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Open_CSPERB_plots.py
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Open_CSPERB_plots.py
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import matplotlib.pyplot as plt
import numpy as N
import pickle
from sys import path
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib import colors
from scipy.interpolate import interp2d
def flux_limits(mf, Ts, flux_limits_file):
# Net flux limits in W.m2 for Ts in K and for mass flows of 1 to 5 kg/s in OD 60.3 mm 740H pipes with 1.2 mm wall thickness.
data = N.loadtxt(flux_limits_file, delimiter=',')
mfs = data[0,1:]
Tdata = data[1:,0]
fluxlimdata = data[1:,1:]
fit = interp2d(mfs, Tdata, fluxlimdata)
flux_lim = fit(mf, Ts)
return flux_lim[:,0]
def tower_receiver_plots(files, efficiency=True, maps_3D=True, flux_map=True, flow_paths=True, saveloc=None, billboard=False, flux_limits_file=None):
print "plotting"
fileo = open(files,'r')
data = pickle.load(fileo)
fileo.close()
if saveloc == None:
saveloc = files
height = data['height']
n_banks = data['n_banks']
n_elems = data['n_elems']
n_tubes = data['n_tubes']
D_tubes_o = data['D_tubes_o']
D_tubes_i = data['D_tubes_i']
eff_abs = data['eff_abs']
abs_t = data['abs_t']
eff_ems = data['eff_ems']
ems_t = data['ems_t']
k_t = data['k_t']
if billboard:
width = data['width']
ahr = data['wh']
ahr_map = data['wh_map']
else:
radius = data['radius']
ahr = data['ahr']
ahr_map = data['ahr_map']
fp = data['fp']
areas = data['areas']
areas_fp = data['areas_fp']
HC = data['HC']
T_in = data['T_in']
T_out = data['T_out']
h_conv_ext = data['h_conv_ext']
h = data['h']
m = data['m']
flux_in = data['flux_in']
q_net = data['q_net']
q_rad = data['q_rad']
q_ref = data['q_ref']
q_conv = data['q_conv_ext']
T_amb = data['T_amb']
T_HC = data['T_HC']
T_w_int = data['T_w_int']
T_ext = data['T_ext']
h_conv_int = data['h_conv_int']
V = data['V']
fluxmap = data['fluxmap']
HC = data['HC']
n_tubes = data['n_tubes']
Dp = data['Dp']
pipe_lengths = data['pipe_lengths']
#maxheight = N.amax(ahr[:,1,:])
#maxrad = N.amax(ahr[:,2,:])
plt.rc('font', size=8)
if efficiency:
#print 'Radius:', radius,' m'
print 'Height:', height,' m'
print 'Thermal power output:', N.sum(q_net)/1e6, 'MWht'
print ' '
print 'eta_abs:', (N.sum(fluxmap*areas[ahr_map])-N.sum(q_ref))/N.sum(fluxmap*areas[ahr_map])
print 'eta_th:', N.sum(q_net)/(N.sum(fluxmap*areas[ahr_map])-N.sum(q_ref))
print 'eta_th_abs:', N.sum(q_net)/N.sum(fluxmap*areas[ahr_map])
print ' '
print 'q_in:', N.sum(fluxmap*areas[ahr_map])/1e6
print 'q_refl:', N.sum(q_ref)/1e6
print 'q_emi:', N.sum(q_rad)/1e6
print 'q_conv:', N.sum(q_conv)/1e6
print 'q_net:', N.sum(q_net)/1e6
print 'peak_absorbed_flux:', N.amax(fluxmap)*eff_abs/1e3
print 'wall_t_max:', N.amax(T_ext)
print 'peak_ratio of allowable:',
for f in range(len(fp)):
mfp = m[f]*N.ones(len(n_tubes[fp[f]]))
nts = N.array(n_tubes[fp[f]])
flux_lims = flux_limits(mfp/nts, T_HC[f], flux_limits_file)/1e3
flux_fp = q_net[fp[f]]/areas[fp[f]]/1e3
flux_fp = N.hstack((flux_fp[0], flux_fp))
print N.around(N.amax(N.hstack(flux_fp/flux_lims)), decimals=3),
print ' '
print ' '
print 'Reflective loss:', N.sum(q_ref)/N.sum(fluxmap*areas[ahr_map])
print 'Convective loss:', N.sum(q_conv)/N.sum(fluxmap*areas[ahr_map])
print 'Radiative loss:', N.sum(q_rad)/N.sum(fluxmap*areas[ahr_map])
print 'Mass flows: ', N.sum(m), m, 'kg/s'
print 'Mass flows pipes: ', m/n_tubes[0], 'kg/s'
p_w = []
for f in xrange(len(fp)):
print 'Flow path '+str(f+1)+' :'
vels = m[f]/n_tubes[fp[f]]/(N.pi*(D_tubes_i/2.)**2.*HC.rho(T_HC[f][1:]))
print 'Velocities: ', N.amin(vels), N.amax(vels), 'm/s'
print 'Pressure drop: ', N.add.accumulate(Dp[fp[f]])[-1]/1e5, 'bar'
p_w.append(m[f]*N.sum(Dp[fp[f]]/(HC.rho(T_HC[f][1:])+HC.rho(T_HC[f][:-1]))/2.))
