| description abstract | Additive manufacturing (AM) is a transformational digital manufacturing technology featured with rapidity, customizability, precision, and economy, which is fundamentally altering the way components are designed and manufactured. AM enables the freedom of design, and makes full use of complexity of geometry which “comes for free”. Applying AM technology to nuclear industry can yield advanced reactor designs with function and structure matched for the best thermal, fluidic and mechanical performance. In this work, an AM-informed reactor core design with silicon carbide (SiC) matrix and tri-structural isotropic (TRISO) particle fuel is proposed and analyzed. The core is an integrated 3D-printed SiC bulk with helical cruciform coolant channels, and the UO2-bearing TRISO fuel particles are dispersed in the bulk. A multiphysics analysis framework for irregular geometry is developed to analyze and further optimize the reactor design. The TRISO particle positions are generated with discrete element method (DEM). The Reactor Monte Carlo code (RMC) and the commercial computational fluid dynamics (CFD) software star-ccm+ are used for the neutronic and thermal-fluidic analyses, respectively. RMC simulates the neutron transport to predict the effective multiplication factor and power distribution. star-ccm+ calculates the flow and heat transfer in coolant channels and heat conduction in solid matrix with the power distribution as the heat source. Preliminary results show that the power peaking factor FQ decreases below 1.65, the heat transfer area increases by 30.3% and the fuel peaking temperature decreases by 25 K. The optimized AM-informed design enjoys better neutronic and thermal-fluidic performance than those with regular geometry. | |
