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Prof. Yeon Moon Choo
Pusan National University

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0 Water
0 entropy
0 River
0 swmm
0 Flood Reduction

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Journal article
Published: 27 July 2021 in Entropy
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Since the 1960s, many rivers have been destroyed as a consequence of the process of rapid urbanization. As accurate figures are important to repair rivers, there have been many research reports on methods to obtain the exact river slope and elevation. Until now, many research efforts have analyzed the river using measured river topographic factors, but when the flow velocity changes rapidly, such as during a flood, surveying is not easy; and due to cost, frequent measurements are difficult. Previous research has focused on the cross section of the river, so the information on the river longitudinal profile is insufficient. In this research, using informational entropy theory, equations are presented that can calculate the average river slope, river slope, and river longitudinal elevation for a river basin in real time. The applicability was analyzed through a comparison with the measured data of river characteristic factors obtained from the river plan. The parameters were calculated using informational entropy theory and nonlinear regression analysis using actual data, and then the longitudinal elevation entropy equation for each river and the average river slope were calculated. As a result of analyzing the applicability of the equations presented in this study by R2 and Root Mean Square Error, all R2 values were over 0.80, while RMSE values were analyzed to be between 0.54 and 2.79. Valid results can be obtained by calculating river characteristic factors.

ACS Style

Yeon-Moon Choo; Ji-Min Kim; Ik-Tae An. Research on the Longitudinal Section of River Restoration Using Probabilistic Theory. Entropy 2021, 23, 965 .

AMA Style

Yeon-Moon Choo, Ji-Min Kim, Ik-Tae An. Research on the Longitudinal Section of River Restoration Using Probabilistic Theory. Entropy. 2021; 23 (8):965.

Chicago/Turabian Style

Yeon-Moon Choo; Ji-Min Kim; Ik-Tae An. 2021. "Research on the Longitudinal Section of River Restoration Using Probabilistic Theory." Entropy 23, no. 8: 965.

Journal article
Published: 21 June 2021 in Water
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The shear velocity and friction coefficient for representing the resistance of flow are key factors to determine the flow characteristics of the open-channel flow. Various studies have been conducted in the open-channel flow, but many controversies remain over the form of equation and estimation methods. This is because the equations developed based on theory have not fully interpreted the friction characteristics in an open-channel flow. In this paper, a friction coefficient equation is proposed by using the entropy concept. The proposed equation is determined under the rectangular, the trapezoid, the parabolic round-bottomed triangle, and the parabolic-bottomed triangle open-channel flow conditions. To evaluate the proposed equation, the estimated results are compared with measured data in both the smooth and rough flow conditions. The evaluation results showed that R (correlation coefficient) is found to be above 0.96 in most cases, and the discrepancy ratio analysis results are very close to zero. The advantage of the developed equation is that the energy slope terms are not included, because the determination of the exact value is the most difficult in the open-channel flow. The developed equation uses only the mean velocity and entropy M to estimate the friction loss coefficient, which can be used for maximizing the design efficiency.

ACS Style

Yeon-Moon Choo; Jong-Gu Kim; Sang-Ho Park. A Study on the Friction Factor and Reynolds Number Relationship for Flow in Smooth and Rough Channels. Water 2021, 13, 1714 .

AMA Style

Yeon-Moon Choo, Jong-Gu Kim, Sang-Ho Park. A Study on the Friction Factor and Reynolds Number Relationship for Flow in Smooth and Rough Channels. Water. 2021; 13 (12):1714.

Chicago/Turabian Style

Yeon-Moon Choo; Jong-Gu Kim; Sang-Ho Park. 2021. "A Study on the Friction Factor and Reynolds Number Relationship for Flow in Smooth and Rough Channels." Water 13, no. 12: 1714.

