k-ε 난류모형을 이용한 중층 밀도류의 수치모의

최성욱,최성욱,Choi, Seongwook,Choi, Sung-Uk 한국수자원학회 2017 한국수자원학회논문집 Vol.50 No.9

This study presents a numerical model for simulating dense interflows. The governing equations are provided and the finite difference method is used with the $k-{\varepsilon}$ turbulence model. The model is used to simulate a dense interflow established in a deep ambient water, resulting velocity and excess density profiles. It is observed that velocity decreases in the longitudinal direction due to water entrainment in the vicinity of the outlet and rarely changes for increased Richardson number. Similarity collapses of velocity and excess density are obtained, but those of turbulent kinetic energy and dissipation rate are not. A shape factor for the dense interflow is obtained from the simulated profiles. The value of this shape factor can be used in the layer-averaged modeling of dense interflows. In addition, a buoyancy-related parameter ($c_{3{\varepsilon}}$) for the $k-{\varepsilon}$ model and the volume expansion coefficient (${\beta}_0$) are obtained from the simulated results.

비선형 k-ε 모형을 이용한 부분 식생 개수로 흐름의 평균흐름 및 난류구조 수치모의

최성욱,최성욱,김태준,Choi, Seongwook,Choi, Sung-Uk,Kim, Taejoon 대한토목학회 2014 대한토목학회논문집 Vol.34 No.3

This study presents a numerical modeling of mean flow and turbulence structures of partly-vegetated open-channel flows. For this, Reynolds-averaged Navier-Stokes equations with vegetation drag terms are solved numerically using the non-linear k-${\varepsilon}$ model. The numerical model is applied to laboratory experiments of Nezu and Onitsuka (2001), and simulated results are compared with data from measurement and computations by Kang and Choi's (2006) Reynolds stress model. The simulation results indicate that the proposed numerical model simulates the mean flow well. Twin vortices are found to be generated at the interface between vegetated and non-vegetated zones, where turbulence intensity and Reynolds stress show their maximums. The model simulates the pattern of the Reynolds stress well but under-predicts the intensity of Reynolds stress slightly.

慶南 一部 住民의 胃集團檢診에 關한 X-線學的 觀察 : 경남 일부 주민의 위집단검진에 관한 X-선학적 관찰

최성욱 부산의대 1976 부산의대잡지 - 부산대학교 의과대학 Vol.16 No.2

기니아-픽 精管 및 精囊에 있어서 Prostaglandin E1의 作用機轉에 關한 硏究 : 기니아-픽 정관 및 정낭에 있어서 Prostaglandin E1의 작용기전에 관한 연구

최성욱 부산의대 1975 부산의대잡지 - 부산대학교 의과대학 Vol.15 No.1

Prediction of Local Scour around Bridge Piers in the Cohesive Bed Using Support Vector Machines

최성욱,최성욱 대한토목학회 2022 KSCE Journal of Civil Engineering Vol.26 No.5

Local scour around bridge piers is one of the most important factors threatening the life of bridges. The three-dimensional highly complicated horseshoe vortex and downflow are known to be the main agents responsible for pier scour. If the bed consists of cohesive sediment, it will add another level of complexity to the pier scour problem. Various approaches have attempted to predict scour depth, but no universal method is available to date. This study presents a prediction of local scour around bridge piers in the cohesive bed using support vector machines (SVMs), a machine learning technique. The maximum scour depth is predicted with seven dimensional variables, including velocity, flow depth, size of bed sediment, pier width, clay content, water content, and bed shear strength. The training and validation of the SVMs are conducted with 197 data from six datasets. Comparisons are made with the training and validation of the adaptive-network-based fuzzy inference system (ANFIS) method. The training of the ANFIS method appears successful, but the validation fails because of overfitting. The predictions with dimensionless variables are compared, and shown to be worse. In addition, the SVMs are found to predict the maximum scour depths better than three existing formulas, gene expression programming (GEP), and a non-linear regression model. The SVMs are applied to two datasets, revealing the importance of the coverage of the training data. Finally, to investigate the contributions of each variable, the mean absolute percent errors (MAPEs) and correlation coefficient are computed by predicting the maximum scour depths by excluding each variable.

Longitudinal change in flow structures and energy loss of free jumps and submerged jumps of flows over an embankment-type weir

최성욱,최성욱 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.3

This study numerically investigates the longitudinal changes in the flow structures and energy loss of the free jumps and the submerged jumps. The hydraulic jumps from flows over an embankment-type weir are considered. For the numerical simulations, the 2D Unsteady Reynolds-Averaged Navier-Stokes equations are solved using the k SST turbulence model. Flow structures and their longitudinal changes are compared with the available experimental data, showing moderate agreement. The simulation results indicate that the decaying patterns of the flow structures for the free jump are roughly similar to those for the submerged jump. The decaying rate decreases with increasing submergence ratio, in which process the adverse pressure gradient plays a key role. It is also confirmed that the loss of the kinetic energy increases with decreasing submergence ratio. For both free jump and submerged jump, the process of dissipating the kinetic energy terminates within the developed zone, with the decaying process of the flow structure unfinished.

