw':
rad = rad_rcslw(nGG, P, TT if use_Tmax else Tavg, xh2o, xco2, xco,
fvs) # TT gives better results than Tavg
elif method == 'wsgg':
rad = rad_wsgg()
elif method == 'planckmean':
rad = rad_planck_mean()
else:
raise ValueError('unknown radiation method')
#------------------- get q, Q
x, xQ, q, Q = parallel_planes(rad, L, ntheta, P, T, xH2O, xCO2, xCO, xCH4,
fvsoot)
print("# x (m), Q (kW/m3)")
for i in range(len(xQ)):
print(f'{xQ[i]:.5f} {Q[i]/1000:.5f}')
#print("# x (m), q (kW/m2)")
#for i in range(len(x)):
# print(f'{x[i]:.5f} {q[i]/1000:.5f}')
#-------------------------------------------------------------------------
print()
return xQ, Q
#----------------- define parameters
T = 2000.0 # K
P = 101325.0 # atm
xH2O = 0.8 # xH2O=0.2 is roughly stoich. CH4/air products
xCO2 = 0.2 # xCO2=0.1 is roughly stoich. CH4/air products
xCO = 0.0
xCH4 = 0.0
fvsoot = 0.0
#----------------- create radiation objects
planckmean = rad_planck_mean()
wsgg = rad_wsgg()
rcslw = rad_rcslw(4, P, T, xH2O, xCO2, xCO, fvsoot)
#----------------- compute absorption coefficients and weights
kabs_pm, awts_pm = planckmean.get_k_a(T, P, xH2O, xCO2, xCO, xCH4, fvsoot)
kabs_wsgg, awts_wsgg = wsgg.get_k_a(T, P, xH2O, xCO2, xCO, xCH4, fvsoot)
kabs_rcslw, awts_rcslw = rcslw.get_k_a(T, P, xH2O, xCO2, xCO, xCH4, fvsoot)
#----------------- output results
print(f"---------------------------")
print(f"T (K) = {T:.3f}")
print(f"P (Pa) = {P:.3f}")
print(f"xH2O = {xH2O:.3f}")
print(f"xCO2 = {xCO2:.3f}")
print(f"xCO = {xCO:.3f}")
def ex_B3(method, nGG=4):
import numpy as np
from cyparallel_planes import parallel_planes
#from parallel_planes import parallel_planes
from pyrad import pyrad_planck_mean as rad_planck_mean
from pyrad import pyrad_wsgg as rad_wsgg
from pyrad import pyrad_rcslw as rad_rcslw
################################################################################
#--------------------- parameters
nGGa = nGG + 1
P = 101325.0
L = 1.0
ntheta = 101
nx = 1001
Twall = 400.0
xco2 = 0.0
xco = 0.0
xh2o = 0.0
xch4 = 0.0
fvs = 0.0
#---------------------
xCO2 = np.full(nx, xco2, dtype=np.float64)
xCO = np.full(nx, xco, dtype=np.float64)
xH2O = np.full(nx, xh2o, dtype=np.float64)
xCH4 = np.full(nx, xch4, dtype=np.float64)
fvsoot = np.full(nx, fvs, dtype=np.float64)
x = np.zeros(nx)
T = np.full(nx, Twall, dtype=np.float64)
x = np.linspace(0, L, nx)
for i in range(nx):
T[i] = 400.0 + 1400.0 * np.sin(np.pi * x[i] / L)**2
xH2O[i] = 1E-4 + (1.0 - 1E-4) * np.sin(np.pi * x[i] / L)**2
xCO2[i] = 1.0 - xH2O[i]
xH2O_avg = np.average(xH2O)
xCO2_avg = 1.0 - xH2O_avg
T_avg = np.average(T)
if method == 'rcslw':
rad = rad_rcslw(nGG, P, T_avg, xH2O_avg, xCO2_avg, xco, fvs)
elif method == 'wsgg':
rad = rad_wsgg()
elif method == 'planckmean':
rad = rad_planck_mean()
else:
raise ValueError('unknown radiation method')
#------------------- get q, Q
x, xQ, q, Q = parallel_planes(rad, L, ntheta, P, T, xH2O, xCO2, xCO, xCH4,
fvsoot)
print("# x (m), Q (kW/m3)")
for i in range(len(xQ)):
print(f'{xQ[i]:.5f} {Q[i]/1000:.5f}')
#print("# x (m), q (kW/m2)")
#for i in range(len(x)):
# print(f'{x[i]:.5f} {q[i]/1000:.5f}')
#-------------------------------------------------------------------------
print()
return x, xQ, q, Q
def ex_S2(method, nGG=24):
import numpy as np
from cyparallel_planes import parallel_planes
#from parallel_planes import parallel_planes
from pyrad import pyrad_planck_mean as rad_planck_mean