Journal article
Published: 20 June 2021 in Water
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The annual average rainfall in Busan area is increasing, causing frequent flooding of Busan’s Suyeong and Oncheon rivers. Due to the increase in urbanized areas and climate change, it is difficult to reduce flood damage. Therefore, new methods are needed to reduce urban inundation. This study models the effects of three flood reduction methods involving Oncheon River, Suyeong River, and the Hoedong Dam, which is situated on the Suyeong. Using EPA-SWMM, a virtual model of the dam and the rivers was created, then modified with changes to the dam’s height, the installation of a floodgate on the dam, and the creation of an underground waterway to carry excess flow from the Oncheon to the Hoedong Dam. The results of this study show that increasing the height of the dam by 3 m, 4 m, or 6 m led to a 27%, 37%, and 48% reduction in flooding, respectively, on the Suyeong River. It was also found that installing a floodgate of 10 × 4 m, 15 × 4 m, or 20 × 4 min the dam would result in a flood reduction of 2.7% and 2.9%, respectively. Furthermore, the construction of the underground waterway could lead to an expected 25% flood reduction in the Oncheon River. Measures such as these offer the potential to protect the lives and property of citizens in densely populated urban areas and develop sustainable cities and communities. Therefore, the modifications to the dam and the underground waterway proposed in this study are considered to be useful.

ACS Style

Yeon-Moon Choo; Sang-Bo Sim; Yeon-Woong Choe. A Study on Urban Inundation Using SWMM in Busan, Korea, Using Existing Dams and Artificial Underground Waterways. Water 2021, 13, 1708 .

AMA Style

Yeon-Moon Choo, Sang-Bo Sim, Yeon-Woong Choe. A Study on Urban Inundation Using SWMM in Busan, Korea, Using Existing Dams and Artificial Underground Waterways. Water. 2021; 13 (12):1708.

Chicago/Turabian Style

Yeon-Moon Choo; Sang-Bo Sim; Yeon-Woong Choe. 2021. "A Study on Urban Inundation Using SWMM in Busan, Korea, Using Existing Dams and Artificial Underground Waterways." Water 13, no. 12: 1708.

Journal article
Published: 14 May 2021 in Entropy
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In general, this new equation is significant for designing and operating a pipeline to predict flow discharge. In order to predict the flow discharge, accurate determination of the flow loss due to pipe friction is very important. However, existing pipe friction coefficient equations have difficulties in obtaining key variables or those only applicable to pipes with specific conditions. Thus, this study develops a new equation for predicting pipe friction coefficients using statistically based entropy concepts, which are currently being used in various fields. The parameters in the proposed equation can be easily obtained and are easy to estimate. Existing formulas for calculating pipe friction coefficient requires the friction head loss and Reynolds number. Unlike existing formulas, the proposed equation only requires pipe specifications, entropy value and average velocity. The developed equation can predict the friction coefficient by using the well-known entropy, the mean velocity and the pipe specifications. The comparison results with the Nikuradse’s experimental data show that the R2 and RMSE values were 0.998 and 0.000366 in smooth pipe, and 0.979 to 0.994 or 0.000399 to 0.000436 in rough pipe, and the discrepancy ratio analysis results show that the accuracy of both results in smooth and rough pipes is very close to zero. The proposed equation will enable the easier estimation of flow rates.

ACS Style

Yeon-Woong Choe; Sang-Bo Sim; Yeon-Moon Choo. New Equation for Predicting Pipe Friction Coefficients Using the Statistical Based Entropy Concepts. Entropy 2021, 23, 611 .

AMA Style

Yeon-Woong Choe, Sang-Bo Sim, Yeon-Moon Choo. New Equation for Predicting Pipe Friction Coefficients Using the Statistical Based Entropy Concepts. Entropy. 2021; 23 (5):611.

Chicago/Turabian Style

Yeon-Woong Choe; Sang-Bo Sim; Yeon-Moon Choo. 2021. "New Equation for Predicting Pipe Friction Coefficients Using the Statistical Based Entropy Concepts." Entropy 23, no. 5: 611.

