Mineral oil has been widely used as an insulating oil for electrical transformers for a long time, but the necessity of employing new insulation oil such as vegetable oil has been increased due to urgent needs for the biodegradability when it leaks and also for the thermal stability at a higher operation temperature. Although specific periods are required between the production and consumption, there are still short of the data to prove the insulation oils' storage stability depending upon various circumstances and their resources. Thus, this paper demonstrates the insulation oils' oxidation characteristics of both mineral and vegetable oils when each was exposed to different environments for 12 weeks. From this test, some properties including total acid number, water content and dielectric breakdown were changed under specific conditions and resources. Vegetable oils showed higher hydrophilicity and water saturation than those of mineral oils due to their molecular compositions. Under sunlight exposure condition, all insulation oils oxidized and changed their properties when exposing to the direct light, regardless of the resource used.
Park, Myeongnam;Kim, Hyunseung;Cho, Jaehoon;Lulu, Addis;Shin, Dongil
Journal of the Korean Institute of Gas
/
v.21
no.2
/
pp.41-49
/
2017
Recently, as the number of facilities using chemicals is increasing, the amount of handling is rapidly increasing. However, chemical spills are occurring steadily, and if large quantities of chemicals are leaked in time, they are likely to cause major damage. These industrial complexes use information obtained from a number of sensors to detect and monitor leaking areas, and are used in industrial fields by applying existing fixed sensors to robots and drones. Therefore, it is necessary to propose a sensor placement method at the interface for rapid detection and response based on various leaking scenarios reflecting leaking conditions and environmental conditions of the chemical handling process. In this study, COMSOL was used to analyze the actual accident scenarios by applying the medium parameter to the case of chemical leaks. Based on the accident scenarios, the objective function is selected so that the velocity of each robot is calculated by attaching importance to each item of sensor detection probability, sensing time and sensing scenario number. We also confirmed the feasibility of this method of reliability analysis for unexpected leak accidents. Based on the above results, it is expected that it will be helpful to trace back the leakage source based on the concentration data of the portable sensor to be applied later.
The social need for stable hydrogen storage technologies that respond to the increasing demand for hydrogen energy is increasing. Among them, underground hydrogen storage is recognized as the most economical and reasonable storage method because of its vast hydrogen storage capacity. In Korea, low-depth hydrogen storage using artificial protective structures is being considered. Further, establishing corresponding safety standards and ground stability evaluation is becoming essential. This study evaluated the hydro-mechanical behavior of the ground during a hydrogen gas leak from a low-depth underground hydrogen storage facility through the HM coupled analysis model. The predictive reliability of the simulation model was verified through benchmark experiments. A parameter study was performed using a metamodel to analyze the sensitivity of factors affecting the surface uplift caused by the upward infiltration of high-pressure hydrogen gas. Accordingly, it was confirmed that the elastic modulus of the ground was the largest. The simulation results are considered to be valuable primary data for evaluating the complex analysis of hydrogen gas explosions as well as hydrogen gas leaks in the future.
Gu, Yun-Jeong;Song, Bonggeun;Lee, Wonhee;Song, Byunghun;Shin, Junho
Journal of the Korean Institute of Gas
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v.26
no.4
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pp.27-35
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2022
When LPG leaks from the storage tank, the gas try to sink to the ground because LPG is heavier than air. The gas easily creates vapor clouds causing aggressive accidents in no airflow. Therefore, It is important to prevent in advance by analyzing the damaged range caused from LPG leakage and vapor clouds. So, this study analyzed the range of damaged by LPG leakage and vapor clouds with consideration of the cold air flow which is generated by the topographical characteristics and the land use status at night time in the Jeju Hagari. As a result of the cold air flow using KLAM_21, about 2 m/s of cold air was introduced in from the southeast due to the influence of the terrain. The range of damaged by LPG leakage and vapor cloud was analyzed using ALOHA. When the leak hole size is 10 cm at the wind speed of 2 m/s, the range corresponding to LEL 60 % (12,600 ppm) was 61 m which range is expected to influence in nearby residential areas. These results of this study can be used as basic data to prepare preventive measures of accidents caused by vapor cloud. Forward, it is necessary to apply CFD modeling such as FLACS to check the vapor cloud formation due to LPG leakage in a relatively narrow area and to check the cause analysis.