from pyrad import pyrad_wsgg as rad_wsgg
from pyrad import pyrad_rcslw as rad_rcslw
sigma = 5.670367E-8 # Stephan-Boltzmann constant
################################################################################
#--------------------- parameters
TT = 1000.0
P = 101325.0
xco2_1 = 0.4
xco2_2 = 0.1
Lhot = 0.5
ntheta = 101
nxh = 1001 # for Lcold=0 changes below to keep dx roughly constant
Lcold = np.array([0, 0.01, 0.025, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.75, 1.0, 1.5, 2.0])
nGGa = nGG+1
xco = 0.0; xh2o=0.0; xch4=0.0; fvs = 0.0
#---------------------
print("# Lcold (m), q(L)/σT^4")
qsigT4 = np.empty(len(Lcold))
for iLcold in range(len(Lcold)):
L = Lcold[iLcold] + Lhot
xco2_avg = (xco2_1*0.5+xco2_2*Lcold[iLcold])/L
nx = int(nxh*L/Lhot)
xCO2 = np.full(nx, xco2_1, dtype=np.float64)
xCO = np.full(nx, xco, dtype=np.float64)
xH2O = np.full(nx, xh2o, dtype=np.float64)
xCH4 = np.full(nx, xch4, dtype=np.float64)
fvsoot = np.full(nx, fvs, dtype=np.float64)
x = np.zeros(nx)
dx = L/(nx-1)
T = np.full(nx, TT, dtype=np.float64)
for i in range(1,nx): # mimic c++; pythonic gives different grid/T due to roundoff
x[i] = x[i-1] + dx
xCO2[i] = xco2_1 if x[i] <= Lhot else xco2_2
if method=='rcslw':
rad = rad_rcslw(nGG, P, TT, xh2o, xco2_avg, xco, fvs)
elif method=='wsgg':
rad = rad_wsgg()
elif method=='planckmean':
rad = rad_planck_mean()
else:
raise ValueError('unknown radiation method')
#--------------------- get q, Q
x, xQ, q, Q = parallel_planes(rad, L, ntheta, P, T, xH2O, xCO2, xCO, xCH4, fvsoot, True)
#-------------------------------------------------------------------------
qsigT4[iLcold] = q[nx-1]/sigma/TT**4
print(f'{Lcold[iLcold]:10.3f} {qsigT4[iLcold]:15.5f}')
print()
return Lcold, qsigT4
def ex_S3(method, nGG=24):
import numpy as np
from cyparallel_planes import parallel_planes
#from parallel_planes import parallel_planes
from pyrad import pyrad_planck_mean as rad_planck_mean
from pyrad import pyrad_wsgg as rad_wsgg
from pyrad import pyrad_rcslw as rad_rcslw
################################################################################
#--------------------- parameters
P = 101325.0
L = 1.0
ntheta = 101
nx = 1001
Twall = 800.0
nGGa = nGG + 1
xco2 = 0.0
xco = 0.0
xh2o = 0.12
xch4 = 0.0
fvs = 0.0
#---------------------
xCO2 = np.full(nx, xco2, dtype=np.float64)
xCO = np.full(nx, xco, dtype=np.float64)
xH2O = np.full(nx, xh2o, dtype=np.float64)
xCH4 = np.full(nx, xch4, dtype=np.float64)
fvsoot = np.full(nx, fvs, dtype=np.float64)
x = np.zeros(nx)
T = np.full(nx, Twall, dtype=np.float64)
dx = L / (nx - 1)
x[0] = 0.0
Tavg = T[0]
xH2O_avg = 0.0
for i in range(1, nx):
x[i] = x[i - 1] + dx
T[i] = 4000 * x[i] * (L - x[i]) / L / L + Twall
xH2O[i] = 0.8 * x[i] * (L - x[i]) / L / L + xh2o
Tavg += T[i]
xH2O_avg += xH2O[i]
Tavg /= nx
xH2O_avg /= nx
if method == 'rcslw':
rad = rad_rcslw(nGG, P, Tavg, xH2O_avg, xco2, xco, fvs)
elif method == 'wsgg':
rad = rad_wsgg()
elif method == 'planckmean':
rad = rad_planck_mean()
else:
raise ValueError('unknown radiation method')
#------------------- get q, Q
x, xQ, q, Q = parallel_planes(rad, L, ntheta, P, T, xH2O, xCO2, xCO, xCH4,
fvsoot)
print("# x (m), Q (kW/m3)")
for i in range(len(xQ)):
print(f'{xQ[i]:.5f} {Q[i]/1000:.5f}')
#print("# x (m), q (kW/m2)")
#for i in range(len(x)):
# print(f'{x[i]:.5f} {q[i]/1000:.5f}')
#-------------------------------------------------------------------------
print()
return xQ, Q