def test_getstates(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
p = f1d.pars
# Create a dummy x and z
csn0, csp0, ce0, T0 = 0.5 * p.c_s_n_max, 0.5 * p.c_s_p_max, 1200., 298.15
x = numpy.concatenate((csn0 * numpy.ones(p.Nn * p.SolidOrder_n),
csp0 * numpy.ones(p.Np * p.SolidOrder_p),
ce0 * numpy.ones(p.Nce), (T0, )))
phisn0, phisp0, ien0, iep0, phie0, jn0, jp0 = 0.05, 3.8, 0.1, 0.2, 0.3, 0.4, 0.5
z = numpy.concatenate((phisn0 * numpy.ones(p.Nn),
phisp0 * numpy.ones(p.Np), ien0 * numpy.ones(p.Nn),
iep0 * numpy.ones(p.Np), phie0 * numpy.ones(p.Nce),
jn0 * numpy.ones(p.Nn), jp0 * numpy.ones(p.Np)))
# Run the function
states = f1d.get_states(x, z)
# x = [c_ss, c_avg]
# names = ['c_ss', 'c_avg']
for k in states:
print '#########################################'
print '~~~ ', k, ' ~~~'
print states[k]
print
def test_getEdgeEtas(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
p = f1d.pars
#
T0 = 298.15
# io = [10., 1.]
aFRT_n, aFRT_p = 0.5 * p.Faraday / (p.R * T0), 0.5 * p.Faraday / (p.R * T0)
Rf = 0.0
j_rxn0, j_rxnN = (1. / (p.Area * (p.a_s_p * p.L_p))) / p.Faraday, (
1. / (p.Area * (p.a_s_p * p.L_p))) / p.Faraday * 1.1
eta1, etaNm1 = (1. / aFRT_n) * math.asinh(
p.Faraday / (2 * io[0]) * j_rxn0), (1. / aFRT_n) * math.asinh(
p.Faraday / (2 * io[-1]) * j_rxnN)
eta0, etaN = f1d.getEdgeEtas(io, aFRT_n, aFRT_p, Rf, j_rxn0, j_rxnN, eta1,
etaNm1)
x = [eta0, eta1, etaNm1, etaN]
names = ['eta0', 'eta1', 'etaNm1', 'etaN']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
def test_elytediff(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
p = f1d.pars
# Execute the cce function
cer = 1220.
# c_e = numpy.ones( p.Nce, dtype='d' )*cer
c_e = numpy.linspace(.9, 1.1, num=p.Nce, dtype='d') * cer
i_e = numpy.zeros_like(c_e, dtype='d')
T = 298.15
Cur = 0.0
f1d.cce(c_e)
c_e_dot, cemats, ce_bcs, c_ex = f1d.electrolyte_diffusion(c_e, i_e, Cur, T)
x = [c_e_dot, cemats, ce_bcs, c_ex]
names = ['c_e_dot', 'cemats', 'ce_bcs', 'c_ex']
# x = [c_ss, c_avg]
# names = ['c_ss', 'c_avg']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
def test_phiemats(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
p = f1d.pars
# Execute the cce function
cer = 1220.
