Prediction of the spatial configuration of the umbilical cable during deep-sea mining in-situ tests is of great significance because dynamic change may cause the umbilical cable to touch the ground or overturn the mining vehicle. In the present paper, a real-time prediction method for the dynamic spatial configuration of the umbilical cable during the deep-sea mining process is proposed. At first, the environmental information, position and motion of the vessel–umbilical cable–mining system were collected by sensors arranged at different locations. Then, the data were converted and transformed to the local vessel coordinate system. After that, the commercial software OrcaFlex was employed to conduct real-time simulation, in which the spatial configuration of the umbilical cable was predicted by the lumped mass method. Furthermore, the proposed real-time simulation method was employed in a sea trial test of deep-sea mining in an area with a water depth of 1100 m. Comparing the prediction results with the trajectory of the USBL beacon obtained from the monitoring data, the maximum distance of some specific points was close to 5 m, and most of them were less than 3 m. Meanwhile, it could also give the dynamic responses of the deep-sea mining system. For example, the maximum top tension of the umbilical cable was less than 15 kN, which could be used to evaluate the health condition of the system. During the sea trial test, the proposed method played an important role in ensuring the safety of the umbilical cable during wide-range movement of the mining vehicle. With characteristics of good real-time performance, accurate prediction, high reliability and stability, the proposed method could enhance the confidence of engineers for on-site operation as a powerful digital tool for visualization of the subsea working state.

Deep-sea polymetallic nodule provinces harbor rich benthic microbial communities that underpin biogeochemical cycles and sustain abyssal ecosystem functions. Recent studies have begun to map their abundance, diversity and community structure, emphasizing the role of environmental gradients and spatial heterogeneity. Yet the spatiotemporal dynamics and assembly mechanisms of these microbes remain largely unresolved. Mining-induced sediment plumes further complicate the picture: they modify microbial biomass, activity and composition, but the trajectories of community succession and the functional consequences of disturbance are still unclear. Thresholds used to gauge plume impacts also differ markedly among studies, hampering consistent risk assessments. In summary, a stark contrast exists between the limited in situ observational data, the widely varying impact thresholds reported across studies, and the pressing need for unified standards in environmental impact assessments for deep-sea mining. It recommends future work that integrates multi-omics, time-series in situ monitoring, cross-regional comparisons and standardized evaluation frameworks to refine microbial indicators and ecological thresholds for deep-sea mining impact assessments.

Dense polymetallic nodule fields are found in different areas of the Pacific and Indian Oceans. However, limited knowledge exists about microbial diversity, processes and functions in deep-sea polymetallic nodule sediments. This study investigated microbial diversity, composition and function in sediments from various locations and depths in a western Pacific polymetallic nodule province. Sediment cores were collected, DNA extracted, and the V3–V4 regions of the 16S rRNA gene were sequenced using Illumina MiSeq. The test results show that the abundance and diversity of microbial communities in sediments from different sites vary significantly. The dominant microbial communities at the family level in the three sediment samples were all mainly Marinobacteraceae and Alcanivoracaceae. Sediment samples from core 1 had similar microbial structures and microbial community functions. Surface sediment had higher species richness, diversity and evenness than the middle layer. The dominant phylum at different depths was consistent. There was significant spatial heterogeneity in the microbial community within sediments from polymetallic nodule regions. This study expands on our knowledge of the spatial and vertical distribution of microbial community diversity beneath polymetallic nodules in deep-sea settings.

The umbilical cable is an important component of the deep-sea mining system, serving as the sole connection between the surface support vessel and the seabed mining system. The harsh marine environment poses significant challenges to umbilical cable safety. Methods based on traditional time-domain simulation are time-consuming and it is hard for them to meet the needs of real-time prediction. In this paper, a novel forecasting method is proposed, PFLM-PSML, which integrates the theory of potential flow (PF), the lumped mass method (LM), and a parameterised supervised machine learning method (PSML) to forecast the safety of umbilical cables. Six environmental and system parameters—wave height, wave direction, current velocity, current direction, cable length, and the relative position between vehicle and vessel—are used as model inputs, while outputs include cable top tension, curvature, and mining vehicle overturning moments. The model employs Latin hypercube sampling and an active learning approach with hybrid kernel functions to efficiently map input–output relationships. Validation through numerical simulations and a 6000 m deep-sea trial confirms that the proposed method achieves high accuracy and a computational speed thousands of times faster than traditional approaches, enabling real-time mechanical state prediction. Parametric analyses reveal that increases in wave height, current velocity, and water depth lead to higher cable tension and vehicle overturning moments. The PFLM-PSML framework demonstrates strong potential for real-time safety assessment and control of deep-sea mining systems under complex ocean conditions.

Sediment dynamics play a crucial role in deep-sea mining, affecting both collection efficiency and environmental disturbance, yet are often inadequately represented in numerical simulations. This study employs a non-Newtonian fluid model to simulate sediment behavior, validated through experimental jet flushing data. We compare flow field distributions and particle trajectories under a conventional rigid flat bottom and a deformable sediment bottom. Key operational parameters—including travelling velocity, flow rate, and particle deployment depth—are evaluated for their impact on collection performance under sediment conditions. Results indicate that the rigid flat bottom assumption overlooks critical sediment–particle interactions, such as bearing and immobilization effects. Negative pressure within the collection zone leads to sediment accumulation, narrowing flow channels and increasing particle capture rates—albeit at the cost of increased flow field turbulence. Capture failure modes include particle ejection from and retention within the collection flow field. Higher flow rates are necessary to maintain performance under increased travelling velocity, while capture efficiency is highly sensitive to particle deployment depth. These findings provide practical insights for optimizing deep-sea mining system parameters and assessing seafloor environmental impact.