SCONE: A Student-Oriented Modifiable Monte Carlo Particle Transport Framework
Mikolaj Kowalski, Paul Cosgrove, Jakob Broman, Eugene Shwageraus
Abstract
Over the last decade, the importance of the Monte Carlo as a neutron transport calculation method has greatly increased. This paper describes a Monte Carlo particle transport framework SCONE, which aims to provide with easy-to-learn environment for graduate students to learn about Monte Carlo methods and explore new ideas. The paper lists the steps taken to enhance new user experience of SCONE and briefly discuses how the architecture supports its goals. The current version of the code is compared against Serpent and shown to provide with sufficient accuracy to be used for teaching and proof-of-concept applications.
Topics & Concepts
Monte Carlo methodComputer scienceNeutron transportStatistical physicsMonte Carlo method in statistical physicsHybrid Monte CarloNeutronPhysicsMathematicsMarkov chain Monte CarloNuclear physicsStatisticsScientific Research and DiscoveriesAdvanced Data Processing TechniquesSoftware Reliability and Analysis Research