• Journal of Environmental Science International
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• v.22 no.5
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• pp.581-589
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• 2013

Surface Image Velocimetry(SIV) is an instrument to measure water surface velocity by using image processing techniques. Since SIV is a non-contact type measurement method, it is very effective and useful to measure water surface velocity for steep mountainous streams, such as streams in Jeju island. In the present study, a surface imaging velocimetry system was used to calculate the flow rate for flood event due to a typhoon. At the same time, two types of electromagnetic surface velocimetries (electromagnetic surface current meter and Kalesto) were used to observe flow velocities and compare the accuracies of each instrument. The comparison showed that for velocity distributions root mean square error(RMSE) was 0.33 and R-squared was 0.72. For discharge measurements, root mean square error(RMSE) reached 6.04 and R-squared did 0.92. It means that surface image velocimetry could be used as an alternative method for electromagnetic surface velocimetries in measuring flood discharge.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.359-369
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• 2015

This study analyzed the velocimetry of runoff and measured the flood discharge by applying the SIV (Surface Image Velocimetrer) to the daytime and nighttime flow image data with special reference to Seong-eup Bridge at Cheonmi stream of Jeju during the flow by the severe rainstorm on May 27, 2013. A 1000W lighting apparatus with more than 150 lux was installed in order to collect proper nighttime flow image applied to the SIV. Its value was compared and analyzed with the velocity value of the fixed electromagnetic wave surface velocimetry (Kalesto) at the same point to check the accuracy and applicability of the measured velocity of flow. As a result, determination coefficient $R^2$ values were 0.891 and 0.848 respectively in line with the velocity distribution of the daytime and nighttime image and the flow volume measured with Kalesto was approximately 18.2% larger than the value measured with the SIV.

• Journal of the Korean Society of Visualization
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• v.1 no.2
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• pp.13-16
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• 2003

LSPIV(Large Scale Particle Image Velocimetry) is widely used in the field of civil and environmental engineering. General aspects of LSPIV are introduced and several applications are introduced in this paper. The difference of LSPIV from the conventional PIV techniques is not to use models for experiments but to use the flow fields in nature. For LSPIV a converting process for the captured images is necessary.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.933-942
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• 2021

The surface image velocimetry was developed to measure river flow velocity safely and effectively in flood season. There are a couple of methods in the surface image velocimetry. Among them the spatio-temporal image velocimetry is in the spotlight, since it can estimate mean velocity for a period of time. For the spatio-temporal image velocimetry analyzes a series of images all at once, it can reduce analyzing time so much. It, however, has a little drawback to find out the main flow direction. If the direction of spatio-temporal image does not coincide to the main flow direction, it may cause singnificant error in velocity. The present study aims to propose a new method to find out the main flow direction by using a fast Fourier transform(FFT) to a spatio-temporal (image) volume, which were constructed by accumulating the river surface images along the time direction. The method consists of two steps; the first step for finding main flow direction in space image and the second step for calculating the velocity magnitude in main flow direction in spatio-temporal image. In the first step a time-accumulated image was made from the spatio-temporal volume along the time direction. We analyzed this time-accumulated image by using FFT and figured out the main flow direction from the transformed image. Then a spatio-temporal image in main flow direction was extracted from the spatio-temporal volume. Once again, the spatio-temporal image was analyzed by FFT and velocity magnitudes were calculated from the transformed image. The proposed method was applied to a series of artificial images for error analysis. It was shown that the proposed method could analyze two-dimensional flow field with fairly good accuracy.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.154-162
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• 2022

In this study, a technique for estimating water surface velocity fields in the Universal Transverse Mercator coordinate system using the GPS information of a propagating drone but not ground control points is developed. First, we determine the image direction in which the upper side of an image is directed based on the navigation information of the drone. Subsequently, we assign the start and end frames of the video used and determine the analysis range. Using these two frames, we segment the measurement cross-section into a few subsections at regular intervals. At these subsections, we analyze 30 frame images to create spatio-temporal volumes for calculating the velocity fields. The results of the developed method (propagating drone surface image velocimetry) are compared with those of the existing method (hovering drone surface image velocimetry), and relatively good agreement is indicated between both in terms of the velocity fields.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.3
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• pp.404-413
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• 2013

