• Korean Journal of Hydrosciences
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• v.6
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• pp.1-11
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• 1995

A plunge pool is often employed as an energy-dissipating device at the end of a spillway or a pipe culvert. A jet from spillways or pipes frequently generates a scour hole which threaten the stability of the hydraulic structure. Existing scour prediction formulas of plunge pool of spillways or pipe culverts give a wide range of scour depths, and it is, therefore, difficult to accurately predict those scour depths. In this study, a new experimental method and new sour prediction formulas under submerged circular jet for large bed materials with shallow tailwater depths were developed. A major variable, which was not used in previous scour prediction equations, was the ratio of jet size to bed material size. In this study, jet momentum acting on a bed particle and jet diffustion theory were employed to derive scour prediction formulas. Four theoretical formulas were suggested for the two regions of jet diffusion, i.e., the region of flow establishment and the region of established flow. The semi-theoretically developed scour prediction formulas showed close agreement with laboratory experiments performed on movable bed made of large spherical particles.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.84-98
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• 1995

Network-based model were developed to predict short term future traffic volume based on current traffic, historical average, and upstream traffic. It is presumed that upstream traffic volume can be used to predict the downstream traffic in a specific time period. Three models were developed for traffic flow prediction; a combination of historical average and upstream traffic, a combination of current traffic and upstream traffic, and a combination of all three variables. The three models were evaluated using regression analysis. The third model is found to provide the best prediction for the analyzed data. In order to balance the variables appropriately according to the present traffic condition, a heuristic adaptive weighting system is devised based on the relationships between the beginning period of prediction and the previous periods. The developed models were applied to 15-minute freeway data obtained by regular induction loop detectors. The prediction models were shown to be capable of producing reliable and accurate forecasts under congested traffic condition. The prediction systems perform better in the 15-minute range than in the ranges of 30-to 45-minute. It is also found that the combined models usually produce more consistent forecasts than the historical average.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4060-4066
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• 2021

Flow-accelerated corrosion (FAC) of carbon steel piping is a significant problem in nuclear power plants. The basic process of FAC is currently understood relatively well; however, the accuracy of prediction models of the wall-thinning rate under an FAC environment is not reliable. Herein, we propose a methodology to construct pipe wall-thinning rate prediction models using artificial neural networks and a convolutional neural network, which is confined to a straight pipe without geometric changes. Furthermore, a methodology to generate training data is proposed to efficiently train the neural network for the development of a machine learning-based FAC prediction model. Consequently, it is concluded that machine learning can be used to construct pipe wall thinning rate prediction models and optimize the number of training datasets for training the machine learning algorithm. The proposed methodology can be applied to efficiently generate a large dataset from an FAC test to develop a wall thinning rate prediction model for a real situation.

• The KSFM Journal of Fluid Machinery
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• v.15 no.3
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• pp.64-69
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• 2012

Generally the Shrouded type impeller is considered to free from the loss of tip leakage flow, but it is actually not possible to complete sealing between the rotating impeller and the sealing which is stay still. As a result, there is the possibility of flow leaking between impeller exit to entrance, especially with high pressure ratio compressor machine. The Cavity leakage flow is expected to influence negative effect on a machine performance and also inner flow structure. In this study, Impeller with shroud-casing gap leakage flow is simulated by numerical method (Using CFX 12.1). The influence of leakage flow on compressor performance and efficiency will be analysed, also detail flowfield change will posted.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.30-34
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• 2001

In the present study, we studied the method of predicting the on-design and on-design point performance of axial flow fan with adjustable pitch blades. With the change of stagger angle of axial flow fan with adjustable pitch blade, flow rate and pressure can be changed. Because of this merit adjustable pitch fans are used in many industrial facility. When changing stagger angle or estimating the performance at a wide range of off-design condition, incidence angle changes greatly as the flow rate changes. Therefore, the deviation angle at the blade exit is estimated by the correlation considering the effects of blade design, incidence angle variation. In the loss model, we used known pressure loss model for blade boundary layer and wake, secondary flow, endwall boundary layer and tip leakage flow. The results of modified deviation angle model and experiment were compared for the usefulness of the modified model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3598-3614
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• 2020

