机械
物理
粒子(生态学)
羽流
颗粒流
大涡模拟
涡流
雷诺数
雷诺应力
沉淀
扩散
离散元法
质点速度
经典力学
湍流
气象学
热力学
地质学
海洋学
作者
Yefeng Yang,Jiawang Chen,Yin Wang
摘要
The particle plume, a ubiquitous particle–fluid coupled phenomenon in tailing discharge from deep-sea mining, undergoes suspension and diffusion over distances transportation. Our study is motivated by predicting plume dispersion patterns driven by different initial momentums, relying on understanding complex fluid–particle interaction mechanics. To consider irregular particle shapes and discrete effects, a discrete element method and large-eddy simulation coupled model is established in our in-house solver to simulate particle plumes and investigate flow characteristics from a Lagrangian perspective. The influence of the initial incident velocity W0 on particle flow regimes, movement patterns, velocity, concentration, Reynold shear stress, fluid–particle interactions, and energy budget is explored. The results show that a counter-rotating vortex pair forms in the initial stage, with ambient fluid entrainment inducing coherent vortex splitting into numerous vortex filaments, causing significant radial diffusion. Plume transportation begins with rapid settling, followed by a decrease to a roughly constant level. Increasing W0 enhances the particle velocity, allowing plumes to advance faster. This results in particle diffusion rate and concentration dilution rate increasing with decreasing W0. Away from the nozzle centerline, negative axial velocity magnitudes increase as W0 decreases, prompting particle radial diffusion. Additionally, for cases with low W0, significant particle concentration in regions far from the nozzle dampens pulsatile velocity, resulting in decreased Reynolds stress with decreasing W0. Notably, despite the complexity of particle–fluid interactions in plumes, the conversion of initial gravitational potential energy into particle and fluid kinetic energy is limited across all W0.
科研通智能强力驱动
Strongly Powered by AbleSci AI