def gen_rays(self):
sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree)
rpos = (self.pos + sun_vec).T
direct = N.tile(-sun_vec, (self.pos.shape[0], 1)).T
rays = RayBundle(rpos, direct, energy=N.ones(self.pos.shape[0]))
return rays
def trace(self, rph, iters = 10000, minE = 1e-9, render = False):
"""Commences raytracing using (rph) number of rays per heliostat, for a maximum of
(iters) iterations, discarding rays with energy less than (minE). If render is
True, a 3D scene will be displayed which would need to be closed to proceed."""
# Get the solar vector using azimuth and elevation
sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree)
# Calculate number of rays used. Rays per heliostat * number of heliostats.
num_rays = rph*len(self.field.get_heliostats())
self.no_of_rays += num_rays
# Generates the ray bundle
rot_sun = rotation_to_z(-sun_vec)
direct = N.dot(rot_sun, pillbox_sunshape_directions(num_rays, 0.00465))
xy = N.random.uniform(low=-0.25, high=0.25, size=(2, num_rays))
base_pos = N.tile(self.pos, (rph, 1)).T #Check if its is rph or num_rays
base_pos += N.dot(rot_sun[:,:2], xy)
base_pos -= direct
rays = RayBundle(base_pos, direct, energy=N.ones(num_rays))
# Perform the raytracing
e = TracerEngine(self.plant)
e.ray_tracer(rays, iters, minE, tree=True)
e.minener = minE
rays_in = sum(e.tree._bunds[0].get_energy())
self.helio_hits = sum(e.tree._bunds[1].get_energy())
# Optional rendering
if render == True:
trace_scene = Renderer(e)
trace_scene.show_rays()
def gen_rays(self):
sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree)
rpos = (self.pos + sun_vec).T
direct = N.tile(-sun_vec, (self.pos.shape[0], 1)).T
rays = RayBundle(rpos, direct, energy=N.ones(self.pos.shape[0]))
return rays
def trace(self):
"""Generate a flux map using much more rays than drawn"""
# Generate a large ray bundle using a radial stagger much denser
# than the field.
sun_vec = solar_vector(self.sun_az * degree, self.sun_elev * degree)
hstat_rays = 20
num_rays = hstat_rays * len(self.field.get_heliostats())
rot_sun = rotation_to_z(-sun_vec)
direct = N.dot(rot_sun, pillbox_sunshape_directions(num_rays, 0.00465))
xy = N.random.uniform(low=-0.25, high=0.25, size=(2, num_rays))
base_pos = N.tile(self.pos, (hstat_rays, 1)).T
base_pos += N.dot(rot_sun[:, :2], xy)
base_pos -= direct
rays = RayBundle(base_pos, direct, energy=N.ones(num_rays))
# Perform the trace:
e = TracerEngine(self.plant)
e.ray_tracer(rays, 100, 0.05, tree=True)
e.minener = 1e-5
# Render:
trace_scene = Renderer(e)
trace_scene.show_rays()
def trace(self):
"""Generate a flux map using much more rays than drawn"""
# Generate a large ray bundle using a radial stagger much denser
# than the field.
sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree)
hstat_rays = 20
num_rays = hstat_rays*len(self.field.get_heliostats())
rot_sun = rotation_to_z(-sun_vec)
direct = N.dot(rot_sun, pillbox_sunshape_directions(num_rays, 0.00465))
xy = N.random.uniform(low=-0.25, high=0.25, size=(2, num_rays))
base_pos = N.tile(self.pos, (hstat_rays, 1)).T
base_pos += N.dot(rot_sun[:,:2], xy)
base_pos -= direct
rays = RayBundle(base_pos, direct, energy=N.ones(num_rays))
# Perform the trace:
e = TracerEngine(self.plant)
e.ray_tracer(rays, 100, 0.05, tree=True)
e.minener = 1e-5
# Render:
trace_scene = Renderer(e)
trace_scene.show_rays()
def gen_rays(self):
sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree)
#notice here the angles are positive. Hmmm? The sun rays are pointing up?
rpos = (self.pos + sun_vec).T
#where does self.pos come from? And T?
direct = N.tile(-sun_vec, (self.pos.shape[0], 1)).T
rays = RayBundle(rpos, direct, energy=N.ones(self.pos.shape[0]))
return rays
def calculate_area(self, hstat_az, hstat_elev): ''' Calculates the heliostats areas as seen from the source, necessary for shading calculations. ''' # CONVERSION # sun_vec az 0 -45 -90 +-180 +90 +45 # hstat_az -90 -45 0 +90 +-180 -135 hstat_az = -hstat_az - N.pi/2 for i in xrange(len(self.pos)): self.hstat_normals[i] = solar_vector(hstat_az[i], hstat_elev[i]) self.hstat_proj_areas = [0]*len(self.pos) for i in xrange(len(self.pos)): self.hstat_proj_areas[i] = (6.09**2) * abs(N.dot(-self.sun_vec, self.hstat_normals[i]))
def calculate_area(self, hstat_az, hstat_elev):
'''
Calculates the heliostats areas as seen from the source, necessary for shading calculations.
