Title: Normality-based analysis of multiscale velocity gradients and energy transfer in direct and large-eddy simulations of isotropic turbulence Show Chinese title

Title: 基于正态性的多尺度速度梯度及能量传递的分析在各向同性湍流的直接模拟和大涡模拟中的应用

Abstract: Symmetry-based analyses of multiscale velocity gradients highlight that strain self-amplification and vortex stretching drive forward energy transfer in turbulent flows. By contrast, a strain-vorticity covariance mechanism produces backscatter that contributes to the bottleneck effect in the subinertial range of the energy cascade. We extend these analyses by using a normality-based decomposition of filtered velocity gradients in forced isotropic turbulence to distinguish contributions from normal straining, pure shearing, and rigid rotation at a given scale. Our analysis of direct numerical simulation (DNS) data illuminates the importance of shear layers in the inertial range and (especially) the subinertial range of the cascade. Shear layers contribute significantly to strain self-amplification and vortex stretching and play a dominant role in the backscatter mechanism responsible for the bottleneck effect. Our concurrent analysis of large-eddy simulation (LES) data characterizes how different closure models affect the flow structure and energy transfer throughout the resolved scales. We thoroughly demonstrate that the multiscale flow features produced by a mixed model closely resemble those in a filtered DNS, whereas the features produced by an eddy viscosity model resemble those in an unfiltered DNS at a lower Reynolds number. This analysis helps explain how small-scale shear layers, whose imprint is mitigated upon filtering, amplify the artificial bottleneck effect produced by the eddy viscosity model in the inertial range of the cascade. Altogether, the present results provide a refined interpretation of the flow structures and mechanisms underlying the energy cascade and insight for designing and evaluating LES closure models. Show Chinese abstract

Abstract: 基于对多尺度速度梯度的对称性分析表明，应变自增强和涡旋拉伸驱动湍流中的能量正向传递。 相比之下，应变-涡度协方差机制产生反散射，这有助于能量级联次惯性范围内的瓶颈效应。 我们通过在强制各向同性湍流中使用过滤速度梯度的正态分解，扩展了这些分析，以区分给定尺度下正常应变、纯剪切和刚体旋转的贡献。 我们对直接数值模拟（DNS）数据的分析揭示了剪切层在惯性范围以及（尤其是）级联次惯性范围中的重要性。 剪切层显著促进应变自增强和涡旋拉伸，并在导致瓶颈效应的反散射机制中起主导作用。 我们对大涡模拟（LES）数据的同步分析描述了不同闭合模型如何影响整个解析尺度上的流动结构和能量传递。 我们全面证明，混合模型产生的多尺度流动特征与过滤后的DNS结果非常相似，而涡粘性模型产生的特征则类似于低雷诺数未过滤DNS的结果。 这一分析有助于解释小尺度剪切层的印记在过滤后被减弱，却在级联惯性范围内由涡粘性模型产生的虚假瓶颈效应中被放大。 总的来说，目前的结果提供了对能量级联背后流动结构和机制的更精细解释，并为设计和评估LES闭合模型提供了见解。