def integBulkBc(rad, field, ri, ro, lambdai, lambdao, normed=False):
"""
This function evaluates the radial integral of the input array field
in the boundary layer and in the bulk separately.
:param rad: radius
:type rad: numpy.ndarray
:param field: the input radial profile
:type field: numpy.ndarray
:param ri: the inner core radius
:type ri: float
:param ro: the outer core radius
:type ro: float
:param lambdai: thickness of the inner boundary layer
:type lambdai: float
:param lambdao: thickness of the outer boundary layer
:type lambdao: float
:param normed: when set to True, the outputs are normalised by the volumes
of the boundary layers and the fluid bulk, respectively. In
that case, the outputs are volume-averaged quantities.
:type normed: bool
:returns: two floats that contains the boundary layer and the bulk
integrations (integBc, integBulk)
:rtype: list
"""
# Dissipation in the boundary layers
field2 = field.copy()
mask = (rad<=ro-lambdao) * (rad>=ri+lambdai)
field2[mask] = 0.
integBc = intcheb(field2, len(field2)-1, ri, ro)
if normed:
volBc1 = 4./3.*N.pi*(ro**3-(ro-lambdao)**3)
volBc2 = 4./3.*N.pi*((ri+lambdai)**3-(ri)**3)
volBc = volBc1+volBc2
integBc = integBc/volBc
# Dissipation in the bulk
field2 = field.copy()
mask = (rad>ro-lambdao)
field2[mask] = 0.
mask = (rad<ri+lambdai)
field2[mask] = 0.
integBulk = intcheb(field2, len(field2)-1, ri, ro)
if normed:
volBulk = 4./3.*N.pi*((ro-lambdao)**3-(ri+lambdai)**3)
integBulk = integBulk/volBulk
return integBc, integBulk
def integBotTop(rad, field, ri, ro, lambdai, lambdao, normed=False):
"""
This function evaluates the radial integral of the input array field
in the bottom and top boundary layers separately.
:param rad: radius
:type rad: numpy.ndarray
:param field: the input radial profile
:type field: numpy.ndarray
:param ri: the inner core radius
:type ri: float
:param ro: the outer core radius
:type ro: float
:param lambdai: thickness of the inner boundary layer
:type lambdai: float
:param lambdao: thickness of the outer boundary layer
:type lambdao: float
:param normed: when set to True, the outputs are normalised by the volumes
of the boundary layers. In that case, the outputs are
volume-averaged quantities.
:type normed: bool
:returns: two floats that contains the bottom and top boundary layers
integrations (integBot, integTop)
:rtype: list
"""
field2 = field.copy()
mask = (rad<=ro-lambdao)
field2[mask] = 0.
integTop = intcheb(field2, len(field2)-1, ri, ro)
field2 = field.copy()
mask = (rad>=ri+lambdai)
field2[mask] = 0.
integBot = intcheb(field2, len(field2)-1, ri, ro)
if normed:
volBc1 = 4./3.*N.pi*(ro**3-(ro-lambdao)**3)
volBc2 = 4./3.*N.pi*((ri+lambdai)**3-(ri)**3)
integTop /= volBc1
integBot /= volBc2
return integBot, integTop
def __init__(self, iplot=False, quiet=False):
"""
:param iplot: display the result when set to True (default False)
:type iplot: bool
:param quiet: less verbose when set to True (default is False)
:type quiet: bool
"""
if os.path.exists('tInitAvg'):
file = open('tInitAvg', 'r')
tstart = float(file.readline())
file.close()
logFiles = scanDir('log.*')
tags = []
for lg in logFiles:
nml = MagicSetup(quiet=True, nml=lg)
if nml.start_time > tstart:
if os.path.exists('bLayersR.%s' % nml.tag):
tags.append(nml.tag)
if len(tags) > 0:
print(tags)
else:
tags = None
MagicSetup.__init__(self, quiet=True, nml=logFiles[-1])
a = AvgField()
self.nuss = a.nuss
self.reynolds = a.reynolds
else:
logFiles = scanDir('log.*')
MagicSetup.__init__(self, quiet=True, nml=logFiles[-1])
tags = None
self.nuss = 1.
self.reynolds = 1.
