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A Lagrangian particle random walk model for simulating a deep-sea hydrothermal plume with both buoyant and non-buoyant features

机译:拉格朗日粒子随机游动模型,用于模拟具有浮力和非浮力特征的深海热液羽流

摘要

This paper presents a computational model of simulating a deep-sea hydrothermal plume based on a Lagrangian particle random walk algorithm. This model achieves the efficient process to calculate a numerical plume developed in a fluid-advected environment with the characteristics such as significant filament intermittency and significant plume meander due to flow variation with both time and location. Especially, this model addresses both non-buoyant and buoyant features of a deep-sea hydrothermal plume in three dimensions, which significantly challenge a strategy for tracing the deep-sea hydrothermal plume and localizing its source. This paper also systematically discusses stochastic initial and boundary conditions that are critical to generate a proper numerical plume. The developed model is a powerful tool to evaluate and optimize strategies for the tracking of a deep-sea hydrothermal plume via an autonomous underwater vehicle (AUV).
机译:本文提出了一种基于拉格朗日粒子随机游走算法的深海热液羽流模拟计算模型。该模型实现了一种高效的过程,可以计算在流体对流环境中形成的羽状流,该羽状流具有诸如由于时间和位置随流量变化而显着的细丝间歇性和明显的羽状曲折等特征。尤其是,该模型从三个方面解决了深海热液羽流的非浮性和浮性特征,这极大地挑战了追踪深海热液羽流和定位其来源的策略。本文还系统地讨论了随机初始条件和边界条件,这些条件对于产生适当的数值羽状流至关重要。开发的模型是评估和优化通过自动水下航行器(AUV)跟踪深海热液羽流的策略的有力工具。

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