• Wind and Structures
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• v.10 no.6
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• pp.511-532
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• 2007

The present study aims to generate turbulent inflow data to more accurately represent the turbulent flow around a square cylinder when the inflow turbulence level is significant. The modified random flow generation (RFG) technique in conjunction with a previously developed LES code is successfully adopted into a finite element based fluid flow solver to generate the required inflow turbulence boundary conditions for the three-dimensional (3-D) LES computations of transitional turbulent flow around a square cylinder at Reynolds number of 22,000. The near wall region is modelled without using wall approximate conditions and a wall damping coefficient is introduced into the calculation of sub-grid length scale in the boundary layer of the cylinder wall. The numerical results obtained from simulations are compared with each other and with the experimental data for different inflow turbulence boundary conditions in order to discuss the issues such as the synthetic inflow turbulence effects on the 3-D transitional flow behaviour in the near wake and the free shear layer, the basic mechanism by which stream turbulence interacts with the mean flow over the cylinder body and the prediction of integral flow parameters. The comparison among the LES results with and without inflow turbulence and the experimental data emphasizes that the turbulent inflow data generated by the present RFG technique for the LES computation can be a viable approach in accurately predicting the effects of inflow turbulence on the near wake turbulent flow characteristics around a bluff body.

• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.183-190
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• 2009

The objective of this study is to get simulation data about pulsatile flow around an interior solid body inside a bifurcated tube. All the processes were based on CFD method, with a commercial FVM code, SC/Tetra ver. 6.0 for solving, and with CATIA R16 for generating geometries. The bifurcated tube models were drawn with the bifurcated angle of 45 degrees, considering Murray's law about the diameter ratio. With various locations of the object, the effects of flow on the drag were considered. For the pulsating flow condition, the velocity wave profile was given as the inlet boundary condition. To validate all the result, the simulation was compared with the existing data of the other papers first. Overall flow field of both data were similar, but there was some difference at a zero velocity. Therefore the next simulation was continued with the sine wave profiles where there is no negative flow, and then the data was compared with one of the pulmonary artery velocity where there is negative flow. The final process was to calculate flow variables such as the wall shear stress (WSS) and to compute the drag of the solid object.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.111-119
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• 2012

Applicability of 8 day interval flow data for the calibration of hydrologic model was evaluated using Hydrological Simulation Program-Fortran (HSPF) at Kyungan watershed. The 8 day interval flow monitored by Ministry of Environment located at upstream was calibrated and periodically validated during 2004-2008. And continuous daily flow monitored by Ministry of Construction & Transportation (MOCT) and located at the mouth was compared with daily simulated data during 2004-2007 as spatial validation. Automatic calibration tool which is Model-Independent Parameter Estimation & Uncertainty Analysis (PEST) was applied for HSPF calibration procedure. The model efficiencies for calibration and periodic validation were 0.63 and 0.88, and model performances were fair and very good, respectively, based on criteria of calibration tolerances. Continuous daily stream flow at the mouth of Kyungan watershed were good agreement with observed continuous daily stream flow with showing 0.63 NS value. The PEST program is very useful tool for HSPF hydrologic calibration using non-continuous daily stream flow as well as continuous daily stream flow. The 8 day interval flow data monitored by MOE could be used to calibrate hydrologic model if the continuous daily stream flow is unavailable.

• Nuclear Engineering and Technology
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• v.34 no.4
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• pp.382-395
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• 2002

An experimental study on transient critical heat flux (CHF) under flow coastdown has been performed for the water flow in a non-uniformly heated vertical annulus under low flow and a wide range of pressure conditions. The objectives of this study are to systematically investigate the effect of the flow transient on the CHF and to compare the transient CHF with steady-state CHF The transient CHF experiments have been performed for three kinds of flow transient modes based on the coastdown data of a nuclear power plant reactor coolant pump. At the same inlet subcooling, system pressure and heat flux, the effect of the initial mass flux on the critical mass flux can be negligible. However, the effect of the initial mass flux on the time-to- CHF becomes large as the heat flux decreases. The critical mass flux has the largest value for slow flow reduction rate. There is a pressure effect on the ratio of the transient CHF data to steady-state CHF data. Except under low system pressure conditions, the flow transient CHF was revealed to be conservative compared with the steady-state CHF data. Bowling CHF correlation and thermal hydraulic system code MARS show promising results for the prediction of CHF occurrence .