Journal article
Published: 10 May 2021 in Water
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In recent years, climate abnormalities have been observed globally. Consequently, the scale and size of natural disasters, such as typhoons, wind wave, heavy snow, downpours, and storms, have increased. However, compared to other disasters, predicting the timing, location and severity of damages associated with typhoons and other extreme wind wave events is difficult. Accurately predicting the damage extent can reduce the damage scale by facilitating a speedy response. Therefore, in this study, a model to estimate the cost of damages associated with wind waves and their impacts during coastal storms was developed for the Republic of Korea. The history of wind wave and typhoon damages for coastal areas in Korea was collected from the disaster annual report (1991–2020), and the damage cost was converted such that it reflected the inflation rate as in 2020. Furthermore, data on ocean meteorological factors were collected for the events of wind wave and typhoon damages. Using logistic and linear regression, a wind wave damage prediction model reflecting the coastal regional characteristics based on 74 regions nationwide was developed. This prediction model enabled damage forecasting and can be utilized for improving the law and policy in disaster management.

ACS Style

Yeon Choo; Kun Chun; Hae Jeon; Sang Sim. A Predictive Model for Estimating Damage from Wind Waves during Coastal Storms. Water 2021, 13, 1322 .

AMA Style

Yeon Choo, Kun Chun, Hae Jeon, Sang Sim. A Predictive Model for Estimating Damage from Wind Waves during Coastal Storms. Water. 2021; 13 (9):1322.

Chicago/Turabian Style

Yeon Choo; Kun Chun; Hae Jeon; Sang Sim. 2021. "A Predictive Model for Estimating Damage from Wind Waves during Coastal Storms." Water 13, no. 9: 1322.

Preprint content
Published: 19 April 2021
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Korea’s river design standards set general design standards for river and river-related projects in Korea, which systematize the technologies and methods involved in river-related projects. This includes measurement methods for parts necessary for river design, but do not include information on shear stress. Shear Stress is to one of the factors necessary for river design and operation. Shear stress is one of the most important hydraulic factors used in the fields of water especially for artificial channel design. Shear stress is calculated from the frictional force caused by viscosity and fluctuating fluid velocity. Current methods are based on past calculations, but factors such as boundary shear stress or energy gradient are difficult to actually measure or estimate. The point velocity throughout the entire cross section is needed to calculate the velocity gradient. In other words, the current Korea’s river design standards use tractive force, critical tractive force instead of shear stress because it is more difficult to calculate the shear stress in the current method. However, it is difficult to calculate the exact value due to the limitations of the formula to obtain the river factor called the tractive force. In addition, tractive force has limitations that use empirically identified base value for use in practice. This paper focuses on the modeling of shear stress distribution in open channel turbulent flow using entropy theory. In addition, this study suggests shear stress distribution formula, which can be easily used in practice after calculating the river-specific factor T. and that the part of the tractive force and critical tractive force in the Korea’s river design standards should be modified by the shear stress obtained by the proposed shear stress distribution method. The present study therefore focuses on the modeling of shear stress distribution in open channel turbulent flow using entropy theory. The shear stress distribution model is tested using a wide range of forty-two experimental runs collected from the literature. Then, an error analysis is performed to further evaluate the accuracy of the proposed model. The results revealed a correlation coefficient of approximately 0.95–0.99, indicating that the proposed method can estimate shear stress distribution accurately. Based on this, the results of the distribution of shear stress after calculating the river-specific factors show a correlation coefficient of about 0.86 to 0.98, which suggests that the equation can be applied in practice.

ACS Style

Hae Seong Jeon; Ji Min Kim; Yeon Moon Choo. Entropy-Based Shear Stress Distribution in Open Channel for all types of Flow using Experimental Data. 2021, 1 .

AMA Style

Hae Seong Jeon, Ji Min Kim, Yeon Moon Choo. Entropy-Based Shear Stress Distribution in Open Channel for all types of Flow using Experimental Data. . 2021; ():1.

Chicago/Turabian Style

Hae Seong Jeon; Ji Min Kim; Yeon Moon Choo. 2021. "Entropy-Based Shear Stress Distribution in Open Channel for all types of Flow using Experimental Data." , no. : 1.

