4 papers · 1 filter
Dynamics of a Data-Driven Low-Dimensional Model of Turbulent Minimal Pipe Flow
C. Ricardo Constante-Amores, Alec J. Linot, Michael D. Graham
The simulation of turbulent flow requires many degrees of freedom to resolve all the relevant times and length scales. However, due to the dissipative nature of the Navier-Stokes e…
Extracting dominant dynamics about unsteady base flows
Alec J. Linot, Barbara Lopez-Doriga, Yonghong Zhong +1
A wide range of techniques exist for extracting the dominant flow dynamics and features about steady, or periodic base flows. However, there have been limited efforts in extracting…
Hierarchical equivariant graph neural networks for forecasting collective motion in vortex clusters and microswimmers
Alec J. Linot, Haotian Hang, Eva Kanso +1
Data-driven modeling of collective dynamics is a challenging problem because emergent phenomena in multi-agent systems are often shaped by long-range interactions among individuals…
On the laminar solutions and stability of accelerating and decelerating channel flows
Alec J. Linot, Peter J. Schmid, Kunihiko Taira
We study the effect of acceleration and deceleration on the stability of channel flows. To do so, we derive an exact solution for laminar profiles of channel flows with arbitrary,…