Hello sfepy users!
I am using sfepy to do thermal simulations of (BIG!) electric resistors.
Nothing fancy, but i would like to be able to use temperature dependent
thermal conductivities as my system gets very hot.
At the moment I am employing the Laplace weak term:
int(s * \nabla q *\nabla p)
where s is the thermal conductivity, q is the test field parameter and p is
the temperature field
What i want is for s to depend on the temperature. I wonder which strategy
1: To limit myself to a linear s, i.e. s(q)=s0+\alpha * q.
In that case i guess i can do this:
int(s(q) * \nabla q *\nabla p) = int(s0 * \nabla q *\nabla p) +
int(\alpha * q * \nabla q *\nabla p)
Unfortunately the second term is not implemented. Looking at the
source, this would be some work to implement.
2: To iterate and after each iteration assign new values of s at each
point. This would not be a big deal when doing
time dependent simulations, but steady-state would be much slower to
calculate I guess? An added plus would be
that arbitrary c(q) could be used.
3: Ask for help here, and go "Ahhh! Of course!", when you state the
obvious, easily implementable and fantastic solution.
I have only used sfepy for about a week, and this is the first time i am
messing around with weak formulation FEM, so this
question might be really silly, but I ask anyway: Is the strategy above
completely crazy or am I on the right track?