Journal article
Published: 10 September 2019 in Water
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Frequent localized torrential rains, excessive population density in urban areas, and increased impervious areas have led to massive flood damage that has been causing overloading of drainage systems (watersheds, reservoirs, drainage pump sites, etc.). Flood concerns are raised around the world in the events of rain. Flood forecasting, a typical nonstructural measure, was developed to help prevent repetitive flood damage. However, it is difficult to apply flood prediction techniques using training processes because training needs to be applied at every usage. Other techniques that use predicted rainfall data are also not appropriate for small watershed, such as single drainage area. Thus, in this paper, a flood prediction method is proposed by improving four criteria (50% water level, 70% water level, 100% water level, and first flooding of water pipes) in an attempt to reduce flooding in urban areas. The four criteria nodes are generated using a rainfall runoff simulation with synthetic rainfall at various durations. When applying real-time rainfall data, these nodes have the advantage of simple application. The improved flood nomograph made in this way is expected to help predict and prepare for rainstorms that can potentially cause flood damage.

ACS Style

Yeon Moon Choo; Deok Jun Jo; Gwan Seon Yun; Eui Hoon Lee; Choo; Jo; Yun; Lee. A Study on the Improvement of Flood Forecasting Techniques in Urban Areas by Considering Rainfall Intensity and Duration. Water 2019, 11, 1883 .

AMA Style

Yeon Moon Choo, Deok Jun Jo, Gwan Seon Yun, Eui Hoon Lee, Choo, Jo, Yun, Lee. A Study on the Improvement of Flood Forecasting Techniques in Urban Areas by Considering Rainfall Intensity and Duration. Water. 2019; 11 (9):1883.

Chicago/Turabian Style

Yeon Moon Choo; Deok Jun Jo; Gwan Seon Yun; Eui Hoon Lee; Choo; Jo; Yun; Lee. 2019. "A Study on the Improvement of Flood Forecasting Techniques in Urban Areas by Considering Rainfall Intensity and Duration." Water 11, no. 9: 1883.

Journal article
Published: 10 January 2018 in Water
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Imperviousness has increased due to urbanization, as has the frequency of extreme rainfall events by climate change. Various countermeasures, such as structural and nonstructural measures, are required to prepare for these effects. Flood forecasting is a representative nonstructural measure. Flood forecasting techniques have been developed for the prevention of repetitive flood damage in urban areas. It is difficult to apply some flood forecasting techniques using training processes because training needs to be applied at every usage. The other flood forecasting techniques that use rainfall data predicted by radar are not appropriate for small areas, such as single drainage basins. In this study, a new flood forecasting technique is suggested to reduce flood damage in urban areas. The flood nomograph consists of the first flooding nodes in rainfall runoff simulations with synthetic rainfall data at each duration. When selecting the first flooding node, the initial amount of synthetic rainfall is 1 mm, which increases in 1 mm increments until flooding occurs. The advantage of this flood forecasting technique is its simple application using real-time rainfall data. This technique can be used to prepare a preemptive response in the process of urban flood management.

ACS Style

Eui Hoon Lee; Joong Hoon Kim; Yeon Moon Choo; Deok Jun Jo. Application of Flood Nomograph for Flood Forecasting in Urban Areas. Water 2018, 10, 53 .

AMA Style

Eui Hoon Lee, Joong Hoon Kim, Yeon Moon Choo, Deok Jun Jo. Application of Flood Nomograph for Flood Forecasting in Urban Areas. Water. 2018; 10 (1):53.

Chicago/Turabian Style

Eui Hoon Lee; Joong Hoon Kim; Yeon Moon Choo; Deok Jun Jo. 2018. "Application of Flood Nomograph for Flood Forecasting in Urban Areas." Water 10, no. 1: 53.

