Synchronization of turbulence in channel flow

被引:18
作者
Wang, Mengze [1 ]
Zaki, Tamer A. [1 ]
机构
[1] Johns Hopkins Univ, Dept Mech Engn, Baltimore, MD 21218 USA
关键词
turbulence simulation; LARGE-SCALE STRUCTURES; BOUNDARY-LAYERS; ASSIMILATION; RECONSTRUCTION; PREDICTABILITY;
D O I
10.1017/jfm.2022.397
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Synchronization of turbulence in channel flow is investigated using continuous data assimilation. The flow is unknown within a region of the channel. Beyond this region the velocity field is provided, and is directly prescribed in the simulation, while the pressure is unknown throughout the entire domain. Synchronization takes place when the simulation recovers the full true state of the flow, or in other words when the missing region is accurately re-established, spontaneously. Successful synchronization depends on the orientation, location and size of the missing layer. For friction Reynolds numbers up to one thousand, wall-attached horizontal layers can synchronize as long as their thickness is less than approximately thirty wall units. When the horizontal layer is detached from the wall, the critical thickness increases with height and is proportional to the local wall-normal Taylor microscale. A flow-parallel, vertical layer that spans the height of the channel synchronizes when its spanwise width is of the order of the near-wall Taylor microscale, while the criterion for a crossflow vertical layer is set by the advection distance within a Lyapunov time scale. Finally, we demonstrate that synchronization is possible when only planar velocity data are available, rather than the full outer state, as long as the unknown region satisfies the condition for synchronization in one direction. These numerical experiments demonstrate the capacity of accurately reconstructing, or synchronizing, the missing scales of turbulence from observations, using continuous data assimilation.
引用
收藏
页数:27
相关论文
共 59 条
[51]   The synchronisation of intense vorticity in isotropic turbulence [J].
Vela-Martin, Alberto .
JOURNAL OF FLUID MECHANICS, 2021, 913
[52]   State estimation in turbulent channel flow from limited observations [J].
Wang, Mengze ;
Zaki, Tamer A. .
JOURNAL OF FLUID MECHANICS, 2021, 917
[53]   Discrete adjoint of fractional-step incompressible Navier-Stokes solver in curvilinear coordinates and application to data assimilation [J].
Wang, Mengze ;
Wang, Qi ;
Zaki, Tamer A. .
JOURNAL OF COMPUTATIONAL PHYSICS, 2019, 396 :427-450
[54]   Spatial reconstruction of steady scalar sources from remote measurements in turbulent flow [J].
Wang, Qi ;
Hasegawa, Yosuke ;
Zaki, Tamer A. .
JOURNAL OF FLUID MECHANICS, 2019, 870 :316-352
[55]  
Wu Jie-Zhi, 2007, Vorticity and vortex dynamics
[56]   Data compression for turbulence databases using spatiotemporal subsampling and local resimulation [J].
Wu, Zhao ;
Zaki, Tamer A. ;
Meneveau, Charles .
PHYSICAL REVIEW FLUIDS, 2020, 5 (06)
[57]   Regeneration of small eddies by data assimilation in turbulence [J].
Yoshida, K ;
Yamaguchi, J ;
Kaneda, Y .
PHYSICAL REVIEW LETTERS, 2005, 94 (01)
[58]   From limited observations to the state of turbulence: Fundamental difficulties of flow reconstruction [J].
Zaki, Tamer A. ;
Wang, Mengze .
PHYSICAL REVIEW FLUIDS, 2021, 6 (10)
[59]   From Streaks to Spots and on to Turbulence: Exploring the Dynamics of Boundary Layer Transition [J].
Zaki, Tamer A. .
FLOW TURBULENCE AND COMBUSTION, 2013, 91 (03) :451-473