When, what and how image transformation techniques should be used to reduce error in Particle Image Velocimetry data?

© 2019 Elsevier Ltd Particle Image Velocimetry is commonly used to compute velocity fields in several areas including fluid mechanics, hydraulics and geophysics. However, acquired images often contain deformations caused either by camera lenses or placement. In this work the most popular digital transformation methods used to remove/reduce these deformations are benchmarked and suggestions tailoring specific transformations to different types of deformations are made. This article also shows the reduction of the error associated to the first and second order statistics, in the case of two-dimensional Particle Image Velocimetry, when the transformation techniques are applied to the computed velocity fields, and not the raw images, a common option in available commercial software

A Rapid, Empirical Method for Detection and Estimation of Outlier Frames in Particle Imaging Velocimetry Data using Proper Orthogonal Decomposition

This paper develops a method for detection and removal of outlier images from digital Particle Image Velocimetry data using Proper Orthogonal De-composition (POD). The outlier is isolated in the leading POD modes, removed and a replacement value re-estimated. The method is used to estimate and replace whole images within the sequence. This is particularly useful, if a single PIV image is suddenly heavily contaminated with background noise, or to estimate a dropped frame within a sequence. The technique is tested on a synthetic dataset that permits the effective acquisition frequency to be varied systematically, before application to flow field frames obtained from a large-eddy simulation. As expected, outlier re-estimation becomes more difficult when the integral time scale for the flow is long relative to the sampling period. However, the method provides a systematic improvement in predicting frames compared to interpolating from neighbouring(1) frames

Image-based tracking technique assessment and application to a fluid–structure interaction experiment

This work analyses the accuracy and capabilities of two image-based tracking techniques related to digital image correlation and the Lucas–Kanade optical flow method, with the subsequent quantification of body motion in a fluid–structure interaction experiment. A computer-controlled shaker was used as a benchmark case to create a one-dimensional oscillatory target motion. Three target frequencies were recorded. The measurements obtained with a low-cost digital camera were compared to a high-precision motion tracking system. The comparison was performed under changes in image resolution, target motion and sampling frequency. The results show that, with a correct selection of the processing parameters, both tracking techniques were able to track the main motion and frequency of the target even after a reduction of four and five times the sampling frequency and image resolution, respectively. Within this good agreement, the Lucas–Kanade technique shows better accuracy under tested conditions, achieving up to 15.6% of lower tracking error. Nevertheless, the achievement of this higher accuracy is highly dependent on the position of the selected initial target point. These considerations are addressed to satisfactorily track the response of a wall-mounted cylinder subjected to a range of turbulent flows using a single camera as the measuring device

Implications of the selection of a particular modal decomposition technique for the analysis of shallow flows.

This work deals with the capabilities of two synoptic modal decomposition techniques for the identification of the spatial patterns and temporal dynamics of coherent structures in shallow flows. Using two different experimental datasets it is shown that due to the linear behaviour of large-scale, quasi-two-dimensional flow structures, there are almost no differences in the identification of dominant modes between the results obtained from a traditional proper orthogonal decomposition and the more recently developed dynamic mode decomposition. However, it is also shown that nonlinear dynamics can arise in the transition of these structures to a quasi-two-dimensional behaviour, which can result in the proper orthogonal decomposition identifying structures composed of multi-frequencies, a sign of a convoluted dynamics. Thus dynamic mode decomposition is recommended instead for the analysis of such phenomena. In addition, this paper introduces a simple ranking methodology for the use of the dynamic mode decomposition technique in shallow flows, which is based on the results of the proper orthogonal decomposition

An experimental study of the flow induced by the motion of a hinged door separating two rooms

