Large-scale Particle Image Velocimetry Research Articles

Pulsed LED line light for large-scale PIV—development and use in wave load measurements

In this paper the development of a high-power pulsed LED line light and its use to apply particle image velocimetry (PIV) during wave impact measurements are described. An electrical circuit that generates high-current pulses is designed and built, which is used to overdrive a number of commercially available LEDs. The limit for this overdrive-capacity is determined as function of pulse duration for various commercial available LEDs. Two systems of cylindrical convex lenses are designed to act as a collimator and reduce divergence of the LED bundle and the resulting light sheet properties (maximum light intensity and sheet thickness) are investigated. An array of LEDs of 60 cm length (referred to as the LED line light) is designed and manufactured. For the two lens systems, the LED line light provides proper light sheet conditions to illuminate measurement regions in the order of either 0.3 × 0.3 m2, or 1 × 1 m2, at a sufficiently constant light sheet thickness of 5 mm. The application of the LED line light is demonstrated by quantifying the instantaneous flow field of a wave impacting on a blunt object in a wave flume. PIV measurements are conducted at an acquisition rate of 25 frame pairs per second, quantifying maximum flow velocities in the order of 1.0 m s−1 at a LED pulse width of 200 μs. The system, consisting of the LED line light, a CMOS camera and open source PIV processing software provides the possibility to perform 2D planar PIV measurements for a fraction of the costs of a commercially available laser based PIV system.

Large Scale Infrared-Based Remote Sensing of Turbulence Metrics in Surface Waters: Going Beyond Mean Flow

In recent years field-scale applications of image-based velocimetry methods, often referred to as large scale particle image velocimetry (LSPIV), have been increasingly deployed. These velocimetry measurements have several advantages—they allow high resolution, non-contact measurement of surface velocity over a large two dimensional area, from which the bulk flow can be inferred. However, visiblelight LSPIV methods can have significant limitations. The water surface often lacks natural features that can be tracked in the visible and generally requires seeding with tracer particles, which creates concerns regarding the fidelity with which tracer particles track the flow, and introduces challenges in achieving sufficient and uniform seeding density, in particular in regions with appreciable velocity accelerations such as turbulence. In LSPIV, image collection is generally limited to daylight hours, and can suffer from non-uniformity of illumination across the camera’s field of view. Due to these issues LSPIV often requires spatio-temporal averaging, and as a result is generally able to extracting the mean, but not the instantaneous, velocity field, and hence is often not a suitable tool for calculating turbulence metrics of the flow.

Large-Scale Particle Image Velocimetry to Measure Streamflow from Videos Recorded from Unmanned Aerial Vehicle and Fixed Imaging System

The accuracy of river velocity measurements plays an important role in the effective management of water resources. Various methods have been developed to measure river velocity. Currently, image-based techniques provide a promising approach to avoid physical contact with targeted water bodies by researchers. In this study, measured surface velocities collected under low flow and high flow conditions in the Houlong River, Taiwan, using large-scale particle image velocimetry (LSPIV) captured by an unmanned aerial vehicle (UAV) and a terrestrial fixed station were analyzed and compared. Under low flow conditions, the mean absolute errors of the measured surface velocities using LSPIV from a UAV with shooting heights of 9, 12, and 15 m fell within 0.055 ± 0.015 m/s, which was lower than that obtained using LSPIV on video recorded from a terrestrial fixed station (i.e., 0.34 m/s). The mean absolute errors obtained using LSPIV derived from UAV aerial photography at a flight height of 12 m without seeding particles and with different seeding particle densities were slightly different, and fell within the range of 0.095 ± 0.025 m/s. Under high flow conditions, the mean absolute errors associated with using LSPIV derived from terrestrial fixed photography and LSPIV derived from a UAV with flight heights of 32, 62, and 112 m were 0.46 m/s and 0.49 m/s, 0.27 m, and 0.97 m/s, respectively. A UAV flight height of 62 m yielded the best measured surface velocity result. Moreover, we also demonstrated that the optimal appropriate interrogation area and image acquisition time interval using LSPIV with a UAV were 16 × 16 pixels and 1/8 s, respectively. These two parameters should be carefully adopted to accurately measure the surface velocity of rivers.

