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<p>Tailings emissions from deep-sea mining pose serious threats to marine ecosystems. In particular, sedimentary plumes formed by high concentrations of fine particles have become a key source of environmental risk because of their large-scale diffusion potential and long-term persistence in the environment. Using a coupled computational fluid dynamics (CFD)–discrete element method (DEM) framework, this study introduces a particle-coarsening algorithm and develops a CFD–coarse-grained DEM (CFD–CGDEM) numerical model to efficiently simulate the transport and diffusion dynamics of fine particles of deep-sea tailings. The results reveal that the initial concentration, emission volume, and particle density of tailings particle groups significantly impact their sedimentation rates and diffusion behavior. Specifically, particle groups with large initial concentrations, volumes, and densities show a higher sedimentation rate. However, sedimentary rings formed on the seabed during sedimentation show a blocking effect on the diffusion of subsequent particles. In-depth analysis shows that the expansion rate of deposition rings is mainly controlled by the physical properties (volume and density) of the particles, with weak correlations with the initial concentration. Meanwhile, smaller particle groups show stronger diffusion ability. These results provide a valuable theoretical basis for the formulation of environmental assessment and control strategies for deep-sea mining tailings emissions, which is of great significance in promoting the development of environmentally friendly and sustainable deep-sea resources.</p>

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Simulation of Plumes Generated by the Discharge of Fine-Grained Tailings in Deep-Sea Mining

  • 期刊论文

  • 发表日期：

    2026年6月3日

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  • Yuwen Chen,
  • Changsheng Yang,
  • Xiaochang Shi,
  • Bo Zhou,
  • Wenbin Ma

摘要

Tailings emissions from deep-sea mining pose serious threats to marine ecosystems. In particular, sedimentary plumes formed by high concentrations of fine particles have become a key source of environmental risk because of their large-scale diffusion potential and long-term persistence in the environment. Using a coupled computational fluid dynamics (CFD)–discrete element method (DEM) framework, this study introduces a particle-coarsening algorithm and develops a CFD–coarse-grained DEM (CFD–CGDEM) numerical model to efficiently simulate the transport and diffusion dynamics of fine particles of deep-sea tailings. The results reveal that the initial concentration, emission volume, and particle density of tailings particle groups significantly impact their sedimentation rates and diffusion behavior. Specifically, particle groups with large initial concentrations, volumes, and densities show a higher sedimentation rate. However, sedimentary rings formed on the seabed during sedimentation show a blocking effect on the diffusion of subsequent particles. In-depth analysis shows that the expansion rate of deposition rings is mainly controlled by the physical properties (volume and density) of the particles, with weak correlations with the initial concentration. Meanwhile, smaller particle groups show stronger diffusion ability. These results provide a valuable theoretical basis for the formulation of environmental assessment and control strategies for deep-sea mining tailings emissions, which is of great significance in promoting the development of environmentally friendly and sustainable deep-sea resources.