#print 'Heat transfer coefficient (kW/m2/K): ', h_conv_int[fp[f]]/1e3
print 'Pumping work: ', N.sum(p_w), p_w, 'W'
print 'Work produced: ', N.sum(q_net)*(1.-T_amb/T_out), 'W'
print 'Second law efficiency :', (N.sum(q_net)*(1.-T_amb/T_out)-N.sum(p_w))/N.sum(fluxmap*areas[ahr_map])
print 'Number of tubes per bank: ', n_tubes[0]
print "Qcon:", N.sum(fluxmap*areas[ahr_map])
print 'Tin:',T_in,' Tout:',T_out
print 'Peak fraction of allowable: ',
for f in range(len(fp)):
mfp = m[f]*N.ones(len(n_tubes[fp[f]]))
nts = N.array(n_tubes[fp[f]])
flux_lims = flux_limits(mfp/nts, T_HC[f], flux_limits_file)/1e3
flux_fp = q_net[fp[f]]/areas[fp[f]]/1e3
flux_fp = N.hstack((flux_fp[0], flux_fp))
print N.around(N.amax(N.hstack(flux_fp/flux_lims)), decimals=3),
print ' '
if maps_3D:
fig = plt.figure(figsize=(6,3.4), dpi=1000)
plt.subplots_adjust(left=0., bottom=0.06, top =1.02, right=1.01, wspace=0)
angres_per_bank = 1
ax = fig.add_subplot(1,2,1, projection='3d', aspect=1.3)
flux = q_net/areas/1e6 #N.hstack(fluxmap)[N.hstack(ahr_map)]/1e6
# Set-up the colormap:
cNorm = colors.Normalize(vmin=0., vmax=1.2)
mp = cm.ScalarMappable(norm=cNorm, cmap=cm.plasma)
for i in xrange(len(flux)):
ts = ahr[i,0,:]
hs = ahr[i,1,:]
rs = ahr[i,2,0]
dt = (ts[1]-ts[0])/float(angres_per_bank)
for j in xrange(angres_per_bank):
thetas = [ts[0]+float(j)*dt, ts[0]+(j+1.)*dt]
x = rs*N.cos(thetas)
y = rs*N.sin(thetas)
z0 = N.ones(2)*hs[0]
z1 = N.ones(2)*hs[1]
x = N.vstack((x, x))
y = N.vstack((y, y))
z = N.vstack((z0, z1))
face = mp.to_rgba(flux[i])
surf = ax.plot_surface(x, y, z, shade=False, antialiased=False, color=face, edgecolor=face, linewidth=0.5, alpha=1)
rcard = N.amax(radius)+0.5
zcard = N.amax(height)+0.5
ax.scatter(xs=[0,rcard,0,-rcard], ys=[rcard,0,-rcard,0], zs=[zcard,zcard,zcard,zcard], s=150, c=N.tile([1,1,1,0.5],(4,1)), lw=0, zorder=9999.)
ax.text(-rcard,0,zcard, s='W', zorder=10000., ha='center', va='center')
ax.text(0,rcard,zcard, s='N', zorder=10000., ha='center', va='center')
ax.text(rcard,0,zcard, s='E', zorder=10000., ha='center', va='center')
ax.text(0,-rcard,zcard, s='S', zorder=10000., ha='center', va='center')
ax.set_xlim(-radius, radius)
ax.set_ylim(-radius, radius)
ax.set_zlim(0, height)
ax.view_init(elev=25, azim=95)
mp = cm.ScalarMappable(cmap=cm.plasma)
mp.set_array(N.hstack([N.amin(flux),N.amax(flux)]))
cbar = plt.colorbar(mp, orientation='horizontal', pad=0.1, shrink=0.8)
cbar.set_label(r'$\dot{q}^{\prime \prime}_\mathrm{abs}$ [MW.m$^{-2}$]')
plt.figtext(0.25, 0.01, '(a)')
plt.savefig(open(saveloc+'_3D_maps.png','w'), dpi=400)
ax = fig.add_subplot(1,2,2, projection='3d', aspect=1.3)
flux = T_ext[N.hstack(ahr_map)]
# Set-up the colormap:
cNorm = colors.Normalize(vmin=N.amin(flux), vmax=N.amax(flux))
mp = cm.ScalarMappable(norm=cNorm, cmap=cm.hot)
for i in xrange(len(flux)):
ts = ahr[i,0,:]
hs = ahr[i,1,:]
rs = ahr[i,2,0]
for j in xrange(angres_per_bank):
thetas = [ts[0]+float(j)/angres_per_bank*(ts[1]-ts[0]), ts[0]+(j+1.)/angres_per_bank*(ts[1]-ts[0])]
x = rs*N.cos(thetas)
y = rs*N.sin(thetas)
z0 = N.ones(2)*hs[0]
z1 = N.ones(2)*hs[1]
x = N.vstack((x, x))
y = N.vstack((y, y))
z = N.vstack((z0, z1))
face = mp.to_rgba(T_ext[i])
surf = ax.plot_surface(x, y, z, shade=False, antialiased=False, color=face, edgecolor=face, linewidth=0.5, alpha=1)
ax.scatter(xs=[0,rcard,0,-rcard], ys=[rcard,0,-rcard,0], zs=[zcard,zcard,zcard,zcard], s=150, c=N.tile([1,1,1,0.5],(4,1)), lw=0, zorder=9999.)
ax.text(-rcard,0,zcard, s='W', zorder=10000., ha='center', va='center')
ax.text(0,rcard,zcard, s='N', zorder=10000., ha='center', va='center')
ax.text(rcard,0,zcard, s='E', zorder=10000., ha='center', va='center')
ax.text(0,-rcard,zcard, s='S', zorder=10000., ha='center', va='center')
ax.set_xlim(-radius, radius)
ax.set_ylim(-radius, radius)
ax.set_zlim(0, height)
ax.view_init(elev=25, azim=95)
mp = cm.ScalarMappable(cmap=cm.hot)
mp.set_array(N.hstack([N.amin(T_ext-273.15),N.amax(T_ext-273.15)]))
cbar = plt.colorbar(mp, orientation='horizontal', pad=0.1, shrink=0.8)
cbar.set_label(r'$T_\mathrm{abs}$ [$^{\circ}$C]')
plt.figtext(0.75, 0.01, '(b)')
plt.savefig(open(saveloc+'_3D_maps.png','w'), dpi=400)
plt.close(fig)
if flux_map:
fig = plt.figure(figsize=(3,3.4), dpi=1000)
plt.subplots_adjust(left=0., bottom=0.06, top =1.02, right=1.01, wspace=0)
angres_per_bank = 1
ax = fig.add_subplot(1,1,1, projection='3d', aspect=1.3)
banks = N.shape(fluxmap)[1]
fluxmap = N.concatenate((fluxmap[:,banks/4:], fluxmap[:,:banks/4]), axis=1) # correction to start from east
flux = N.hstack(fluxmap)/1e6
# Set-up the colormap:
if isinstance(flux_map,list) and len(flux_map)==2:
vmin, vmax = flux_map
else:
vmin=0.
