Browsing by Author "Yoo, Sung Soo"

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    Analysis of the Flow Performance of the Complex Cross-Section Module to Reduce the Sedimentation in a Combined Sewer Pipe
    (MDPI, 2020-11) Ji, Hyon Wook; Yoo, Sung Soo; Koo, Dan Daehyun; Kang, Jeong-Hee; Engineering Technology, School of Engineering and Technology
    The difference in the amount of stormwater and sewage in a combined sewer system is significantly large in areas where heavy rainfall is concentrated. This leads to a low water level and slow flow velocity inside the pipes, which causes sedimentation and odor on non-rainy days. A complex cross-section module increases the flow velocity by creating a small waterway inside the pipe for sewage to flow on non-rainy days. While considering Manning’s equation, we applied the principle where the flow velocity is proportional to two-thirds of the power of the hydraulic radius. The flow velocity of a circular pipe with a diameter of 450 mm and the corresponding complex cross-section module was analyzed by applying Manning’s equation and numerical modeling to show the effects of the complex cross-section module. The tractive force was compared based on a lab-scale experiment. When all conditions were identical except for the cross-sectional shape, the average flow velocity of the complex cross-section module was 14% higher while the size of the transported sand grains was up to 0.5 mm larger. This increase in flow velocity can be even higher if the roughness coefficient of aging pipes can be decreased.
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    Determination of Internal Elevation Fluctuation from CCTV Footage of Sanitary Sewers Using Deep Learning
    (MDPI, 2021) Ji, Hyon Wook; Yoo, Sung Soo; Koo, Dan Daehyun; Kang, Jeong-Hee; Engineering Technology, School of Engineering and Technology
    The slope of sewer pipes is a major factor for transporting sewage at designed flow rates. However, the gradient inside the sewer pipe changes locally for various reasons after construction. This causes flow disturbances requiring investigation and appropriate maintenance. This study extracted the internal elevation fluctuation from closed-circuit television investigation footage, which is required for sanitary sewers. The principle that a change in water level in sewer pipes indirectly indicates a change in elevation was applied. The sewage area was detected using a convolutional neural network, a type of deep learning technique, and the water level was calculated using the geometric principles of circles and proportions. The training accuracy was 98%, and the water level accuracy compared to random sampling was 90.4%. Lateral connections, joints, and outliers were removed, and a smoothing method was applied to reduce data fluctuations. Because the target sewer pipes are 2.5 m concrete reinforced pipes, the joint elevation was determined every 2.5 m so that the internal slope of the sewer pipe would consist of 2.5 m linear slopes. The investigative method proposed in this study is effective with high economic feasibility and sufficient accuracy compared to the existing sensor-based methods of internal gradient investigation.
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    Hydraulic and Structural Analysis of Complex Cross-Section Reinforced Concrete Pipes to Improve Sewage Flow in a Combined Sewer System
    (MDPI, 2021-11) Ji, Hyon Wook; Kang, Jeong-Hee; Koo, Dan Daehyun; Yoo, Sung Soo; Engineering Technology, School of Engineering and Technology
    A complex cross-section reinforced concrete pipe that combines a sub-pipe for the flow of sewage in dry weather and a main pipe for the flow of rainwater was developed to reduce sedimentation of the combined sewer system in dry weather. The sub-pipe was designed, considering the flow velocity, constructability, and maintenance. By fitting the sewage data in the dry weather to the normal distribution, the ratio of the cross-sectional area of sewage flow to that of the pipe was determined to be approximately 0.418, which could cover 99.85% of the sewage volume of the target site. Based on this ratio, the diameter of the sub-pipe corresponding to the combined sewer system with a pipe diameter between 450 and 1300 mm was determined. The hydraulic performance analysis results showed that the flow velocity increased by 11 to 12% compared to the circular pipe based on the full sub-pipe and by more than 15% depending on the water level. The shear stress increased by more than 16.5%, and higher tractive force was observed. Structural safety was determined as the crack load and failure load far exceeded the minimum criteria, thereby verifying the feasibility and field applicability of the complex cross-section reinforced concrete pipe.