'''
# CONVERSION
# sun_vec az 0 -45 -90 +-180 +90 +45
# hstat_az -90 -45 0 +90 +-180 -135
hstat_az = -hstat_az - N.pi / 2
for i in xrange(len(self.pos)):
self.hstat_normals[i] = solar_vector(hstat_az[i], hstat_elev[i])
self.hstat_proj_areas = [0] * len(self.pos)
for i in xrange(len(self.pos)):
self.hstat_proj_areas[i] = (6.1**2) * abs(
N.dot(-self.sun_vec, self.hstat_normals[i]))
def trace(self):
"""Generate a flux map using much more rays than drawn"""
# Generate a large ray bundle using a radial stagger much denser
# than the field.
sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree)
#hstat_rays
hstat_rays = 1000
num_rays = hstat_rays*len(self.field.get_heliostats())
rot_sun = rotation_to_z(-sun_vec)
direct = N.dot(rot_sun, pillbox_sunshape_directions(num_rays, 0.00465))
xy = N.random.uniform(low=-0.25, high=0.25, size=(2, num_rays))
base_pos = N.tile(self.pos, (hstat_rays, 1)).T
base_pos += N.dot(rot_sun[:,:2], xy)
base_pos -= direct
rays = RayBundle(base_pos, direct, energy=N.ones(num_rays))
# Perform the trace:
e = TracerEngine(self.plant)
e.ray_tracer(rays, 100, 0.05, tree=True)
e.minener = 1e-6 # default 1e-5
# Render:
#trace_scene = Renderer(e)
#trace_scene.show_rays()
# Initialise a histogram of hits:
energy, pts = self.reclist.get_optics_manager().get_all_hits()
x, y = self.reclist.global_to_local(pts)[:2]
rngx = 0.55 #0.5
rngy = 0.55 #0.5
bins = 100 #50
H, xbins, ybins = N.histogram2d(x, y, bins, \
range=([-rngx,rngx], [-rngy,rngy]), weights=energy)
#print(H, xbins, ybins)
total=N.sum(H)
print(total)
extent = [ybins[0], ybins[-1], xbins[-1], xbins[0]]
plt.imshow(H, extent=extent, interpolation='nearest')
plt.colorbar()
plt.title("front")
plt.show()
def traceMP(self, rays_per_run, iters = 10000, minE = 1e-9, render = False,procs = 1):
"""Commences raytracing using (rph) number of rays per heliostat, for a maximum of
(iters) iterations, discarding rays with energy less than (minE). If render is
True, a 3D scene will be displayed which would need to be closed to proceed."""
# Get the solar vector using azimuth and elevation
sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree)
rot_sun = rotation_to_z(-sun_vec)
# Calculate number of rays used. Rays per heliostat * number of heliostats.
rppph = int(rays_per_run/(procs*len(self.field.get_heliostats())))
rpp = rppph*len(self.field.get_heliostats())
rpr = rpp*procs #actual rays per run used
ray_sources = []
n = 1
while n <= procs:
direct = N.dot(rot_sun, pillbox_sunshape_directions(rpp, 0.00465))
xy = N.random.uniform(low=-0.25, high=0.25, size=(2, rpp))
base_pos = N.tile(self.pos, (rppph, 1)).T
base_pos += N.dot(rot_sun[:,:2], xy)
base_pos -= direct
rays = RayBundle(base_pos, direct, energy=N.ones(rpp))
ray_sources.append(rays)
n += 1
e = TracerEngineMP(self.plant)
e.multi_ray_sim(ray_sources,procs)
self.plant = e._asm
self.helio_hits = sum(e.tree._bunds[1].get_energy())
# Note that you may need some stuff in here
if render == True:
trace_scene = Renderer(e)
trace_scene.show_rays(resolution=10)
render = False
return rpr #this is special
def _fmap_btn_fired(self):
"""Generate a flux map using much more rays than drawn"""
# Generate a large ray bundle using a radial stagger much denser
# than the field.
sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree)
hstat_rays = 1000
num_rays = hstat_rays*len(self.field.get_heliostats())
rot_sun = rotation_to_z(-sun_vec)
direct = N.dot(rot_sun, pillbox_sunshape_directions(num_rays, 0.00465))
xy = N.random.uniform(low=-0.25, high=0.25, size=(2, num_rays))
base_pos = N.tile(self.pos, (hstat_rays, 1)).T
base_pos += N.dot(rot_sun[:,:2], xy)
base_pos -= direct
rays = RayBundle(base_pos, direct, energy=N.ones(num_rays))
# Perform the trace:
self.rec.get_optics_manager().reset()
e = TracerEngine(self.plant)
e.ray_tracer(rays, 1000, 0.05)
# Show a histogram of hits:
energy, pts = self.rec.get_optics_manager().get_all_hits()
x, y = self.rec.global_to_local(pts)[:2]
rngx = 0.5
rngy = 0.5
bins = 50
H, xbins, ybins = N.histogram2d(x, y, bins, \
range=([-rngx,rngx], [-rngy,rngy]), weights=energy)
self.fmap.axes[0].images=[]
self.fmap.axes[0].imshow(H, aspect='auto')
wx.CallAfter(self.fmap.canvas.draw)