vmax=1.2
cNorm = colors.Normalize(vmin, vmax)
mp = cm.ScalarMappable(norm=cNorm, cmap=cm.viridis)
for i in xrange(len(flux)):
ts = ahr[i,0,:]
hs = ahr[i,1,:]
rs = ahr[i,2,0]
dt = (ts[1]-ts[0])/float(angres_per_bank)
for j in xrange(angres_per_bank):
thetas = [ts[0]+float(j)*dt, ts[0]+(j+1.)*dt]
x = rs*N.cos(thetas)
y = rs*N.sin(thetas)
z0 = N.ones(2)*hs[0]
z1 = N.ones(2)*hs[1]
x = N.vstack((x, x))
y = N.vstack((y, y))
z = N.vstack((z0, z1))
face = mp.to_rgba(flux[i])
surf = ax.plot_surface(x, y, z, shade=False, antialiased=False, color=face, edgecolor=face, linewidth=0.5, alpha=1)
rcard = N.amax(radius)+0.5
zcard = N.amax(height)+0.5
ax.scatter(xs=[0,rcard,0,-rcard], ys=[rcard,0,-rcard,0], zs=[zcard,zcard,zcard,zcard], s=150, c=N.tile([1,1,1,0.5],(4,1)), lw=0, zorder=9999.)
ax.text(-rcard,0,zcard, s='W', zorder=10000., ha='center', va='center')
ax.text(0,rcard,zcard, s='N', zorder=10000., ha='center', va='center')
ax.text(rcard,0,zcard, s='E', zorder=10000., ha='center', va='center')
ax.text(0,-rcard,zcard, s='S', zorder=10000., ha='center', va='center')
ax.set_xlim(-radius, radius)
ax.set_ylim(-radius, radius)
ax.set_zlim(0, height)
ax.view_init(elev=25, azim=95)
mp = cm.ScalarMappable(cmap=cm.viridis)
mp.set_array(N.hstack([vmin, vmax]))
cbar = plt.colorbar(mp, orientation='horizontal', pad=0.1, shrink=0.8)
cbar.set_label(r'$\dot{q}^{\prime \prime}_\mathrm{in}$ [MW.m$^{-2}$]')
plt.savefig(open(saveloc+'_3D_flux.png','w'), dpi=400)
fig = plt.figure(figsize=(3,3.4), dpi=1000)
plt.subplots_adjust(left=0., bottom=0.06, top =1.02, right=1.01, wspace=0)
angres_per_bank = 1
ax = fig.add_subplot(1,1,1, projection='3d', aspect=1.3)
banks = N.shape(fluxmap)[1]
fluxmap = N.concatenate((fluxmap[:,banks/4:], fluxmap[:,:banks/4]), axis=1) # correction to start from east
flux = T_ext[N.hstack(ahr_map)]-273.15
# Set-up the colormap:
if isinstance(flux_map,list) and len(flux_map)==2:
vmin, vmax = flux_map
else:
vmin=520.
vmax=780.
cNorm = colors.Normalize(vmin, vmax)
mp = cm.ScalarMappable(norm=cNorm, cmap=cm.hot)
for i in xrange(len(flux)):
ts = ahr[i,0,:]
hs = ahr[i,1,:]
rs = ahr[i,2,0]
dt = (ts[1]-ts[0])/float(angres_per_bank)
for j in xrange(angres_per_bank):
thetas = [ts[0]+float(j)*dt, ts[0]+(j+1.)*dt]
x = rs*N.cos(thetas)
y = rs*N.sin(thetas)
z0 = N.ones(2)*hs[0]
z1 = N.ones(2)*hs[1]
x = N.vstack((x, x))
y = N.vstack((y, y))
z = N.vstack((z0, z1))
face = mp.to_rgba(flux[i])
surf = ax.plot_surface(x, y, z, shade=False, antialiased=False, color=face, edgecolor=face, linewidth=0.5, alpha=1)
rcard = N.amax(radius)+0.5
zcard = N.amax(height)+0.5
ax.scatter(xs=[0,rcard,0,-rcard], ys=[rcard,0,-rcard,0], zs=[zcard,zcard,zcard,zcard], s=150, c=N.tile([1,1,1,0.5],(4,1)), lw=0, zorder=9999.)
ax.text(-rcard,0,zcard, s='W', zorder=10000., ha='center', va='center')
ax.text(0,rcard,zcard, s='N', zorder=10000., ha='center', va='center')
ax.text(rcard,0,zcard, s='E', zorder=10000., ha='center', va='center')
ax.text(0,-rcard,zcard, s='S', zorder=10000., ha='center', va='center')
ax.set_xlim(-radius, radius)
ax.set_ylim(-radius, radius)
ax.set_zlim(0, height)
ax.view_init(elev=25, azim=95)
mp = cm.ScalarMappable(cmap=cm.hot)
mp.set_array(N.hstack([vmin, vmax]))
cbar = plt.colorbar(mp, orientation='horizontal', pad=0.1, shrink=0.8)
cbar.set_label(r'${T_\mathrm{w,ext}}$ [$^{\circ}$C]')
plt.savefig(open(saveloc+'_3D_T.png','w'), dpi=400)
fig = plt.figure(figsize=(3,3.4), dpi=1000)
plt.subplots_adjust(left=0., bottom=0.06, top =1.02, right=1.01, wspace=0)
angres_per_bank = 1
ax = fig.add_subplot(1,1,1, projection='3d', aspect=1.3)
banks = N.shape(fluxmap)[1]
fluxmap = N.concatenate((fluxmap[:,banks/4:], fluxmap[:,:banks/4]), axis=1) # correction to start from east
flux = q_net/areas/1e6
# Set-up the colormap:
if isinstance(flux_map,list) and len(flux_map)==2:
vmin, vmax = flux_map
else:
vmin=0.
