• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.7
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• pp.982-990
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• 2019

The interest of researchers and governments in exploiting tidal energy resources is increasing. Jangjuk strait is a place with high tidal energy density potential and is therefore appropriate for the constructing of a tidal turbine farm. In this study, a numerical approach is presented to evaluate the current flow and power potential in Jangjuk strait with an ADCIRC model. Then, the tidal field characteristics are utilized as input parameters for tidal resource calculation with an in-house program. The 1 MW scale tidal energy converter devices are employed and arranged in 4 layouts to investigate the annual energy yield as well as flow deficit due to the wake ef ect at the surveyed area. The best-performed array generates an annual energy yield up to 12.96 GWh/year (without considering the wake effect); this value is reduced by 0.16 GWh/year when accounting for the energy loss caused by the flow deficit. Moreover, by altering the turbine yaw angle during the flood and ebb tides, the impacts of this factor on the energy extraction are analyzed. This indicates that the turbine array attains the maximum tidal power when the turbine yaw angle is at 346° and 164° (clockwise, to the North) for the spring and neap tide in turns.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.6
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• pp.523-531
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• 2008

In hole type CPTu equipment which combines the concepts of inhole test method and piezocone test method was newly developed in order to evaluate the dynamic properties of marine soils. It is possible to perform inhole type CPTu without any additional source device because the source and receiver are contained inside the cone rod, which is different from the conventional seismic cone system. In this study, laboratory tests using kaolinite as soft soil and numerical simulations using finite element method were carried out to investigate the effects of several parameters including test methods and soil conditions on the test results from inhole type CPTu and to find out the optimum test method. It was found that it is necessary to maintain the length of swing arm as well as the distance between source and receiver consistently to obtain the rigorous test results. The laboratory test and numerical results also reveal that contrary to the input wave frequency, the water content of soil layer and the disturbance due to the installation of swing arm apparently affect the shear wave velocity.

• Economic and Environmental Geology
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• v.49 no.1
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• pp.31-41
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• 2016

A program code was developed to calculate block hydraulic conductivity of the 2-D DFN(discrete fracture network) system based on equivalent pipe network, and implemented to examine the effect of joint orientation distribution on the hydraulic characteristics of fractured rock masses through numerical experiments. A rock block of size $32m{\times}32m$ was used to generate the DFN systems using two joint sets with fixed input parameters of joint frequency and gamma distributed joint size, and various normal distributed joint trend. DFN blocks of size $20m{\times}20m$ were selected from center of the $32m{\times}32m$ blocks to avoid boundary effect. Twelve fluid flow directions were chosen every $30^{\circ}$ starting at $0^{\circ}$. The directional block conductivity including the theoretical block conductivity, principal conductivity tensor and average block conductivity were estimated for generated 180 2-D DFN blocks. The effect of joint orientation distribution on block hydraulic conductivity and chance for the equivalent continuum behavior of the 2-D DFN system were found to increase with the decrease of mean intersection angle of the two joint sets. The effect of variability of joint orientation on block hydraulic conductivity could not be ignored for the DFN having low intersection angle between two joint sets.

• Journal of Biosystems Engineering
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• v.29 no.4
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• pp.341-346
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• 2004

Recent livestock people concern not only increase of production, but also superior quality of animal-breeding environment. So far, the optimization of the breeding and air environment has been focused on the production increase. In the very near future, the optimization will be emphasized on the environment for the animal welfare and health. Especially, cattle farming demands the precision livestock farming and special attention has to be given to the management of feeding, animal health and fertility. The management of individual animal is the first step for precision livestock farming and animal welfare, and recognizing each individual is important for that. Though electronic identification of a cattle such as RFID(Radio Frequency Identification) has many advantages, RFID implementations practically involve several problems such as the reading speed and distance. In that sense, computer vision might be more effective than RFID for the identification of an individual animal. The researches on the identification of cattle via image processing were mostly performed with the cows having black-white patterns of the Holstein. But, the native Korean and Japanese cattle do not have any definite pattern on the body. The purpose of this research is to identify the Japanese black cattle that does not have a body pattern using computer vision technology and neural network algorithm. Twelve heads of Japanese black cattle have been tested to verify the proposed scheme. The values of input parameters were specified and then computed using the face images of cattle. The images of cattle faces were trained using associate neural network algorithm, and the algorithm was verified by the face images that were transformed using brightness, distortion, and noise factors. As a result, there was difference due to transform ratio of the brightness, distortion, and noise. And, the proposed algorithm could identify 100% in the range from -3 to +3 degrees of the brightness, from -2 to +4 degrees of the distortion, and from 0% to 60% of the noise transformed images. It is concluded that our system can not be applied in real time recognition of the moving cows, but can be used for the cattle being at a standstill.

