• Journal of Auto-vehicle Safety Association
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• v.10 no.3
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• pp.20-26
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• 2018

It was a pilot study for developing an algorithm to determine the presence or absence of cervical spine injury by analyzing the severity factor of the patients in motor vehicle occupant accidents. From August 2012 to October 2016, we used the KIDAS database, called as Korean In-Depth Accident Study database, collected from three regional emergency centers. We analyzed the general characteristics with several factors. Moreover, cervical spine injury patients were divided into two groups: Group 1 for from Quebec Task Force (hereinafter 'QTF') grade 0 to 1, and group 2 for from QTF grade 2 to 4. The score was assigned according to the distribution ratio of cervical spine injured patients compared to the total injured patients, and the cut-off value was derived from the total score by summation of the assigned score of each factors. 987 patients (53.0%) had no cervical spine injuries and 874 patients (47.0%) had cervical spine injuries. QTF grade 2 was found in 171 patients (9.2%) with musculoskeletal pain, QTF grade 3 was found in 38 patients (2.0%) with spinal cord injuries, and QTF grade 4 was found in 119 patients (6.4%) with dislocation or fracture, respectively. We selected the statistically significant factors, which could be affected the cervical spine injury, like the collision direction, the seating position, the deformation extent, the vehicle type and the frontal airbag deployment. Total score, summation of the assigned each factors, 10 was presented as a cut-off value to determine the cervical spine injury. In this study, it was meaningful as a pilot study to develop algorithms by selecting limited influence factors and proposing cut-off value to determine cervical spine injury. However, since the number of data samples was too small, additional data collection and influencing factor analysis should be performed to develop a more delicate algorithm.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.35-45
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• 2008

Trucking is the most frequently used mode for freight movement due to relatively lower shipping costs and its operational flexibility. However, truck traffic can contribute to serious safety problems where they occupy high percentage of the total traffic. Heavy truck crashes arc more likely to result in serious injuries and fatalities than are crashes involving light vehicles. Therefore, safety issues for truck traffic are very significant both for public agencies and for general travelers. The objective of our study is to find truck-involved accident patterns according to traffic conditions and main factors as well as to find the most critical factor through conventional statistical techniques. A vailable data were obtained from TASAS (Traffic Accident Surveillance and Analysis System). Once critical factors are identified, effective and efficient truck management strategies can be discussed.

• Journal of the Korean Society of Safety
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• v.27 no.5
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• pp.219-223
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• 2012

For an off-site consequence analysis at nuclear power plant, MELCOR Accident Consequence Code System(MACCS) II code is widely used as a software tool. In this study, the algorithm of web-based off-site consequence analysis program(OSCAP) using the MACCS II code was developed for an Integrated Leak Rate Test (ILRT) interval extension and Level 3 probabilistic safety assessment(PSA), and verification and validation(V&V) of the program was performed. The main input data for the MACCS II code are meteorological, population distribution and source term information. However, it requires lots of time and efforts to generate the main input data for an off-site consequence analysis using the MACCS II code. For example, the meteorological data are collected from each nuclear power site in real time, but the formats of the raw data collected are different from each site. To reduce the efforts and time for risk assessments, the web-based OSCAP has an automatic processing module which converts the format of the raw data collected from each site to the input data format of the MACCS II code. The program also provides an automatic function of converting the latest population data from Statistics Korea, the National Statistical Office, to the population distribution input data format of the MACCS II code. For the source term data, the program includes the release fraction of each source term category resulting from modular accident analysis program(MAAP) code analysis and the core inventory data from ORIGEN. These analysis results of each plant in Korea are stored in a database module of the web-based OSCAP, so the user can select the defaulted source term data of each plant without handling source term input data.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.29-43
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• 2007

An automobile black box can provide sufficient and accurate information for investigating the causes of vehicle accidents as well as preventing them in the future. The database of accident information from stored data in the black box can provide a variety of services to the general public when it is accessed in a reasonable manner. minimizing intrusion into drivers' privacy. Therefore, the black box could become the main intelligent automobile Part, with extensive benefits for all associated industries as well as government agencies and insurance companies. While the introduction and spread of the black box are imminent in Korea, this paper reviews technology and product trends of the black box. In particular, this paper presents findings on the investigation of black box-related patent applications and an in-depth study of core patents from several leading counties, including the United States. In addition, this paper describes trends of standardization and legislation in leading countries and presents methods of standardization with suggestions for some development topics related to black box technology.

