Simultaneous PIV/PTV velocimetry technique in a turbulent particle-laden flow

Experimental investigation of preferential concentration in zooplankton swimming in turbulence

Turbulence can cause particles to accumulate within specific regions of the flow. One mechanism responsible for this phenomenon, called preferential concentration, consists in particle-fluid interactions yielding inhomogeneous spatial distribution of particles into clusters or depleted regions due to density difference or finite-size effects. In the case of living particles such as plankton, clustering may also originate from their motility or from their behavioral response to turbulent forcing. Preferential concentration of plankton has attracted much attention, because it is a key determinant of encounter rates and therefore relevant for a wide range of ecological processes. However, most studies have focused on microscopic cells, and consequently the case of larger organisms remains poorly studied. Here, we use high-performance particle tracking and three-dimensional Voronoï analysis to test for the emergence of clustering in the spatial distribution of calanoid copepods, the most important metazoans in the oceans in terms of biomass. We found that neither inertia nor motility resulted in significant departure from a random Poisson process over a range of turbulence intensity from very strong to moderate. However, we observed weak clustering in calm water, which may originate from hydrodynamic and olfactory interactions between organisms. Our results improve our understanding of fluid-particle interactions in the zooplankton and have important implications for the modeling of their encounter rates in turbulence.

Simultaneous Eulerian-Lagrangian velocity measurements of particulate pipe flow in transitional regime

We present a unique pipe flow rig capable of simultaneous particle tracking and flow velocity measurements in a dilute, neutrally buoyant particulate pipe flow in regimes of transition to turbulence. The flow consists of solid glass spheres for the disperse phase and a density-matching fluid for the carrier phase. The measurements are conducted using a bespoke, combined two-dimensional particle image velocimetry and particle tracking velocimetry technique. The technique takes advantage of a phase discrimination approach that involves separating the disperse and carrier phases based on their respective image characteristics. Our results show that the rig and the technique it implements can effectively be employed to study transitional particulate pipe flows at dilute concentrations.

Terminal fall velocity: the legacy of Stokes from the perspective of fluvial hydraulics

This review article, dedicated to the bicentenary celebration of Sir George Gabriel Stokes' birthday, presents the state-of-the-science of terminal fall velocity, highlighting his rich legacy from the perspective of fluvial hydraulics. It summarizes the fluid drag on a particle and the current status of the drag coefficient from both the theoretical and empirical formulations, highlighting the three major realms-Stokesian, transitional and Newtonian realms. The force system that drives the particle motion falling through a fluid is described. The response of terminal fall velocity to key factors, which include particle shape, hindered settling and turbulence (nonlinear drag, vortex trapping, fast tracking and effects of loitering), is delineated. The article puts into focus the impact of terminal fall velocity on fluvial hydraulics, discussing the salient role that the terminal fall velocity plays in governing the hydrodynamics of the sediment threshold, bedload transport and suspended load transport. Finally, an innovative perspective is presented on the subject's future research track, emphasizing open questions.

Particle Image Velocimetry of Oil-Water Two-Phase Flow with High Water Cut and Low Flow Velocity in a Horizontal Small-Diameter Pipe

Velocity and flow field are both parameters to measure flow characteristics, which can help determine the logging location and response time of logging instruments. Particle image velocimetry (PIV) is an intuitive velocity measurement method. However, due to the limitations of image acquisition equipment and the flow pipe environment, the velocity of a horizontal small-diameter pipe with high water cut and low flow velocity based on PIV has measurement errors in excess of 20%. To solve this problem, this paper expands one-dimensional displacement sub-pixel fitting to two dimensions and improves the PIV algorithm by Kriging interpolation. The improved algorithm is used to correct the blank and error vectors. The simulation shows that the number of blank and error vectors is reduced, and the flow field curves are smooth and closer to the actual flow field. The experiment shows that the improved algorithm has a maximum measurement error of 5.9%, which is much lower than that of PIV, and that it also has high stability and a repeatability of 3.14%. The improved algorithm can compensate for the local missing flow field and reduce the requirements related to the measurement equipment and environment. The findings of this study can be helpful for the interpretation of well logging data and the design of well logging instruments.