def trace(self): ''' Raytrace method. Raytraces successive bundles and stores the resultsogf the shading, blicking, incoming radiative power on the heliostats and the fluxmap on the receiver. ''' # Generate a large ray bundle using [a radial stagger much denser # than the field] a Buie sunshape with radius equal to the longest # dimension of the field. #============= render = False #============= sun_vec = solar_vector(self.sun_az*degree, self.sun_elev*degree) # Generate the following number of rays num_rays = 500000. iters = 40 # Results bins: incoming = N.zeros(len(self.pos)) prev_incoming = N.zeros(len(self.pos)) incoming_Q = N.zeros(len(self.pos)) incoming_stdev = N.zeros(len(self.pos)) shading = N.ones(len(self.pos)) prev_shading = N.zeros(len(self.pos)) shading_Q = N.zeros(len(self.pos)) shading_stdev = N.zeros(len(self.pos)) blocking = N.zeros(len(self.pos)) prev_blocking = N.zeros(len(self.pos)) blocking_Q= N.zeros(len(self.pos)) blocking_stdev= N.zeros(len(self.pos)) timer_mcrt = 0. timer_postprocess = 0. # Receiver bins: dl=11./50. bins = N.arange(-5.5,5.5+dl, dl) fluxmap = N.zeros((len(bins)-1,len(bins)-1)) # Raytrace: mcrt = time.clock() e = TracerEngineMP(self.plant) procs = 8 e.minener = 1e-10 timer_mcrt += time.clock()-mcrt hits_helios=0 i=0 #while hits_helios < 20e6: for i in xrange(iters): print ' ' print ' ' print 'ITERATION ', i+1#, ' of ', iters mcrt = time.clock() # Perform the trace: sources = [] self.flux = 1000. for s in xrange(procs): sources.append(self.gen_rays(num_rays/float(procs), flux=self.flux/float(procs))) e.multi_ray_sim(sources, procs) self.plant = e._asm self.field._heliostats = self.plant._assemblies[0].get_surfaces() self.rec = self.plant._objects[0].get_surfaces()[0] timer_mcrt += time.clock()-mcrt postprocess = time.clock() # Render: if render: trace_scene = Renderer(e) trace_scene.show_rays(resolution=10) # Get the energy and location of all hits using optics manager en, pts = self.rec.get_optics_manager().get_all_hits() x, y = self.rec.global_to_local(pts)[:2] # FLUX MAP OPERATIONS #=========================================================================== H, xbins, ybins = N.histogram2d(x, y, bins, weights=en) extent = [ybins[0], ybins[-1], xbins[-1], xbins[0]] fluxmap = (fluxmap*float(i)+H/(1000.*dl**2.))/(i+1.) #=========================================================================== # BLOCKAGE and SHADING #=========================================================================== # Detect blockage and look for the parents of the blocked rays. Identify from which heliostats teh oarents come and associate the blockage losses to the heliostats where blockage is suffered. hz = (e.tree._bunds[1].get_vertices()[2]) < (self.field._th-self.rec_h/2.) hits_helios += N.sum(hz) print 'Useful rays:', hits_helios # Get the 3rd bundle (after 2 hits): bund_2 = e.tree._bunds[2].get_vertices() bund_2_ener = e.tree._bunds[2].get_energy() # Remove receiver hits from the bundle to get only hits on heliostats: bund_2_helio_hits = N.ravel(N.nonzero(bund_2[2] < (self.field._th-self.rec_h/2.))) bund_2_bloc = bund_2[:, bund_2_helio_hits] # Get the bundle emitting the blocked rays and isolate the blocked rays: bund_1_helio_blocs = e.tree._bunds[2].get_parents()[bund_2_helio_hits] bund_1 = e.tree._bunds[1].get_vertices() bund_1_ener = e.tree._bunds[1].get_energy() bund_1_bloc = bund_1[:, bund_1_helio_blocs] # Screen the field to find where blocked rays originate: for h in xrange(len(self.pos)): # Get the information from the optics manager of the heliostat: abs_hstats, hits_hstats, dirs_hstats = self.field._heliostats[h].get_optics_manager().get_all_hits() blocs = [] hit_0s = [] # Check if any hits: if len(hits_hstats)!=0: # Screen through every hit: for r in xrange(N.shape(hits_hstats)[1]): # Is the hit a ray that will be blocked or a blocked ray? bloc = N.nonzero(hits_hstats[0,r] == bund_1_bloc[0])[0] # Next "if" is because if there are no valid hits the bloc returns an empty array or to isolate each hit in case of 2 hits matching. if len(bloc)>0: for b in xrange(len(bloc)): # If sthe first coordinate matches, do the rest of them? if (hits_hstats[:,r]==N.ravel(bund_1_bloc[:,bloc[b]])).all(): # If so add the blocked energy to the result bin. blocs.append(bund_1_helio_blocs[bloc[b]]) else: hit_0 = N.nonzero(hits_hstats[0,r] == bund_1[0])[0] if len(hit_0)>0: for s in xrange(len(hit_0)): if (hits_hstats[:,r]==N.ravel(bund_1[:,hit_0[s]])).all(): hit_0s.append(e.tree._bunds[1].get_parents()[hit_0[s]]) prev_blocking[h] = blocking[h] # Monte-Carlo sampling: blocking[h] = (blocking[h]*i+N.sum(bund_1_ener[blocs]))/(i+1.) # Shading is the theoretical energy hitting subtracted by the energy absorbed without the backside blocking. prev_incoming[h] = incoming[h] # Monte-Carlo sampling: incoming[h] = (incoming[h]*i+N.sum(e.tree._bunds[0].get_energy()[hit_0s]))/(i+1.) prev_shading[h] = shading[h] # Monte-Carlo sampling: shading[h] = (shading[h]*i+self.flux*self.hstat_proj_areas[h]-incoming[h])/(i+1.) # Streamlined stats variable: incoming_Q = incoming_Q+i/(i+1.)