Combined use of LS-PIV and CFD for the characterization of turbulent flow in the contact chamber of ‘COSTA AZUL’ wastewater treatment plant, Carlos Paz

Abstract The Costa Azul wastewater treatment plant is situated in Carlos Paz city (Córdoba, Argentina). The treated water is discharged to the San Roque reservoir, which is the source of water for the city of Córdoba and surrounding towns. Consequently, it is of great importance to evaluate the potential impact on the water quality reservoir for the preservation of public health. Currently, the WWTP lacks an accurate flow monitoring system at the last treatment: disinfection. This problem led to the development of a methodology in which experimental in-situ work and computational fluid dynamics (CFD) were applied, in a combined way, to calibrate the flow measurement system. First, large-scale particle image velocimetry (LS-PIV) was applied. The results made it possible to obtain characteristic parameters of the average flow: cross-sectional velocity profiles, recirculation and flow stagnation zones, flow discharge and characteristic parameters of the contact chamber. Second, numerical models, based on the Reynolds-average Navier–Stokes equations with the k–ε turbulent closure model were used. Based on the simulation results, it was possible to calibrate the discharge equation for a rectangular weir, and elaborate recommendations to improve the discharge measurement system and hydraulics in the area of the contact chamber curves.

Development of a three-axis accelerometer and large-scale particle image velocimetry (LSPIV) to enhance surface velocity measurements in rivers

A three-axis accelerometer was combined with large-scale particle image velocimetry (LSPIV) to obtain nonintrusive and safe surface velocity measurements. Dual cameras were established at the Yu-Feng gauging station of Shimen Reservoir to capture near-field and far-field images and analyze the surface velocity of rivers. Surface velocity measurements were obtained with a flow meter, LPSIV with ground control points, and LSPIV with a three-axis accelerometer to compare the measurement accuracy. The results show that the relative root mean square error (RMSE) values for LSPIV with ground control points and with the three-axis accelerometer are 21% and 18%, respectively. The LSPIV technique with the three-axis accelerometer slightly improved the measurement accuracy of the surface velocity. However a three-axis accelerometer can be utilized to replace the traditional ground control points for yielding the camera pose parameters. Furthermore, the effects of the camera pose, three-axis acceleration, interrogation area (IA), and image resolution on surface velocity measurements were explored. The camera pose parameters, namely, roll (θ) and tilt (τ), and three-axis acceleration parameters, including Xa and Ya, influence surface velocity measurements. If the measurement error of the surface velocity is controlled within ±10%, the acceptable variational ranges of θ, τ, Xa, and Ya are 6.2°, 1.3°, 0.11 g, and 0.02 g, respectively. The IA size and image resolution also significantly affect the accuracy of surface velocity measurements. Therefore, the selection of a suitable IA size and image resolution is crucial for accurately measuring surface velocity.

Effect of vertical velocity profile approximations on estimates of dam breach discharge using surface velocities

AbstractIn order to investigate the relationship between water surface velocity and breach hydrograph, a series of dam breach experiments with a generalised landslide dam were conducted in an open channel of 50 m × 4 m × 2 m. The large‐scale particle image velocimetry (LSPIV) technique was applied to measure the time history of water surface velocity during the dam breach process, and the hydrography was obtained by integrating the surface velocity along the water depth. The influence of different vertical velocity profile approximation and suspended sediment concentration on the peak breach discharge were analysed and discussed. The results showed that the water depth over the breach crest can be described as a function of water surface velocity using . A simple formula based on surface velocity and breach width for the estimation of breach discharge was further proposed and verified.