vmax=1.2
cNorm = colors.Normalize(vmin, vmax)
mp = cm.ScalarMappable(norm=cNorm, cmap=cm.plasma)
for i in xrange(len(flux)):
ts = ahr[i,0,:]
hs = ahr[i,1,:]
rs = ahr[i,2,0]
dt = (ts[1]-ts[0])/float(angres_per_bank)
for j in xrange(angres_per_bank):
thetas = [ts[0]+float(j)*dt, ts[0]+(j+1.)*dt]
x = rs*N.cos(thetas)
y = rs*N.sin(thetas)
z0 = N.ones(2)*hs[0]
z1 = N.ones(2)*hs[1]
x = N.vstack((x, x))
y = N.vstack((y, y))
z = N.vstack((z0, z1))
face = mp.to_rgba(flux[i])
surf = ax.plot_surface(x, y, z, shade=False, antialiased=False, color=face, edgecolor=face, linewidth=0.5, alpha=1)
rcard = N.amax(radius)+0.5
zcard = N.amax(height)+0.5
ax.scatter(xs=[0,rcard,0,-rcard], ys=[rcard,0,-rcard,0], zs=[zcard,zcard,zcard,zcard], s=150, c=N.tile([1,1,1,0.5],(4,1)), lw=0, zorder=9999.)
ax.text(-rcard,0,zcard, s='W', zorder=10000., ha='center', va='center')
ax.text(0,rcard,zcard, s='N', zorder=10000., ha='center', va='center')
ax.text(rcard,0,zcard, s='E', zorder=10000., ha='center', va='center')
ax.text(0,-rcard,zcard, s='S', zorder=10000., ha='center', va='center')
ax.set_xlim(-radius, radius)
ax.set_ylim(-radius, radius)
ax.set_zlim(0, height)
ax.view_init(elev=25, azim=95)
mp = cm.ScalarMappable(cmap=cm.plasma)
mp.set_array(N.hstack([vmin,vmax]))
cbar = plt.colorbar(mp, orientation='horizontal', pad=0.1, shrink=0.8)
cbar.set_label(r'$\dot{q}^{\prime \prime}_\mathrm{abs}$ [MW.m$^{-2}$]')
plt.savefig(open(saveloc+'_3D_Q-net.png','w'), dpi=400)
if flow_paths:
fig = plt.figure(figsize=(4,2.+(len(fp)-1)*1.), dpi=1000)
bot = 0.13
top = 0.87
if len(fp)==1:
bot=0.18
top=0.82
plt.subplots_adjust(left=0.15, bottom=bot, right=0.95, top = top)
for f in xrange(len(fp)):
plt.subplot(len(fp),1,f+1)
if len(fp)>1:
plt.text(x=1, y=660, s='Flow path %s'%str(f+1), va='top')
bank_lengths = pipe_lengths[f]
bank_lengths_2 = (bank_lengths[1:]+bank_lengths[:-1])/2.
#plt.plot(bank_lengths_2, T_ext[fp[f]]-273.15, label=r'T${_\mathrm{abs}}$', color='0')
#plt.plot(bank_lengths_2, T_w_int[fp[f]]-273.15, label=r'T${_\mathrm{wall,int}}$', color='0.4')
plt.plot(bank_lengths, T_HC[f]-273.15, label=r'T${_\mathrm{HC}}$', color='0.6')
plt.xlim(xmax=bank_lengths[-1])
plt.ylabel('T [$^{\circ}$C]')
plt.xlabel('Flow path length [m]')
plt.subplot(len(fp),1,1)
plt.legend(loc=3,ncol=3, borderaxespad=0, bbox_to_anchor=(0.,1.05))
plt.savefig(open(saveloc+'_Temp_fp.png','w'), dpi=400)
plt.close(fig)
fig = plt.figure(figsize=(4,2.+(len(fp)-1)*1.1), dpi=1000)
plt.subplots_adjust(left=0.15, bottom=bot, right=0.95, top = top)
for f in xrange(len(fp)):
plt.subplot(len(fp),1,f+1)
if len(fp)>1:
plt.text(x=bank_lengths[-5], y=980, s='Flow path %s'%str(f+1), ha='right')
bank_lengths = pipe_lengths[f]
bank_lengths_2 = (bank_lengths[1:]+bank_lengths[:-1])/2.
plt.plot(bank_lengths_2, flux_in[f]/1e3, label=r'${\dot{q}_\mathrm{in}^{\prime \prime}}$', color='0')
plt.plot(bank_lengths_2, q_net[fp[f]]/areas[fp[f]]/1e3, label=r'${\dot{q}^{\prime \prime}_\mathrm{abs}}$', color='0.6')
flux_lims = flux_limits(N.ones(len(fp[f]))/n_tubes[fp[f]]*m[f], T_HC[f], flux_limits_file)/1e3
print N.amax(flux_in[f]/1e3)
plt.plot(bank_lengths, flux_lims, color='r')
plt.yticks(N.arange(-200,1600, 200))
plt.grid(1, which='both')
plt.ylabel('Flux [kW.m$^{-2}$]')
if f==0:
plt.legend(loc=3,ncol=3, borderaxespad=0, bbox_to_anchor=(0.,1.05))
plt.xlabel('Flow path length [m]')
plt.savefig(open(saveloc+'_flux_fp.png','w'), dpi=400)
plt.close(fig)
fig = plt.figure(figsize=(6,2.+(len(fp)-1)*1.1), dpi=1000)
plt.subplots_adjust(left=0.10, bottom=bot, right=0.95, top = top)
for f in xrange(len(fp)):
plt.subplot(len(fp),1,f+1)
if len(fp)>1:
plt.text(x=1, y=-5, s='Flow path %s'%str(f+1), va='bottom')
bank_lengths = pipe_lengths[f]
bank_lengths_2 = (bank_lengths[1:]+bank_lengths[:-1])/2.