*(incoming-prev_incoming)**2. blocking_Q = blocking_Q+i/(i+1.)*(blocking-prev_blocking)**2. shading_Q = shading_Q+i/(i+1.)*(shading-prev_shading)**2. # Standard deviatiosn updates: if i>0: incoming_stdev = N.sqrt(incoming_Q/i) blocking_stdev = N.sqrt(blocking_Q/i) shading_stdev = N.sqrt(shading_Q/i) print 'Shading=', N.sum(shading) print 'Blockage=', N.sum(blocking) timer_postprocess += time.clock()-postprocess print 'timer_mcrt: ', timer_mcrt/60., 'min' print 'timer_postprocess: ', timer_postprocess/60., 'min' print 'Peak flux (kW/m2):', N.amax(fluxmap) print 'AVG flux (kW/m2): ', N.sum(fluxmap)/(N.shape(fluxmap)[0]*N.shape(fluxmap)[1]) print 'Total radiative power (kW): ', N.sum(fluxmap*(11./50.)**2) i+=1 #=========================================================================== e.tree._bunds = [] for clear in xrange(len(e._asm.get_surfaces())): e._asm.get_surfaces()[clear].get_optics_manager().reset() #=========================================================================== '''
class TowerScene():
# Location of the sun:
sun_az = 0
sun_zenith = 35.05 #34.96
sun_vec = solar_vector(sun_az * degree, sun_zenith * degree)
hstat_normals = N.zeros((218, 3))
# import custom coordinate file
pos = N.loadtxt(
"/home/charles/Documents/Tracer/examples/sandia_hstat_coordinates.csv",
delimiter=',')
# Field-based calculations for source size parameters
#===================================================
t_pos = pos.T
xc_min = t_pos[0][N.argmin(t_pos[0])]
xc_max = t_pos[0][N.argmax(t_pos[0])]
yc_min = t_pos[1][N.argmin(t_pos[1])]
yc_max = t_pos[1][N.argmax(t_pos[1])]
x_dist = xc_max - xc_min
y_dist = yc_max - yc_min
xc_cent = (xc_min + xc_max) / 2
yc_cent = (yc_min + yc_max) / 2
field_centre = N.r_[xc_cent, yc_cent, 0]
#===================================================
def __init__(self):
self.gen_plant()
def gen_rays(self, num_rays, flux=1000.):
#========================
individual_source = False
#========================
if individual_source:
# Pillbox source on a per-heliostat basis
radius = 1.20 * math.sqrt(2 * 3.405**2)
direction = N.array(-self.sun_vec)
ray_list = []
num_surfs = self.pos.shape[0]
for i in xrange(num_surfs):
centre = N.c_[50 * self.sun_vec + self.pos[i]]
#rayb = solar_disk_bundle(num_rays/num_surfs, centre, direction, radius, 4.65e-3, flux)
rayb = buie_sunshape(num_rays / num_surfs,
centre,
direction,
radius,
CSR=0.01,
flux=flux)
ray_list.append(rayb)
rays = concatenate_rays(ray_list)
del ray_list
else:
# Large pillbox sunshape source disc source covering entire field area:
radius = 1.10 * math.sqrt((self.x_dist / 2)**2 +
(self.y_dist / 2)**2)
self.source_area = N.pi * radius**2
centre = N.c_[300 * self.sun_vec + self.field_centre]
direction = N.array(-self.sun_vec)
#rays = solar_disk_bundle(num_rays, centre, direction, radius, 4.65e-3, flux)
rays = buie_sunshape(num_rays,
centre,
direction,
radius,
CSR=0.01,
flux=flux,
pre_process_CSR=False)
return rays
def gen_plant(self,
width=6.1,
height=6.1,
absorptivity=0.04,
aim_height=60.,
sigma_xy=1e-3,
rec_w=11.,
rec_h=11.):
self.pos[:,
1] = self.pos[:,
1] - 4. # correction for the true position of the plate on the tower.
self.width = width
self.height = height
self.absorptivity = absorptivity
self.field = HeliostatField(self.pos, width, height, absorptivity,
aim_height, sigma_xy)
self.rec_w = rec_w
self.rec_h = rec_h
rec, recobj = one_sided_receiver(self.rec_w, self.rec_h)
rec_trans = rotx(N.pi / -2)
rec_trans[2, 3] = self.field._th
# Evaluating just the receiver
recobj.set_transform(rec_trans)
self.plant = Assembly(objects=[recobj], subassemblies=[self.field])
def aim_field(self):
hstat_az, hstat_elev = self.field.aim_to_sun(self.sun_az * degree,
self.sun_zenith * degree)
return hstat_az, hstat_elev
def calculate_area(self, hstat_az, hstat_elev):
'''
Calculates the heliostats areas as seen from the source, necessary for shading calculations.
'''
# CONVERSION
# sun_vec az 0 -45 -90 +-180 +90 +45
# hstat_az -90 -45 0 +90 +-180 -135
hstat_az = -hstat_az - N.pi / 2
for i in xrange(len(self.pos)):
self.hstat_normals[i] = solar_vector(hstat_az[i], hstat_elev[i])
self.hstat_proj_areas = [0] * len(self.pos)
for i in xrange(len(self.pos)):
self.hstat_proj_areas[i] = (6.1**2) * abs(
N.dot(-self.sun_vec, self.hstat_normals[i]))
def trace(self, num_rays=1e5, nbins_w=50., nbins_h=50.):
'''
Raytrace method.
Raytraces successive bundles and stores the resultsogf the shading, blicking, incoming radiative power on the heliostats and the fluxmap on the receiver.