Compound-eye imaging imitation-based whole-field flow measurement

Large-scale particle image velocimetry (LSPIV) has been increasingly applied in whole-field flow measurement for its non-contact operation mode. However, due to the complicated flow conditions and optical disturbances on the water-air interface, commonly-used imaging technologies are degenerated by the low visibility and image distortion. There are also increased challenges for control point calibration. This paper proposes an imaging measurement method that imitates the imaging computation mechanism in compound eyes. The method is independent of ground control points and can achieve flow measurement with natural patterns, which can solve the problem caused by the lack of visible tracers. Field evaluation results demonstrate that this is the first method to achieve real-world whole-field flow measurement in challenging conditions. Specifically, the velocimetry error is less than 5%, while ranging from 5% to 15% for other LSPIV systems. The method meets current hydrological standards and acquires flow data in wild rivers, performance that is realized with difficulty by other methods.

Assessing different imaging velocimetry techniques to measure shallow runoff velocities during rain events using an urban drainage physical model

Abstract. Although surface velocities are key in the calibration of physically based urban drainage models, the shallow water depths developed during non-extreme precipitation and the potential risks during flood events limit the availability of this type of data in urban catchments. In this context, imaging velocimetry techniques are being investigated as suitable non-intrusive methods to estimate runoff velocities, when the possible influence of rain has yet to be analyzed. This study carried out a comparative assessment of different seeded and unseeded imaging velocimetry techniques based on large-scale particle image velocimetry (LSPIV) and bubble image velocimetry (BIV) through six realistic but laboratory-controlled experiments, in which the runoff generated by three different rain intensities was recorded. First, the use of naturally generated bubbles and water shadows and glares as tracers allows unseeded techniques to measure extremely shallow flows. However, these techniques are more affected by raindrop impacts, which even lead to erroneous velocities in the case of high rain intensities. At the same time, better results were obtained for high intensities and in complex flows with techniques that use artificial particles. Finally, the study highlights the potential of these imaging techniques for measuring surface velocities in real field applications as well as the importance of considering rain properties to interpret and assess the results obtained. The robustness of the techniques for real-life applications yet remains to be proven by means of further studies in non-controlled environments.

Application of spherical-rod float image velocimetry for evaluating high flow rate in mountain rivers

Spherical-rod float image velocimetry (SFIV) is a convenient technique combining the positive functions of a rod float velocimetry (RFV) and large-scale particle image velocimetry (LSPIV) for measuring high flow rate in mountain rivers. The SFIV is the principle that the sphere allowing little image distortion according to the orientation is used as a floating tracer for LSPIV. The drifting distances of a spherical-rod float were calculated by geometrical interpretation of spherical images recorded in an experimental open channel and mountain rivers. The depth-reflecting velocities estimated by SFIV in the rivers as in the open channel coincided approximately with the velocities by visual observation from river bank despite of the long shooting distance, weather impact, and flow complicated by topography and bed materials. The velocity coefficients obtained from the experimental channel were used to evaluate depth-averaged velocity for river discharges. The high discharges estimated by SFIV in mountain rivers distributed mostly within the range of the rating curve established by RFV. The results show that the safe and efficient SFIV is a highly applicable technique in mountain rivers with the high flow rate and complex flow. In order to practically use SFIV in mountain rivers, additional studies are required for velocity coefficients depending on the water depth and draft.

Recent advancements towards large-scale flow diagnostics by robotic PIV

The present work reviews the recent developments in the domain of particle image velocimetry (PIV) with attention to its use for large-scale problems of interest for industrial aerodynamics. The article introduces the fundamental principles of flow seeding for large-scale experiments based on the helium-filled soap bubble (HFSB) technique. The measurement of flow tracers in a three-dimensional domain is presented, which is based on Lagrangian tracking methods. Furthermore, the concept of co-axial volumetric velocimetry is introduced and its combination with robotic arm manipulation is shown. The work presents two main examples of applications to aerodynamic problems: the first is the flow field around a propeller aircraft at wind tunnel free-stream velocity up to 50 m s−1, which to date is considered the boundary of large-scale PIV application with HFSB. The second example is the complex three-dimensional flow field around a cyclist at full scale. The work summarizes developments obtained in the last 3 years of research, demonstrating that the domain of PIV techniques is still undergoing vivid developments.

