Large-scale Particle Image Velocimetry Measurements Research Articles

Experimental investigations on the effects of longitudinal groove fabric for drag reductions on a track cyclist

The previous study has shown that the longitudinal groove fabric can reduce drag forces on a circular cylinder by forcing a drag crisis (Zheng et al. 2021). In this study, the effects of the longitudinal groove fabric are investigated on a full-scale track cycling mannequin. The force measurement results show that the longitudinal groove fabric on the upper arms can achieve a maximum drag reduction of about 7% at a flow speed of 17 m/s, and its control effects depend on flow speeds. Large-scale particle image velocimetry measurements further show that the drag reductions on the upper arm are characterized by diminished streamwise velocity deficits. The control effects also vary on different spanwise locations of the arm, where the flow behaves distinctively. The measurements also reveal the distinct flow dynamics at different heights, i.e., wake interactions and swirling motions, showing the complexity of reducing drag forces from a track cyclist.

LSPIV measurements to assess the impact of a bridge on a weakly undulating flow

The modification of the surface velocity field of the weakly undulating flow in a reach of the Suquía River (Córdoba city, Argentina) due to the placement of a bridge was investigated in a physical model. Measurements using Large-Scale Particle Image Velocimetry (LSPIV) allowed evaluating how the hydraulic structure changes the size, shape, wavelength, and relative position to river centerline of the wave train downstream of the first ridge of the weak undular jump. Analysis and discussion of results in terms of the dimensionless parameters reported in the literature (obtained from laboratory studies) are offered. Results show that LSPIV is a reliable, fast low-cost tool to gather valuable information regarding the surficial flow field at the physical model scale in the presence of a weakly undular flow.

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.

LSPIV Measurements of Two‐Dimensional Flow Structure in Streams Using Small Unmanned Aerial Systems: 2. Hydrodynamic Mapping at River Confluences

AbstractAlthough past field work at stream confluences has relied on velocity information at specific cross sections to examine flow structure, detailed characterizations of spatial and temporal variations in the hydrodynamics of confluences are lacking. This study uses large‐scale particle image velocimetry (LSPIV) obtained from small unmanned aerial systems (sUAS), a method evaluated in a companion paper, to map surficial patterns of mean flow and turbulent structures at two small stream confluences in unprecedented levels of detail. LSPIV reveals two‐dimensional flow patterns within different hydrodynamic zones in each confluence as well as similarities and differences in hydrodynamic conditions between the confluences. As expected based on extant conceptual models of confluence hydrodynamics, the spatial arrangement of characteristic hydrodynamic zones varies with confluence planform geometry and with changes in incoming flow conditions. However, local morphological features, such as bars and irregularities in channel banks, also exert a strong influence on the spatial structure of flow and in some cases influence confluence hydrodynamics to an extent comparable to changes in incoming flow conditions. The usefulness of sUAS‐based LSPIV is demonstrated by the correspondence between patterns of flow curvature revealed by this method and patterns of helical motion documented at cross sections within the confluences using acoustic Doppler velocimetry. The method can also be used to characterize the structure of turbulent vortices within the mixing interface between confluent streams under appropriate conditions. Hydrodynamic mapping using sUAS‐based LSPIV enriches the interpretation of traditional in‐stream velocity data acquired in the field and provides information on surface velocity patterns in rivers at a resolution similar to that of numerical models.

LSPIV Measurements of Two‐Dimensional Flow Structure in Streams Using Small Unmanned Aerial Systems: 1. Accuracy Assessment Based on Comparison With Stationary Camera Platforms and In‐Stream Velocity Measurements

AbstractMeasuring two‐dimensional (2‐D) patterns of flow in rivers at high resolution over large areas is challenging using traditional velocity‐measurement methods, which provide data at specific locations or cross sections. Large‐scale particle image velocimetry (LSPIV) based on imagery obtained from fixed camera platforms can measure flow velocity on the surface of rivers and is generally accurate compared to near‐surface velocity measurements obtained by traditional methods. The proliferation of inexpensive small unmanned aerial systems (sUAS) equipped with high‐resolution cameras and onboard GPS has the potential to facilitate measurements of flow patterns in rivers using LSPIV, but few studies have assessed the accuracy of sUAS‐derived LSPIV compared to fixed‐platform LSPIV and in‐stream velocity measurements. This study assesses the accuracy of sUAS‐based LSPIV for measuring 2‐D mean surface velocities as well as quasi‐instantaneous 2‐D velocities obtained from successive image frames. For persistent 2‐D flow, mean velocities derived from sUAS‐based LSPIV match those obtained by stationary camera platforms, and velocities measured by both LSPIV methods agree with near‐surface velocities measured by an acoustic Doppler velocimeter. Quasi‐instantaneous velocities are degraded by camera movement and low pixel resolution, but capturing the evolution of 2‐D flow structures is possible in certain circumstances. The results confirm that sUAS‐derived LSPIV provides accurate, high‐resolution measurements of mean surface velocities over large spatial areas of persistent 2‐D flow and can characterize evolving 2‐D flow structures under favorable conditions. sUAS‐based LSPIV is a valuable new method for mapping of 2‐D patterns of surface flow in rivers—an issue explored in a companion paper.