This study aims to solve the entangled loop between demographic transition (DT) and economic growth by analyzing cross-country data. We undertake a national-level group analysis to verify the compressed transition of demographic variables over time. Assuming that the LA (latecomer advantage) on DT over time exists, we verify that the DT of the latecomer is compressed by providing a formal proof of LA on DT over income. As a DT has the double-kinked functions of income, we check them in multiple aspects: early maturation, leftward threshold, and steeper descent under a contour map and econometric methods. We find that the developing countries (the latecomer) have speedy DT (CDT, compressed DT) as well as speedy income such that DT of the latecomers starts at lower levels of income, lasts for a shorter period, and finishes at the earlier stage of economic development compared to that of developed countries (the early mover). To check the balance of DT, we classify countries into four groups of DT---balanced, slow, unilateral, and rapid transition countries. We identify that the main causes of rapid transition are due to the strong family planning programs of the government. Finally, we check the effect of latecomer's CDT on economic growth inversely: we undertake the simulation of the CDT effect on economic growth and the aging process for the latecomer. A worrying result is that the CDT of the latecomer shows a sharp upturn of the working-age population, followed by a sharp downturn in a short period. Compared to early-mover countries, the latecomer countries cannot buy more time to accommodate the workable population for the period of demographic bonus and prepare their aging societies for demographic onus. Thus, we conclude that CDT is not necessarily advantageous to developing countries. These outcomes of the latecomer's CDT can be re-interpreted as follows. Developing countries need power sources to pump up economic development, such as the following production factors: labor, physical and financial capital, and economic systems. As for labor, the properties of early maturation and leftward thresholds on DTs of the latecomer mean that demographic movement occurs at an unusually early stage of economic development; this is similar to a plane that leaks fuel before or just before take-off, with the result that it no longer flies higher or farther. What is worse, the property of steeper descent represents the falling speed of a plane so that it cannot be sustained at higher levels, and then plummets to all-time lows.
Journal of the Korea Institute of Information Security & Cryptology
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v.33
no.3
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pp.499-510
/
2023
Recently, an intelligent and advanced cyber attack attacks a computer network of a public institution using a file containing malicious code or leaks information, and the damage is increasing. Even in public institutions with various information protection systems, known attacks can be detected, but unknown dynamic and encryption attacks can be detected when existing signature-based or static analysis-based malware and ransomware file detection methods are used. vulnerable to The detection method proposed in this study extracts the detection result data of the system that can detect malicious code and ransomware among the information protection systems actually used by public institutions, derives various attributes by combining them, and uses a machine learning classification algorithm. Results are derived through experiments on how the derived properties are classified and which properties have a significant effect on the classification result and accuracy improvement. In the experimental results of this paper, although it is different for each algorithm when a specific attribute is included or not, the learning with a specific attribute shows an increase in accuracy, and later detects malicious code and ransomware files and abnormal behavior in the information protection system. It is expected that it can be used for property selection when creating algorithms.
Fuel gases such as methane and propane are used in explosion hazardous area of domestic plants and can form non-uniform mixtures with the influence of process conditions due to leakage. The fire-explosion risk assessment using literature data measured under uniform mixtures, damage prediction can be obtained the different results from actual explosion accidents by gas leaks. An explosion characteristics such as explosion pressure and flame velocity of non-uniform gas mixtures with concentration change similar to that of facility leak were examined. The experiments were conducted in a closed 0.82 m long stainless steel duct with observation recorded by color high speed camera and piezo pressure sensor. Also we proposed the quantification method of non-uniform mixtures from a regression analysis model on the change of concentration difference with time in explosion duct. For the non-uniform condition of this study, the area of flame surface enlarged with increasing the concentration non-uniform in the flame propagation of methane and was similar to the wrinkled flame structure existing in a turbulent flame. The time to peak pressure of methane decreased as the non-uniform increased and the explosion pressure increased with increasing the non-uniform. The ranges of KG (Deflagration index) of methane with the concentration non-uniform were 1.30 to 1.58 [MPa·m/s] and the increase rate of KG was 17.7% in methane with changing from uniform to non-uniform.
