This paper presents a novel method for measuring three-dimensional (3D) water surface dynamics in a partially filled pipe. The study on investigation of the 3D free surface dynamics in partially filled pipes is very limited. The method involves tinting the water white with titanium dioxide so that the water surface appears like a solid surface to image-based measuring systems. This method uses a high-resolution projector to project a stochastic pattern of light onto the water surface and uses two high-resolution cameras to capture the pattern on the deformed water surface. The 3D instantaneous water surface fluctuation can be computed from the images captured by the two cameras using a standard Digital Image Correlation algorithm. It is demonstrated that the surface dynamics parameters of turbulent flow in partially filled pipes, including surface fluctuations and surface velocity, can be measured using the projector, high-resolution cameras and DIC algorithm.

Recent studies have sought to use Microsoft Kinect sensors to measure water surface shape in steady flows or transient flow processes. They have typically employed a white colourant, usually titanium dioxide (TiO₂), in order to make the surface opaque and visible to the infrared-based sensors. However, the ability of Kinect Version 1 (KV1) and Kinect Version 2 (KV2) sensors to measure the deformation of ostensibly smooth reflective surfaces has never been compared, with most previous studies using a V1 sensor with no justification. Furthermore, the TiO₂ has so far been used liberally and indeterminately, with no consideration as to the type of TiO₂ to use, the optimal proportion to use or the effect it may have on the very fluid properties being measured. This paper examines the use of anatase TiO₂ with two generations of the Microsoft Kinect sensor. Assessing their performance for an ideal flat surface, it is shown that surface data obtained using the V2 sensor is substantially more reliable. Further, the minimum quantity of colourant to enable reliable surface recognition is discovered (0.01% by mass). A stability test shows that the colourant has a strong tendency to settle over time, meaning the fluid must remain well mixed, having serious implications for studies with low Reynolds number or transient processes such as dam breaks. Furthermore, the effect of TiO₂ concentration on fluid properties is examined. It is shown that previous studies using concentrations in excess of 1% may have significantly affected the viscosity and surface tension, and thus the surface behaviour being measured. It is therefore recommended that future studies employ the V2 sensor with an anatase TiO₂ concentration of 0.01%, and that the effects of TiO₂ on the fluid properties are properly quantified before any TiO₂-Kinect-derived dataset can be of practical use, for example, in validation of numerical models or in physical models of hydrodynamic processes.

Turbulent flow has been known to contain coherent flow structures. The size, shape, timescale and dynamics of these coherent structures are important in understanding turbulent flow processes such as pollutant mixing and particle transport. A range of methods exist for the detection of coherent structures in 2D or 3D data, but there are limited objective methods available for 1D data. Existing 1D techniques are subjective, require calibration with manual visualizations, or are based only on detecting velocity extremes and thus only detect structures according to a limited definition. A technique is presented here for objectively detecting structures using a phase-space method modified from a previously described despiking method. This method requires no calibration or subjective input, and identifies structures based on extremes in velocity, acceleration and jerk. This method gives turbulence statistics comparable with previous methods while recognizing a broader and more realistic definition of the physical properties of coherent structures by considering also the first and second derivative of velocity.