k-w SST 모형을 이용한 수중도수와 잠긴흐름의 수치모의

최성욱,최성욱 한국수자원학회 2021 한국수자원학회논문집 Vol.54 No.11

This study presents numerical simulations of submerged jump and washed-out jump resulted from the flow over the embankment type weir. Unsteady Reynolds Averaged Navier-Stokes (URANS) equations are solved with the SST turbulence model. Validations are carried out using the experimental results in the literature, revealing that computed roller shape, free surface, and mean velocity are in good agreement with measured data. The volume fractions of water of the submerged jump and washed-out jump are compared, and the characteristics of the two flows from the double-averaged volume fractions of water are presented. The condition under which the transition occurs from the submerged jump to washed-out jump is presented by the relation between the relative embankment length and submergence factor via numerical simulations by changing the weir length, discharge, and tailwater depth. 본 연구에서는 제방 형태의 보를 월류하는 수중도수와 잠긴흐름을 수치모의 하였다. 수치모의를 위하여 URANS 방정식을 해석하였으며, 난류폐합식으로 SST 모형을 사용하였다. 기존의 실험결과를 이용하여 수치모형을 검증하였는데, 모의된 롤러의 형상, 자유수면, 그리고 평균유속분포가 실험결과와 비교적 잘 일치하는 것을 확인하였다. 수중도수와 잠긴흐름에서 물의 체적비 분포를 비교하였으며, 각 흐름에 대한 2중 평균된 체적비의 특성을 제시하였다. 수치모의를 이용하여 보의 길이, 유량, 그리고 하류 수위에 따라 수중도수에서 잠긴흐름으로 천이되는 조건을 검토하였으며, 천이가 발생할 때의 상대 월류수심을 침수비의 함수로 제시하였다.

저수지 퇴배사 모의를 위한 준정류모형

최성욱,최성욱,Choi, Sung-Uk,Choi, Seong-Wook 한국수자원학회 2012 한국수자원학회논문집 Vol.45 No.2

This paper presents a quasi-steady model for numerical simulations of reservoir sedimentation and reservoir flushing. The quasi-steady model is based on the assumption that the flow is steady with time-dependent stream morphology change. This is reasonable because stream morphology changes over a long period, while the flow changes rapidly. The proposed model is first applied to two laboratory experiments for reservoir sedimentation. The channel is shown to be adjusted to new sediment supply at the upstream by changing both the flow depth and slope. Simulated water surface and bed profiles compare favorably to measured data. The model is also applied to reservoir flushing. Good agreement between simulated and measured data is not obtained due to time variation of outflow generated to facilitate the flushing in the experiment. Finally, relationships for equilibrium flow depth and bed slope are proposed and tested through numerical experiments.

[NEW YEAR ESSAY 2024] 최성욱 센트비 대표 : 간절함을 담은 초심

최성욱 중앙일보에스 2024 Forbes Korea = 포브스 코리아 Vol.2024 No.1

기계학습을 이용한 비점성토 및 점성토 지반에서 시간의존 교각주위 국부세굴의 예측

최성욱,최성욱,최병웅 한국수자원학회 2021 한국수자원학회논문집 Vol.54 No.12

This paper presents a machine learning technique applied to prediction of time-dependent local scour around bridge piers in both non-cohesive and cohesive beds. The support vector machines (SVM), which is known to be free from overfitting, is used. The time- dependent scour depths are expressed by 7 and 9 variables for the non-cohesive and cohesive beds, respectively. The SVM models are trained and validated with time series data from different sources of experiments. Resulting Mean Absolute Percentage Error (MAPE) indicates that the models are trained and validated properly. Comparisons are made with the results from Choi and Choi’s formula and Scour Rate in Cohesive Soils (SRICOS) method by Briaud et al., as well as measured data. This study reveals that the SVM is capable of predicting time-dependent local scour in both non-cohesive and cohesive beds under the condition that sufficient data of good quality are provided. 본 논문에서는 기계학습을 이용하여 비점성토 및 점성토 지반에서 시간에 따른 교각주위 국부세굴을 예측하였다. 기계학습 기법으로는 과적합 오차를 유발하지 않는다고 알려진 Support Vector Machines (SVM) 기법이 사용되었다. 비점성토 지반 및 점성토 지반에서 시간에 따라 발달하는 세굴심을 7개 및 9개의 변수를 각각 이용하여 표현하였다. 여러 실험을 통해 얻어진 시계열 자료를 이용하여 개발된 모형을 학습시키고 검증하였다. 계산된 평균절대비오차(MAPE)에 의하면 모형의 학습과 검증이 적절하게 수행된 것으로 나타났다. 실험 결과뿐 아니라 Choi and Cho 공식과 Briaud et al.이 제시한 SRICOS 방법에 의한 결과와 비교하였다. 본 연구를 통해 양질의 자료가 충분히 제공되는 경우 SVM 모형이 비점성토 및 점성토 지반 시간의존 국부세굴을 예측할 수 있음을 보여주었다.