• Transactions of the Korean Society of Mechanical Engineers B
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• v.23 no.1
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• pp.123-130
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• 1999

The objective of the current study is to understand steady 3-dimensional flow phenomena in a bifurcated duct experimentally. A bifurcation model is fabricated with transparent acrylic resin to visualize the whole flow field with the PIV system. The gray level cross-correlation method is applied to the image processing algorithm. The subpixel and the area interpolation methods are used to obtain the final velocity vectors. The finite volume predictions are used to analyze the flow patterns in the bifurcation model. The results of the computer simulation and the PIV experiment for three-dimensional flow show the recirculation zone and the formation of the paired secondary flow distal to the apex of the bifurcation model. The results obtained with the two methods also show that the branch flow strongly strikes the inner wall due to the inertial effect and accompanied helical motion as it flows toward the outer wall.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.41-49
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• 2010

Stepped weir of this study was suggested a type of natural type structures. Unique flow, such as Wave type flow, at downstream of mild slope stepped occurs. WTF(Wave type flow) is different with hydraulic jump occurred at Round crest weir. WTF is phenomenon to rise the water level by recirculation area occurred by step height at downstream of mild slope stepped. Wave height of WTF condition is higher than tailwater level and maximum velocity of WTF condition occurs in area of water surface. In this results, WTF presents to be important factor for design of join area of weir with levee. This study got and analyzed hydraulic condition occurred of WTF, scales of WTF and velocity profiles on flow patterns using experiments. WTF was not consider to stepped weir design and this results can be important data for design of stepped weir and structures.

• Journal of Families and Better Life
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• v.34 no.3
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• pp.85-94
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• 2016

The study aims to investigate the effects of social anxiety and self-discrepancy on the internet game flow of adolescents, and to explore the moderating effect of self-discrepancy on the relationship between social anxiety and internet game flow. For this purpose, questionnaires on social anxiety, self-discrepancy and internet game flow were administered to 900 middle and high school students in the Gyeonggi region. The data were analyzed through frequency analysis, t-test, Pearson's correlation analysis, stepwise multiple regression analysis, and hierarchical regression analysis using SPSS Win 21. The major findings of the research are as follows. First, social anxiety and internet game flow of adolescents showed a significant difference by gender. The level of social anxiety was higher for girls than that of boys, while the level of internet game flow was higher for boys than that of girls. Self-discrepancy showed a significant difference by grade. The level of self-discrepancy was higher for middle school students than high school students. Second, self-discrepancy was the most significant predictor of the internet game flow in adolescents. Also, gender and social anxiety were significant predictors. Third, the moderating effect of self-discrepancy was found in the relationship between social anxiety and internet game flow in adolescents.

• Journal of Environmental Science International
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• v.26 no.9
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• pp.1031-1043
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• 2017

Recently severe drought caused the water shortage around the western parts of Chungcheongnamdo province, South Korea. A Diversion tunnel from the Geum river to the Boryong dam, which is the water supply dam for these areas has been proposed to solve this problem. This study examined hydraulic impacts on the Geum river associated with the diversion plan assuming the severe drought condition of 2015 would persist for the simulation period of 2016. The hydraulic simulation model was verified using hydrologic and hydraulic data including hourly discharges of the Geum river and its 8 tributaries, fluctuation of tidal level at the mouth of the river, withdrawals and return flows and operation records of the Geum river barrage since Feb. 1, 2015 through May 31, 2015. For the upstream boundary condition of the Geum river predicted inflow series using the nonlinear regression equation for 2015 discharge data was used. In order to estimate the effects of uncertainty in inflow prediction to the results total four inflow series consisting of upper limit flow, expected flow, lower limit flow and instream flow were used to examine hydraulic impacts of the diversion plan. The simulation showed that in cases of upper limit and expected flows there would be no problem in taking water from the Geum river mouth with a minimum water surface level of EL(+) 1.44 m. Meanwhile, the simulation also showed that in cases of lower limit flow and instream flow there would be some problems not only in taking water for water supply from the mouth of the Geum river but also operating the diversion facility itself with minimum water surface levels of EL(+) 0.94, 0.72, 0.43, and 0.14 m for the lower limit flow without/with diversion and the instream flow without/with diversion, respectively.