plt.plot(bank_lengths_2, -q_ref[fp[f]]/areas[fp[f]]/1e3, label=r'${\dot{q}^{\prime \prime}_\mathrm{ref}}$', color='0.6')
plt.plot(bank_lengths_2, -q_conv[fp[f]]/areas[fp[f]]/1e3, label=r'${\dot{q}^{\prime \prime}_\mathrm{conv}}$', color='0.4')
plt.plot(bank_lengths_2, -q_rad[fp[f]]/areas[fp[f]]/1e3, label=r'${\dot{q}^{\prime \prime}_\mathrm{rad}}$', color='0')
#plt.hlines(y=0., xmin=0., xmax=N.amax(bank_lengths_2), lw=0.5)
plt.hlines(y=0., xmin=0., xmax=N.amax(bank_lengths_2), lw=0.5)
plt.ylabel('Flux [kW.m$^{-2}$]')
if f==0:
plt.legend(loc=3,ncol=3, borderaxespad=0, bbox_to_anchor=(0.,1.05))
plt.xlabel('Flow path length [m]')
plt.savefig(open(saveloc+'_losses_fp.png','w'), dpi=400)
plt.close(fig)
fig = plt.figure(figsize=(6,2.+(len(fp)-1)*1.1), dpi=1000)
plt.subplots_adjust(left=0.10, bottom=bot, right=0.90, top = 0.95)
for f in xrange(len(fp)):
plt.subplot(len(fp),1,f+1)
bank_lengths = pipe_lengths[f]
bank_lengths_2 = (bank_lengths[1:]+bank_lengths[:-1])/2.
plt.plot(bank_lengths_2, V[fp[f]], color='0.5')
plt.annotate("", xy=(0, V[fp[f]][len(fp[f])/2]), xytext=(bank_lengths_2[len(fp[f])/2], V[fp[f]][len(fp[f])/2]), arrowprops=dict(arrowstyle="->", color='0.5'))
#plt.arrow(x=bank_lengths_2[100], y=V[fp[f]][100], dx=-bank_lengths_2[100], dy=0, color='0.5', length_includes_head=True, lw=0.5)
plt.ylabel('HC velocity [m.s$^{-1}$]')
plt.xlabel('Flow path length [m]')
plt.twinx()
Dploc = -N.add.accumulate(Dp[fp[f]])/1e5
if len(fp)>1:
plt.text(x=18, y=Dploc[20], s='Flow path %s'%str(f+1), va='top')
plt.plot(bank_lengths_2, Dploc, color='0')
plt.annotate("", xy=(bank_lengths_2[-1], Dploc[-len(fp[f])/2]), xytext=(bank_lengths_2[-len(fp[f])/2], Dploc[-len(fp[f])/2]), arrowprops=dict(arrowstyle="->"), color='0')
#plt.arrow(x=bank_lengths_2[-100], y=Dploc[-100], dx=bank_lengths_2[-1]-bank_lengths_2[-100], dy=0, color='00', length_includes_head=True, lw=0.5)
plt.ylabel('Pressure drop [bar]', rotation=-90, va='bottom')
#plt.legend(loc=1)
plt.xlabel('Flow path length [m]')
plt.savefig(open(saveloc+'_p_drops.png','w'), dpi=400)
plt.close(fig)
fig = plt.figure(figsize=(4,2.+(len(fp)-1)*1.1), dpi=1000)
plt.subplots_adjust(left=0.15, bottom=bot, right=0.95, top = top)
for f in xrange(len(fp)):
plt.subplot(len(fp),1,f+1)
if len(fp)>1:
plt.text(x=1, y=-5, s='Flow path %s'%str(f+1), va='bottom')
bank_lengths = pipe_lengths[f]
bank_lengths_2 = (bank_lengths[1:]+bank_lengths[:-1])/2.
plt.plot(bank_lengths_2, h_conv_int[fp[f]], color='k', lw=1)
#plt.hlines(y=0., xmin=0., xmax=N.amax(bank_lengths_2), lw=0.5)
plt.ylabel('h [W.m$^{-2}$.K$^{-1}$]')
if f==0:
plt.legend(loc=3,ncol=3, borderaxespad=0, bbox_to_anchor=(0.,1.05))
plt.xlabel('Flow path length [m]')
plt.savefig(open(saveloc+'_h_int.png','w'), dpi=400)
plt.close(fig)
def flow_path_plot(files='/home/charles/Documents/Boulot/These/Sodium receiver_CMI/ref_case_result_1', fps=[0], saveloc=None, flux_limits_file=None):
import matplotlib.gridspec as gridspec
print "plotting"
fileo = open(files,'r')
data = pickle.load(fileo)
fileo.close()
if saveloc == None:
saveloc = files
ahr = data['ahr']
radius = data['radius']
height = data['height']
n_banks = data['n_banks']
n_elems = data['n_elems']
n_tubes = data['n_tubes']
D_tubes_o = data['D_tubes_o']
D_tubes_i = data['D_tubes_i']
eff_abs = data['eff_abs']
abs_t = data['abs_t']
eff_ems = data['eff_ems']
ems_t = data['ems_t']
k_t = data['k_t']
ahr_map = data['ahr_map']
fp = data['fp']
areas = data['areas']
areas_fp = data['areas_fp']
HC = data['HC']
T_in = data['T_in']
T_out = data['T_out']
h_conv_ext = data['h_conv_ext']
h = data['h']
m = data['m']
flux_in = data['flux_in']
q_net = data['q_net']
q_rad = data['q_rad']
q_ref = data['q_ref']
q_conv = data['q_conv_ext']
T_amb = data['T_amb']
T_HC = data['T_HC']
T_w_int = data['T_w_int']
T_ext = data['T_ext']
h_conv_int = data['h_conv_int']
V = data['V']
fluxmap = data['fluxmap']
HC = data['HC']
n_tubes = data['n_tubes']
Dp = data['Dp']
pipe_lengths = data['pipe_lengths']
maxheight = N.amax(ahr[:,1,:])
maxrad = N.amax(ahr[:,2,:])
plt.rc('font', size=8)
for flow_path in fps:
fig = plt.figure(figsize=(6.,6.))
