New question #149194 on DOLFIN:
https://answers.launchpad.net/dolfin/+question/149194
Dear all,
I need to solve the drift-diffusion equations for a degenerate semiconductor.
The following code works well when the doping is not too high +/- 1000. However
at doping of +/- 10000 the problem does not converge and I get the error below.
I think this has something to do with the numbers becoming too big but I'd like
to know exactly where the error happens.
Also any ideas on how to scale the problem for this not to happen? I am using
dolfin 0.9.9.
Newton iteration 1000: r (abs) = -nan (tol = 1.000e-10) r (rel) = -nan (tol =
1.000e-09)
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
/home/chaffra/Projects/Fenics/Semifem/test/ddtest.py in <module>()
59 newton_solver = problem.newton_solver()
60 newton_solver.parameters['maximum_iterations'] = 1000
---> 61 problem.solve(u_func)
/usr/local/lib/python2.6/dist-packages/dolfin/fem/variationalproblem.py in
solve(self, u)
64
65 # Solve
---> 66 cpp.VariationalProblem.solve(self, u)
67
68 # Return solution
RuntimeError: *** Error: Newton solver did not converge.
------------------------My example
from dolfin import *
#from semifem.utils.fermi_dirac import fermi_dirac_integral,
form_compiler_parameters
m = UnitInterval(100)
Q = FunctionSpace(m,'CG',1)
W = MixedFunctionSpace([Q,Q,Q])
u_func = Function(W)
u, un, up = split(u_func)
v, vn, vp = TestFunctions(W)
du_func = TrialFunction(W)
du, dun, dup = split(du_func)
class Doping(Expression):
def eval(self, v, x):
if x[0] < 0.5:
v[0] = 10000
else:
v[0] = -10000
n = exp(u-un)
p = exp(-(u-up))
d = Doping()
rho = p+d-n
mun = Constant(10000)
mup = Constant(1000)
L1 = inner(grad(u),grad(v))*dx -rho*v*dx
a1 = derivative(L1,u_func,du_func)
L2 = inner(mun*n*grad(un), grad(vn))*dx
a2 = derivative(L2, u_func, du_func)
L3 = inner(mup*p*grad(up), grad(vp))*dx
a3 = derivative(L3,u_func,du_func)
bc_left0 = DirichletBC(W.sub(0),0.0,"x[0]<DOLFIN_EPS")
bc_left1 = DirichletBC(W.sub(1),1e-1,"x[0]<DOLFIN_EPS")
bc_left2 = DirichletBC(W.sub(2),1e-1, "x[0]<DOLFIN_EPS")
bc_right0 = DirichletBC(W.sub(0),0.0,"x[0] == 1")
bc_right1 = DirichletBC(W.sub(1),0.0,"x[0] == 1")
bc_right2 = DirichletBC(W.sub(2),0.0,"x[0] == 1")
problem = VariationalProblem(a1+a2+a3,L1+L2+L3,bcs=[bc_left0, bc_left1,
bc_left2, bc_right0, bc_right1, bc_right2],nonlinear=True,
form_compiler_parameters={})
newton_solver = problem.newton_solver()
newton_solver.parameters['maximum_iterations'] = 1000
problem.solve(u_func)
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