• Nuclear Engineering and Technology
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• v.40 no.1
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• pp.69-76
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• 2008

Most pressurized water reactors use Venturi flow meters to measure the feedwater flow rate. However, fouling phenomena, which allow corrosion products to accumulate and increase the differential pressure across the Venturi flow meter, can result in an overestimation of the flow rate. In this study, a soft-sensing model based on fuzzy support vector regression was developed to enable accurate on-line prediction of the feedwater flow rate. The available data was divided into two groups by fuzzy c means clustering in order to reduce the training time. The data for training the soft-sensing model was selected from each data group with the aid of a subtractive clustering scheme because informative data increases the learning effect. The proposed soft-sensing model was confirmed with the real plant data of Yonggwang Nuclear Power Plant Unit 3. The root mean square error and relative maximum error of the model were quite small. Hence, this model can be used to validate and monitor existing hardware feedwater flow meters.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.59-60
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• 2006

Some useful flow regime data are obtained from the experiments using the flight producing hyper-gravity(2g) conditions and on ground(1g) with the identical flow conditions. The flow regime data obtained at 1g and 2g conditions are compared with new dimensionless flow regime map using Fr, Bo and We number related with gravity, surface tension and inertia force.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.565-575
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• 2022

Recently, in the field of water resource engineering, interest in predicting time series water levels and flow rates using deep learning technology that has rapidly developed along with the Fourth Industrial Revolution is increasing. In addition, although water-level and flow-rate prediction have been performed using the Long Short-Term Memory (LSTM) model and Gated Recurrent Unit (GRU) model that can predict time-series data, the accuracy of flow-rate prediction in rivers with rapid temporal fluctuations was predicted to be very low compared to that of water-level prediction. In this study, the Paldang Bridge Station of the Han River, which has a large flow-rate fluctuation and little influence from tidal waves in the estuary, was selected. In addition, time-series data with large flow fluctuations were selected to collect water-level and flow-rate data for 2 years and 7 months, which are relatively short in data length, to be used as training and prediction data for the LSTM and GRU models. When learning time-series water levels with very high time fluctuation in two models, the predicted water-level results in both models secured appropriate accuracy compared to observation water levels, but when training rapidly temporal fluctuation flow rates directly in two models, the predicted flow rates deteriorated significantly. Therefore, in this study, in order to accurately predict the rapidly changing flow rate, the water-level data predicted by the two models could be used as input data for the rating curve to significantly improve the prediction accuracy of the flow rates. Finally, the results of this study are expected to be sufficiently used as the data of flood warning system in urban rivers where the observation length of hydrological data is not relatively long and the flow-rate changes rapidly.

• Journal of Korean Society of Forest Science
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• v.101 no.1
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• pp.20-27
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• 2012

The flowed soil volume is able to be estimated simply from topographic data of before and after the debris flow. However, it is often difficult to obtain high resolution topographic data before debris flow because debris flow was occurred in mountainous area and airborne Lidar data was mainly surveyed in urban area. For this reason, Woo(2011) developed the topographic restoration method that can reconstruct the topography before the debris flow using airborne Lidar data. In this study, we applied the topographic restoration method on Inje county, Bongwha county and Jecheon city, produced topography data before debris flow that RMSE is from 0.16 to 0.34 m. Also, a soil variation was analyzed by topography data before and after debris flow, and it was used to estimate a real soil volume flowed to downstream and a spatial distribution showing collapses, flows, sedimentations appeared to debris flow.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.264-284
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• 2021

As the next-generation network architecture, software-defined networking (SDN) has great potential. But how to forward data packets safely is a big challenge today. In SDN, packets are transferred according to flow rules which are made and delivered by the controller. Once flow rules are modified, the packets might be redirected or dropped. According to related research, we believe that the key to forward data flows safely is keeping the consistency of flow rules. However, existing solutions place little emphasis on the safety of flow rules. After summarizing the shortcomings of the existing solutions, we propose FRChain to ensure the security of SDN data forwarding. FRChain is a novel scheme that uses blockchain to secure flow rules in SDN and to detect compromised nodes in the network when the proportion of malicious nodes is less than one-third. The scheme places the flow strategies into blockchain in form of transactions. Once an unmatched flow rule is detected, the system will issue the problem by initiating a vote and possible attacks will be deduced based on the results. To simulate the scheme, we utilize BigchainDB, which has good performance in data processing, to handle transactions. The experimental results show that the scheme is feasible, and the additional overhead for network performance and system performance is less than similar solutions. Overall, FRChain can detect suspicious behaviors and deduce malicious nodes to keep the consistency of flow rules in SDN.