c_e = numpy.ones(p.Nce) * cer
cex = numpy.ones(p.Nce + 4) * cer
cebcs = numpy.ones(4) * cer
T = 298.15
f1d.cce(c_e)
F1, F2, F3, C_phie, C_phie_cex, phiemats = f1d.phi_e_mats(
c_e, cebcs, cex, T)
x = [F1, F2, F3, C_phie, C_phie_cex]
names = ['F1', 'F2', 'F3', 'Cphie', 'Cphiex']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
def test_daesystem(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
p = f1d.pars
T = 298.15
Cur = 0.0
# Create a dummy x and z
csn0, csp0, ce0, T0 = p.theta_n0 * p.c_s_n_max, p.theta_p0 * p.c_s_p_max, 1220., T
c_e = ce0 * numpy.ones(p.Nce, dtype='d')
# csn = csn0*numpy.ones(p.Nn*p.SolidOrder_n, dtype='d')
# csp = csp0*numpy.ones(p.Np*p.SolidOrder_p, dtype='d')
csn = numpy.linspace((1.0 * p.theta_n0) * p.c_s_n_max,
(1.0 * p.theta_n0) * p.c_s_n_max,
num=p.Nn * p.SolidOrder_n,
dtype='d')
csp = numpy.linspace((1.0 * p.theta_p0) * p.c_s_p_max,
(1.0 * p.theta_p0) * p.c_s_p_max,
num=p.Np * p.SolidOrder_p,
dtype='d')
x = numpy.concatenate((csn, csp, c_e, (T0, )))
print ' x_p0', ' x_n0'
print p.theta_p0, p.theta_n0
print csn[0:p.Nn] / p.c_s_n_max
Un0 = batteqns.refPotential(p.Udat_n, csn[0:p.Nn] / p.c_s_n_max, T)
Up0 = batteqns.refPotential(p.Udat_p, csp[0:p.Np] / p.c_s_p_max, T)
print ' Up0', ' Un0'
print Up0, Un0
phisn0, phisp0, ien0, iep0, phie0, jn0, jp0 = Un0, Up0, 0.0, 0.0, 0.0, 0.0, 0.0
z = numpy.concatenate(
(phisn0, phisp0, ien0 * numpy.ones(p.Nn, dtype='d'),
iep0 * numpy.ones(p.Np, dtype='d'),
phie0 * numpy.ones(p.Nce, dtype='d'),
jn0 * numpy.ones(p.Nn, dtype='d'), jp0 * numpy.ones(p.Np, dtype='d')))
f1d.cce(c_e)
f, g = f1d.dae_system(x, z, Cur, get_derivs=1)
x = [f, g]
names = ['f', 'g']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
def params_testing(basepath, confname):
"""
Checks to see that the buildpars method in params will run. Does not do anything
to ensure the correctness of the data
"""
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
Pdat = {'RunInput': RunInput}
V_init = 4.1
a = params.params()
a.buildpars(V_init, Pdat)
def test_cce(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
p = f1d.pars
# Execute the cce function
c_e = numpy.ones(p.Nce) * 1220.
f1d.cce(c_e)
print p.C_ce
def test_init(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
f1d = full_1d.FULL_1D(RunInput)
for key in f1d.varinf:
print '#########################################'
print '~~~ ', key, ' ~~~'
print
for subkey in f1d.varinf[key]:
print '\t~~~ ', subkey, ' ~~~'
print '\t', f1d.varinf[key][subkey]
print
def test_soldiff(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
p = f1d.pars
# Setup the solid_diffusion function inputs
elec = 'cathode'
if elec == 'cathode':
x, r = p.Np, p.SolidOrder_p
csmax = p.c_s_p_max
asf = p.a_s_p * p.L_p
csdat, Dsdat = p.csdat_p, p.Dsdat_p
theta_0 = 0.3596914899
elif elec == 'anode':
x, r = p.Nn, p.SolidOrder_n
csmax = p.c_s_n_max
asf = p.a_s_n * p.L_n
csdat, Dsdat = p.csdat_n, p.Dsdat_n
theta_0 = 0.83058516056702
cs_sz = x * r
csr = theta_0 * csmax
c_s = numpy.ones(cs_sz, dtype='d') * csr
j_rxn = (1. / (p.Area * (asf))) / p.Faraday * numpy.zeros(x, dtype='d')
msz = (x, r)
T = 298.15
c_s_dot, c_ss, c_avg, As, Bs = f1d.solid_diffusion(c_s, j_rxn, T, csdat,
Dsdat, msz)
x = [c_s_dot[0:p.Np], c_ss, c_avg, As[:, :, 0], Bs[:, 0]]
names = ['c_s_dot', 'c_ss', 'c_avg', 'As', 'Bs']
# x = [c_ss, c_avg]
# names = ['c_ss', 'c_avg']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
def test_thermFactors(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
