Simulation of particle agglomeration, attrition and breakup for nuclear waste transport and retrieval processes

About the Project

The safe retrieval, transport and processing of radioactive waste slurries is one of the most significant engineering challenges in nuclear decommissioning. These operations involve complex turbulent flows carrying heterogeneous suspensions of particles with varied sizes, shapes and material properties. A critical but poorly understood feature of such flows is that particle size distributions are not stationary. Particles can agglomerate through cohesive interactions, fragment under hydrodynamic stress, or gradually wear down through repeated collisions with other particles and surfaces (attrition). These changes in particle size distributions directly affect settling behaviour, rheology, pipeline transport characteristics, blockage risk and the efficiency of downstream treatment operations. Despite the importance of these processes, existing models for nuclear waste transport typically assume fixed or overly simplified particle populations, leaving a significant gap in predictive capability.

This PhD will address that gap by developing a novel multi-scale fluid dynamics simulation framework that connects the physics of individual particle collisions to bulk-scale turbulent transport predictions. The novelty of the work lies in bridging the gap between particle-resolved contact and failure mechanics with Lagrangian particle tracking of millions of individual particles in turbulent flows, facilitated using state-of-the-art machine learning techniques.