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A model of bubble-induced turbulence based on large-scale wake interactions

机译:基于大规模尾流相互作用的气泡引起的湍流模型

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摘要

Navier–Stokes simulations of the agitation generated by a homogeneous swarm of high-Reynolds-number rising bubbles are performed. The bubbles are modelled by fixed momentum sources of finite size randomly distributed in a uniform flow. The mesh grid is regular with a spacing close to the bubble size. This allows us to simulate a swarm of a few thousand bubbles in a computational domain of a hundred bubble diameters, which corresponds to a gas volume fraction α from 0.6% to 4%. The small-scale disturbances close to the bubbles are not resolved but the wakes are correctly described from a distance of a few diameters. This simple model reproduces well all the statistical properties of the vertical velocity fluctuations measured in previous experiments: scaling as α0.4, self-similar probability density functions and power spectral density including a subrange evolving as the power −3 of the wavenumber k. It can therefore be concluded that bubble-induced agitation mainly results from wake interactions. Considering the flow in a frame that is fixed relative to the bubbles, the combined use of both time and spatial averaging makes it possible to distinguish two contributions to the liquid fluctuations. The first is the spatial fluctuations that are the consequence of the bubble mean wakes. The second corresponds to the temporal fluctuations that are the result of the development of a flow instability. Note that the latter is not due to the destabilization of individual bubble wakes, since a computation with a single bubble leads to a steady flow. It is a collective instability of the randomly distributed bubble wakes. The spectrum of the time fluctuations shows a peak around a frequency fcwi, which is independent of α. From the present results it is possible to determine the origin of the overall properties of the total fluctuations observed in the experiments. The scaling of the velocity fluctuation as α^0.4 is a combination of the scalings of the spatial and temporal fluctuations, which are different from each other. As the time fluctuations are symmetric in the vertical direction, the asymmetry of the probability density function of the vertical velocity comes from that of the spatial fluctuations. Both contributions exhibit a k−3 spectral behaviour around the same range of wavenumbers, which explains why it is observed regardless of the nature of the dominant contribution.
机译:进行了由高雷诺数上升气泡的均匀群产生的搅动的Navier-Stokes模拟。气泡由有限大小的固定动量源建模,这些动量源随机分布在均匀流中。网格是规则的,间距接近气泡大小。这使我们能够在气泡直径为一百的计算域中模拟数千个气泡的群,这对应于从0.6%到4%的气体体积分数α。气泡附近的小规模扰动没有解决,但从几个直径的距离正确地描述了尾流。这个简单的模型很好地再现了先前实验中测得的垂直速度波动的所有统计特性:缩放为α0.4,自相似概率密度函数和功率谱密度,包括随波数k的幂-3演化的子范围。因此可以得出结论,气泡引起的搅动主要是由尾流相互作用引起的。考虑到相对于气泡固定的框架中的流动,时间和空间平均的组合使用可以区分两种对液体波动的贡献。首先是空间波动,这是气泡均值苏醒的结果。第二个对应于由于流动不稳定性的发展而引起的时间波动。请注意,后者并不是由于单个气泡唤醒的不稳定,因为使用单个气泡进行计算会导致流量稳定。这是随机分布的气泡唤醒的集体不稳定性。时间波动的频谱显示了一个频率fcwi附近的峰值,该频率与α无关。根据目前的结果,有可能确定实验中观察到的总波动的总体性质的起源。速度波动的标度为α^ 0.4,是空间和时间波动的标度的组合,它们彼此不同。由于时间波动在垂直方向上是对称的,因此垂直速度的概率密度函数的不对称性来自空间波动的不对称性。两种贡献在相同波数范围内均表现出k-3光谱行为,这解释了为什么不管主要贡献的性质如何都观察到它。

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