Pdat = {'RunInput': RunInput}
V_init = 4.1
p = params.params()
p.buildpars(V_init, Pdat)
plt.figure(1)
plt.plot(p.Udat_p['x'], p.Udat_p['activity'], label='cathode')
plt.plot(p.Udat_n['x'], p.Udat_n['activity'], label='anode')
plt.legend()
plt.show()
def test_precsAmats(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
Pdat = {'RunInput': RunInput}
V_init = 4.1
p = params.params()
p.buildpars(V_init, Pdat)
x = [p.A1n, p.A2n, p.A1p, p.A2p]
names = ['A1n', 'A2n', 'A1p', 'A2p']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
def test_cspre(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
# Execute the phi_s_mats function
p = f1d.pars
x = [p.A_csn_pre, p.B_csn_pre, p.A_csp_pre, p.B_csp_pre]
names = ['An', 'Bn', 'Ap', 'Bp']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
def test_jacpre(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
# Execute the jac_pre function
f1d.jac_pre()
p = f1d.pars
x = [p.f_x, p.f_z, p.g_x, p.g_z]
names = ['fx', 'fz', 'gx', 'gz']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
def test_fullocp(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
Pdat = {'RunInput': RunInput}
V_init = 4.1
p = params.params()
p.buildpars(V_init, Pdat)
print 'xn0:', p.theta_n0
print 'xp0:', p.theta_p0
plt.figure(1)
plt.plot(p.xs, p.Up, label='U_p')
plt.plot(p.xs, p.Ua, label='U_n')
plt.plot(p.xs, p.OCP, label='OCP')
plt.legend()
plt.show()
import confreader path = '/Users/mk/Desktop/battsim/battsimpy/data/Model_v1/Model_Pars/des_prop.txt' #path = '/Users/mk/Desktop/battsim/battsimpy/testConf.conf' testdat = confreader.reader(path) print testdat.conf_data
def test_cnsolver(basepath, confname):
# Config data load
path = basepath + 'battsimpy/' + confname
cfr = confreader.reader(path)
RunInput = cfr.conf_data
# Initialize the model
f1d = full_1d.FULL_1D(RunInput)
p = f1d.pars
T = 298.15
Cur = 0.0
# Create a dummy x and z
csn0, csp0, ce0, T0 = p.theta_n0 * p.c_s_n_max, p.theta_p0 * p.c_s_p_max, 1220., T
c_e = ce0 * numpy.ones(p.Nce, dtype='d')
# csn = csn0*numpy.ones(p.Nn*p.SolidOrder_n, dtype='d')
# csp = csp0*numpy.ones(p.Np*p.SolidOrder_p, dtype='d')
csn = numpy.linspace((1.0 * p.theta_n0) * p.c_s_n_max,
(1.0 * p.theta_n0) * p.c_s_n_max,
num=p.Nn * p.SolidOrder_n,
dtype='d')
csp = numpy.linspace((1.0 * p.theta_p0) * p.c_s_p_max,
(1.0 * p.theta_p0) * p.c_s_p_max,
num=p.Np * p.SolidOrder_p,
dtype='d')
x = numpy.concatenate((csn, csp, c_e, (T0, )))
# print ' x_p0',' x_n0'
# print p.theta_p0, p.theta_n0
# print csn[0:p.Nn]/p.c_s_n_max
Un0 = batteqns.refPotential(p.Udat_n, csn[0:p.Nn] / p.c_s_n_max, T)
Up0 = batteqns.refPotential(p.Udat_p, csp[0:p.Np] / p.c_s_p_max, T)
#
# print ' Up0',' Un0'
# print Up0, Un0
phisn0, phisp0, ien0, iep0, phie0, jn0, jp0 = Un0, Up0, 0.0, 0.0, 0.0, 0.0, 0.0
z = numpy.concatenate(
(phisn0, phisp0, ien0 * numpy.ones(p.Nn, dtype='d'),
iep0 * numpy.ones(p.Np, dtype='d'),
phie0 * numpy.ones(p.Nce, dtype='d'),
jn0 * numpy.ones(p.Nn, dtype='d'), jp0 * numpy.ones(p.Np, dtype='d')))
f1d.cce(c_e)
Cur_vec = numpy.array([Cur, Cur, Cur], dtype='d')
x_nxtf, z_nxtf, newtonStats = f1d.cn_solver(x, z, Cur_vec)
states = f1d.get_states(x_nxtf, z_nxtf)
plt.figure(1)
plt.plot(states['phi_e'])
plt.ylim([-1, 1])
# plt.plot(states['c_e'])
# plt.ylim([1219,1221])
plt.show()
x = [x_nxtf, z_nxtf, newtonStats]
names = ['x_nxtf', 'z_nxtf', 'newtonStats']
for i, mat in enumerate(x):
print '#########################################'
print '~~~ ', names[i], ' ~~~'
print mat
print