The indoor air flow and mass exchange induced by the rotating motion of a hinged door separating two rooms is investigated. Experiments were conducted in a scale model based on Reynolds number matching. Flow visualisations show the transport mechanism associated with the open and close phases of the door motion. In the room into which the door is opened a large-scale vortex is formed during opening, which is advected along the walls. In the adjacent room, a volume of fluid spreads both longitudinally and transversely. Concentration measurements were carried out to quantify the mass exchange generated by these flow patterns. Results are presented in dimensionless form for the volume of fluid exchanged and are compared to earlier data. The effects of hold open time and door speed on the exchanged fluid volume are investigated. The exchange volume increases with hold open time, but it does not vary considerably with door speed for a constant hold open time. Further, three-dimensional velocity measurements were carried out near the doorway and the characteristics of the velocity field developed are also presented

Performance of PIV and PTV for granular flow measurements

As tools and techniques to measure experimental granular flows become increasingly sophisticated, there is a need to rigorously assess the validity of the approaches used. This paper critically assesses the performance of Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV) for the measurement of granular flow properties. After a brief review of the PIV and PTV techniques, we describe the most common sources of error arising from the applications of these two methods. For PTV, a series of controlled experiments of a circular motion is used to illustrate the errors associated with the particle centroid uncertainties and the linear approximation of particle trajectories. The influence of these errors is then examined in experiments on dry monodisperse granular flows down an inclined chute geometry. The results are compared to those from PIV analysis in which errors are influenced by the size of the interrogation region. While velocity profiles estimated by the two techniques show strong agreement, second order statistics, e.g. the granular temperature, display very different profiles. We show how the choice of the sampling interval, or frame rate, affects both the magnitude of granular temperature and the profile shape determined in the case of PTV. In addition, the determined magnitudes of granular temperature from PIV tends to be considerably lower when directly measured or largely overestimated when theoretically scaled than those of PTV for the same tests, though the shape of the profiles is less sensitive to frame rate. We finally present solid concentration profiles obtained at the sidewalls and and examine their relationship to the determined shear rate and granular temperature profiles

Experimental and Modelling Investigations of Air Exchange and Infection Transfer due to Hinged-Door Motion in Office and Hospital Settings

Occupants spend a significant amount of time indoors where temperature and air quality has an important impact on their comfort, health and work performance. Understanding the role of airflow exchange between spaces is crucial to describe the processes of mixing and transport of substances driven by air motion and therefore essential for evaluating indoor air quality. This work presents the results of field measurements and laboratory experiments designed to characterise door operation and to quantify its influence on air volumes exchanged between rooms due to door motion. The field study was conducted to identify typical total door cycle times in single person offices. The laboratory experiments were conducted in a scale model to investigate the exchange flow between two generic rooms. The model consisted of a water filled tank divided into two equal rooms, which were connected by a computer-controlled hinged door. Flow visualisations were used to describe flow patterns and concentration measurements of Rhodamine WT were performed to quantify exchange volumes. With hold open times of between 0s and 26.67s the total fluid volume exchanged was found to be between 67% and 98% of the total volume swept. Based on the exchange volume found in these experiments combined with the Wells-Riley equation the effect of ventilation rate on the probability of occupants in an adjacent room becoming infected was investigated. With ventilation rates for a medium air quality the risk of infection is low (<0.05). However, the probability of infection quickly rises with lower ventilation rates

Lattice Boltzmann Method simulations of high Reynolds number flows past porous obstacles

Lattice Boltzmann Method (LBM) simulations for turbulent flows over fractal and non-fractal obstacles are presented. The wake hydrodynamics are compared and discussed in terms of flow relaxation, Strouhal numbers and wake length for different Reynolds numbers. Three obstacle topologies are studied, Solid (SS), Porous Regular (PR) and Porous Fractal (FR). In particular, we observe that the oscillation present in the case of the solid square can be annihilated or only pushed downstream depending on the topology of the porous obstacle. The LBM is implemented over a range of four Reynolds numbers from 12,352 to 49,410. The suitability of LBM for these high Reynolds number cases is studied. Its results are compared to available experimental data and published literature. Compelling agreements between all three tested obstacles show a significant validation of LBM as a tool to investigate high Reynolds number flows in complex geometries. This is particularly important as the LBM method is much less time consuming than a classical Navier–Stokes equation-based computing method and high Reynolds numbers need to be achieved with enough details (i.e., resolution) to predict for example canopy flows