Retrieving accurate temporal and spatial information about Taylor slug flows from non-invasive NIR photometry measurements

Abstract

In this article, we introduce a novel approach to retrieve spatial- and time-resolved Taylor slug flow information from a single non-invasive photometric flow sensor. The presented approach uses disperse phase surface properties to retrieve the instantaneous velocity information from a single sensor’s time-scaled signal. For this purpose, a photometric sensor system is simulated using a ray-tracing algorithm to calculate spatially resolved near-infrared transmission signals. At the signal position corresponding to the rear droplet cap, a correlation factor of the droplet’s geometric properties is retrieved and used to extract the instantaneous droplet velocity from the real sensor’s temporal transmission signal. Furthermore, a correlation for the rear cap geometry based on the a priori known total superficial flow velocity is developed, because the cap curvature is velocity sensitive itself. Our model for velocity derivation is validated, and measurements of a first prototype showcase the capability of the device. Long-term measurements visualize systematic fluctuations in droplet lengths, velocities, and frequencies that could otherwise, without the observation on a larger timescale, have been identified as measurement errors and not systematic phenomenas.