• Journal of Satellite, Information and Communications
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• v.5 no.1
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• pp.58-62
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• 2010

This paper presents the effects of RF performance parameters on the Galileo receiver design via simulation after reviewing the requirements of the Galileo receiver structure. At first, we considered the general requirements, structure and characteristics of the Galileo system. Then we designed the Galileo receiver focused on performance requirement of 16 dB C/N which is equal to 15 % Error Vector Magnitude(EVM) by using Advanced Design System(ADS) simulation program. In order to verify the function of Automatic Gain Control(AGC)), we measured the IF output power level by changing the input power level at the front - end of the receiver. We analyzed the performance degradation due to phase noise variations of Local Oscillator(LO) in the Galileo receiver through EVM when the minimum sensitivity level of -127 dBm is applied at the receiver. We also analyzed the performance degradation according to variable Analog-to-Digital Converter(ADC) bits within the Dynamic range, -92 ~ -139 dBm, which has been defined by gain range (-2.5 ~ +42.5 dB) in the AGC operation. The results clearly show that the performance of the Galileo receiver can be improved by increasing ADC bits and reducing Phase Noise of LO.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6247-6253
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• 2015

This paper presents the transient-response improved LDO regulator based on parallel error amplifiers. The proposed LDO regulator consists of an error amplifier (E/A1) which has a high gain and narrow bandwidth and a second amplifier (E/A2) which has low gain and wide bandwidth. These amplifiers are in parallel structure. Also, to improve the transient-response properties and slew-rate, some circuit block is added. Using pole-splitting technique, an external capacitor is reduced in a small on-chip size which is suitable for mobile devices. The proposed LDO has been designed and simulated using a Megna/Hynix $0.18{\mu}m$ CMOS parameters. Chip layout size is $500{\mu}m{\times}150{\mu}m$. Simulation results show 2.5 V output voltage and 100 mA load current in an input condition of 2.7 V ~ 3.3 V. Regulation Characteristic presents voltage variation of 26.1 mV and settling time of 510 ns from 100mA to 0 mA. Also, the proposed circuit has been shown voltage variation of 42.8 mV and settling time of 408 ns from 0 mA to 100 mA.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.346-353
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• 2016

In the design conditions of some research reactors, the siphon phenomenon can cause continuous efflux of water during pipe rupture. A siphon breaker is a safety device that can prevent water efflux effectively. However, the analysis of the siphon breaking is complicated because many variables must be included in the calculation process. For this reason, a simulation program was developed with a user-friendly GUI to analyze the siphon breaking easily. The program was developed by MFC programming using Visual Studio 2012 in Windows 8. After saving the input parameters from a user, the program proceeds with three steps of calculation using fluid mechanics formulas. Bernoulli's equation is used to calculate the velocity, quantity, water level, undershooting, pressure, loss coefficient, and factors related to the two-phase flow. The Chisholm model is used to predict the results from a real-scale experiment. The simulation results are shown in a graph, through which a user can examine the total breaking situation. It is also possible to save all of the resulting data. The program allows a user to easily confirm the status of the siphon breaking and would be helpful in the design of siphon breakers.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.593-606
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• 2016

Computer simulation is widely used in a variety of computational science and engineering fields, including computational fluid dynamics, nano physics, computational chemistry, structural dynamics, and computer-aided optimal design, to simulate the behavior of a system. As the demand for the accuracy and complexity of the simulation grows, however, the cost of executing the simulation is rapidly increasing. It, therefore, is very important to lower the total execution time of the simulation especially when that simulation makes a huge number of repetitions with varying values of input parameters. In this paper we develop a simulation service system that provides the ability to predict the result of the requested simulation without actual execution for that simulation: by recording and then returning previously obtained or predicted results of that simulation. To achieve the goal of avoiding repetitive simulation, the system provides two main functionalities: (1) storing simulation-result records into database and (2) predicting from the database the result of a requested simulation using statistical machine learning techniques. In our experiments we evaluate the prediction performance of the system using real airfoil simulation result data. Our system on average showed a very low error rate at a minimum of 0.9% for a certain output variable. Using the system any user can receive the predicted outcome of her simulation promptly without actually running it, which would otherwise impose a heavy burden on computing and storage resources.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.721-731
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• 2010

The rainfall-runoff relationship is very difficult to predict because it is complicate factor affected by many temporal and spatial parameters of the basin. In recent, models which is based on artificial intelligent such as neural network, genetic algorithm fuzzy etc., are frequently used to predict discharge while stochastic or deterministic or empirical models are used in the past. However, the discharge data which are generally used for prediction as training and validation set are often estimated from rating curve which has potential error in its estimation that makes a problem in reliability. Therefore, in this study, water stage is predicted from antecedent rainfall and water stage data for short term using three models of neural network which trained by error back propagation algorithm and optimized by genetic algorithm and training error back propagation after it is optimized by genetic algorithm respectively. As the result, the model optimized by Genetic Algorithm gives the best forecasting ability which is not much decreased as the forecasting time increase. Moreover, the models using stage data only as the input data give better results than the models using precipitation data with stage data.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.71-80
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• 2018

For the stream management, time of concentration is one of the important factors. In particular, as the requirement about various application of the stream increased, accuracy assessment of concentration time in the stream as waterfront area is extremely important for securing evacuation at the flood. the past studies for the assessment of concentration time, however, were only performed on the single hydrological event in the complex basin of natural streams. The development of a assessment methods for the concentration time on the complex hydrological event in a single watershed of urban streams is insufficient. Therefore, we estimated the concentration time using the rainfall- runoff data for the past 10 years (2006~2015) for the Oncheon stream, the representative stream of the Busan, where frequent flood were taken place by heavy rains, in addition, reviewed the reliability using artificial neural network method based on Matlab. We classified a total of 254 rainfalls events based on over unrained 12 hours. Based on the classification, we estimated 6 parameters (total precipitation, total runoff, peak precipitation/ total precipitation, lag time, time of concentration) to utilize for the training and validation of artificial neural network model. Consequently, correlation of the parameter, which was utilized for the training and the input parameter for the predict and verification were 0.807 and 0.728, respectively. Based on the results, we predict that it can be utilized to estimate concentration time and analyze reliability of urban stream.