论文标题
高雷诺数中的加速度统计量表
Scaling of acceleration statistics in high Reynolds number turbulence
论文作者
论文摘要
通过将文献中的数据与各向同性湍流的直接数值模拟结合起来，可以大大扩展雷诺数数量范围，从而检查了湍流中加速度统计的缩放。较高雷诺数的加速度差异与基于多型模型的先前预测不同，该预测将拉格朗日间歇性的特征是欧拉尔间间歇性的天真扩展。对于加速度的高阶时刻，分歧甚至更为突出。取而代之的是，从已知的确切关系开始，我们将加速度方差的缩放缩放与Eulerian四阶速度梯度和速度增量统计量的缩放。该预测与方差数据非常吻合。我们的工作强调了对独立于欧拉（Eulerian）对应的拉格朗日间歇性的模型的需求。
The scaling of acceleration statistics in turbulence is examined by combining data from the literature with new data from well-resolved direct numerical simulations of isotropic turbulence, significantly extending the Reynolds number range. The acceleration variance at higher Reynolds numbers departs from previous predictions based on multifractal models, which characterize Lagrangian intermittency as a naive extension of Eulerian intermittency. The disagreement is even more prominent for higher-order moments of the acceleration. Instead, starting from a known exact relation, we relate the scaling of acceleration variance to that of Eulerian fourth-order velocity gradient and velocity increment statistics. This prediction is in excellent agreement with the variance data. Our work highlights the need for models that consider Lagrangian intermittency independent of the Eulerian counterpart.
