A probabilistic collision–energy framework for predicting polymetallic nodule degradation in deep–sea mining risers

Particle degradation during long–distance hydraulic lifting can reduce nodule recovery, increase blockage risk, and generate fine particles that affect downstream handling and discharge control in deep–sea mining systems. However, direct prediction over kilometer–scale riser distances remains difficult. Resolved computational fluid dynamics–discrete element method (CFD–DEM) simulations are limited to short pipe sections, while empirical models provide limited insight into collision–energy mechanisms. This study develops a probabilistic collision–energy framework to predict nodule degradation in deep–sea mining risers. The model combines particle–wall impact accessibility, concentration–dependent shielding, impact–velocity probability distribution, fatigue–controlled fragmentation, and abrasion–induced surface loss in a unified formulation. Abrasion and fragmentation are treated as distinct mass–transfer pathways, linking fines generation and daughter–fragment redistribution to collision–energy exposure. Key collision statistics are assessed using CFD–DEM data, and the full model is evaluated against long–distance experimental particle–size distribution (PSD) data. Results show that particle–particle contacts are more frequent than particle–wall impacts but have lower wall–equivalent destructive energy, mainly contributing to cumulative abrasion and fine generation. Wall impacts are more relevant to fatigue damage and primary fragmentation. Pipe enlargement suppresses wall–impact fragmentation, whereas increasing solid concentration shifts degradation toward particle–particle abrasion. The resulting regime map distinguishes abrasion–dominated and fragmentation–prone conditions, providing a practical basis for degradation–risk assessment in deep–sea hydraulic lifting.