Thermal design and analysis of a passive modular molten salt microreactor concept

Countries and organizations around the world are in need of better energy sources that meet modern increases of demand and flexibility, such as remote power capabilities. Nuclear fission reactors have the potential to meet these needs but are not viable in their current form, due to four major challenges: proliferation concerns, economics, waste management, and a lack of passive accident prevention. Many entities in different countries are developing Generation IV reactors, particularly molten salt reactors, to try to overcome these challenges and meet their countries’ needs. However, all current designs fall short of optimal accident prevention, and have various challenges in the area of proliferation, economics, and waste management. The molten salt microreactor (MSMR) is a concept created by researchers at Brigham Young University designed to overcome each of the major challenges of current nuclear power with a uniquely simple concept. This paper presents a proof of concept for the MSMR, and lays the foundation for future design optimization. Among other innovations, the MSMR design strategically employs thermally conductive plates to help remove heat during unplanned transients. The modeling was completed in STARCCM+ and confirms the MSMR's capability to remain below safe operating limits (1204 °C for Hastelloy, 1570 °C for FLiNaK, and 1084 °C for copper) for steady state operation and during key transients. The result of this analysis is a robust design that appears promising given the initial scoping analyses conducted in this work. Future work will involve fully optimizing the MSMR's design in terms of coolant tube location, fin size and frequency, plate thickness, reactor percentage modeled, and material selection for structures and fuel. These modifications could potentially improve the reactor's temperature profiles, fuel lifetime, and material lifetime. The MSMR design and simulation data will also be used in conjunction with data science methods to develop beneficial correlations and design procedures to greatly increase the speed of future reactor design for any reactor concept.