def murakami(molar_abundance):
al_p = 0.075
pv_X_Mg = 0.94
fp_X_Mg = 0.79
molar_weight=[pv_X_Mg*molar_mass['Mg']+(1.-pv_X_Mg)*molar_mass['Fe']+(1.-al_p)*molar_mass['Si']+al_p*molar_mass['Al']+3.*molar_mass['O'], \
fp_X_Mg*molar_mass['Mg']+(1.-fp_X_Mg)*molar_mass['Fe']+molar_mass['O']]
list_p = []
list_Vs = []
list_Vp = []
pv_density = []
fp_density = []
pv_shearmod = []
fp_shearmod = []
prem_shearmod = []
for p in numpy.arange(28,141,5.):
#T=geotherm.geotherm_formula(p)
#T=geotherm.geotherm(p)
T=geotherm.geotherm_brown(p) #by far the best fit
density = [0., 0.]
bulk_mod =[0., 0.]
shear_mod = [0., 0.]
# pv:
# values from ricolleau table 1
V0 = 164.
K_0 = 245.
K_prime = 4.
dKdT = -.036
a_0 = 3.19e-5
a_1 = 0.88e-8
gamma_0 = 1.48
atoms_per_unit_cell = 4.
G_0 = 166.
G_prime = 1.57
#dGdT = -.02 unused
eta_0s = 2.4
q = 1.4
n = 5.
#murakami supp. material Table 5:
K_0 = 281.
K_prime = 4.1
G_0 = 173. #-25. #looks good :-)
G_prime = 1.56
V, density[0], bulk_mod[0], shear_mod[0] \
= compute_moduli(p,T,V0,K_0,K_prime,dKdT,a_0,a_1,gamma_0, molar_weight[0], atoms_per_unit_cell,n, eta_0s, q, G_0, G_prime)
pv_density.append(density[0])
# fp:
# values from ricolleau table 1
if (p<=50.):
V0 = 76.44
K_0 = 158.
K_prime = 4.
dKdT = -.034
a_0 = 2.20e-5
a_1 = 3.61e-8
else:
V0 = 74.04
K_0 = 170.
K_prime = 4.
dKdT = -.034
a_0 = 2.20e-5
a_1 = 3.61e-8
#missing values, should we use 0?
#dKdT = 0.
#a_0 = 0.
#a_1 = 0.
gamma_0 = 1.50
atoms_per_unit_cell = 4.
if (p>=50.): # reading from fig 3 in Murakami (X_Mg=0.79)
G_0 = 116. # low spin
G_prime = 1.65
#dGdT = -.02 unused
else:
G_0 = 103. # high spin
G_prime = 1.78
#dGdT = -.02 unused
eta_0s = 3.0
q = 1.5
n = 2.
V, density[1], bulk_mod[1],shear_mod[1] \
= compute_moduli(p,T,V0,K_0,K_prime,dKdT,a_0,a_1,gamma_0, molar_weight[1], atoms_per_unit_cell,n, eta_0s, q, G_0, G_prime)
fp_density.append(density[1])
#if (p>=50.): # from the text in Murakami (page 2), X_Mg = 0.92
# shear_mod[1] = 130. + 2.04*p -.02*(T-300) # low spin
#else:
# shear_mod[1] = 113. + 2.15*p -.02*(T-300)
pv_shearmod.append(shear_mod[0])
fp_shearmod.append(shear_mod[1])
V_p,V_s,V_phi = seismic.get_velocities(molar_abundance, molar_weight, bulk_mod, shear_mod, density, T)
list_p.append(p)
list_Vp.append(V_p)
list_Vs.append(V_s)
# shearmodulus = density * V_s^2: (Sanne)
prem_shearmod.append(prem.prem_density(p)*pow(prem.prem_V(p)[1],2.0))
return list_p, list_Vs, list_Vp, pv_density, fp_density, pv_shearmod, fp_shearmod, prem_shearmod
fp_shearmod.append(shear_mod[1])
V_p,V_s,V_phi = seismic.get_velocities(molar_abundance, molar_weight, bulk_mod, shear_mod, density, T)
list_p.append(p)
list_Vp.append(V_p)
list_Vs.append(V_s)
# shearmodulus = density * V_s^2: (Sanne)
prem_shearmod.append(prem.prem_density(p)*pow(prem.prem_V(p)[1],2.0))
return list_p, list_Vs, list_Vp, pv_density, fp_density, pv_shearmod, fp_shearmod, prem_shearmod
#compute prem
prem_p = numpy.arange(28.3,135.0,5)
prem_vp = [prem.prem_V(y)[0] for y in prem_p]
prem_vs = [prem.prem_V(y)[1] for y in prem_p]
prem_density = [prem.prem_density(y) for y in prem_p]
#compute murakami for 100% fp
molar_abundance=[0., 1.0]
list_p, fp_Vs, fp_Vp, pv_density, fp_density, pv_shearmod, fp_shearmod, prem_shearmod \
= murakami(molar_abundance)
molar_abundance=[1.0, .0]
_, pv_Vs, pv_Vp, _,_,_,_,_ \
= murakami(molar_abundance)
#molar_abundance=[0.95, .05]
molar_abundance=[0.93, .07]
_, mix_Vs, mix_Vp, _,_,_,_,_ \