Unseeded large scale PIV measurements corrected for the capillary-gravity wave dynamics

Large scale particle image velocimetry (LSPIV) has become a reliable and accurate technique to measure water surface velocity field in open channels and rivers. The LSPIV technique is based on a camera view framing the water surface, complemented with image-processing methods to compute water surface displacements between consecutive frames. Using LSPIV, high flow velocities, such as flood conditions, are accurately measured, whereas determinations of low flow regimes is more challenging, especially in the absence of floating material carried by the stream. In fact, in unseeded conditions, typical surface feature dynamics must be taken into account. Indeed, besides surface structures advected by the current, capillary-gravity waves propagate on the surface, with their own speed and direction. In this study, the discrimination between these phenomena is discussed, providing a new method to distinguish and to correct unseeded LSPIV measurements with capillary-gravity wave dynamics. Current velocity obtained with such a correction at low flow speed in an artificial channel and in a natural river is in fair agreement with reference observations indicating the need of accounting for the speed and direction of capillary-gravity waves on the surface to obtain reliable measurements of the current vector field, and, as a further result, of the flow discharge over a river cross-section.

Validation of large-scale particle image velocimetry to acquire free-surface flow fields in vegetated rivers

The reliability of large-scale particle image velocimetry (LSPIV) methodology to measure a 2D surface velocity field in a vegetated lowland stream is evaluated. To this end, measurements of the free-surface flow field obtained with LSPIV are compared with measurements with an electromagnetic current meter (ECM) close to the surface at four different locations. The measurements were performed monthly, allowing the evaluation of the LSPIV measurements in relation to different vegetated conditions. The difference observed between the mean velocities measured with ECM and LSPIV remains low in winter, whereas an increase is observed in summer. Inappropriate particle seeding density and unsteadiness of the flow are the main sources of LSPIV reliability reduction. Nonetheless, the seasonal average frequency of reliable LSPIV measurements is 97%, 95% and 78% in winter, spring and summer, respectively. The results illustrate that LSPIV is an inexpensive methodology, which provides high-resolution and reliable data to study the flow-field distribution in vegetated rivers, provided some considerations are taken into account to deal with the added complexity of the vegetation presence and the field conditions.

Considerations on direct stream flow measurements using video imagery: Outlook and research needs

The paper presents measurements acquired with Large-Scale Particle Image Velocimetry (LSPIV) during normal flows and floods in the Iowa River (U.S.A). For normal flows, comparison is made with measurements obtained with Acoustic Doppler Current Profilers (ADCP) in order to test LSPIV’s performance and to address concerns potentially affecting the accuracy of the measurements. The historic flood of the Iowa River during the summer of 2008 was captured for testing LSPIV capabilities during extreme flows. Lacking alternative measurements during the flood, the LSPIV measurements are compared to the rating curve extrapolated for high flows using a one-to-one discharge–stage relationship. The comparison reveals limitations of the single-values rating curve for providing discharge estimates during high flows. Finally, the paper summarizes lessons learned during these and previous LSPIV studies with the intent to chart the research needed to enhance this promising non-intrusive field measurement technique.

Performance of image-based velocimetry (LSPIV) applied to flash-flood discharge measurements in Mediterranean rivers

Summary Flash-floods that occur in Mediterranean regions result in significant casualties and economic impacts. Remote image-based techniques such as Large-Scale Particle Image Velocimetry (LSPIV) offer an opportunity to improve the accuracy of flow rate measurements during such events, by measuring the surface flow velocities. During recent floods of the Ardeche river, LSPIV performance tests were conducted at the Sauze–Saint Martin gauging station without adding tracers. The rating curve is well documented, with gauged discharge ranging from 4.8 m 3 s −1 to 2700 m 3 s −1 , i.e., mean velocity from 0.02 m s −1 to 2.9 m s −1 . Mobile LSPIV measurements were carried out using a telescopic mast with a remotely-controlled platform equipped with a video camera. Also, LSPIV measurements were performed using the images recorded by a fixed camera. A specific attention was paid to the hydraulic assumptions made for computing the river discharge from the LSPIV surface velocity measurements. Simple solutions for interpolating and extrapolating missing or poor-quality velocity measurements, especially in the image far-field, were applied. Theoretical considerations on the depth-average velocity to surface velocity ratio (or velocity coefficient) variability supported the analysis of velocity profiles established from available gauging datasets, from which a velocity coefficient value of 0.90 (standard deviation 0.05) was derived. For a discharge of 300 m 3 s −1 , LSPIV velocities throughout the river cross-section were found to be in good agreement (±10%) with concurrent measurements by Doppler profiler (ADCP). For discharges ranging from 300 to 2500 m 3 s −1 , LSPIV discharges usually were in acceptable agreement (

