• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.12
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• pp.1133-1138
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• 2005

In this study, we have prepared, as the pluse power source, a commercially supplied Li-ion battery with a capacity of 700 mAh and AC resistivity of 60 md at 1 kHz and nonaqeous asymmetric hybrid capacitor composed of an activated carbon cathode and MCMB anode, and have examined the electrochemical characteristics of hybrid capacitor and the pulse performances of parallel connected hybrid capacitor/Li-ion battery source. The nonaqueous asymmetric hybrid capacitors constituted with each stack number of pairs composed of the cathode, the porous separator and the anode electrode were housed in Al-laminated film cell. The 10 stacked hybrid capacitor, which was charged and discharged at a constant current at 0.25 $mA/cm^2$ between 3 and 4.3 V, has exhibited the capacitance of 108F and the lowest equivalent series resistance was 32 $m{\Omega}$ at 1 kHz. On the other hand, the enhanced run time of Li-ion battery assisted by the hybrid capacitor was obtained with increasing of current density and pulse width in Pulse mode. The best improvement, $84\;\%$ for hybrid capacitor/Li-ion battery was obtained in the condition of a 7C-rate pulse (100 msec)/0.5C-rate standby/$10\;\%$ duty cycle.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.51-59
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• 1993

This paper develops practical and realistic reliability models and methods for the evaluation of system-reliability and system reliability-based rating of various types of box-girder bridge superstructures. The strength limit state model for box-girder bridges suggested in the paper are based on not only the basic flexural strength but also the strength interaction equations which simultaneously take into account flexure, shear and torsion. And the system reliability problem of box-girder superstructure is formulated as parallel-series models obtained from the FMA(Failure Mode Approach) based on major failure mechanisms or critical failure states of each girder. In the paper, an improved IST(Importance Sampling Technique) simulation algorithm is used for the system reliability analysis of the proposed models. This paper proposes a practical but rational approach for the evaluation of capacity rating in terms of the equivalent system-capacity rating corresponding to the estimated system-reliability index which is derived based on the concept of the equivalent FOSM(First Order Second Moment) form of system reliability index. The results of the reliability evaluation and rating of existing bridges indicate that the reserved reliability and capacity rating at system level are significantly different from those of element reliability or conventional methods especially in the case of highly redundant box-girder bridges.

• Nuclear Engineering and Technology
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• v.47 no.6
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• pp.678-699
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• 2015

Although the harsh space environment imposes many severe challenges to space pioneers, space exploration is a realistic and profitable goal for long-term humanity survival. One of the viable and promising options to overcome the harsh environment of space is nuclear propulsion. Particularly, the Nuclear Thermal Rocket (NTR) is a leading candidate for nearterm human missions to Mars and beyond due to its relatively high thrust and efficiency. Traditional NTR designs use typically high power reactors with fast or epithermal neutron spectrums to simplify core design and to maximize thrust. In parallel there are a series of new NTR designs with lower thrust and higher efficiency, designed to enhance mission versatility and safety through the use of redundant engines (when used in a clustered engine arrangement) for future commercialization. This paper proposes a new NTR design of the second design philosophy, Korea Advanced NUclear Thermal Engine Rocket (KANUTER), for future space applications. The KANUTER consists of an Extremely High Temperature Gas cooled Reactor (EHTGR) utilizing hydrogen propellant, a propulsion system, and an optional electricity generation system to provide propulsion as well as electricity generation. The innovatively small engine has the characteristics of high efficiency, being compact and lightweight, and bimodal capability. The notable characteristics result from the moderated EHTGR design, uniquely utilizing the integrated fuel element with an ultra heat-resistant carbide fuel, an efficient metal hydride moderator, protectively cooling channels and an individual pressure tube in an all-in-one package. The EHTGR can be bimodally operated in a propulsion mode of $100MW_{th}$ and an electricity generation mode of $100MW_{th}$, equipped with a dynamic energy conversion system. To investigate the design features of the new reactor and to estimate referential engine performance, a preliminary design study in terms of neutronics and thermohydraulics was carried out. The result indicates that the innovative design has great potential for high propellant efficiency and thrust-to-weight of engine ratio, compared with the existing NTR designs. However, the build-up of fission products in fuel has a significant impact on the bimodal operation of the moderated reactor such as xenon-induced dead time. This issue can be overcome by building in excess reactivity and control margin for the reactor design.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Journal of Korea Soil Environment Society
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• v.4 no.1
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• pp.109-118
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• 1999

Recently, transport parameters of conservative solutes such as KCl in a porous medium have been successfully determined using time domain reflectometry (TDR) . This study was initiated to Investigate the applicability of TDR technique to monitoring the fate of a heavy metal ion in a sandy soil and the distribution of its concentration along travel distance with time. A column test was conducted in a laboratory that consists of monitoring both resident and flux concentrations of $ZnCl_2$in a sandy soil under a breakthrough condition. A tracer of $ZnCl_2$(10 g/L) was injected onto the top surface of the sample as pulse type as soon as a steady-state condition was achieved. Time-series measurements of resistance and electrical conductivity were performed at 10 cm and 20 cm of distances from the inlet boundary by horizontal-positioning of parallel TDR metallic rods and using an EC-meter for the effluent exiting the bottom boundary respectively. In addition. Zn ions of the effluent were analyzed by ICP-AES. Since the mode and position of concentration detected by TDR and effluent were different, comparison between ICP analysis and TDR-detected concentration was made by predicting flux concentration using CDE model accommodating a decay constant with the transport parameters obtained from the resident concentrations. The experimental results showed that the resident concentration resulted in earlier and higher peak than the flux concentration obtained by EC-meter, implying the homogeneity of the packed sandy soil. A close agreement was found between the predicted from the transport parameters obtained by TDR and the measured $ZnCl_2$concentration. This indicates that TDR technique can also be applied to monitoring heavy metal concentrations in the soil once that a decay constant is obtained for a given soil.