Stochastic media contains many different materials and particles that are mixed together. Several different types of reactors use nuclear fuel that can be considered a stochastic media. This research focuses on developing fast and efficient models to analyze radiation transport behavior in the media. These models can help computer simulations improve the understanding of several important properties of the fuel and make better reactor core designs.
3-D particle systems, characterized by the stochastic distribution of spherical inclusions in a background material, are typical radiation transport media encountered in many scientific and engineering fields. In the area of nuclear engineering, some advanced nuclear reactor designs, such as the Very High Temperature Gas-Cooled Reactors (VHTR), the Fort Saint Vrain (FSV) reactor or innovative light water reactor designs (LWRs) loaded with fully ceramic microencapsulated (FCM), utilize unique fuel elements called TRISO fuel particles that are fabricated to different fuel types (fissile or fertile) and different sizes (to achieve high packing fractions). These fuel particles are randomly packed in the reactor core at volume packing fractions ranging from 5% to 60%. To provide reliable predictions neutronic safety analysis in nuclear reactors, one needs to model the stochastic distributions of particles in the system, which presents a significant computational challenge to the study of radiation transport in 3-D particle systems. The work focuses on developing new algorithm targeting stochastic properties for Monte Carlo transport code and the applications on fuel design assessment. This research becomes important in the analysis of the stochastic distribution of fuel particles in Very High Temperature Gas-cooled Reactors (VHTR’s) and current light water reactors loaded with TRISO fuels. Nuclear reactors loaded with TRISO fuels have increased safety and are key in the design of some next generation reactors.