An improved parallel Random Sequential Addition algorithm in RMC code for dispersion fuel analysis

With growing interest in Accident Tolerant Fuels (ATF) such as Fully Ceramic Micro-Encapsulated (FCM) fuel, explicit modeling processes play an increasingly important role in the precise simulation of particle transport in stochastic media. Current explicit modeling methods in RMC utilize Random Sequential Addition (RSA), where particles are randomly and sequentially packed into fuel. However, at high packing fractions, the RSA process becomes highly inefficient as simulation times increase exponentially. An improved RSA algorithm was developed by employing Octree-based Acceleration and Parallel Processing. The accuracy of the algorithm was then verified against particle distributions generated via Serpent2. The Iterative RSA-DEM Method for simulating stochastic geometry was then developed to generate explicit particle distributions beyond the RSA infinite-time saturation limit. The results show that the improved algorithms can produce highly accurate results with greatly reduced simulation time, with the capability to be easily adapted for different nuclear fuel configurations.