Large-scale eddies measured with large scale particle image velocimetry

Large-scale eddies are turbulent features of open channels that advect along the direction of the mean flow in a streamwise rolling motion and comprise the entire flow depth. In order to advance the understanding of large-scale eddies, it is increasingly important to make measurements on a large scale test section or in a river reach. The objective of this research was to measure characteristics of large-scale eddies using large scale particle image velocimetry (LSPIV) for the first time. A gravel-bed flume was chosen in order that the LSPIV technology could be applied for an environment where the eddies were known to exist. LSPIV was used to make free-surface velocity measurements in the flume for quasi-steady, uniform flow. After removing erroneous LSPIV measurements due to light reflections and inadequate seed concentrations, turbulence decomposition via the triple decomposition theorem was used to isolate the large-scale eddies from the small-scale bursting derived eddies. Visual inspection of the decomposed data, coupled with quantitative analyses of the statistical moments of the decomposed velocity and evaluation of the velocity spectrum, were used to objectively choose a decomposition time-step. The decomposed data was visualized and characteristics of the large-scale eddies were measured. LSPIV data showed that the eddy length of the large-scale eddies was approximately 4 H , agreeing with past research. The large-scale eddies were not fully organized within the flow. The eddies propagated downstream as long-lived stable structures throughout the test section. Future research of the large-scale eddies is needed under a wide range of conditions, and LSPIV is expected to help serve this need in both large scale laboratory investigations and in the field under a range of bed conditions and flow conditions.

Sensitivity study of large-scale particle image velocimetry measurement of river discharge using numerical simulation

This study deals with the uncertainty of large-scale particle image velocimetry (LSPIV) measurements in rivers. LSPIV belongs to the methods of local remote sensing of rivers, like Radar- and Lidar-based techniques. These methods have many potential advantages, in comparison with classical river gauging, but they have a fundamental drawback: they are indirect measurements. As such they need to be assessed in reference to direct measurements. A first validation method consists in the comparison of LSPIV measurements with classic gauging results, in field and laboratory experiments. Unfortunately, in both cases, it is impossible in practice to control all the parameters and to distinguish the impact of the various error sources. In the present study we propose a more theoretical assessment of LSPIV potential through numerical simulation. The idea is simply to mathematically formulate the present state of knowledge of the measurement including both the physics of the phenomenon (the illuminated river) and the physics of the sensor (the camera and the PIV tracking). The dilemma about when to start this type of simulation is the following: – The simulation is satisfactory if we can validate it which means to be able to compare simulations and observations over a wide range of conditions. – The simulation is useful to get preliminary insights about the most important measurement conditions to organize validation studies. Our simulator is composed of three blocks: (1) The river block represents the unidirectional river flow by the association of the EDM model and a theoretical vertical velocity profile giving a 3D velocity distribution. This hydraulic model is complemented by features representing free surface tracers, the illumination of the free-surface (shadows and sun reflection) and the effect of the wind. (2) The camera block transforms the river state parameters into raster images according to the intrinsic and extrinsic parameters of the camera. (3) The LSPIV analysis block performs a classical LSPIV analysis, including geometric transformation of the images, PIV analysis to obtain a surface velocity field, and discharge computation. We tried to keep a good balance between the different blocks of the simulator (i.e. not to make one component much more sophisticated than the others). The simulator was partly tested during the development of its different blocks, and then globally validated. It reproduced well the variability observed in the field LSPIV experiments conducted with the real-time continuous system of Hauet et al. [Hauet, A., Kruger, A., Krajewski, W., Bradley, A., Muste, M., Creutin, J.D., Wilson, M., 2008. Experimental system for real-time discharge estimation using an image-based method. Journal of Hydrologic Engineering]. The simulator can also be used to check different scenarios and to assess relative importance of the different sources of error. With two examples, we illustrate this capability of the simulator to assess the relative weight of a given error source and to test a new configuration of measurement.

Case Study: Particle Velocimetry in a Model of Lake Ogallala

In a case study of Lake Ogallala, a reservoir in central Nebraska, large scale particle tracking velocimetry (LSPTV) is used to measure surface velocities in a physical model of the lake. Knowledge of flow patterns in the lake is essential for predicting the transport of dissolved oxygen (DO). A preliminary comparison with acoustic Doppler velocimetery (ADV) measurements shows that both LSPTV and large scale particle image velocimetry (LSPIV) accurately measure surface velocities. In the present study, LSPTV works better near flow boundaries and in regions with high velocity gradients since smaller sampling areas are possible, and unlike LSPIV measurements, LSPTV measurements are unbiased. Discharges measured at eight different transects using LSPTV were within 6% of the discharge measured with an orifice, the worst correlation occurring where the bathymetry was slightly nonuniform (making application of the 1/7-power law suspect). In the prototype, DO content periodically drops to unacceptable levels throughout most of the Keystone Basin (a subbasin of Lake Ogallala). Predicted flow patterns suggest that low DO problems are exacerbated in regions with low velocities since oxygen consumed by macrophytes during nighttime hours is not quickly replenished.