Optimizing superconductor transport properties through large-scale simulation

Building on cutting-edge algorithms and software

We are meeting the need for large-scale approaches to computational superconductivity with the help of the impressive algorithmic and software capabilities and broad expertise housed at the SciDAC Applied Math Institutes with strong connections to MCS and Argonne:

  • adaptive meshing
  • large-scale PDE simulation
  • advanced time-stepping algorithms
  • derivative-free optimization techniques
  • scalable methods in the Toolkit for Advanced Optimization.
    • We are further collaborating with Idaho’s Multiphysics Object-oriented Simulation Environment (MOOSE) group to leverage the SciDAC Institute capabilities for building complex scalable simulations.