In the present study, a towed underwater particle image velocimetry (PIV) system was validated in uniform flow and used to investigate the free-surface effects on the turbulent wake of a simple surface-piercing body. The selected test model was a cylindrical geometry formed by extruding the Wigley hull's waterplane shape in the vertical direction. Due to the constraints of the two-dimensional (2D) PIV system used for the present study, the velocity field measurements were done separately for the vertical and horizontal planes. Using the measured data at several different locations, it was possible to identify the free-surface effects on the turbulent wake in terms of the mean velocity components and turbulence quantities. In order to provide an accuracy level of the data, uncertainty assessment was done following the International Towing Tank Conference standard procedure.

• Journal of Korea Water Resources Association
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• v.41 no.8
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• pp.855-862
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• 2008

Surface Image Velocimetry (SIV) is an instrument to measure water surface velocity by using image processing techniques. To improve its measuring accuracy, it is essential to get high quality images with low skewness. A truck-mounted SIV system would be a good way to get images, since its crane gives high altitude to the images. However, the images taken with a truck-mounted SIV would be swayed due to the movement of crane and the camera by winds. In that case, to analyze the images, it is necessary to compensate the side sway in the images. The present study is to develop an algorithm to analyze the swayed images by combining common image processing techniques and coordinate transform techniques. The system follows the traces of some selected fixed points and calculates the displacements of the video camera. By subtracting the average velocity of the fixed points from that of grid points, the velocity fields of the flow can be corrected. To evaluate the system's performance, two image sets were used, one image set without side sway and another set with side sway. The comparison of their results showed very close with the error of around 6 %.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.739-742
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• 2008

Surface Image Velocity (SIV) is a technique which measures the surface velocity of river by using the principle of Paticle Image Velocimetry (PIV). The technique is economical and efficient way to measure velocity in rivers. The present paper aims to apply the technique to three rivers in Korea. It uses pairs of river surface images taken with two digital-cameras and reference points and cross section data which were acquired through plane survey. The performance of SIV was verified with automatic cart on an experimental flume. The test revealed that average error was less than 10 %, which assures that SIV can be used to measure velocity accurately. When it was applied to rivers with low water levels or rough weather condition, however, it showed the error about 20 %. If the problems of SIV technique are settled down, it can be one of the most convenient and economical ways to measure water discharge anytime and anywhere. And then it would be helpful to river management as developing a real-time river information system.

• Journal of Ocean Engineering and Technology
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• v.25 no.4
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• pp.23-27
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• 2011

This experimental study was performed to find rpms of the impeller and the surface flow accelerator to make a uniform velocity vertical distribution in the circular water channel. PIV technique was employed to measure the water velocity profiles into the water depth from the free surface. The number of instantaneous velocity profiles was decomposed into mean and turbulence velocity components, and the distribution of velocity fluctuation and turbulence intensity were computed for each experimental condition. From these results, the velocity uniformity was quantitatively determined to present the flow quality in the measuring section of the circular water channel. It has been shown that the proper operation of the surface flow accelerator would make the uniform velocity profiles and reduce the velocity fluctuation near the free surface.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.4
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• pp.453-460
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• 2005

Experiments were conducted to investigate the effect of the surface roughness on the flat plate turbulent boundary layer. The square rods were installed at the leading edge to make surface roughness. The particle image velocimetry was used to measure the mean velocities and velocity fluctuation component. All measurements were made over a range of w/k=1. 2 5 and $Re_x=80.000{\sim}360,000$. Friction velocity was measured by using Clauser plot method. The level of turbulent intensities on roughness surface appears more strongly than that of turbulent intensities on flat plate. A correlation of boundary layer thickness in term of $Re_x$ and w/k are presented.