'''
# Generate a large ray bundle using [a radial stagger much denser
# than the field] a Buie sunshape with radius equal to the longest
# dimension of the field.
#=============
render = False
#=============
sun_vec = solar_vector(self.sun_az * degree, self.sun_zenith * degree)
bundlesize = 1e4
iters = int(num_rays / bundlesize)
# Results bins:
incoming = N.zeros(len(self.pos))
prev_incoming = N.zeros(len(self.pos))
incoming_Q = N.zeros(len(self.pos))
incoming_stdev = N.zeros(len(self.pos))
shading = N.ones(len(self.pos))
prev_shading = N.zeros(len(self.pos))
shading_Q = N.zeros(len(self.pos))
shading_stdev = N.zeros(len(self.pos))
blocking = N.zeros(len(self.pos))
prev_blocking = N.zeros(len(self.pos))
blocking_Q = N.zeros(len(self.pos))
blocking_stdev = N.zeros(len(self.pos))
timer_mcrt = 0.
timer_postprocess = 0.
# Receiver bins:
dlw = self.rec_w / nbins_w
dlh = self.rec_h / nbins_h
bins_w = N.arange(-self.rec_w / 2., self.rec_w / 2. + dlw, dlw)
bins_h = N.arange(-self.rec_h / 2., self.rec_h / 2. + dlh, dlh)
bins = [bins_w, bins_h]
self.bins = bins
fluxmap = N.zeros((len(bins_w) - 1, len(bins_h) - 1))
# Raytrace:
mcrt = time.clock()
e = TracerEngineMP(self.plant)
procs = 1
e.minener = 1e-10
timer_mcrt += time.clock() - mcrt
hits_helios = 0
i = 0
#while hits_helios < num_rays:
for i in xrange(iters):
print ' '
print ' '
print 'ITERATION ', i + 1, ' of ', iters
#print hits_helios, 'hits out of ', num_rays
mcrt = time.clock()
# Perform the trace:
sources = []
self.flux = 1000.
for s in xrange(procs):
sources.append(
self.gen_rays(num_rays=bundlesize / float(procs),
flux=self.flux / float(procs)))
e.multi_ray_sim(sources=sources, procs=procs)
self.plant = e._asm
self.field._heliostats = self.plant._assemblies[0].get_surfaces()
self.rec = self.plant._objects[0].get_surfaces()[0]
timer_mcrt += time.clock() - mcrt
postprocess = time.clock()
# Render:
if render:
trace_scene = Renderer(e)
trace_scene.show_rays(resolution=10)
# Get the energy and location of all hits using optics manager
en, pts = self.rec.get_optics_manager().get_all_hits()
x, y = self.rec.global_to_local(pts)[:2]
# FLUX MAP OPERATIONS
#===========================================================================
H, xbins, ybins = N.histogram2d(x,
y,
bins,
weights=en / (dlw * dlh) * 1e-3)
extent = [ybins[0], ybins[-1], xbins[-1], xbins[0]]
fluxmap = (fluxmap * float(i) + H) / (i + 1.)
#===========================================================================
# BLOCKAGE and SHADING
#===========================================================================
# Detect blockage and look for the parents of the blocked rays. Identify from which heliostats the parents come and associate the blockage losses to the heliostats where blockage is suffered.
hz = (e.tree._bunds[1].get_vertices()[2]) < (self.field._th -
self.rec_h / 2.)
hits_helios += N.sum(hz)
print 'Useful rays:', hits_helios
# Get the 3rd bundle (after 2 hits):
bund_2 = e.tree._bunds[2].get_vertices()
bund_2_ener = e.tree._bunds[2].get_energy()
# Remove receiver hits from the bundle to get only hits on heliostats:
bund_2_helio_hits = N.ravel(
N.nonzero(bund_2[2] < (self.field._th - self.rec_h / 2.)))
bund_2_bloc = bund_2[:, bund_2_helio_hits]
# Get the bundle emitting the blocked rays and isolate the blocked rays:
bund_1_helio_blocs = e.tree._bunds[2].get_parents(
)[bund_2_helio_hits]
bund_1 = e.tree._bunds[1].get_vertices()
bund_1_ener = e.tree._bunds[1].get_energy()
bund_1_bloc = bund_1[:, bund_1_helio_blocs]
# Screen the field to find where blocked rays originate:
for h in xrange(len(self.pos)):
# Get the information from the optics manager of the heliostat:
abs_hstats, hits_hstats, dirs_hstats = self.field._heliostats[
h].get_optics_manager().get_all_hits()
blocs = []
hit_0s = []
# Check if any hits:
if len(hits_hstats) != 0:
# Screen through every hit:
for r in xrange(N.shape(hits_hstats)[1]):
# Is the hit a ray that will be blocked or a blocked ray?
bloc = N.nonzero(hits_hstats[0,
r] == bund_1_bloc[0])[0]
# Next "if" is because if there are no valid hits the bloc returns an empty array or to isolate each hit in case of 2 hits matching.
if len(bloc) > 0:
for b in xrange(len(bloc)):
# If sthe first coordinate matches, do the rest of them?
if (hits_hstats[:, r] == N.ravel(
bund_1_bloc[:, bloc[b]])).all():
# If so add the blocked energy to the result bin.
blocs.append(bund_1_helio_blocs[bloc[b]])
else:
hit_0 = N.nonzero(hits_hstats[0,
r] == bund_1[0])[0]
if len(hit_0) > 0:
for s in xrange(len(hit_0)):
if (hits_hstats[:, r] == N.ravel(
bund_1[:, hit_0[s]])).all():
hit_0s.append(
e.tree._bunds[1].get_parents()[
hit_0[s]])
prev_blocking[h] = blocking[h]
# Monte-Carlo sampling:
blocking[h] = (blocking[h] * i +
N.sum(bund_1_ener[blocs])) / (i + 1.)