• Journal of the Korean Society of Safety
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• v.23 no.6
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• pp.14-20
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• 2008

A large number of accidents have been occurred in the domestic shipbuilding industry. Its number of accidents is approximately twice than that of manufacturing industry and three times larger than that of whole industry in general. There are several reasons that make it hard to control the accidents. First, it is because the shipbuilding industry is composed of many subcontractors who may need improvement in safety education and safety management. Second, the shipyard environments are exposed to lots of hazards such as high elevation works, isolated workspaces, heavyweight and huge structures/components. Last, the shipbuilding industry has grown too rapidly in a short period. For that reason, the safety management standards and safety consciousness could not catch up the speed of its development. In this study, it is suggested to use a more efficient and easier way to conduct safety management using a web-based safety management system for the shipbuilding industry. This system is composed of four main parts, which is available for self-auditing with legal support. Those are checklists based safety and health evaluation, safety inspection, user shared accident database and user shared bulletin board. It is expected that this system can help us to reduce risks in the shipbuilding industry considerably.

• Journal of Environmental Health Sciences
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• v.47 no.2
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• pp.175-181
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• 2021

Objectives: The correlation between the size of a leak hole, the volume of the leakage, and the range of influence was investigated for a hydrochloric acid tank-lorry. Methods: For the case of a tank-lorry chemical accident, KORA (Korea Off-site Risk Assessment Supporting Tool) was used to predict the leak rate and the range of influence according to the size of the leak hole. The correlation was studied using R. Results: As a result of analyzing the leak rate change according to the leak hole size in a 35% hydrochloric acid tank-lorry, as the size of the leak hole increased from 1 to 100 mm, the leak rate increased from 0.008 to 83.94 kg/sec, following the power function. As a result of calculating the range of influence under conditions ranging from 1 to 100 mm in size and 10 to 60 minutes of leakage time, it was found that the range spanned from a minimum of 5.4 m to a maximum of 307.9 m. As a result of multiple regression analysis using R, the quadratic function model best explained the correlation between the size of the leak hole, the leak time, and the range of influence with an adjected coefficient of determination of 0.97 and a root mean square error of 22.33. Conclusion: If a correlation database for the size of a leak hole is accumulated for various substances and under various conditions, the amount of leakage and the range of influence can easily be calculated, facilitating field response activities.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.281-288
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• 2022

This study quantitatively analyzed the human casualties that can occur when a multicopter-type Urban Air Mobility (UAM) with a weight of about 1 ton and a speed of about 100 km/h falls in an urban area. Based on the population density and building database in Seoul, the population exposed to collisions in the event of a UAM crash was derived. Through the ballistic descent model, the accident impact radius of the UAM fall was calculated. In addition, the change in human casualties on the ground was analyzed when the accident impact radius increased. Finally, the ground risk map was created for Seoul, and it was confirmed that about 1 to 10 people could be injured when a UAM crash.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• Journal of Environmental Health Sciences
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• v.49 no.3
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• pp.149-158
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• 2023

Background: Injury is one of the major health problems in South Korea. Few studies have evaluated both intentional and unintentional injury when investigating the association between exposure to air pollutants and injury. Objectives: We aimed to explore the association between short-term exposure to ambient air pollution and years of life lost (YLLs) due to injury. Methods: Data on daily YLLs for 2002~2019 were obtained from the the Death Statistics Database of the Korean National Statistical Office. This study estimated short-term exposure to particulate matter with an aerodynamic diameter of <10 ㎛ (PM₁₀), particulate matter with an aerodynamic diameter of <2.5 ㎛ (PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃). This time series study was conducted using a generalized additive model (GAM) assuming a Gaussian distribution. We also evaluated a delayed effect of ambient air pollution by constructing a lag structure up to seven days. The best-fitting lag was selected based on smallest generalized cross validation (GCV) value. To explore effect modification by intentionality of injury (i.e., intentional injury [self-harm, assault] and unintentional injury), we conducted stratified subgroup analyses. Additionally, we stratified unintentional injury by mechanism (traffic accident, fall, etc.). Results: During the study period, the average daily YLLs due to injury was 307.5 years. In the intentional injury, YLLs due to self-harm and assault showed positive association with air pollutants. In the unintentional injury, YLLs due to fall, electric current, fire and poisoning showed positive association with air pollutants, whereas YLLs due to traffic accident, mechanical force and drowning/submersion showed negative associations with air pollutants. Conclusions: Injury is recognized as preventable, and effective strategies to create a safe society are important. Therefore, we need to establish strategies to prevent injury and consider air pollutants in this regard.

• Journal of the Korean Institute of Gas
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• v.2 no.2
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• pp.48-54
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• 1998

In this study a computerized prototype system was developed with Safety Management Information System(SMIS version 1.0) as a main system and database as subsystems to handle information. Safety management information consists of management aspects and technical elements, but SMIS consists of 4 modules of technical elements to interrelate safety technologies closely. SMIS enables gas industries to manage process safety information effectively and to evaluate hazards. The results from SMIS can be used to the operation manual and the emergency plan. Data base consists of 3 modules of accident data, material data, and equipment data to support SMIS. Also, the case study results proved the usefulness of SMIS for searching and accumulating process safety data. Especially, MIS which has the database suggests a formal structure for scattered raw safety data in gas industries and brings reduction of man power and time.