• Journal of the Korean Society of Safety
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• v.23 no.4
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• pp.72-78
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• 2008

In any form of construction work, it is essential that accidents be prevented at every stage from foundation preparation to build completion. For this, it is necessary to use models that can assess risk and provide instruction for safe work processes so that the risk of accidents is reduced. Currently, however, very few models can perform these tasks. In this paper, we presents a model that assesses risk quantitatively by analyzing risk factors involved in stage of construction such as foundation work, erection work, structural work, equipment work, finishing work and etc work. The model performs assessment based on examples of accidents and by investing actual conditions during construction. In addition, we presents in this paper a safety management system was developed to assess risk during construction and to effectively train laborers.

• Environmental Analysis Health and Toxicology
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• v.10 no.1_2
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• pp.21-35
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• 1995

Risk assessment processes, which include processes for the estimation of human cancer potency using animal bioassay data and calculation of human exposure, entail uncertainties. In the exposure assessment process, exposure scenarios with various assumptions could affect the exposure amount and excess cancer risk. We compared risk estimates among various exposure scenarios of vinyl chloride, trichloroethylene and tetrachloroethylene in tap water. The contaminant concentrations were analyzed from tap water samples in Seoul from 1993 to 1994. The oral and inhalation cancer potencies of the contaminants were estimated using multistage, Weibull, lognormal, and Mantel-Bryan model in TOX-RISK computer software. In the first case, human excess cancer risk was estimated by the US EPA method used to set the MCL(maximum contaminant level). In the second and third case, the risk was estimated for multi-route exposure with and without adopting Monte-Carlo simulation, respectively. In the second case, exposure input parameters and cancer potencies used probability distributions, and in the third case, those values used point estimates(mean, and maximum or 95% upper-bound value). As a result, while the excess cancer risk estimated by US EPA method considering only direct ingestion tended to be underestimated, the risk which was estimated by considering multi-route exposure without Monte-Carlo simulation and then using the maximum or 95% upper-bound value as input parameters tended to be overestimated. In risk assessment for volatile organic compounds, considering multi-route exposure with adopting Monte-Carlo analysis seems to provide the most reasonable estimations.

• Journal of Oriental Neuropsychiatry
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• v.35 no.2
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• pp.153-162
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• 2024

Objectives: Among OECD countries, South Korea has been having the highest suicide rate since 2018, with 24.1 deaths per 100,000 people reported in 2020. The objectie of this study was to examine the use of generative artificial intellicence (AI) chatbots to train third-year Korean medicine (KM) students in conducting suicide risk assessments for patients with depressive disorders to train students for their clinical practice skills. Methods: The Claude 3 Sonnet model was utilized for chatbot simulations. Students performed mock consultations using standardized suicide risk assessment tools including Ask Suicide-Screening Questions (ASQ) tool and ASQ Brief Suicide Safety Assessment. Experiences and attitudes were collected through an anonymous online survey. Responses were rated on a 1~5 Likert scale. Results: Thirty-six students aged 22~30 years participated in this study. Their scores for interest and appropriateness (4.66±0.57), usefulness (4.60±0.61), and overall experience (4.63±0.60) were high. Their evaluation of the usability of artificial intelligence chatbot was also high at 4.58±0.70 points. However, their trust in chatbot responses (Q12) was lower (3.86±0.99). Common issues related to dissatisfaction included conversation disruptions due to token limits and inadequate chatbot responses. Conclusions: This is the first study investigating generative AI chatbots for suicide risk assessment training in KM education. Students reported high satisfaction, although their trust in chatbot accuracy was moderate. Technical limitations affected their experience. These preliminary findings suggest that generative AI chatbots hold promise for clinical training, particularly for education in psychiatry. However, improvements in response accuracy and conversation continuity are needed.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.353-363
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• 2019

This paper presents a comprehensive simulation and assessment of gas dispersion above sea from a subsea release using a Computational Fluid Dynamics (CFD) approach. A 3D CFD model is established to evaluate the behavior of flammable gas above sea, and a jack-up drilling platform is included to illustrate the effect of flammable gas cloud on surface vessels. The simulations include a matrix of scenarios for different surface release rates, distances between surface gas pool and offshore platform, and wind speeds. Based on the established model, the development process of flammable gas cloud above sea is predicted, and the dangerous area generated on offshore platform is assessed. Additionally, the effect of some critical factors on flammable gas dispersion behavior is analyzed. The simulations produce some useful outputs including the detailed parameters of flammable gas cloud and the dangerous area on offshore platform, which are expected to give an educational reference for conducting a prior risk assessment and contingency planning.

• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.1-9
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• 2022

Most factories deal with toxic or flammable chemicals in their industrial processes. These hazardous substances pose a risk of leakage due to accidents, such as fire and explosion. In the event of chemical release, massive casualties and property damage can result; hence, quantitative risk prediction and assessment are necessary. Several methods are available for evaluating chemical dispersion in the atmosphere, and most analyses are considered neutral in dispersion models and under far-field wind condition. The foregoing assumption renders a model valid only after a considerable time has elapsed from the moment chemicals are released or dispersed from a source. Hence, an initial dispersion model is required to assess risk quantitatively and predict the extent of damage because the most dangerous locations are those near a leak source. In this study, the dispersion model for initial consequence analysis was developed with three-dimensional unsteady advective diffusion equation. In this expression, instantaneous leakage is assumed as a puff, and wind velocity is considered as a coordinate transform in the solution. To minimize the buoyant force, ethane is used as leaked fuel, and two different diffusion coefficients are introduced. The calculated concentration field with a molecular diffusion coefficient shows a moving circular iso-line in the horizontal plane. The maximum concentration decreases as time progresses and distance increases. In the case of using a coefficient for turbulent diffusion, the dispersion along the wind velocity direction is enhanced, and an elliptic iso-contour line is found. The result yielded by a widely used commercial program, ALOHA, was compared with the end point of the lower explosion limit. In the future, we plan to build a more accurate and general initial risk assessment model by considering the turbulence diffusion and buoyancy effect on dispersion.