par = MagicRadial(field='bLayersR', iplot=False, tags=tags)
self.varS = N.sqrt(N.abs(par.varS))
self.ss = par.entropy
if os.path.exists('tInitAvg'):
logFiles = scanDir('log.*', tfix=1409827718.0)
# Workaround for code mistake before this time
tfix = 1409827718.0
tagsFix = []
for lg in logFiles:
nml = MagicSetup(quiet=True, nml=lg)
if nml.start_time > tstart:
if os.path.exists('bLayersR.%s' % nml.tag):
tagsFix.append(nml.tag)
if len(tagsFix) > 0:
print('Fix temp. tags', tagsFix)
parFix = MagicRadial(field='bLayersR', iplot=False, tags=tagsFix)
self.varS = N.sqrt(N.abs(parFix.varS))
self.ss = parFix.entropy
self.tags = tagsFix
self.uh = par.uh
self.duh = par.duhdr
self.rad = par.radius
self.ro = self.rad[0]
self.ri = self.rad[-1]
self.reh = 4.*N.pi*intcheb(self.rad**2*self.uh, len(self.rad)-1,
self.ri, self.ro)/(4./3.*N.pi*(self.ro**3-self.ri**3))
# Thermal dissipation boundary layer
if hasattr(par, 'dissS'):
self.dissS = par.dissS
self.epsT = -4.*N.pi*intcheb(self.rad**2*self.dissS, len(self.rad)-1,
self.ro, self.ri)
self.epsTR = 4.*N.pi*self.rad**2*self.dissS
ind = getMaxima(-abs(self.epsTR-self.epsT))
try:
self.dissTopS = self.ro-self.rad[ind[0]]
self.dissBotS = self.rad[ind[-1]]-self.ri
self.dissEpsTbl, self.dissEpsTbulk = integBulkBc(self.rad, self.epsTR,
self.ri, self.ro, self.dissBotS, self.dissTopS)
except IndexError:
self.dissTopS = self.ro
self.dissBotS = self.ri
self.dissEpsTbl, self.dissEpsTbulk = 0., 0.
print('thDiss bl, bulk', self.dissEpsTbl/self.epsT, self.dissEpsTbulk/self.epsT)
# First way of defining the thermal boundary layers: with var(S)
#rThLayer = getMaxima(self.rad, self.varS)
ind = argrelextrema(self.varS, N.greater)[0]
if len(ind) != 0:
self.bcTopVarS = self.ro-self.rad[ind[0]]
self.bcBotVarS = self.rad[ind[-1]]-self.ri
else:
self.bcTopVarS = 1.
self.bcBotVarS = 1.
if hasattr(self, 'epsT'):
self.varSEpsTbl, self.varSEpsTbulk = integBulkBc(self.rad, self.epsTR,
self.ri, self.ro, self.bcBotVarS, self.bcTopVarS)
print('var(S) bl, bulk', self.varSEpsTbl/self.epsT, self.varSEpsTbulk/self.epsT)
# Second way of defining the thermal boundary layers: intersection of the slopes
d1 = matder(len(self.rad)-1, self.ro, self.ri)
self.ttm = 3.*intcheb(self.ss*self.rad**2, len(self.rad)-1, self.ri, self.ro) \
/(self.ro**3-self.ri**3)
dsdr = N.dot(d1, self.ss)
self.beta = dsdr[len(dsdr)/2]
print('beta', self.beta)
self.slopeTop = dsdr[2]*(self.rad-self.ro)+self.ss[0]
self.slopeBot = dsdr[-1]*(self.rad-self.ri)+self.ss[-1]
self.dtdrm = dsdr[len(self.ss)/2]
self.slopeMid = self.dtdrm*(self.rad-(self.ri+self.ro)/2.)+self.ss[len(self.ss)/2]
