Streamflow Observations From Cameras: Large-Scale Particle Image Velocimetry or Particle Tracking Velocimetry?

2017 ◽  
Vol 53 (12) ◽  
pp. 10374-10394 ◽  
Author(s):  
F. Tauro ◽  
R. Piscopia ◽  
S. Grimaldi
Keyword(s):  
Particle Image Velocimetry ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Large Scale ◽  
Particle Image ◽  
Image Velocimetry ◽  
Scale Particle

scholarly journals Evidence of preferential sweeping during snow settling in atmospheric turbulence

2021 ◽  
Vol 928 ◽  
Author(s):  
Jiaqi Li ◽  
Aliza Abraham ◽  
Michele Guala ◽  
Jiarong Hong
Keyword(s):  
Particle Image Velocimetry ◽  
Flow Field ◽  
Particle Tracking ◽  
Particle Tracking Velocimetry ◽  
Large Scale ◽  
Particle Image ◽  
Atmospheric Flow ◽  
Image Velocimetry ◽  
Snow Particle ◽  
Scale Particle

We present a field study of snow settling dynamics based on simultaneous measurements of the atmospheric flow field and snow particle trajectories. Specifically, a super-large-scale particle image velocimetry (SLPIV) system using natural snow particles as tracers is deployed to quantify the velocity field and identify vortex structures in a 22 m  $\times$  39 m field of view centred 18 m above the ground. Simultaneously, we track individual snow particles in a 3 m  $\times$  5 m sample area within the SLPIV using particle tracking velocimetry. The results reveal the direct linkage among vortex structures in atmospheric turbulence, the spatial distribution of snow particle concentration and their settling dynamics. In particular, with snow turbulence interaction at near-critical Stokes number, the settling velocity enhancement of snow particles is multifold, and larger than what has been observed in previous field studies. Super-large-scale particle image velocimetry measurements show a higher concentration of snow particles preferentially located on the downward side of the vortices identified in the atmospheric flow field. Particle tracking velocimetry, performed on high resolution images around the reconstructed vortices, confirms the latter trend and provides statistical evidence of the acceleration of snow particles, as they move toward the downward side of vortices. Overall, the simultaneous multi-scale particle imaging presented here enables us to directly quantify the salient features of preferential sweeping, supporting it as an underlying mechanism of snow settling enhancement in the atmospheric surface layer.

Development and Testing of an Unmanned Aerial Vehicle for Large Scale Particle Image Velocimetry

2014 ◽  
Author(s):  
Christopher Pagano ◽  
Flavia Tauro ◽  
Salvatore Grimaldi ◽  
Maurizio Porfiri
Keyword(s):  
Particle Image Velocimetry ◽  
Large Scale ◽  
Field Experiments ◽  
Particle Image ◽  
Low Cost ◽  
Surface Flow ◽  
Natural Environments ◽  
Natural Stream ◽  
Image Velocimetry ◽  
Scale Particle

Large scale particle image velocimetry (LSPIV) is a nonintrusive environmental monitoring methodology that allows for continuous characterization of surface flows in natural catchments. Despite its promise, the implementation of LSPIV in natural environments is limited to areas accessible to human operators. In this work, we propose a novel experimental configuration that allows for unsupervised LSPIV over large water bodies. Specifically, we design, develop, and characterize a lightweight, low cost, and stable quadricopter hosting a digital acquisition system. An active gimbal maintains the camera lens orthogonal to the water surface, thus preventing severe image distortions. Field experiments are performed to characterize the vehicle and assess the feasibility of the approach. We demonstrate that the quadricopter can hover above an area of 1×1m2 for 4–5 minutes with a payload of 500g. Further, LSPIV measurements on a natural stream confirm that the methodology can be reliably used for surface flow studies.

Multi-camera large-scale particle image velocimetry

2020 ◽  
Vol 31 (8) ◽  
pp. 084004
Author(s):  
Ryota Tsubaki
Keyword(s):  
Particle Image Velocimetry ◽  
Large Scale ◽  
Particle Image ◽  
Image Velocimetry ◽  
Scale Particle

Large Scale Particle Image Velocimetry for Low Velocity and Shallow Water Flows

2004 ◽  
Vol 130 (9) ◽  
pp. 937-940 ◽  
Author(s):  
E. A. Meselhe ◽  
T. Peeva ◽  
M. Muste
Keyword(s):  
Particle Image Velocimetry ◽  
Shallow Water ◽  
Large Scale ◽  
Particle Image ◽  
Low Velocity ◽  
Water Flows ◽  
Shallow Water Flows ◽  
Image Velocimetry ◽  
Scale Particle

scholarly journals Stream discharge using mobile large-scale particle image velocimetry: A proof of concept

2008 ◽  
Vol 44 (9) ◽  
Author(s):  
Y. Kim ◽  
M. Muste ◽  
A. Hauet ◽  
W. F. Krajewski ◽  
A. Kruger ◽  
...  
Keyword(s):  
Particle Image Velocimetry ◽  
Large Scale ◽  
Particle Image ◽  
Proof Of Concept ◽  
Stream Discharge ◽  
Image Velocimetry ◽  
Scale Particle

Large scale particle image velocimetry measurement of river surface velocity based on images captured by a camera of the mobile phone

2020 ◽  
Author(s):  
Wen-Cheng Liu ◽  
Wei-Che Huang
Keyword(s):  
Particle Image Velocimetry ◽  
Mobile Phone ◽  
Large Scale ◽  
Particle Image ◽  
Digital Camera ◽  
Real Space ◽  
Surface Velocity ◽  
Image Velocimetry ◽  
Scale Particle ◽  
Perspective Center

<p>In this research, we conducted LSPIV (Large Scale Particle Image Velocimetry) measurements to measure river surface velocity based on images recorded by mobile phone. The realization of this research is based on the developments of two products. The first one is the digital camera, which has been combined with the mobile phone after several years of development. The second one is the three-axis accelerometer, which can measure the attitude of the object. A three-axis accelerometer is one of the necessary parts of the mobile phone nowadays, as many functions of the mobile phone, such as step counting, Do Not Disturb mode, games, require the detection of attitude.</p><p>In LSPIV, there are nine parameters of the collinear equation. Three of parameters are the coordinates of the perspective center in the image space (focus distance d and image center position (u, v)), which can be determined in advance in the laboratory; the other three parameters are the coordinates (x, y, z) of the perspective center in real space, which can be set to (0, 0, 0); the last three parameters are the attitude of the camera (i.e., the mobile phone), which is determined by the depression angle, the horizontal angle, and the left-right rotation angle and can be measured by three-axis accelerometer. Therefore, river surface velocity could be analyzed by LSPIV with not only continuous images captured by a camera of the mobile phone but also the acceleration values obtained by the three-axis accelerometer when each image was captured.</p><p>In the present study, Yufeng gauging station, which is in the upstream catchment of the Shihmen Reservoir in Taiwan, is selected as the study site. Two other measurement methods were used to measure the river surface velocity and the comparison was conducted. One is using a handheld digital flow meter and another is using LSPIV with control points to calculate the parameters for measuring the river surface velocity.</p>

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