# Shading is the theoretical energy hitting subtracted by the energy absorbed without the backside blocking.
prev_incoming[h] = incoming[h]
# Monte-Carlo sampling:
incoming[h] = (incoming[h] * i + N.sum(
e.tree._bunds[0].get_energy()[hit_0s])) / (i + 1.)
prev_shading[h] = shading[h]
# Monte-Carlo sampling:
shading[h] = (shading[h] * i +
self.flux * self.hstat_proj_areas[h] -
incoming[h]) / (i + 1.)
# Streamlined stats variable:
incoming_Q = incoming_Q + i / (i + 1.) * (incoming -
prev_incoming)**2.
blocking_Q = blocking_Q + i / (i + 1.) * (blocking -
prev_blocking)**2.
shading_Q = shading_Q + i / (i + 1.) * (shading - prev_shading)**2.
# Standard deviatiosn updates:
if i > 0:
incoming_stdev = N.sqrt(incoming_Q / i)
blocking_stdev = N.sqrt(blocking_Q / i)
shading_stdev = N.sqrt(shading_Q / i)
print 'Shading=', N.sum(shading)
print 'Blockage=', N.sum(blocking)
timer_postprocess += time.clock() - postprocess
print 'timer_mcrt: ', timer_mcrt / 60., 'min'
print 'timer_postprocess: ', timer_postprocess / 60., 'min'
print 'Peak flux (kW/m2):', N.amax(fluxmap)
print 'AVG flux (kW/m2): ', N.sum(fluxmap) / (N.shape(fluxmap)[0] *
N.shape(fluxmap)[1])
print 'Total radiative power (kW): ', N.sum(fluxmap *
(11. / 50.)**2)
i += 1
#===========================================================================
e.tree._bunds = []
for clear in xrange(len(e._asm.get_surfaces())):
e._asm.get_surfaces()[clear].get_optics_manager().reset()
#===========================================================================
del (self.plant)
results = {
'positions': self.pos,
'blocking': blocking,
'blocking_stdev': blocking_stdev,
'shading': shading,
'shading_stdev': shading_stdev,
'incoming': incoming,
'incoming_stdev': incoming_stdev,
'fluxmap': fluxmap,
'extent': extent,
'width': self.width,
'height': self.height,
'absorptivity': self.absorptivity,
'rec_width': self.rec_w,
'rec_height': self.rec_h,
'rec_bins': self.bins
}
filesave = open(
'/home/charles/Documents/Boulot/These/Heliostat field/Sandia_data',
'w')
pickle.dump(results, filesave)
filesave.close()
def trace(self, num_rays=1e5, nbins_w=50., nbins_h=50.):
'''
Raytrace method.
Raytraces successive bundles and stores the resultsogf the shading, blicking, incoming radiative power on the heliostats and the fluxmap on the receiver.
'''
# Generate a large ray bundle using [a radial stagger much denser
# than the field] a Buie sunshape with radius equal to the longest
# dimension of the field.
#=============
render = False
#=============
sun_vec = solar_vector(self.sun_az * degree, self.sun_zenith * degree)
bundlesize = 1e4
iters = int(num_rays / bundlesize)
# Results bins:
incoming = N.zeros(len(self.pos))
prev_incoming = N.zeros(len(self.pos))
incoming_Q = N.zeros(len(self.pos))
incoming_stdev = N.zeros(len(self.pos))
shading = N.ones(len(self.pos))
prev_shading = N.zeros(len(self.pos))
shading_Q = N.zeros(len(self.pos))
shading_stdev = N.zeros(len(self.pos))
blocking = N.zeros(len(self.pos))
prev_blocking = N.zeros(len(self.pos))
blocking_Q = N.zeros(len(self.pos))
blocking_stdev = N.zeros(len(self.pos))
timer_mcrt = 0.
timer_postprocess = 0.
# Receiver bins:
dlw = self.rec_w / nbins_w
dlh = self.rec_h / nbins_h
bins_w = N.arange(-self.rec_w / 2., self.rec_w / 2. + dlw, dlw)
bins_h = N.arange(-self.rec_h / 2., self.rec_h / 2. + dlh, dlh)
bins = [bins_w, bins_h]
self.bins = bins
fluxmap = N.zeros((len(bins_w) - 1, len(bins_h) - 1))
# Raytrace:
mcrt = time.clock()
e = TracerEngineMP(self.plant)
procs = 1
e.minener = 1e-10
timer_mcrt += time.clock() - mcrt
hits_helios = 0
i = 0
#while hits_helios < num_rays:
for i in xrange(iters):
print ' '
print ' '
print 'ITERATION ', i + 1, ' of ', iters
#print hits_helios, 'hits out of ', num_rays
mcrt = time.clock()
# Perform the trace:
sources = []
self.flux = 1000.
for s in xrange(procs):
sources.append(
self.gen_rays(num_rays=bundlesize / float(procs),
flux=self.flux / float(procs)))
e.multi_ray_sim(sources=sources, procs=procs)
self.plant = e._asm
self.field._heliostats = self.plant._assemblies[0].get_surfaces()
self.rec = self.plant._objects[0].get_surfaces()[0]
timer_mcrt += time.clock() - mcrt
postprocess = time.clock()
# Render:
if render:
trace_scene = Renderer(e)
trace_scene.show_rays(resolution=10)
# Get the energy and location of all hits using optics manager
en, pts = self.rec.get_optics_manager().get_all_hits()
x, y = self.rec.global_to_local(pts)[:2]
# FLUX MAP OPERATIONS
#===========================================================================
H, xbins, ybins = N.histogram2d(x,
y,
bins,
weights=en / (dlw * dlh) * 1e-3)
extent = [ybins[0], ybins[-1], xbins[-1], xbins[0]]
fluxmap = (fluxmap * float(i) + H) / (i + 1.)