ncols = 2
nrows = 5
gs = gridspec.GridSpec(ncols=ncols, nrows=nrows, width_ratios=[.9,2.], left=0.01, top=.98, wspace=0.25, right=0.98, hspace=0.08, bottom=0.08)
# Text:
plt.figtext(x=0.02, y=0.95, s='Flow-path %s'%str(flow_path))
plt.figtext(x=0.02, y=0.92, s='Net power gain: %s MW${_\mathrm{th}}$'%str(N.around(N.sum(q_net[fp[flow_path]]/1e6), decimals=1)))
plt.figtext(x=0.02, y=0.89, s=r'Efficiency: %s%%'%str(N.around(N.sum(q_net[fp[flow_path]])/N.sum(flux_in[flow_path]*areas_fp[flow_path]), decimals=3)*100.))
# 3D receiver snipet with only flow_path in dense:
rec3Dsnipet = fig.add_subplot(gs[1:3,0], projection='3d', aspect=1.4)
angres_per_bank = 1
banks = N.shape(fluxmap)[1]
fluxmap_fp = fluxmap#N.concatenate((fluxmap[:,banks/4:], fluxmap[:,:banks/4]), axis=1) # correction to start from south
flux = N.hstack(fluxmap_fp)/1e6
# Set-up the colormap:
vmin=0.
vmax=1.2
cNorm = colors.Normalize(vmin, vmax)
mp = cm.ScalarMappable(norm=cNorm, cmap=cm.viridis)
for i in xrange(len(flux)):
if (i == N.hstack(fp[flow_path])).any():
alpha = 1
lw = 0.5
else:
alpha=0.1
lw = 0
ts = ahr[i,0,:]-N.pi/2. # south origin for banks
hs = ahr[i,1,:]
rs = ahr[i,2,0]
dt = (ts[1]-ts[0])/float(angres_per_bank)
for j in xrange(angres_per_bank):
thetas = [ts[0]+float(j)*dt, ts[0]+(j+1.)*dt]
x = rs*N.cos(thetas)
y = rs*N.sin(thetas)
z0 = N.ones(2)*hs[0]
z1 = N.ones(2)*hs[1]
x = N.vstack((x, x))
y = N.vstack((y, y))
z = N.vstack((z0, z1))
face = mp.to_rgba(flux[i])
surf = rec3Dsnipet.plot_surface(x, y, z, shade=False, antialiased=False, color=face, edgecolor=face, linewidth=lw, alpha=alpha)
rcard = N.amax(radius)+0.5
zcard = N.amax(height)+0.5
rec3Dsnipet.scatter(xs=[0,rcard,0,-rcard], ys=[rcard,0,-rcard,0], zs=[zcard,zcard,zcard,zcard], s=150, c=N.tile([1,1,1,0.7],(4,1)), lw=0, zorder=9999.)
rec3Dsnipet.text(-rcard,0,zcard, s='W', zorder=10000., ha='center', va='center')
rec3Dsnipet.text(0,rcard,zcard, s='N', zorder=10000., ha='center', va='center')
rec3Dsnipet.text(rcard,0,zcard, s='E', zorder=10000., ha='center', va='center')
rec3Dsnipet.text(0,-rcard,zcard, s='S', zorder=10000., ha='center', va='center')
rec3Dsnipet.set_xlim(-radius/1.2, radius/1.2)
rec3Dsnipet.set_ylim(-radius/1.2, radius/1.2)
rec3Dsnipet.set_zlim(0, height)
rec3Dsnipet.set_xticks([],[])
rec3Dsnipet.set_yticks([],[])
rec3Dsnipet.set_zticks([],[])
# Get rid of colored axes planes
# First remove fill
rec3Dsnipet.xaxis.pane.fill = False
rec3Dsnipet.yaxis.pane.fill = False
rec3Dsnipet.zaxis.pane.fill = False
rec3Dsnipet.set_axis_off()
rec3Dsnipet.view_init(elev=25, azim=95)
mp = cm.ScalarMappable(cmap=cm.viridis)
mp.set_array(N.hstack([vmin, vmax]))
cbar = plt.colorbar(mp, orientation='horizontal', pad=-0.05, shrink=0.8)
cbar.set_label(r'$\dot{q}^{\prime \prime}_\mathrm{in}$ [MW.m$^{-2}$]')
# T ext 3D:
# 3D receiver snipet with only flow_path in dense:
rec3Dsnipet = fig.add_subplot(gs[3:5,0], projection='3d', aspect=1.4)
rec3Dsnipet.set_facecolor('None')
angres_per_bank = 1
banks = N.shape(fluxmap)[1]
fluxmap_fp = fluxmap#N.concatenate((fluxmap[:,banks/4:], fluxmap[:,:banks/4]), axis=1) # correction to start from east
flux = N.hstack(T_ext)-273.15
# Set-up the colormap:
vmin=N.amin(flux)
vmax=N.amax(flux)
cNorm = colors.Normalize(vmin, vmax)
mp = cm.ScalarMappable(norm=cNorm, cmap=cm.hot)
for i in xrange(len(flux)):
if (i == N.hstack(fp[flow_path])).any():
alpha = 1
lw = 0.5
else:
alpha=0.1
lw = 0
ts = ahr[i,0,:]-N.pi/2. # south origin for banks
hs = ahr[i,1,:]
rs = ahr[i,2,0]
dt = (ts[1]-ts[0])/float(angres_per_bank)
for j in xrange(angres_per_bank):
thetas = [ts[0]+float(j)*dt, ts[0]+(j+1.)*dt]
x = rs*N.cos(thetas)
y = rs*N.sin(thetas)
z0 = N.ones(2)*hs[0]
z1 = N.ones(2)*hs[1]
x = N.vstack((x, x))
y = N.vstack((y, y))
z = N.vstack((z0, z1))
face = mp.to_rgba(flux[i])
surf = rec3Dsnipet.plot_surface(x, y, z, shade=False, antialiased=False, color=face, edgecolor=face, linewidth=lw, alpha=alpha)
rcard = N.amax(radius)+0.5
zcard = N.amax(height)+0.5
rec3Dsnipet.scatter(xs=[0,rcard,0,-rcard], ys=[rcard,0,-rcard,0], zs=[zcard,zcard,zcard,zcard], s=150, c=N.tile([1,1,1,0.7],(4,1)), lw=0, zorder=9999.)
