Full-core Reactor Analysis using Monte Carlo: Challenges and Progress
Computational Scientist, Mathematics and Computer Science (MCS) Division, Argonne National Laboratory
The Monte Carlo (MC) method is one of the most appealing options for high-fidelity simulation of nuclear reactors. However, its use for such problems has been limited by a number of factors: prohibitive execution time required to reach acceptable statistics, excessive memory requirements, slow fission source convergence, and the ability to incorporate multiphysics feedback, to name a few. In the last decade, much progress has been made towards addressing some of these challenges. In this talk, I will discuss the progress to-date, where the community stands with respect to carrying our full core MC simulations, and how the trends in computing architectures will influence future developments.
Paul Romano is a computational scientist at Argonne National Laboratory who primarily works on high-performance computing and software development for nuclear energy applications. He is the original author and lead developer of OpenMC, an open source code for simulating particle transport via the Monte Carlo method that is widely used in nuclear engineering R&D. He received his B.S. in nuclear engineering and mathematics from Rensselaer Polytechnic Institute and his Ph.D. in nuclear science and engineering from Massachusetts Institute of Technology.