Book chapter
Published: 09 August 2015 in Advances in Intelligent Systems and Computing
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In the previous companion paper, six new/improved metaheuristic optimization algorithms developed by members of Hydrosystem laboratory in Korea University (KU) are introduced. The six algorithms are Cancer Treatment Algorithm (CTA), Extraordinary Particle Swarm Optimization (EPSO), Improved Cluster HS (ICHS), Multi-Layered HS (MLHS), Sheep Shepherding Algorithm (SSA), and Vision Correction Algorithm (VCA). The six algorithms are tested and compared through six well-known unconstrained benchmark functions and a pipe sizing problem of water distribution network. Performance measures such as mean, best, and worst solutions (under given maximum number of function evaluations) are used for the comparison. Optimization results are obtained from thirty independent optimization trials. Obtained Results show that some of the newly developed/improved algorithms show superior performance with respect to mean, best, and worst solutions when compared to other existing algorithms.

ACS Style

Joong Hoon Kim; Young Hwan Choi; Thi Thuy Ngo; Jiho Choi; Ho Min Lee; Yeon Moon Choo; Eui Hoon Lee; Do Guen Yoo; Ali Sadollah; Donghwi Jung. KU Battle of Metaheuristic Optimization Algorithms 2: Performance Test. Advances in Intelligent Systems and Computing 2015, 207 -213.

AMA Style

Joong Hoon Kim, Young Hwan Choi, Thi Thuy Ngo, Jiho Choi, Ho Min Lee, Yeon Moon Choo, Eui Hoon Lee, Do Guen Yoo, Ali Sadollah, Donghwi Jung. KU Battle of Metaheuristic Optimization Algorithms 2: Performance Test. Advances in Intelligent Systems and Computing. 2015; ():207-213.

Chicago/Turabian Style

Joong Hoon Kim; Young Hwan Choi; Thi Thuy Ngo; Jiho Choi; Ho Min Lee; Yeon Moon Choo; Eui Hoon Lee; Do Guen Yoo; Ali Sadollah; Donghwi Jung. 2015. "KU Battle of Metaheuristic Optimization Algorithms 2: Performance Test." Advances in Intelligent Systems and Computing , no. : 207-213.

Book chapter
Published: 09 August 2015 in Advances in Intelligent Systems and Computing
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Each of six members of hydrosystem laboratory in Korea University (KU) invented either a new metaheuristic optimization algorithm or an improved version of some optimization methods as a class project for the fall semester 2014. The objective of the project was to help students understand the characteristics of metaheuristic optimization algorithms and invent an algorithm themselves focusing those regarding convergence, diversification, and intensification. Six newly developed/improved metaheuristic algorithms are Cancer Treatment Algorithm (CTA), Extraordinary Particle Swarm Optimization (EPSO), Improved Cluster HS (ICHS), Multi-Layered HS (MLHS), Sheep Shepherding Algorithm (SSA), and Vision Correction Algorithm (VCA). This paper describes the details of the six developed/improved algorithms. In a follow-up companion paper, the six algorithms are demonstrated and compared through well-known benchmark functions and a real-life engineering problem.

ACS Style

Joong Hoon Kim; Young Hwan Choi; Thi Thuy Ngo; Jiho Choi; Ho Min Lee; Yeon Moon Choo; Eui Hoon Lee; Do Guen Yoo; Ali Sadollah; Donghwi Jung. KU Battle of Metaheuristic Optimization Algorithms 1: Development of Six New/Improved Algorithms. Advances in Intelligent Systems and Computing 2015, 197 -205.

AMA Style

Joong Hoon Kim, Young Hwan Choi, Thi Thuy Ngo, Jiho Choi, Ho Min Lee, Yeon Moon Choo, Eui Hoon Lee, Do Guen Yoo, Ali Sadollah, Donghwi Jung. KU Battle of Metaheuristic Optimization Algorithms 1: Development of Six New/Improved Algorithms. Advances in Intelligent Systems and Computing. 2015; ():197-205.

Chicago/Turabian Style

Joong Hoon Kim; Young Hwan Choi; Thi Thuy Ngo; Jiho Choi; Ho Min Lee; Yeon Moon Choo; Eui Hoon Lee; Do Guen Yoo; Ali Sadollah; Donghwi Jung. 2015. "KU Battle of Metaheuristic Optimization Algorithms 1: Development of Six New/Improved Algorithms." Advances in Intelligent Systems and Computing , no. : 197-205.