• Title/Summary/Keyword: 수소 위험성 평가 모델

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Dispersal of Hazardous Substance in a City Environment Based on Weather Conditions and Its Risk Assessment at the Pedestrian Level (기상조건에 따른 도시내 위험물질 확산정보와 보행자환경 위험영향평가)

  • Kim, Eun-Ryoung;Lee, Gwang-Jin;Yi, Chaeyeon
    • Journal of Environmental Impact Assessment
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    • v.26 no.4
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    • pp.242-256
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    • 2017
  • In this paper, dispersion scenarios concerning various meteorological conditions and real urban structures were made to estimate the impacts of hazardous substance leakage accidents and to reduce damages. Based on the scenario of the hazardous substance dispersion, the characteristics of the risk in the pedestrian environment were analyzed in Gangnam, Seoul. The scenarios are composed of 48 cases according to the meteorological conditions of wind direction and wind speed. In order to analyze the dispersion characteristics of the hazardous substances, simulations were conducted using a computational fluid dynamic (CFD) model with hydrogen fluoride releases. The validation for the simulated wind was conducted at a specific period, and all the calculated verification indices were within the valid range. As a result of simulated dispersion field at pedestrian level, it was found that the dispersion pattern was influenced by the flow, which was affected by the artificial obstacles. Also, in the case of the weakest wind speed of the inflow, the dispersion of the hazardous substance appeared in the direction of the windward side at the pedestrian level due to the reverse flow occurred at lower layers. Through this study, it can be seen that the artificial structures forming the city have a major impact on the flow formed in urban areas. The proposed approach can be used to simulate the dispersion of the hazardous substances and to assess the risk to pedestrians in the industrial complexes dealing with actual hazardous substances in the future.

Consequence Analysis of Hydrogen Filling Stations based on Cascade Compressing Systems (케스케이드 방식 압축시스템 기반의 수소충전소에 대한 정성적 위험성평가)

  • Ahn, Byeong-Jun;Rhim, Jong-Kuk
    • Journal of the Korean Institute of Gas
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    • v.25 no.2
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    • pp.13-21
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    • 2021
  • Because of the recent expansion of hydrogen vehicle supply, the installation of hydrogen filling station is expected to gradually expand. This study attempts to predict the damage scale and propose a safer design form based on the scenario that assumes the worst case of a hydrogen station. A Flacs solver using computational fluid dynamics (CFD) was used to predict the damage scale, and the accuracy was verified by comparing it with the experimental results of previous researchers. The damage scale prediction was conducted for hydrogen leakage and explosion, and the prediction target was the KR model based on the measured values. And as a comparative review model, a roofless model was selected without a ceiling. As a result of analyzing the two models, it was possible to confirm the accumulation and retention of hydrogen gas up to 60 vol% or more in the KR model, whereas in the case of the Roofless model, the phenomenon of discharge and diffusion to the outside of the charging station by riding the wall after leakage. I was able to check. In conclusion, it was reviewed that the type of hydrogen charging station without ceiling is more advantageous for safety than the hydrogen filling station model.

QSPR analysis for predicting heat of sublimation of organic compounds (유기화합물의 승화열 예측을 위한 QSPR분석)

  • Park, Yu Sun;Lee, Jong Hyuk;Park, Han Woong;Lee, Sung Kwang
    • Analytical Science and Technology
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    • v.28 no.3
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    • pp.187-195
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    • 2015
  • The heat of sublimation (HOS) is an essential parameter used to resolve environmental problems in the transfer of organic contaminants to the atmosphere and to assess the risk of toxic chemicals. The experimental measurement of the heat of sublimation is time-consuming, expensive, and complicated. In this study, quantitative structural property relationships (QSPR) were used to develop a simple and predictive model for measuring the heat of sublimation of organic compounds. The population-based forward selection method was applied to select an informative subset of descriptors of learning algorithms, such as by using multiple linear regression (MLR) and the support vector machine (SVM) method. Each individual model and consensus model was evaluated by internal validation using the bootstrap method and y-randomization. The predictions of the performance of the external test set were improved by considering their applicability to the domain. Based on the results of the MLR model, we showed that the heat of sublimation was related to dispersion, H-bond, electrostatic forces, and the dipole-dipole interaction between inter-molecules.