RESEARCH ON THE INFLUENCE OF FREE SURFACE ON THE FLOW CHARACTERISTICS OF SUBMARINE WAKE

The flow characteristics around the submarine will affect the maneuverability of the submarine, especially when the submarine is near the water surface, the existence of the free surface will increase the complexity of the wake field of the submarine. In order to explore the influence mechanism of free surface on the flow characteristics of submarine wake when the submarine near the free surface, the research on the flow characteristics of submarine wake is carried out with the help of large-scale underwater three-dimensional particle image velocimetry technology. Firstly, the accuracy of the test method in this study is verified by the standard model experiment of DTMB in USA; Then, the wake field of the submarine is measured by the model test, and the axial velocity and pulsating velocity of the propeller disk under different submergence depths and different speeds are obtained. At the same time, the wave and the velocity field of the longitudinal section which can not be measured by the model test are supplemented by numerical simulation, and the influence mechanism of the free surface on the flow characteristics of the wake field is expounded from the wave point of view. The results show that: When the submarine near the water surface, with the increase of Fr, the upper isopleth of the axial velocity at the propeller disk tends to be flattened; and compared with the 4D submergence depths, the local maximum value of pulsating velocity appears in the 1.5D submergence depths, and the structure of pulsating velocity moves down as a whole. When the free surface exists, the velocity of flow field between the hull and the free surface increases obviously, especially in the area of the propeller disk. With the increase of Fr, the height of the free surface of the propeller disk decreases gradually, which leads to a larger fluid velocity and the squeeze phenomenon of wake field on propeller disk.

Large-Scale Particle Image Velocimetry for Estimating Vena-Contracta Width for Flow in Contracted Open Channels

This paper presents the findings of a flume study using large-scale particle velocimetry (LSPIV) to estimate the top-width of the vena contracta formed by an approach open-channel flow entering a contraction of the channel. LSPIV is an image-based method that non-invasively measures two-dimensional instantaneous free-surface velocities of water flow using video equipment. The experiments investigated the requisite dimensions of two essential LSPIV components—search area and interrogation area– to establish the optimum range of these components for use in LSPIV application to contractions of open-channel flows. Of practical concern (e.g., bridge hydraulics) is flow contraction and contraction scour that can occur in the vena contracta region. The study showed that optimum values for the search area (SA) and interrogation area (IA) were 10 and 60 pixels, respectively. Also, the study produced a curve indicating a trend for vena-contracta width narrowing with a variable ratio of approach-channel and contracted-channel widths and varying bed shear stress of approach flow.

A laboratory experiment of rip currents between the ends of breaking wave crests

abstract In order to investigate the rip current formed between the ends of breaking wave crests, a laboratory experiment was conducted over a bathymetry with an equilibrium profile. For the experiment, pseudo intersecting wave trains were produced in a wave basin, where regular waves were generated by running two parts of wave maker out of phase. The pseudo intersecting wave trains were compared with the intersecting wave trains, which are formed by the interference of two wave trains with slightly different directions and are the cause of the rip current, by conducting numerical simulations using FUNWAVE. The rip current developments between the ends of breaking wave crests through their node regions were confirmed similarly in both numerical simulations. In the hydraulic experiment using the pseudo intersecting wave trains, the rip current flow was observed by utilizing Large Scale Particle Image Velocimetry and Acoustic Doppler Velocimetry, and the wave height and the mean surface were measured. From the observations, it was confirmed that the rip current was developed through the node region with relatively low wave height, and it was found that its strength was varied by the refraction and dissipation of the ends of wave crests due to the wave-current interaction. The horizontal and vertical velocity profiles of the rip current were presented in the present experiment. The comparison between the measured results and the numerical results showed a reasonable agreement, however, also confirmed the limitation of the numerical model on breaking and mixing process. Using particle trajectories, it was observed that vortices were developed at the ends of breaking wave crests, which played a role of generating and accelerating the rip current.