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    Measurement of Wastewater Discharge in Sewer Pipes Using Image Analysis
    (MDPI, 2020-06) Ji, Hyon Wook; Yoo, Sung Soo; Lee, Bong-Jae; Koo, Dan Daehyun; Kang, Jeong-Hee; Engineering Technology, School of Engineering and Technology
    Generally, the amount of wastewater in sewerage pipes is measured using sensor-based devices such as submerged area velocity flow meters or non-contact flow meters. However, these flow meters do not provide accurate measurements because of impurities, corrosion, and measurement instability due to high turbidity. However, cameras have advantages such as their low cost, easy service, and convenient operation compared to the sensors. Therefore, in this study, we examined the following three methods for measuring the flow rate by capturing images inside of a sewer pipe using a camera and analyzing the images to calculate the water level: direct visual inspection and recording, image processing, and deep learning. The MATLAB image processing toolbox was used for analysis. The image processing found the boundary line by adjusting the contrast of the image or removing noise; a network to find the boundary line between wastewater and sewer pipe was created after training the image segmentation results and placing them into three categories using deep learning. From the recognized water levels, geometrical features were used to identify the boundary lines, and flow velocities and flow rates were calculated from Manning’s equation. Using direct inspection and image-processing techniques, boundary lines in images were detected at rates of 12% and 53%, respectively. Although the deep-learning model required training, it demonstrated 100% water-level detection, thereby proving to be the most advantageous method. Moreover, there is enough potential to increase the accuracy of deep learning, and it can be a possible replacement for existing flow measurement sensors.
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    The Mechanical Properties of High Strength Reinforced Cured-in-Place Pipe (CIPP) Liner Composites for Urban Water Infrastructure Rehabilitation
    (MDPI, 2018-08) Ji, Hyun Wook; Yoo, Sung Soo; Kim, Jonghoon; Koo, Dan Daehyun; Engineering Technology, School of Engineering and Technology
    Most urban areas in the world have water infrastructure systems, including the buried sewer and water pipelines, which are assessed as in need of extensive rehabilitation. Deterioration by many other factors affects structural integrity. Trenchless technologies such as Cured-in-Place Pipe (CIPP) are now applied in numerous projects while minimizing disturbance in an urban environment. The main purpose of this study is to develop a high strength CIPP material using various composite materials (e.g., glass fiber, carbon fiber, polyester felt, unsaturated polyester resin, and others). Composite samples were made of the materials and tested using three-point bend apparatus to find mechanical properties, which include the flexural modulus, strength, and deflection. A composite combination with glass fibers with thin felt layers shows the best results in mechanical properties. Flexural modulus is a key factor for CIPP liner thickness design. Glass fiber composite yields between four and nine times higher values than the minimum value specified in the American Society for Testing and Materials (ASTM) F1216. This study provides a fundamental baseline for high strength CIPP liners that are capable of using conventional curing technologies.
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    Study of structural properties and development of high strength Cured-In-Place Pipe (CIPP) liner for sewer pipes using glass fiber
    (KSWW, 2020-04) Ji, Hyon Wook; Koo, Dan Daehyun; Yoo, Sung Soo; Kang, Jeong-Hee; Engineering Technology, School of Engineering and Technology
    Cured-in-place-pipe(CIPP) is the most adopted trenchless application for sewer rehabilitation to extend the life of the existing sewer without compromising both direct construction and indirect social costs especially applied in the congested urban area. This technology is globally and domestically known to be the most suitable for partial and full deteriorated pipe structure rehabilitation in a sewer system. The typical design of CIPP requires a significant thickness of lining to support loading causing sewage flow interruption and increasing material cost. This paper presents development of a high strength glass fiber composite lining material for the CIPP application and structural test results. The test results exhibit that the new glass fiber composite lining material has 12 times of flexural strength, 6.2 times of flexural modulus, and 0.5 Creep Retention Factor. These test results can reduce lining design thickness 35% at minimum. Even though taking into consideration extra materials such as outer and inner films for actual field applications, the structural capacity of the composite material significantly increases and it reduces 20 percent or more line thickness as compared to the conventional CIPP. We expect that the newly developed CIPP lining material lowers material costs and minimizes flow capacity reduction, and fully replaceable to the conventional CIPP lining materials.