• Journal of the Korean Institute of Gas
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• v.22 no.6
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• pp.40-43
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• 2018

For pressure safety valves, open failure and close failure are partially dependent on each other. A method is proposed in this work that uses a Markov process model and a Weibull distribution model in order to construct a reliability model for two kinds of failure. A pressure safety valve model is obtained from a known open failure model, an induced close failure model, and a simultaneous failure model that reproduces recently reported inspection results. It is expected that the application of the proposed method can be expanded to quantitative risk assessment of various systems that have partially dependent multiple failure states.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.674-683
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• 2010

The current study was performed to examine the agricultural suitability of the cultivated upland nearby abandoned mining areas in Korea using three different scientific risk assessment models of Korea, USA and UK. For this, three mining sites DM, MG and KS were selected among 687 abandoned mines through preliminary risk assessment. A wide range of parameters were obtained through analysis of both soil and crop samples from the selected areas for heavy metal concentration and questionnaires to the communities along with the selected mining sites. Heavy metal concentration in soil samples was lower than the values previously reported by the Ministry of Environment (ME, 2002). However, both As and Cd concentration in the soil samples exceeded the concern level for agricultural area of the Soil Environment Conservation Act. Judging from the contaminant criteria for the crops, only Zn level in pepper, soybean and corn from the mining area DM exceeded the criteria whereas As, Cd, $Cr^{6+}$, Cu, Hg, Ni, Pb did not exceed the criteria. It was demonstrated that there would be human health risk by Pb accumulated in crops from both mining areas MG and KS when estimated by the risk assessment models of Korea and USA. Against it, results of the risk assessment model of UK showed human health risk by Pb in the crops from all study areas.

• Journal of Environmental Health Sciences
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• v.44 no.5
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• pp.460-467
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• 2018

Objectives: The objectives of this study are to estimate the inhalation exposure level of benzene for workers using Tier 1 exposure models ECETOC TRA (European Center for Ecotoxicology and Toxicology of Chemicals Target Risk Assessment) and Stoffenmanager, and to investigate their reliability for exposure assessment in K-REACH. Methods: Two exposure scenarios, 'manufacture of benzene' and 'use as solvents,' were developed for assessment of workers' exposure to benzene. The Process Category (PROC) for ECETOC TRA was collected from the European Chemical Agency (ECHA) registration dossier, and the Activity for Stoffenmanager was converted from PROC using translation of exposure models (TREXMO). The information related to exposure, such as working duration, Respiratory Protective Equipment (RPE), Local Exhaust Ventilation (LEV), and Risk Management Measure (RMM) were classified into high, medium, and low exposure conditions. The risk was determined by the ratio of the estimated exposure and occupational exposure limits of benzene. Results: Under high exposure conditions, the worker exposure level calculated from all PROCs and Activities exceeded the risk level, with the exception of PROC 1 and Activity 1. In the medium exposure condition, PROC 8a, 8b, and 9 and Activity 3, 7, and 8 all exceeded the risk, whereas in the low condition, all PROCs and Activities were determined to be safe. As a result, action corresponding with the low exposure condition is required to reduce the risk of exposure among workers in workplaces where benzene is manufactured or used as a solvent. In addition, the predicted exposure levels derived from the exposure models were lower than measured levels. The exposure levels estimated from Stoffenmanager were more conservative than those from ECETOC TRA. Conclusions: This study demonstrates the feasibility of exposure models for exposure assessment through the example of occupational inhalation exposure assessment for benzene. For more active utilization of exposure models in K-REACH, the exact application of collected information and accurate interpretation of obtained results are necessary.

• Journal of Radiation Industry
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• v.17 no.1
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• pp.83-92
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• 2023

When assessing the risk of radioactive wastes transportation on land, computer codes such as RADTRAN and RISKIND are used as deterministic methods. Transportation risk assessment using the deterministic method requires a relatively short assessment time. On the other hand, transportation risk assessment using the probabilistic method requires a relatively long assessment time, but produces more reliable results. Therefore, a study is needed to evaluate the exposure dose using a deterministic method that can be evaluated relatively quickly, and to compare and analyze the exposure dose result using a probabilistic method. The purpose of this study is to evaluate the exposure dose during transportation of radioactive wastes using deterministic and probabilistic methods, and to compare and analyze them. For this purpose, the main exposure factors were selected and various exposure situations were set. The distance between the radioactive waste and the receptor, the size of the package, and the speed of vehicle were selected as the main exposure factors. The exposure situation was largely divided into when the radioactive wastes were stationary and when they were passing. And the dose (rate) model of the deterministic overland transportation risk assessment computer code was analyzed. Finally, the deterministic method of the RADTRAN computer code and the RISKIND computer code and the probabilistic method of the MCNP 6 computer code were used to evaluate the exposure dose in various exposure situations during transportation of radioactive wastes. Then we compared and analyzed them. As a result of the evaluation, the tendency of the exposure dose (rate) was similar when the radioactive wastes were stationary and passing. For the same situation, the evaluation results of the RADTRAN computer code were generally more conservative than the results of the RISKIND computer code and the MCNP 6 computer code. The evaluation results of the RISKIND computer code and the MCNP 6 computer code were relatively similar. The results of this study are expected to be used as basic data for establishing the radioactive wastes transportation risk assessment system in Korea in the future.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2941-2959
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• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.