Real-time on-machine observations close to interelectrode gap in a tool-based hybrid laser-electrochemical micromachining process

A tool-based hybrid laser-electrochemical micromachining process involves concurrent application of two process energies i.e. electrochemical and laser in the same machining zone by means of a hybrid tool which serves as an ECM tool as well as a multimode waveguide. It is a relatively novel process finding applications in defect-free machining of difficult-to-cut materials without affecting their microstructure. In order to understand the physical phenomena occurring during this process, in-situ observations are required. Therefore, in this work, a real time observation was carried out of a novel tool-based hybrid laser electrochemical micromachining process. A combination of high-speed imaging and Large Scale Particle Image Velocimetry (LSPIV) was used to visualize the tool-based hybrid laser-ECM process in real time. It also allowed to carry out experimental investigations on the by-products and bubble generation which have a direct effect on process performance in terms of accuracy and efficiency. The real-time on-machine observations are unique of its kind and they will facilitate the understanding of underlying mechanisms governing this hybrid laser-electrochemical micromachining process. This will ultimately help in improving the quality of parts manufactured. This research is also a step forward towards making these physics-based hybrid processes deterministic by employing high-speed imaging in a closed loop control.

Application of masked two-dimensional Fourier spectra for improving the accuracy of STIV-based river surface flow velocity measurements

Space-time image velocimetry (STIV) is a well-established image-based technique for measuring river surface flow from videos or image time series. Because the fundamental measurement mechanism is relatively simple, STIV has been used widely in research and for practical purposes in Japan and other countries. The advantage of STIV over other imaging techniques such as large-scale particle image velocimetry (LSPIV) is its robustness. More specifically, the streamwise velocity component can be efficiently estimated by simply measuring the slope appearing in a space-time image (STI) that represents the advection of surface textures. However, in the course of practical applications cases occur in which STIV yields erroneous results when the measurement conditions at the river site are not satisfactory for accurate measurements, such as when the water surface includes textures other than those directly related to turbulent advection. In this research, surface textures are classified into ten types and image filters based on wavenumber–frequency spectra are developed to improve the quality of the STI so that the texture contains only those features that represents the advection of surface turbulence. The quality of the STI can be improved with the filters and thus further increase the robustness of the measurement technique.

Metrics for the Quantification of Seeding Characteristics to Enhance Image Velocimetry Performance in Rivers

River flow monitoring is essential for many hydraulic and hydrologic applications related to water resource management and flood forecasting. Currently, unmanned aerial systems (UASs) combined with image velocimetry techniques provide a significant low-cost alternative for hydraulic monitoring, allowing the estimation of river stream flows and surface flow velocities based on video acquisitions. The accuracy of these methods tends to be sensitive to several factors, such as the presence of floating materials (transiting onto the stream surface), challenging environmental conditions, and the choice of a proper experimental setting. In most real-world cases, the seeding density is not constant during the acquisition period, so it is not unusual for the patterns generated by tracers to have non-uniform distribution. As a consequence, these patterns are not easily identifiable and are thus not trackable, especially during floods. We aimed to quantify the accuracy of particle tracking velocimetry (PTV) and large-scale particle image velocimetry (LSPIV) techniques under different hydrological and seeding conditions using footage acquired by UASs. With this aim, three metrics were adopted to explore the relationship between seeding density, tracer characteristics, and their spatial distribution in image velocimetry accuracy. The results demonstrate that prior knowledge of seeding characteristics in the field can help with the use of these techniques, providing a priori evaluation of the quality of the frame sequence for post-processing.

Multi-camera large-scale particle image velocimetry

Large-scale particle image velocimetry (LSPIV) has been widely used for quantifying the velocity distribution of environmental water surfaces, especially river flows. In LSPIV, the evaluated velocity distribution of a region far from the camera tends to have a large uncertainty due to strong image distortion and reduced image resolution, especially for directions parallel to the viewing angle. This study proposes a method that overcomes this problem by combining the results of LSPIV measurements of images obtained from different viewing angles. The velocity component for the direction orthogonal to the viewing angle (the 1D velocity component) for each viewing angle was extracted and then the 2D velocity field was reconstructed based on a least squares algorithm. To validate the proposed method, a rigid rotating disk experiment and a circulatory flow flume experiment were conducted. The method was used to reproduce a complex flow formed around an opposite river edge using images obtained from two different locations on a river bank. Circulatory flow was not visible from results obtained from single viewing angles but was successfully represented in the reconstructed velocity field.