In light of recent social concerns related to issues such as water supply pipe deterioration leading to problems like leaks and degraded water quality, the significance of maintenance efforts to enhance water source quality and ensure a stable water supply has grown substantially. In this study, scan statistic was applied to analyze water quality complaints and water leakage accidents from 2015 to 2021 to present a reasonable method to identify areas requiring improvement in water management. SaTScan, a spatio-temporal statistical analysis program, and ArcGIS were used for spatial information analysis, and clusters with high relative risk (RR) were determined using the maximum log-likelihood ratio, relative risk, and Monte Carlo hypothesis test for I city, the target area. Specifically, in the case of water quality complaints, the analysis results were compared by distinguishing cases occurring before and after the onset of "red water." The period between 2015 and 2019 revealed that preceding the occurrence of red water, the leak cluster at location L2 posed a significantly higher risk (RR: 2.45) than other regions. As for water quality complaints, cluster C2 exhibited a notably elevated RR (RR: 2.21) and appeared concentrated in areas D and S, respectively. On the other hand, post-red water incidents of water quality complaints were predominantly concentrated in area S. The analysis found that the locations of complaint clusters were similar to those of red water incidents. Of these, cluster C7 exhibited a substantial RR of 4.58, signifying more than a twofold increase compared to pre-incident levels. A kernel density map analysis was performed using GIS to identify priority areas for waterworks management based on the central location of clusters and complaint cluster RR data.
The increased demand for electronic components, spurred by the Fourth Industrial Revolution and the COVID-19 pandemic, has facilitated human life but also escalated the production of e-waste. Discussions on the impact of e-waste have primarily revolved around environmental, health, and social issues, with global legislations focusing on addressing these concerns. However, e-waste poses unique security risks, such as potential technological and personal information leaks, unlike conventional waste. Current discourse on e-waste security is notably insufficient. This study aims to empirically analyze the relatively overlooked trends in e-waste security, employing three methodologies. Firstly, it assesses the general trend in discussions on e-waste by analyzing year-wise documents and media reports. Secondly, it identifies key trends in e-waste security by examining documents on the subject. Thirdly, the study reviews national security guidelines related to e-waste disposal to assess the necessity of designing security strategies for e-waste management. This research is significant as it is one of the first in korea to address e-waste from a security perspective and offers a multi-dimensional analysis of e-waste security trends. The findings are expected to enhance domestic awareness of e-waste and its security issues, providing an opportunity for proactive response to these security risks.
Due to the rapid development of IT in recent years, not only personal information but also the key technologies and information leakage that companies have are becoming important issues. For the enterprise, the core technology that the company possesses is a very important part for the survival of the enterprise and for the continuous competitive advantage. Recently, there have been many cases of technical infringement. Technology leaks not only cause tremendous financial losses such as falling stock prices for companies, but they also have a negative impact on corporate reputation and delays in corporate development. In the case of SMEs, where core technology is an important part of the enterprise, compared to large corporations, the preparation for technological leakage can be seen as an indispensable factor in the existence of the enterprise. As the necessity and importance of Information Security Management (ISM) is emerging, it is necessary to check and prepare for the threat of technology infringement early in the enterprise. Nevertheless, previous studies have shown that the majority of policy alternatives are represented by about 90%. As a research method, literature analysis accounted for 76% and empirical and statistical analysis accounted for a relatively low rate of 16%. For this reason, it is necessary to study the management model and prediction model to prevent leakage of technology to meet the characteristics of SMEs. In this study, before analyzing the empirical analysis, we divided the technical characteristics from the technology value perspective and the organizational factor from the technology control point based on many previous researches related to the factors affecting the technology leakage. A total of 12 related variables were selected for the two factors, and the analysis was performed with these variables. In this study, we use three - year data of "Small and Medium Enterprise Technical Statistics Survey" conducted by the Small and Medium Business Administration. Analysis data includes 30 industries based on KSIC-based 2-digit classification, and the number of companies affected by technology leakage is 415 over 3 years. Through this data, we conducted a randomized sampling in the same industry based on the KSIC in the same year, and compared with the companies (n = 415) and the unaffected firms (n = 415) 1:1 Corresponding samples were prepared and analyzed. In this research, we will conduct an empirical analysis to search for factors influencing technology leakage, and propose an early warning system through data mining. Specifically, in this study, based on the questionnaire survey of SMEs conducted by the Small and Medium Business Administration (SME), we classified the factors that affect the technology leakage of SMEs into two factors(Technology Characteristics, Organization Characteristics). And we propose a model that informs the possibility of technical infringement by using Support Vector Machine(SVM) which is one of the various techniques of data mining based on the proven factors through statistical analysis. Unlike previous studies, this study focused on the cases of various industries in many years, and it can be pointed out that the artificial intelligence model was developed through this study. In addition, since the factors are derived empirically according to the actual leakage of SME technology leakage, it will be possible to suggest to policy makers which companies should be managed from the viewpoint of technology protection. Finally, it is expected that the early warning model on the possibility of technology leakage proposed in this study will provide an opportunity to prevent technology Leakage from the viewpoint of enterprise and government in advance.
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