• The Journal of Engineering Geology
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• v.15 no.3
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• pp.289-301
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• 2005

Groundwater level drawdown of the first stage resulted from groundwater leakage into tunnel was predicted by an analytical approximation. And numerical modeling was performed to predict the flow rates into tunnel and the groundwater level decline in the vicinity of future proposed tunnel area using a groundwater flow model MODFLOW. Groundwater level of the first stage was predicted to decrease by 15.3 m in analytical approximation. The flow rates in the total length of the future tunnel, when it is excavated, would be approximately $1,870m^3/day$ in numerical model. The model predicts that the groundwater levels in the area around the future tunnel are expected to drop between 5 to 25 m relative to current groundwater levels. Under condition for a $50\%$ tunnel conductance increase, the flow rate was estimated to be $2,518m^3/day$ and the groundwater level drawdown was predicted to be between 5 to 35 m The flow rate and the predicted groundwater level drawdown under a $2,518m^3/day$ tunnel conductance decrease was estimated to be $1,273m^3/day$ and between 2 to 12 m.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.279-289
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• 2022

Since the frequency of heavy rainfall is increasing due to climate change, water levels in the river exceed past historical records. The rating-curve is to convert water level into flow dicscharge from the regression analysis of the water level and corresponding flow discharges. However, the rating-curve involves many uncertainties because of the limited data especially when observed water level exceed past historical water levels. In order to compensate for insufficient data and increase the accuracy of flow discharge data, this study estimates the flow discharge in the river computed mathematically using Monte Carlo simulation based on a 1D hydrodynamic numerical model. Based on the existing rating curve, a random combination of coefficients constituting the rating-curve creates a number of virtual rating curve. From the computed results of the hydrodynamic model, it is possible to estimate flow discharge which reproduces best fit to the observed water level. Based on the statistical evaluation of these samples, a method for mathematically estimating the water level and flow discharge of all cross sections is porposed. The proposed methodology is applied to the junction of Yochoen Stream in the Seomjin River. As a result, it is confirmed that the water level reproducibility was greatly improved. Also, the water level and flow discharge can be calculated mathematically when the proposed method is applied.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1151-1154
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• 2008

The water level data sets among hydrologic observation data are correspond to the hydraulic head for each observation point and determine flow direction. The level difference among reservoir, river, and groundwater determines groundwater flow direction, just like water flows in the downstream direction because the water level of upstream point is higher than that of downstream point. We can analyze the relationship among the components in hydrologic cycle by comparing the water level differences. This research dealt with the data from Nakdong river watershed in Gyungsangnam-Do. Three data group are used for the analysis and onr group is composed of reservoir, river, and groundwater data sets. The data sets are closely(within 10 km) located in the interested area.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.5
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• pp.613-623
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• 1999

A Lagrangian particle dispersion mode l(LPDM) coupled with the prognostic flow model based on nonequilibrium level 2.5 turbulence closure has been dcveloped to simulate the dispersion from an elevated emission source. The proposed model did not require any empirical formula or data for the turbulent statistics such as velocity variances and Lagrangian time scales since the turbulence properties for LPDM were calculated from results of the flow model. The LPDM was validated by comparing the model results against the wind tunnel tracer experiment and ISCST3 model. The calculated wind profile and turbulent velocity variances were in good agreement with those measured in the wind tunnel. The ground level concentrations along the plume centerline as well as the dispersion codfficients also showed good agreement in comparison with the wind tunnel tracer experiment. There were some discrepancies on the horizontal spread of the plume in comparison with the ISCST3 but the maximum ground level concentrations were in a good confidence range. The results of comparisons suggested that the proposed LPDM with the flow model was an effective tool to simulate the dispersion in the flow situation where the turbulent characteristics were not available in advance.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.9
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• pp.622-629
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• 2007

Compact semi-center type automotive air handling system(AHS) is developed in this study and it's performance is compared with the conventional 3-pieces type air hand-ling system. The pressure drop is measured at component level and system level, and air flow rate and air distribution of discharge air through each ducts from air handling system are measured. System level characteristics of pressure drop at face and windshield discharge mode and air flow rate are investigated, and also temperature control linearities are tested. The volume of the air handling system package is reduced about 20%. And air flow rate increase about 5 to 20% compared to the conventional 3-pieces type air handling system at each discharge mode with significantly improved air pressure drop both component and system level. Also, air distribution and temperature controllability meet to evaluation criteria.

• Journal of the Korean Society of Visualization
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• v.21 no.1
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• pp.18-25
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• 2023

In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.