#===========================================================================
# BLOCKAGE and SHADING
#===========================================================================
# Detect blockage and look for the parents of the blocked rays. Identify from which heliostats the parents come and associate the blockage losses to the heliostats where blockage is suffered.
hz = (e.tree._bunds[1].get_vertices()[2]) < (self.field._th -
self.rec_h / 2.)
hits_helios += N.sum(hz)
print 'Useful rays:', hits_helios
# Get the 3rd bundle (after 2 hits):
bund_2 = e.tree._bunds[2].get_vertices()
bund_2_ener = e.tree._bunds[2].get_energy()
# Remove receiver hits from the bundle to get only hits on heliostats:
bund_2_helio_hits = N.ravel(
N.nonzero(bund_2[2] < (self.field._th - self.rec_h / 2.)))
bund_2_bloc = bund_2[:, bund_2_helio_hits]
# Get the bundle emitting the blocked rays and isolate the blocked rays:
bund_1_helio_blocs = e.tree._bunds[2].get_parents(
)[bund_2_helio_hits]
bund_1 = e.tree._bunds[1].get_vertices()
bund_1_ener = e.tree._bunds[1].get_energy()
bund_1_bloc = bund_1[:, bund_1_helio_blocs]
# Screen the field to find where blocked rays originate:
for h in xrange(len(self.pos)):
# Get the information from the optics manager of the heliostat:
abs_hstats, hits_hstats, dirs_hstats = self.field._heliostats[
h].get_optics_manager().get_all_hits()
blocs = []
hit_0s = []
# Check if any hits:
if len(hits_hstats) != 0:
# Screen through every hit:
for r in xrange(N.shape(hits_hstats)[1]):
# Is the hit a ray that will be blocked or a blocked ray?
bloc = N.nonzero(hits_hstats[0,
r] == bund_1_bloc[0])[0]
# Next "if" is because if there are no valid hits the bloc returns an empty array or to isolate each hit in case of 2 hits matching.
if len(bloc) > 0:
for b in xrange(len(bloc)):
# If sthe first coordinate matches, do the rest of them?
if (hits_hstats[:, r] == N.ravel(
bund_1_bloc[:, bloc[b]])).all():
# If so add the blocked energy to the result bin.
blocs.append(bund_1_helio_blocs[bloc[b]])
else:
hit_0 = N.nonzero(hits_hstats[0,
r] == bund_1[0])[0]
if len(hit_0) > 0:
for s in xrange(len(hit_0)):
if (hits_hstats[:, r] == N.ravel(
bund_1[:, hit_0[s]])).all():
hit_0s.append(
e.tree._bunds[1].get_parents()[
hit_0[s]])
prev_blocking[h] = blocking[h]
# Monte-Carlo sampling:
blocking[h] = (blocking[h] * i +
N.sum(bund_1_ener[blocs])) / (i + 1.)
# Shading is the theoretical energy hitting subtracted by the energy absorbed without the backside blocking.
prev_incoming[h] = incoming[h]
# Monte-Carlo sampling:
incoming[h] = (incoming[h] * i + N.sum(
e.tree._bunds[0].get_energy()[hit_0s])) / (i + 1.)
prev_shading[h] = shading[h]
# Monte-Carlo sampling:
shading[h] = (shading[h] * i +
self.flux * self.hstat_proj_areas[h] -
incoming[h]) / (i + 1.)
# Streamlined stats variable:
incoming_Q = incoming_Q + i / (i + 1.) * (incoming -
prev_incoming)**2.
blocking_Q = blocking_Q + i / (i + 1.) * (blocking -
prev_blocking)**2.
shading_Q = shading_Q + i / (i + 1.) * (shading - prev_shading)**2.
# Standard deviatiosn updates:
if i > 0:
incoming_stdev = N.sqrt(incoming_Q / i)
blocking_stdev = N.sqrt(blocking_Q / i)
shading_stdev = N.sqrt(shading_Q / i)
print 'Shading=', N.sum(shading)
print 'Blockage=', N.sum(blocking)
timer_postprocess += time.clock() - postprocess
print 'timer_mcrt: ', timer_mcrt / 60., 'min'
print 'timer_postprocess: ', timer_postprocess / 60., 'min'
print 'Peak flux (kW/m2):', N.amax(fluxmap)
print 'AVG flux (kW/m2): ', N.sum(fluxmap) / (N.shape(fluxmap)[0] *
N.shape(fluxmap)[1])
print 'Total radiative power (kW): ', N.sum(fluxmap *
(11. / 50.)**2)
i += 1
#===========================================================================
e.tree._bunds = []
for clear in xrange(len(e._asm.get_surfaces())):
e._asm.get_surfaces()[clear].get_optics_manager().reset()
#===========================================================================
del (self.plant)
results = {
'positions': self.pos,
'blocking': blocking,
'blocking_stdev': blocking_stdev,
'shading': shading,
'shading_stdev': shading_stdev,
'incoming': incoming,
'incoming_stdev': incoming_stdev,
'fluxmap': fluxmap,
'extent': extent,
'width': self.width,
'height': self.height,
'absorptivity': self.absorptivity,
'rec_width': self.rec_w,
'rec_height': self.rec_h,
'rec_bins': self.bins
}
filesave = open(
'/home/charles/Documents/Boulot/These/Heliostat field/Sandia_data',
'w')
pickle.dump(results, filesave)
filesave.close()
def gen_plant(self):
#--------------
# field
#--------------
# heliostats
self.hst_w = 1.85
self.hst_h = 2.44
reflectivity = 0.9
slope_type = 'normal' #'normal' or 'pillbox' or 'perfect'-- for one mirror only
slope_error = 1.64e-3 #rad (0 is a perfect mirror)
curved = True # or False: flat mirror
self.oneMirror = False # or True: for simulating just one mirror
hst_file = './examples/heliostat_field_example/hst_info.csv' #or None
#hst_file=None
if self.oneMirror:
if hst_file != None:
# index of the position of the heliostats
index = 2
pos = N.zeros(3)
foc = 0.
