AI 中文总结
本研究开发了一种基于微连续介质物理的计算流体动力学模型，可准确预测粘性泥沙重力流的关键特征，能捕捉四种主要流态，经实验验证后可预测泥沙属性对自维持粘性泥沙重力流发育的影响。
AI 中文摘要
重力驱动的泥沙流是海洋、水库和湖泊内泥沙再分布的主要原因，对海岸侵蚀、淤积、碳埋藏及水生系统中污染物迁移具有重要意义。尽管该现象普遍存在，但目前对泥沙重力流（SGFs）的机理性认识仍有限。对于粘性细颗粒泥沙（即泥浆），由于黏土基质具有低渗透性、黏塑性流变学及絮凝等复杂特性，这一知识缺口尤为突出。本研究基于泥沙固体分数与流变屈服应力关系的独立测量结果，开发了一种计算流体动力学模型，可准确预测富含黏土的粘性泥沙重力流的关键特征。该模型尤其能捕捉到在蒙脱石或高岭石黏土浆的锁交换实验中观测到的四种主要流态：低密度浊流、高密度浊流、泥流及泥石流。通过与先前泥沙流形态、速度及运移距离的实验观测结果对比，对模型进行了验证。总体而言，本研究证明了该模型可预测内在（粒径、颗粒密度、流变学）及外在（泥沙地形、固体分数）泥沙属性对自维持粘性泥沙重力流发育的影响。
英文摘要
Gravity driven sediment flows are responsible for a major portion of sediment redistribution within oceans, reservoirs, and lakes, with important implications in coastal erosion, siltation, carbon burial, and contaminant migration in aquatic systems. Despite the ubiquity of this phenomenon, current mechanistic understanding of sediment gravity flows (SGFs) remains limited. This knowledge gap is particularly acute in the case of cohesive, fine-grained sediments (i.e., muds) due to the complex properties of the clay matrix, including low permeability, viscoplastic rheology, and flocculation. In this work, we develop a computational fluid dynamics model that accurately predicts key features of cohesive, clay-rich SGFs based on independent measurements of the relation between sediment solid fraction and rheological yield stress. In particular, the model captures the four primary flow regimes (low density turbidity currents, high density turbidity currents, mudflows, and mudslides) observed in lock-exchange experiments with slurries containing smectite or kaolinite clay. The model is validated through comparison with previous experimental observations of sediment flow morphology, speed, and runout distance. Overall, we demonstrate the ability to predict the influence of intrinsic (particle size, grain density, and rheology) and extrinsic sediment properties (sediment topography and solid fraction) in the development of self-sustaining cohesive SGFs.