rec3Dsnipet.text(-rcard,0,zcard, s='W', zorder=10000., ha='center', va='center')
rec3Dsnipet.text(0,rcard,zcard, s='N', zorder=10000., ha='center', va='center')
rec3Dsnipet.text(rcard,0,zcard, s='E', zorder=10000., ha='center', va='center')
rec3Dsnipet.text(0,-rcard,zcard, s='S', zorder=10000., ha='center', va='center')
rec3Dsnipet.set_xlim(-radius/1.2, radius/1.2)
rec3Dsnipet.set_ylim(-radius/1.2, radius/1.2)
rec3Dsnipet.set_zlim(0, height)
rec3Dsnipet.set_xticks([],[])
rec3Dsnipet.set_yticks([],[])
rec3Dsnipet.set_zticks([],[])
# Get rid of colored axes planes
# First remove fill
rec3Dsnipet.xaxis.pane.fill = False
rec3Dsnipet.yaxis.pane.fill = False
rec3Dsnipet.zaxis.pane.fill = False
rec3Dsnipet.set_axis_off()
rec3Dsnipet.view_init(elev=25, azim=95)
mp = cm.ScalarMappable(cmap=cm.hot)
mp.set_array(N.hstack([vmin, vmax]))
cbar = plt.colorbar(mp, orientation='horizontal', pad=-0.05, shrink=0.8)
cbar.set_label(r'${T_\mathrm{wall, ext}}$ [${^\circ}$C]')
# flux fp plot:
fluxplot = fig.add_subplot(gs[0,1])
bank_lengths = pipe_lengths[flow_path]
bank_lengths_2 = (bank_lengths[1:]+bank_lengths[:-1])/2.
if flux_limits_file is not None:
flux_lims = flux_limits(N.ones(len(fp[flow_path]))/n_tubes[fp[flow_path]]*m[flow_path], T_HC[flow_path], flux_limits_file)/1e3
plt.plot(bank_lengths, flux_lims, color='r', label=r'${\dot{q}_\mathrm{LIMIT}^{\prime \prime}}$')
plt.plot(bank_lengths_2, flux_in[flow_path]/1e3, label=r'${\dot{q}_\mathrm{in}^{\prime \prime}}$', color='0')
plt.plot(bank_lengths_2, q_net[fp[flow_path]]/areas[fp[flow_path]]/1e3, label=r'${\dot{q}^{\prime \prime}_\mathrm{net}}$', color='0.6')
plt.legend()
xticks = plt.gca().get_xticks()
plt.xticks(xticks, [])
plt.tick_params(direction='in')
plt.xlim(N.amin(bank_lengths), N.amax(bank_lengths))
plt.ylabel('Flux [kW.m$^{-2}$]')
# Temperatures:
Tplot = fig.add_subplot(gs[1,1])
plt.plot(bank_lengths_2, T_ext[fp[flow_path]]-273.15, label=r'T${_\mathrm{abs}}$', color='0')
plt.plot(bank_lengths_2, T_w_int[fp[flow_path]]-273.15, label=r'T${_\mathrm{wall,int}}$', color='0.4')
plt.plot(bank_lengths, T_HC[flow_path]-273.15, label=r'T${_\mathrm{HC}}$', color='0.6')
plt.legend()
xticks = plt.gca().get_xticks()
plt.xticks(xticks, [])
plt.tick_params(direction='in')
plt.xlim(N.amin(bank_lengths), N.amax(bank_lengths))
plt.ylabel('T [$^{\circ}$C]')
# Fraction of allowable:
Fracplot = fig.add_subplot(gs[2,1])
if flux_limits_file is not None:
plt.plot(bank_lengths_2, q_net[fp[flow_path]]/areas[fp[flow_path]]/1e3/((flux_lims[:-1]+flux_lims[1:])/2.), color='g')
plt.ylabel(r'${\frac{\dot{q}_\mathrm{net}^{\prime \prime}}{\dot{q}_\mathrm{LIMIT}^{\prime \prime}}}$')
xticks = plt.gca().get_xticks()
plt.xticks(xticks, [])
plt.tick_params(direction='in')
plt.xlim(N.amin(bank_lengths), N.amax(bank_lengths))
plt.ylim(-0.1,1.1)
# Pressure drop:
pdroplot = fig.add_subplot(gs[3,1])
Dploc = -N.add.accumulate(Dp[fp[flow_path]])/1e5
plt.plot(bank_lengths_2, Dploc, color='0')
xticks = plt.gca().get_xticks()
plt.xticks(xticks, [])
plt.tick_params(direction='in')
plt.xlim(N.amin(bank_lengths), N.amax(bank_lengths))
plt.ylabel('${p(\ell)-p(0)}$ [bar]')
# Velocity:
vplot = fig.add_subplot(gs[4,1])
plt.plot(bank_lengths_2, V[fp[flow_path]], color='0.5')
plt.xlim(N.amin(bank_lengths), N.amax(bank_lengths))
plt.xlabel('Flow path length (${\ell}$) [m]')
plt.ylabel('${v_\mathrm{Na}}$ [m.s$^{-1}$]')
plt.savefig(open(saveloc+'_fp_%s.png'%str(flow_path),'w'), dpi=400)
plt.close(fig)
def flow_path_plot_billboard(files='/home/charles/Documents/Boulot/These/Sodium receiver_CMI/ref_case_result_1', fps=[0], saveloc=None, flux_limits_file=None):