With the increase of motor vehicles and tourism demand, some traffic problems gradually appear, such as traffic congestion, safety accidents and insufficient allocation of traffic resources. Facing these challenges, a model of Spatio-Temporal Dilated Convolutional Network (STDGCN) is proposed for assistance of extracting highly nonlinear and complex characteristics to accurately predict the future traffic flow. In particular, we model the traffic as undirected graphs, on which graph convolutions are built to extract spatial feature informations. Furthermore, a dilated convolution is deployed into graph convolution for capturing multi-scale contextual messages. The proposed STDGCN integrates the dilated convolution into the graph convolution, which realizes the extraction of the spatial and temporal characteristics of traffic flow data, as well as features of road occupancy. To observe the performance of the proposed model, we compare with it with four rivals. We also employ four indicators for evaluation. The experimental results show STDGCN's effectiveness. The prediction accuracy is improved by 17% in comparison with the traditional prediction methods on various real-world traffic datasets.

• Fire Science and Engineering
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• v.17 no.3
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• pp.55-60
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• 2003

This study established analysis theory for flow characteristics prediction of the spray nozzle and predicted discharge and discharge type of the spray nozzle from numerical analysis. It could know that discharge type of the spray nozzle from prediction data determine to position of nozzle and needle, and flow characteristics prediction of the spray nozzle could know that the characteristics according to shape of nozzle and needle is decided. New model of the spray nozzle that can maximize efficiency of fire suppression from flow characteristics and prediction data of the spray nozzle is presented. The result of this study utilize to data necessary to develop new model of the spray nozzle. Also the result of this study wish to contribute to resource technology security of the spray nozzle, technique ripple effect enlargement of same kind industry and technical development activation of fire protection field etc.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3892-3901
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• 2021

The pressure drop of a moisture separator in a steam generator is the important design parameter to ensure the successful performance of a nuclear power plant. The moisture separators have a wide range of operating conditions based on the arrangement of them. The prediction of the pressure drop in a moisture separator is challenging due to the complexity of the multi-dimensional two-phase vortex flow. In this study, the moisture separator test facility using the air/water two-phase flow was used to predict the pressure drop of a moisture separator in a Korean OPR-1000 reactor. The prototypical steam/water two-phase flow conditions in a steam generator were simulated as air/water two-phase flow conditions by preserving the centrifugal force and vapor quality. A series of experiments were carried out to investigate the effect of hydraulic characteristics such as the quality and liquid mass flux on the two-phase pressure drop. A new prediction model based on the scaling law was suggested and validated experimentally using the full and half scale of separators. The suggested prediction model showed good agreement with the steam/water experimental results, and it can be extended to predict the steam/water two-phase pressure drop for moisture separators.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1126-1135
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• 2022

The MARS code has been assessed for the prediction of onset of flow instability (OFI) in a vertical channel. For assessment, we built an experiment database that consists of experiments under various geometry and thermal-hydraulic condition. It covers pressure from 0.12 to 1.73 MPa; heat flux from 0.67 to 3.48 MW/m²; inlet sub-cooling from 39 to 166 ℃; hydraulic diameters between 2.37 and 6.45 mm of rectangular channels and pipes. It was shown that the MARS code can predict the OFI mass flux for pipes reasonably well. However, it could not predict the OFI in a rectangular channel well with a mean absolute percentage error of 8.77%. In the cases of rectangular channels, the error tends to depend on the hydraulic diameter. Because the OFI is directly related to the subcooled boiling in a flow channel, we suggest a modified subcooled boiling model for better prediction of OFI in a rectangular channel; the net vapor generation (NVG) model and the modified wall evaporation model were modified so that the effect of hydraulic diameter and heat flux can be accurately considered. The assessment of the modified model shows the prediction of OFI mass flux for rectangular channels is greatly improved.

• Journal of Industrial Technology
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• v.14
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• pp.39-48
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• 1994

Up to the present the study on the performance prediction of HAWT was perfomed mainly by assuming the axial flow. So in this paper we aimed at the fully non-axial flow of HAWT. For this purpose, we defined the wind turbine pitch angle in addition to the yaw angle to specify the arbitrary wind direction. And we adopted the Glauert method as the basic analysis method then modified this method suitably for our goal. By comparing the computational results obtained by this modified new Glaurert method with the experimental results, it was proved that our method was a very efficient method.