当前位置:
X-MOL 学术
›
Ocean Model.
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Transport of oil droplets from a jet in crossflow: Dispersion coefficients and Vortex trapping
Ocean Modelling ( IF 3.2 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.ocemod.2020.101736 Cosan Daskiran , Fangda Cui , Michel C. Boufadel , Scott A. Socolofsky , Joseph Katz , Lin Zhao , Tamay Ozgokmen , Brian Robinson , Thomas King
Ocean Modelling ( IF 3.2 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.ocemod.2020.101736 Cosan Daskiran , Fangda Cui , Michel C. Boufadel , Scott A. Socolofsky , Joseph Katz , Lin Zhao , Tamay Ozgokmen , Brian Robinson , Thomas King
Abstract Understanding the trajectory of oil droplets in crossflow jets is important to estimate the pathways of hydrocarbons and to plan countermeasures. We report experimental results of an oil jet with release velocity around 1.5 m/s in a crossflow of 0.3 m/s. The hydrodynamics of the jets obtained with the Large Eddy Simulation (LES) were used to predict the migration of the oil droplets. Two Lagrangian techniques were explored, one with the inertia of the droplet is considered and the other that treats the droplets as massless particles with rising velocities corresponding to their size. We did not note a large difference between the two approaches. The droplets showed stronger segregation in the vertical direction, which renders the usage of a Gaussian distribution approximation in the vertical inapplicable. The dispersion coefficient at each direction was computed for different-sized droplets. The eddy diffusivity computed based on Boussinesq gradient approximation using the LES data was compared with the dispersion coefficients obtained based on Lagrangian tracking. We also found that droplets 500 μ m and larger escape the vortex while smaller ones get trapped within the vortex. A similar outcome was observed using a vortex trapping function based on inward-outward force balancing at the elevation of the vortex core. The counter-rotating vortex pair (CVP) altered the distribution of droplets of 1 mm and smaller significantly, and bimodal concentration distributions with peaks near the CVP vortex cores and minimum concentration near the center plane were obtained in the lateral-horizontal direction. Therefore, measurements of the oil droplet size distribution (DSD) in the center plane of crossflow jets could underestimate the number of small droplets in the whole plume.
中文翻译:
横流中来自射流的油滴传输:分散系数和涡流捕集
摘要 了解横流射流中油滴的轨迹对于估计碳氢化合物的路径和规划对策很重要。我们报告了在 0.3 m/s 的横流中释放速度约为 1.5 m/s 的油射流的实验结果。使用大涡模拟 (LES) 获得的射流流体动力学用于预测油滴的迁移。探索了两种拉格朗日技术,一种考虑了液滴的惯性,另一种将液滴视为无质量粒子,其上升速度与其大小相对应。我们没有注意到这两种方法之间存在很大差异。液滴在垂直方向显示出更强的偏析,这使得在垂直方向上使用高斯分布近似不适用。对于不同尺寸的液滴,计算每个方向的分散系数。将使用 LES 数据基于 Boussinesq 梯度近似计算的涡流扩散率与基于拉格朗日跟踪获得的色散系数进行比较。我们还发现 500 μm 和更大的液滴会逃离涡流,而较小的液滴则被困在涡流中。使用基于涡核高度处的内外力平衡的涡旋捕获函数观察到类似的结果。反向旋转涡旋对 (CVP) 显着改变了 1 mm 及更小液滴的分布,并且在横向-水平方向上获得了双峰浓度分布,在 CVP 涡核附近具有峰值,在中心平面附近具有最小浓度。所以,
更新日期:2021-02-01
中文翻译:
横流中来自射流的油滴传输:分散系数和涡流捕集
摘要 了解横流射流中油滴的轨迹对于估计碳氢化合物的路径和规划对策很重要。我们报告了在 0.3 m/s 的横流中释放速度约为 1.5 m/s 的油射流的实验结果。使用大涡模拟 (LES) 获得的射流流体动力学用于预测油滴的迁移。探索了两种拉格朗日技术,一种考虑了液滴的惯性,另一种将液滴视为无质量粒子,其上升速度与其大小相对应。我们没有注意到这两种方法之间存在很大差异。液滴在垂直方向显示出更强的偏析,这使得在垂直方向上使用高斯分布近似不适用。对于不同尺寸的液滴,计算每个方向的分散系数。将使用 LES 数据基于 Boussinesq 梯度近似计算的涡流扩散率与基于拉格朗日跟踪获得的色散系数进行比较。我们还发现 500 μm 和更大的液滴会逃离涡流,而较小的液滴则被困在涡流中。使用基于涡核高度处的内外力平衡的涡旋捕获函数观察到类似的结果。反向旋转涡旋对 (CVP) 显着改变了 1 mm 及更小液滴的分布,并且在横向-水平方向上获得了双峰浓度分布,在 CVP 涡核附近具有峰值,在中心平面附近具有最小浓度。所以,