Applying large-scale PIV to water monitor discharge experiment

Industrial fires are undeniably the most dangerous type of fires for firefighters, and the master stream from water monitor is one of the safest means to deploy defensive or offensive strategies against such fires. However, few studies pay attention to the efficacy of the master stream. To address this issue, we extracted and analyzed numerical data from physical master streams. The proposed methods comprising of digital image processing (DIP) and large-scale particle image velocimetry (LS-PIV), which were conducted in the full-scale discharge in order to obtain coordinate trajectory pattern as well as the instantaneous and mean vector-velocity fields. The flow vectors in the different zones of the master stream were compared using KAZE feature detection. This study thus offers more extensive and detailed experimental data to validate computational fluid dynamics (CFD) simulations and opens an avenue for future fire-safety research.

Drone-Based Optical Measurements of Heterogeneous Surface Velocity Fields around Fish Passages at Hydropower Dams

In Austria, more than a half of all electricity is produced with the help of hydropower plants. To reduce their ecological impact, dams are being equipped with fish passages that support connectivity of habitats of riverine fish species, contributing to hydropower sustainability. The efficiency of fish passages is being constantly monitored and improved. Since the likelihood of fish passages to be discovered by fish depends, inter alia, on flow conditions near their entrances, these conditions have to be monitored as well. In this study, we employ large-scale particle image velocimetry (LSPIV) in seeded flow conditions to analyse images of the area near a fish passage entrance, captured with the help of a ready-to-fly consumer drone. We apply LSPIV to short image sequences and test different LSPIV interrogation area sizes and correlation methods. The study demonstrates that LSPIV based on ensemble correlation yields velocities that are in good agreement with the reference values regarding both magnitude and flow direction. Therefore, this non-intrusive methodology has a potential to be used for flow monitoring near fish passages on a regular basis, enabling timely reaction to undesired changes in flow conditions when possible.

An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems

Image velocimetry has proven to be a promising technique for monitoring river flows using remotely operated platforms such as Unmanned Aerial Systems (UAS). However, the application of various image velocimetry algorithms has not been extensively assessed. Therefore, a sensitivity analysis has been conducted on five different image velocimetry algorithms including Large Scale Particle Image Velocimetry (LSPIV), Large-Scale Particle Tracking Velocimetry (LSPTV), Kanade–Lucas Tomasi Image Velocimetry (KLT-IV or KLT), Optical Tracking Velocimetry (OTV) and Surface Structure Image Velocimetry (SSIV), during low river flow conditions (average surface velocities of 0.12–0.14 m s − 1 , Q60) on the River Kolubara, Central Serbia. A DJI Phantom 4 Pro UAS was used to collect two 30-second videos of the surface flow. Artificial seeding material was distributed homogeneously across the rivers surface, to enhance the conditions for image velocimetry techniques. The sensitivity analysis was performed on comparable parameters between the different algorithms, including the particle identification area parameters (such as Interrogation Area (LSPIV, LSPTV and SSIV), Block Size (KLT-IV) and Trajectory Length (OTV)) and the feature extraction rate. Results highlighted that KLT and SSIV were sensitive to changing the feature extraction rate; however, changing the particle identification area did not affect the surface velocity results significantly. OTV and LSPTV, on the other hand, highlighted that changing the particle identification area presented higher variability in the results, while changing the feature extraction rate did not affect the surface velocity outputs. LSPIV proved to be sensitive to changing both the feature extraction rate and the particle identification area. This analysis has led to the conclusions that for surface velocities of approximately 0.12 m s − 1 image velocimetry techniques can provide results comparable to traditional techniques such as ADCPs. However, LSPIV, LSPTV and OTV require additional effort for calibration and selecting the appropriate parameters when compared to KLT-IV and SSIV. Despite the varying levels of sensitivity of each algorithm to changing parameters, all configuration image velocimetry algorithms provided results that were within 0.05 m s − 1 of the ADCP measurements, on average.