import matplotlib.gridspec as gridspec
print "plotting"
fileo = open(files,'r')
data = pickle.load(fileo)
fileo.close()
if saveloc == None:
saveloc = files
wh = data['wh']
width = data['width']
height = data['height']
n_banks = data['n_banks']
n_elems = data['n_elems']
n_tubes = data['n_tubes']
D_tubes_o = data['D_tubes_o']
D_tubes_i = data['D_tubes_i']
eff_abs = data['eff_abs']
abs_t = data['abs_t']
eff_ems = data['eff_ems']
ems_t = data['ems_t']
k_t = data['k_t']
wh_map = data['wh_map']
fp = data['fp']
areas = data['areas']
areas_fp = data['areas_fp']
HC = data['HC']
T_in = data['T_in']
T_out = data['T_out']
h_conv_ext = data['h_conv_ext']
h = data['h']
m = data['m']
flux_in = data['flux_in']
q_net = data['q_net']
q_rad = data['q_rad']
q_ref = data['q_ref']
q_conv = data['q_conv_ext']
T_amb = data['T_amb']
T_HC = data['T_HC']
T_w_int = data['T_w_int']
T_ext = data['T_ext']
h_conv_int = data['h_conv_int']
V = data['V']
fluxmap = data['fluxmap']
HC = data['HC']
n_tubes = data['n_tubes']
Dp = data['Dp']
pipe_lengths = data['pipe_lengths']
maxheight = N.amax(wh[:,1,:])
maxwidth = N.amax(wh[:,0,:])
plt.rc('font', size=8)
for flow_path in fps:
fig = plt.figure(figsize=(6.,6.))
ncols = 2
nrows = 5
gs = gridspec.GridSpec(ncols=ncols, nrows=nrows, width_ratios=[.9,2.], left=0.01, top=.98, wspace=0.25, right=0.98, hspace=0.08, bottom=0.08)
# Text:
plt.figtext(x=0.02, y=0.95, s='Flow-path %s'%str(flow_path))
plt.figtext(x=0.02, y=0.92, s='Net power gain: %s MW${_\mathrm{th}}$'%str(N.around(N.sum(q_net[fp[flow_path]]/1e6), decimals=1)))
plt.figtext(x=0.02, y=0.89, s=r'Efficiency: %s%%'%str(N.around(N.sum(q_net[fp[flow_path]])/N.sum(flux_in[flow_path]*areas_fp[flow_path])*100., decimals=1)))
# receiver snipet with only flow_path in dense:
rec3Dsnipet = fig.add_subplot(gs[1:3,0], projection='3d', aspect=1.4)
angres_per_bank = 1
banks = N.shape(fluxmap)[1]
fluxmap_fp = fluxmap
flux = N.hstack(fluxmap_fp)/1e6
# Set-up the colormap:
vmin=0.
vmax=1.2
cNorm = colors.Normalize(vmin, vmax)
mp = cm.ScalarMappable(norm=cNorm, cmap=cm.viridis)
for i in xrange(len(flux)):
if (i == N.hstack(fp[flow_path])).any():
alpha = 1
lw = 0.5
else:
alpha=0.1
lw = 0
ws = wh[i,0,:]
hs = wh[i,1,:]
for j in xrange(angres_per_bank):
x = ws-width/2.
y = ws*0
z0 = N.ones(2)*hs[0]
z1 = N.ones(2)*hs[1]
x = N.vstack((x, x))
y = N.vstack((y, y))
z = N.vstack((z0, z1))
face = mp.to_rgba(flux[i])
surf = rec3Dsnipet.plot_surface(x, y, z, shade=False, antialiased=False, color=face, edgecolor=face, linewidth=lw, alpha=alpha)
rec3Dsnipet.set_xlim(-width/2.2, width/2.2)
rec3Dsnipet.set_ylim(-width/2.2, width/2.2)
rec3Dsnipet.set_zlim(0, height)
rec3Dsnipet.set_xticks([],[])
rec3Dsnipet.set_yticks([],[])
rec3Dsnipet.set_zticks([],[])
# Get rid of colored axes planes
# First remove fill
rec3Dsnipet.xaxis.pane.fill = False
rec3Dsnipet.yaxis.pane.fill = False
rec3Dsnipet.zaxis.pane.fill = False
rec3Dsnipet.set_axis_off()
rec3Dsnipet.view_init(elev=-25, azim=100)
mp = cm.ScalarMappable(cmap=cm.viridis)
mp.set_array(N.hstack([vmin, vmax]))
cbar = plt.colorbar(mp, orientation='horizontal', pad=-0.05, shrink=0.8)
cbar.set_label(r'$\dot{q}^{\prime \prime}_\mathrm{in}$ [MW.m$^{-2}$]')
# T ext 3D:
# 3D receiver snipet with only flow_path in dense:
rec3Dsnipet = fig.add_subplot(gs[3:5,0], projection='3d', aspect=1.4)
rec3Dsnipet.set_facecolor('None')
angres_per_bank = 1
banks = N.shape(fluxmap)[1]
fluxmap_fp = N.concatenate((fluxmap[:,banks/4:], fluxmap[:,:banks/4]), axis=1) # correction to start from east
flux = N.hstack(T_ext)-273.15
# Set-up the colormap:
vmin=N.amin(flux)
vmax=N.amax(flux)