else:
# or hst_file=None,by putting the specific pos and focal
index = -1 #
pos = N.r_[0., 20., 0.]
foc = 30.
else:
index = -1
pos = N.zeros(3)
foc = 0.
heliostat = HeliostatGenerator(self.hst_w,
self.hst_h,
absorptivity=1. - reflectivity,
sigma_xy=slope_error,
slope=slope_type,
curved=curved,
one_mirror=self.oneMirror,
index=index,
pos=pos,
foc=foc)
# layout and field
layout = KnownField(hst_file, pos, foc)
# tracking
tracking_mode = 'AzEl' # 'AzEl'or 'TiltRoll'
# aiming
aiming_mode = 'SinglePoint' # 'MultiFixed' or 'SinglePoint'
#---------------
# receiver
#---------------
rec_w = 1.3
rec_h = 1.3
absorptivity = 0.96
rec_loc = N.r_[0., 0., 26.8] # receiver location
rec_rot = N.r_[106., 0.,
0.] * degree # receiver rot through x, y, z (rad)
receiver = FlatOneSidedReceiver(rec_w, rec_h, absorptivity)
mount_rec = MountReceiver(rec_loc, rec_rot)
#--------------
# solar
#--------------
self.sunshape = 'pillbox'
self.sigma = 4.65e-3
self.DNI = 1000.
sun_az = 180.
sun_zenith = 0.
self.sun_vec = solar_vector(sun_az, sun_zenith)
tower_scene = TowerScene(self.sun_vec, self.oneMirror)
tower_scene(heliostat, layout, aiming_mode, tracking_mode, receiver,
mount_rec)
self.system = tower_scene.system
self.pos = heliostat.pos
def gen_plant(self):
# define the case
if self.case[0]=='A':
if self.case[1]=='1':
if self.case[:4]=='A1.1':
distribution='pillbox'
err=float(self.case[-1])*1.e-3
self.A1(err, distribution)
elif self.case[:4]=='A1.2':
distribution='normal'
err=float(self.case[-1])*1.e-3
self.A1(err, distribution)
elif self.case[1]=='2':
if self.case[3]=='1':
sunshape='pillbox'
self.A2(sunshape)
elif self.case[3]=='2':
sunshape='gaussian'
self.A2(sunshape)
else:
sunshape='buie'
CSR=float(self.case[-1])*1.e-2
self.A2(sunshape, CSR)
else:
if self.case[-1]=='1':
sunshape='pillbox'
else:
sunshape='buie'
self.A3(sunshape)
elif self.case[0]=='B':
if self.case[1]=='1':
sunshape='pillbox'
else:
sunshape='buie'
if self.case[3]=='1':
# solar noon
sun_az=0.
sun_zenith=12.
else:
# morning
sun_az=-104.
sun_zenith=68.
if self.case[-1]=='1':
hst_pos=N.r_[0., 46.5, 0.]
elif self.case[-1]=='2':
hst_pos=N.r_[0., 536.9, 0.]
elif self.case[-1]=='3':
hst_pos=N.r_[-324.3, 427.9, 0.]
else:
hst_pos=N.r_[252.5, 118.1, 0.]
self.B(hst_pos, sunshape, sun_az, sun_zenith)
elif self.case[0]=='C':
if self.case[1]=='1':
sunshape='pillbox'
else:
sunshape='buie'
if self.case[3]=='1':
# solar noon
sun_az=0.
sun_zenith=12.
else:
# morning
sun_az=-104.
sun_zenith=68.
self.C(sunshape, sun_az, sun_zenith)
self.output_parameters(self.savefolder)
#--------------
# field
#--------------
heliostat=HeliostatGenerator(self.hst_w, self.hst_h, absorptivity=1.-self.reflectivity, sigma_xy=self.slope_error, slope=self.slope_type,curved=self.curved, one_mirror=self.oneMirror, index=self.index, pos=self.pos, foc=self.foc)
# layout and field
layout=KnownField(self.hst_file,self.pos,self.foc)
#---------------
# receiver
#---------------
self.loc_z=self.rec_loc[-1]
receiver=FlatOneSidedReceiver(self.rec_w,self.rec_h,self.absorptivity)
mount_rec=MountReceiver(self.rec_loc,self.rec_rot)
#--------------
# solar
#--------------
self.sun_vec=solar_vector(self.sun_az, self.sun_zenith)
if self.sunshape=='buie':
self.BUIE=buie_integration(CSR=self.sun_width, preproc_CSR='CA')
else:
self.BUIE=None
# Creating the tower scene
#------------------------------
tower_scene=TowerScene(self.sun_vec, self.oneMirror)
tower_scene(heliostat, layout, self.aiming_mode, self.tracking_mode,receiver,mount_rec)
self.system=tower_scene.system
self.pos=heliostat.pos
if self.oneMirror:
self.num_hst=1
else:
self.num_hst=len(self.pos)