The bottom of the ocean is rich in mineral resources, and deep-sea mining has been a research hotspot in recent years. As a key part of deep-sea mining operation, polymetallic nodule collection technology has been researched in many countries around the world. The distribution of deep-sea polymetallic nodule mining areas and the characteristics of nodules are summarized, which provides a reference for the study of collection technology and the optimization of pick-up device structure. In order to further establish a deep-sea mining collection technology system, the current development status of polymetallic nodule mechanical, mechanical–hydraulic composite and hydraulic collection technologies are summarized, and the analysis shows that hydraulic collection technology has a more promising commercialization prospect. For the hydraulic collection technology, the research progress of suck-up-based collection technology, Coandă-effect-based collection technology, double-row hydraulic collection sluicing technology and other collection technologies are summarized from three aspects: collecting principle, device structure parameter optimization, and sea trial situation, and the key technical problems of hydraulic ore collection are put forward. Through the comparative analysis of the pick-up efficiency, energy consumption, environmental disturbance and other performances of different devices, it is found that the Coandă-effect-based hydraulic collection technology has better comprehensive performance. A structural design evaluation indicator for the collection head of hydraulic collection technology is proposed, and the prospect of further research on hydraulic collection technology is put forward.

This study employs direct numerical simulation (DNS), combined with the Cartesian cut-cell method and quadtree adaptive mesh refinement, to systematically investigate the effects of surface roughness on the flow past a cylinder. The varying surface roughness is described mainly in terms of the wavenumber $\beta$. Results show that the non-uniform roughness disrupts the symmetry of flow structures and randomizes separation, forming a heterogeneous flow with coexisting small-scale groove vortices and large-scale side vortices. At $Re=100$, the drag coefficient exhibits a maximum at $\beta =30$, with a corresponding 1.48-fold increase in the peak local pressure coefficient over a smooth cylinder. The lift coefficient stabilizes between 0.375 and 0.38 for $\beta \ge 20$. The trend of force varies across different Reynolds number ranges. Beyond a critical roughness at $Re>100$, the mean drag and lift amplitude become roughness-insensitive.

Granular porous media are widely used in groundwater, filtration, drainage, and packed-treatment systems, where pressure loss is commonly represented by macroscopic correlations or reduced pore-network conductance models. These approaches provide useful descriptions of hydraulic response, but the development of nonlinear behaviour across individual pore connections remains incompletely characterised. This study combines pore-resolved computational fluid dynamics (CFD), a Delaunay-based pore–throat–pore representation, and Gaussian Process Regression (GPR) to examine local pressure–velocity responses in four monodisperse sphere-packing realisations. The CFD-derived throat-centre velocity is used together with throat geometry, particle arrangement, and adjacent pore-body geometry to construct a common response mapping across the sampled flow conditions. The analysis reveals a broad distribution of pair-specific nonlinear transition susceptibilities and progressive, network-dependent activation as the inlet velocity increases. Particle arrangement shows the most persistent association with transition susceptibility, while the broader pore–throat–pore geometry contributes to the representation of local hydraulic response. Comparison with the bed-scale CFD pressure loss provides a descriptive, non-mechanistic quantitative cross-scale comparison: the extent of local activation and the relative quadratic contribution to the bed-scale response follow different packing-level orderings and are not directly proportional. The framework therefore provides a pore-pair perspective on heterogeneous nonlinear flow while remaining limited to the investigated packing realisations and the CFD-sampled response domain.