#self.bcTopSlope = -(self.ttm-self.ss[0])/dsdr[2]
self.bcTopSlope = (self.ss[len(self.ss)/2]-self.ss[0])/(self.dtdrm-dsdr[2])
#self.bcBotSlope = (self.ttm-self.ss[-1])/(dsdr[-1])
self.bcBotSlope = -(self.ss[len(self.ss)/2]-self.ss[-1])/(self.dtdrm-dsdr[-1])
# 2nd round with a more accurate slope
bSlope = dsdr[self.rad <= self.ri+self.bcBotSlope/4.].mean()
tSlope = dsdr[self.rad >= self.ro-self.bcTopSlope/4.].mean()
self.slopeBot = bSlope*(self.rad-self.ri)+self.ss[-1]
self.slopeTop = tSlope*(self.rad-self.ro)+self.ss[0]
#self.bcTopSlope = -(self.ttm-self.ss[0])/tSlope
self.bcTopSlope = (self.ss[len(self.ss)/2]-self.ss[0])/(self.dtdrm-tSlope)
#self.bcBotSlope = (self.ttm-self.ss[-1])/bSlope
self.bcBotSlope = -(self.ss[len(self.ss)/2]-self.ss[-1])/(self.dtdrm-bSlope)
if hasattr(self, 'epsT'):
self.slopeEpsTbl, self.slopeEpsTbulk = integBulkBc(self.rad, self.epsTR,
self.ri, self.ro, self.bcBotSlope, self.bcTopSlope)
print('slopes bl, bulk', self.slopeEpsTbl/self.epsT, self.slopeEpsTbulk/self.epsT)
pow = MagicRadial(field='powerR', iplot=False, tags=tags)
self.vi = pow.viscDiss
self.buo = pow.buoPower
self.epsV = -intcheb(self.vi, len(self.rad)-1, self.ro, self.ri)
ind = getMaxima(-abs(self.vi-self.epsV))
if len(ind) > 2:
for i in ind:
if self.vi[i-1]-self.epsV > 0 and self.vi[i+1]-self.epsV < 0:
self.dissTopV = self.ro-self.rad[i]
elif self.vi[i-1]-self.epsV < 0 and self.vi[i+1]-self.epsV > 0:
self.dissBotV = self.rad[i]-self.ri
else:
self.dissTopV = self.ro-self.rad[ind[0]]
self.dissBotV = self.rad[ind[-1]]-self.ri
self.dissEpsVbl, self.dissEpsVbulk = integBulkBc(self.rad, self.vi,
self.ri, self.ro, self.dissBotV, self.dissTopV)
print('visc Diss bl, bulk', self.dissEpsVbl/self.epsV, self.dissEpsVbulk/self.epsV)
# First way of defining the viscous boundary layers: with duhdr
#rViscousLayer = getMaxima(self.rad, self.duh)
if self.kbotv == 1 and self.ktopv == 1:
ind = argrelextrema(self.duh, N.greater)[0]
if len(ind) == 0:
self.bcTopduh = 1.
self.bcBotduh = 1.
else:
if ind[0] < 4:
self.bcTopduh = self.ro-self.rad[ind[1]]
else:
self.bcTopduh = self.ro-self.rad[ind[0]]
if len(self.rad)-ind[-1] < 4:
self.bcBotduh = self.rad[ind[-2]]-self.ri
else:
self.bcBotduh = self.rad[ind[-1]]-self.ri
self.slopeTopU = 0.
self.slopeBotU = 0.
self.uhTopSlope = 0.
self.uhBotSlope = 0.
self.slopeEpsUbl = 0.
self.slopeEpsUbulk = 0.
self.uhBot = 0.
self.uhTop = 0.
else:
ind = argrelextrema(self.uh, N.greater)[0]
if len(ind) == 1:
ind = argrelextrema(self.uh, N.greater_equal)[0]
if len(ind) == 0:
self.bcTopduh = 1.
self.bcBotduh = 1.
