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 to use: 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?

Kind regards Bjarke Dalslet