• Proceedings of the KWS Conference
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• 2009.11a
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• pp.44-44
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• 2009

While the pinch instability theory (PIT) has been widely employed to analyze the spray transfer mode in the gas metal arc welding (GMAW), it cannot predict the detaching drop size accurately. The PIT is modified in this work to increase the accuracy of prediction and to simulate the molten tip geometry to be more physically acceptable. Since the molten tip becomes a cone shape in the spray mode, the effective wire diameter is formulated that the effective diameter is inversely proportional to current square. Modifications are also made to consider the finite length of the liquid column and current leakage through the arc. While the effective diameter influences drop transfer significantly, the current leakage has negligible effects. The effects of modifications on drop transfer are analyzed, and the predicted drop diameters show good agreements with the experimental data of the steel wire.

• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.306-310
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• 2015

IoT(Internet of Things) based underground risk assessment system surrounding water pipeline enables an advanced monitoring and prediction for unexpected underground hazards such as abrupt road-side subsidence and urban sinkholes due to a leak in water pipeline. For the development of successful assessment technology, the PSU(Water Pipeline Safety Unit) which detects the leakage and movement of water pipes. Then, the IoT-based underground risk assessment system surrounding water pipeline will be proposed. The system consists of early detection tools for underground events and correspondence services, by analyzing leakage and movement data collected from PSU. These methods must be continuous and reliable, and cover certain block area ranging a few kilometers, for properly applying to regional water supply changes.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.41-44
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• 2021

In this paper, we propose a monitoring system that can monitor gas leakage concentrations in real time and forecast the amount of gas leaked after one minute. When gas leaks happen, they typically lead to accidents such as poisoning, explosion, and fire, so a monitoring system is needed to reduce such occurrences. Previous research has mainly been focused on analyzing explosion characteristics based on gas types, or on warning systems that sound an alarm when a gas leak occurs in industrial areas. However, there are no studies on creating systems that utilize specific gas explosion characteristic analysis or empirical urban gas data. This research establishes a deep learning model that predicts the gas explosion risk level over time, based on the gas data collected in real time. In order to determine the relative risk level of a gas leak, the gas risk level was divided into five levels based on the lower explosion limit. The monitoring platform displays the current risk level, the predicted risk level, and the amount of gas leaked. It is expected that the development of this system will become a starting point for a monitoring system that can be deployed in urban areas.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.3
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• pp.292-296
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• 2023

Until recently, ships, automobiles, and drones using hydrogen energy are being actively researched. In addition, stations and facilities for hydrogen supply are being developed widely. Among them, a hydrogen pump is necessary for compressing it and transfer to other stations. The liquid hydrogen pump is operated at very high pressure up to 90 MPa. In our research, a reciprocating plunger pump is studied. Especially, a leakage in a liquid hydrogen pump is predicted using a finite element method. As a result, it was found that leak mass flow rates changed from 0.09 to 2.20 kg/h, when the gaps were given from 2 to 6 ㎛. Thus pump efficiencies were calculated from 99.9 to 97.9%, when the gaps changed from 2 to 6 ㎛. These results are useful for the design of the liquid hydrogen pump.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.379.1-379
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• 2002

In this paper the leakage prediction and rotordynamic analysis of an annular seal with a smooth rotor and spiral-grooved stator are performed. For developing a theoretical model, the three-control-volume analysis of the circumferentially-grooved seal is expanded by considering pressure reduction due to the pumping effect of spiral groove and pressure flow through the spiral groove. Validation to the present analysis is achieved by comparisons with available experimental data. (omitted)

• Journal of Biomedical Engineering Research
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• v.12 no.4
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• pp.295-302
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• 1991

In this paper, the inter- and intra-frame distortions in the gray levels of a series of fluorescein ocular fundus photographs are corrected. For doing this, the background images are extracted from original images using the image blurring effect by decimation, and then shading corrected images are obtained by subtracting the background images from the original images pixel by pixel. In a series of fluorescein ocular fundus photographs, after the gray scale distoriton is corrected, the intensity volumes of dye leakage are measured and represented by a graph. These data may be useful for the prediction of prognosis and the therapeutic management.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.162-167
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• 2016

As the simple empirical and phenomenological model applied to the analysis of leakage and explosion of chemical substances does not regard numerous variables, such as positional density of installations and equipment, turbulence, atmospheric conditions, obstacles, and wind effects, there is a significant gap between actual accident consequence and computation. Therefore, the risk management of a chemical plant based on such a computation surely has low reliability. Since a process plant is required to have outcomes more similar to the actual outcomes to secure highly reliable safety, this study was designed to apply the CFD (computational fluid dynamics) simulation technique to analyze a virtual prediction under numerous variables of leakages and explosions very similarly to reality, in order to review the computation technique of the practical safety distance at a process plant.

• Journal of Applied Reliability
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• v.7 no.1
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• pp.31-43
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• 2007

The function of O-ring seals is to prevent leakage during the service life of the components in which they are installed. The life prediction of O-ring is very important at various industry fields. Generally, to evaluated the long-term performance of O-ring in severe environments has applied a life prediction technique based on accelerated life test (ALT). In this work, Accelerated thermal aging test(l20, 130, 140, $150^{\circ}C$) of O-ring was applied for life prediction of O-ring. The property changes after thermal aging test was measured using TGA, DSC, FT - IR, Video Microscope and SEM. Shape parameter and life prediction were obtained using MINITAB program.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.4
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• pp.173-179
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• 2023

This paper analyzes the time-dependent dielectric breakdown(TDDB) degradation mechanism for each stress region of Peri devices manufactured by 4th generation VNAND process, and presents a complementary lifetime prediction model that improves speed and accuracy in a wider reliability evaluation region compared to the conventional model presented. SiON dielectric nMOSFETs were measured 10 times each under 5 constant voltage stress(CVS) conditions. The analysis of stress-induced leakage current(SILC) confirmed the significance of the field-based degradation mechanism in the low electric field region and the current-based degradation mechanism in the high field region. Time-to-failure(TF) was extracted from Weibull distribution to ascertain the lifetime prediction limitations of the conventional E-model and 1/E-model, and a parallel complementary model including both electric field and current based degradation mechanisms was proposed by extracting and combining the thermal bond breakage rate constant(k) of each model. Finally, when predicting the lifetime of the measured TDDB data, the proposed complementary model predicts lifetime faster and more accurately, even in the wider electric field region, compared to the conventional E-model and 1/E-model.

• Journal of Korea Water Resources Association
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• v.46 no.10
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• pp.969-976
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• 2013

Leakage in water distribution system causes social and economic losses by direct water loss into the ground, and additional energy demand for water supply. This research suggests a leak detection model of using adaptive Kalman filtering on real-time data of pipe flow. The proposed model takes into account hourly and daily variations of water demand. In addition, the model's prediction accuracy is improved by automatically calibrating the covariance of noise through innovation sequence. The adaptive Kalman filtering shows more accurate result than the existing Kalman method for virtual sine flow data. Then, the model is applied to data from two real district metered area in JE city. It is expected that the proposed model can be an effective tool for operating water supply system through detecting burst leakage and abnormal water usage.