• Journal of the Korean Institute of Gas
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• v.10 no.1 s.30
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• pp.48-55
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• 2006

In order to establish the comprehensively, quantitatively predictable program to the fire and explosion accidents in the urban gas system, and to set up domestic criteria of societal risk, the collected urban gas accident data have been deeply analyzed. The Poisson probability distribution functions with t=5 for the database of the gas accidents in recent 11 year shows that 'careless work-explosion-pipeline' item has the lowest frequency, whereas 'joint loosening & erosion-release-pipeline' item has the highest frequency. And thus the proper counteractions must be carried out. The further works requires setting up successive database on the fire and explosion accidents systematically to obtain reliable analyses.

• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.163-171
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• 2010

Forest fires have potentials to change the structure and function of forest ecosystems and significantly influence on atmosphere and biogeochemical cycles. Forest fire also affects the quality of public benefits such as carbon sequestration, soil fertility, grazing value, biodiversity, or tourism. The prediction of fire occurrence and its spread is critical to the forest managers for allocating resources and developing the forest fire danger rating system. Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behaviors and its spread. Thus, meteorological factors as well as social factors were considered in the fire danger rating systems. A total of 298 forest fires occurred during the fall season from 2002 to 2006 in South Korea were considered for developing a logistic model of forest fire occurrence. The results of statistical analysis show that only effective humidity and temperature significantly affected the logistic models (p<0.05). The results of ROC curve analysis showed that the probability of randomly selected fires ranges from 0.739 to 0.876, which represent a relatively high accuracy of the developed model. These findings would be necessary for the policy makers in South Korea for the prevention of forest fires.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.266-266
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• 2019

Marine accidents are increasing year by year, and various accidents occur such as engine failure, collision, stranding, and fire. These marine accidents present a risk of large casualties. It is important to prevent accidents beforehand. In this study, we propose a modeling to predict the occurrence of marine accidents by applying the Markov Chain Process that can predict the future based on past data. Applying the proposed modeling, the probability of future marine accidents was calculated and compared with the actual frequency. Through this, a probabilistic model was proposed to prepare a prediction system for marine accidents, and it is expected to contribute to predicting various marine accidents.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.166-176
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• 2021

Due to urbanization and industrialization, the importance of large-scale fire prevention, management and measures is increasing day by day. However, the fire site arrival rate in Golden Time, which is a factor that can minimize large-scale fire damage, of Pohang, a large city with a population of over 500,000, is relatively low. So additional fire fighting power deployment and infrastructure investment are required. However, as budget and manpower are limited, it is necessary to selectively deploy fire fighting power and invest in infrastructure. Therefore, this study attempted to present a fire damage rating that can compare the level of fire damage, which is an index that can help selectively provide fire fighting services in Pohang and make related decisions. For the index, the OD cost matrix was used to predict fire vulnerable areas with a high probability of increasing the fire scale in the event of a fire. Also fire damage was measured by predicting the level of fire damage in the event of a fire according to population, building density, and access of fire trucks. It is expected that the fire damage rating will be able to help in various decisions related to fire fighting service deployment and services not only in Pohang city, but also in other regions.

• Fire Science and Engineering
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• v.29 no.2
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• pp.1-7
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• 2015

Tracking, which is one of main reasons of the electric fire, progresses gradually, and therefore, the possibility of fire caused by tracking can be predicted by analyzing the stage of its progress. This paper is conducted in order to predict possibility of the electric fire caused by the tracking in the simulated electric equipment with load. Non-inductive resistance is used as the load. The tracking is happened in a Polyvinyl-chloride-sheathed flat cord, which is a part of the simulated electric equipment by means of dropping of electrolyte droplet. In order to predict the possibility of electric fire caused by tracking, we detect the whole current waveforms of the simulated electric equipment. The time-energy analysis and probability distribution are used for analysis of the tracking progress from the whole current waveforms. In accordance with the results is used for input date of Neural networks, the neural networks can be predict possibility of the electric fire in the electric equipment by 4 stages.

• Journal of Ship and Ocean Technology
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• v.4 no.4
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• pp.19-33
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• 2000

For the prevention of marine accidents based on human factor, the risk assessment analysis procedure is proposed which consists of (1) the structural analysis of marine accident, (2) the estimation of incidence probability based on the Fault Tree analysis, (3) the prediction of ef-fectiveness to reduced the accident risk by suitable countermeasures in the specified functional system, and (4) the risk assessment by means of minimizing of the total cost expectation and the background risk. As a practical example, the risk assessment analysis for preventing is investigated using the proposed method.

• Structural Engineering and Mechanics
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• v.74 no.6
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• pp.821-832
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• 2020

The fundamental period is an important parameter for seismic design and seismic risk assessment of building structures. In this paper, a simplified theoretical method to predict the fundamental period of masonry infilled reinforced concrete (RC) frame is developed based on the basic theory of engineering mechanics. The different configurations of the RC frame as well as masonry walls were taken into account in the developed method. The fundamental period of the infilled structure is calculated according to the integration of the lateral stiffness of the RC frame and masonry walls along the height. A correction coefficient is considered to control the error for the period estimation, and it is determined according to the multiple linear regression analysis. The corrected formula is verified by shaking table tests on two masonry infilled RC frame models, and the errors between the estimated and test period are 2.3% and 23.2%. Finally, a probability-based method is proposed for the corrected formula, and it allows the structural engineers to select an appropriate fundamental period with a certain safety redundancy. The proposed method can be quickly and flexibly used for prediction, and it can be hand-calculated and easily understood. Thus it would be a good choice in determining the fundamental period of RC frames infilled with masonry wall structures in engineering practice instead of the existing methods.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).