Stochastic model of organizational state transitions in a turbulent pipe flow

Abstract

Flow configurations that display a significant degree of order, characterized by a well-defined number of low-speed streaks along the walls and quasi-streamwise vortical structures, hold valuable insights into the dynamics of turbulent pipes. Using stereoscopic particle image velocimetry, we investigate transitions between these organizational states (OS) in a large pipe rig facility. We find that the OS modes and their transitions exhibit a recurring statistical self-similar pattern, up to time horizons related to the flow outer scales. We also demonstrate that this distinctive statistical behavior can be accurately described by a lower-level Markovian model of the OS mode transitions.