else:
if ind[0] < 4:
self.bcTopduh = self.ro-self.rad[ind[1]]
else:
self.bcTopduh = self.ro-self.rad[ind[0]]
if len(self.rad)-ind[-1] < 4:
self.bcBotduh = self.rad[ind[-2]]-self.ri
else:
self.bcBotduh = self.rad[ind[-1]]-self.ri
self.uhTop = self.uh[self.rad==self.ro-self.bcTopduh][0]
self.uhBot = self.uh[self.rad==self.ri+self.bcBotduh][0]
self.bcBotduh, self.bcTopduh, self.uhBot, self.uhTop = \
getAccuratePeaks(self.rad, self.uh, self.uhTop, \
self.uhBot, self.ri, self.ro)
duhdr = N.dot(d1, self.uh)
#1st round
mask = (self.rad>=self.ro-self.bcTopduh/4)*(self.rad<self.ro)
slopeT = duhdr[mask].mean()
mask = (self.rad<=self.ri+self.bcBotduh/4)*(self.rad>self.ri)
slopeB = duhdr[mask].mean()
self.slopeTopU = slopeT*(self.rad-self.ro)+self.uh[0]
self.slopeBotU = slopeB*(self.rad-self.ri)+self.uh[-1]
self.uhTopSlope = -self.uhTop/slopeT
self.uhBotSlope = self.uhBot/slopeB
#2nd round
mask = (self.rad>=self.ro-self.uhTopSlope/4.)*(self.rad<self.ro)
slopeT = duhdr[mask].mean()
mask = (self.rad<=self.ri+self.uhBotSlope/4)*(self.rad>self.ri)
slopeB = duhdr[mask].mean()
self.uhTopSlope = -self.uhTop/slopeT
self.uhBotSlope = self.uhBot/slopeB
self.slopeEpsUbl, self.slopeEpsUbulk = integBulkBc(self.rad, self.vi,
self.ri, self.ro, self.uhBotSlope, self.uhTopSlope)
self.uhEpsVbl, self.uhEpsVbulk = integBulkBc(self.rad, self.vi,
self.ri, self.ro, self.bcBotduh, self.bcTopduh)
print('uh bl, bulk', self.uhEpsVbl/self.epsV, self.uhEpsVbulk/self.epsV)
# Convective Rol in the thermal boundary Layer
par = MagicRadial(field='parR', iplot=False, tags=tags)
kin = MagicRadial(field='eKinR', iplot=False, tags=tags)
ekinNas = kin.ekin_pol+kin.ekin_tor-kin.ekin_pol_axi-kin.ekin_tor_axi
ReR = N.sqrt(2.*abs(ekinNas)/par.radius**2/(4.*N.pi))
RolC = ReR*par.ek/par.dlVc
self.dl = par.dlVc
y = RolC[par.radius >= self.ro-self.bcTopSlope]
x = par.radius[par.radius >= self.ro-self.bcTopSlope]
self.rolTop = simps(3.*y*x**2, x)/(self.ro**3-(self.ro-self.bcTopSlope)**3)
self.rolbl, self.rolbulk = integBulkBc(self.rad, 4.*N.pi*RolC*self.rad**2,
self.ri, self.ro, self.bcBotSlope, self.bcTopSlope,
normed=True)
self.rebl, self.rebulk = integBulkBc(self.rad, 4.*N.pi*ReR*self.rad**2,
self.ri, self.ro, self.bcBotduh, self.bcTopduh,
normed=True)
self.lengthbl, self.lengthbulk = integBulkBc(self.rad, par.dlVc,
self.ri, self.ro, self.bcBotSlope, self.bcTopSlope,
normed=True)
self.rehbl, self.rehbulk = integBulkBc(self.rad, self.uh*4.*N.pi*self.rad**2,
self.ri, self.ro, self.bcBotduh, self.bcTopduh,
normed=True)
y = RolC[par.radius <= self.ri+self.bcBotSlope]
x = par.radius[par.radius <= self.ri+self.bcBotSlope]
self.rolBot = simps(3.*y*x**2, x)/((self.ri+self.bcBotSlope)**3-self.ri**3)
print('reynols bc, reynolds bulk', self.rebl, self.rebulk)
print('reh bc, reh bulk', self.rehbl, self.rehbulk)
print('rolbc, rolbulk, roltop, rolbot', self.rolbl, self.rolbulk, self.rolBot, self.rolTop)
par.dlVc[0] = 0.
par.dlVc[-1] = 0.
self.lBot, self.lTop = integBotTop(self.rad, 4.*N.pi*self.rad**2*par.dlVc,
self.ri, self.ro, self.bcBotSlope, self.bcTopSlope, normed=True)
uhbm, utbm = integBotTop(self.rad, 4.*N.pi*self.uh,
self.ri, self.ro, self.bcBotSlope, self.bcTopSlope, normed=True)
if iplot:
self.plot()
if not quiet:
print(self)
