湍流衰减增强气泡和颗粒的聚集
Turbulence Decay Intensifies Clustering of Bubbles and Particles
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中文总结 AI 辅助
本文通过实验和直接数值模拟，发现自由衰减湍流中颗粒聚集先增强后减弱，并提出动态重标度方法将衰减湍流行为映射到稳态湍流，适用于宽范围密度比和斯托克斯数。
中文摘要 AI 辅助
我们对湍流中惯性颗粒动力学的理解大多基于统计稳态流动，这是一种特定状态，与许多自然流动不同，在自然流动中能量输入通常是间歇性或周期性的，或者可能突然停止。本文通过互补的实验和直接数值模拟，研究了自由衰减湍流中惯性颗粒和气泡的动力学。虽然颗粒加速度随时间单调衰减，但我们发现聚集可能表现出非单调演化，先急剧增强，随后减弱。我们证明，通过动态重标度湍流演化的长度和时间尺度，加速度和聚集行为都可以映射到稳态湍流中的对应行为。我们推导了动态重标度的有效性条件，实验和数值数据集均满足这些条件。所提出的映射在广泛的密度比范围内仍然适用，从轻颗粒到重颗粒，颗粒尺寸跨越两个数量级的斯托克斯数。
英文摘要
Our understanding of inertial particle dynamics in turbulence is mostly based on flows held in a statistically stationary state, a particular regime that differs from many natural flows where energy input can often be intermittent or cyclic, or may abruptly cease. Here we investigate inertial particle and bubble dynamics in freely decaying turbulence through complementary experiments and direct numerical simulations. While particle accelerations decay monotonically in time, we find evidence that the clustering can exhibit a non-monotonic evolution, intensifying sharply before subsequently weakening. We demonstrate that both the acceleration and clustering behaviors can be mapped onto their counterparts in stationary turbulence using a dynamic rescaling of the evolving length and time scales of the turbulence. Validity conditions for the dynamic rescaling, satisfied by both the experimental and numerical datasets, are derived. The proposed mappings remain applicable across a broad range of density ratios, from light to heavy particles, and particle sizes spanning two orders of magnitude in Stokes number.
发表机构
- University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校）
- Brown University（布朗大学）
- Universidad de Cádiz（加的斯大学）
- Université de Lille（里尔大学）
机构由 AI 辅助整理，请以论文原文为准。
