Hydrogen is considered a cleaner energy source than fossil fuels. As a result, the use of hydrogen in daily life and economic industries is expected to increase. However, the use of hydrogen energy is currently limited because of safety issues. The rate of combustion of the hydrogen mixture is about seven times higher than that of hydrocarbon fuels. The hydrogen mixture is highly flammable and has a low minimum ignition energy. Therefore, it presents considerable risks for fire and explosions in all areas of hydrogen manufacturing, transportation, storage, and use. In this study, the auto-ignition characteristics of hydrogen were investigated numerically for diluted hydrogen mixtures. Auto-ignition temperature, a critical property predicting the fire and explosion risk in hydrogen combustion, was determined in well-stirred reactors. When N₂ and CO₂ were used to dilute the hydrogen/air mixture, the ignition delay time increased with increasing dilution ratios in both cases. The CO₂-diluted mixtures exhibited a longer ignition delay than the N₂-diluted mixtures. We also confirmed that lower initial ignition temperatures increased the ignition delay times at 950 K and above. Overall, the auto-ignition characteristics, such as the concentrations of participating species and ignition delay times, were primarily affected by the initial temperature of the mixture.

Hybrid laminated Al/carbon-fiber-reinforced plastic (CFRP) composites are attracting considerable attention from industries such as aerospace and automobiles owing to their excellent specific strength and specific rigidity. However, when this material is used to fabricate high-pressure fuel storage containers subjected to repeated fatigue loads, fatigue life evaluation for the working load is regulated as an important criterion for operational safety and ease of maintenance. Among the existing evaluation methods for these vessels, the burst test and the hydraulic repeat test require expensive facilities. Thus, the present study aims to develop an improved fatigue life test for Al/CFRP laminated hybrid composites. The test specimen was manufactured using a curved mold considering the shape of a type III high-pressure storage container. The strain-life method was used for fatigue life evaluation, and the life was predicted based on the transition life. The results indicate that the more complex the CFRP stacking sequence, the longer is the transition life. This test method is expected to be useful for ensuring the fatigue safety and economy of hybrid laminate composites.

By analyzing the current status and type of industrial safety accidents caused by industrial machinery, this study aims to examine the importance and necessity of the safety devices that are installed on-site. Additionally, this study aims to determine the implications for Korea by analyzing the status of industrial accidents in major countries and the responses to the accidents. We found that workers could easily access and operate the safety devices and that productivity and convenience were more important than safety. Thus, safety devices need to be mandatorily installed on-site for the safety of workers, and only management supervisors should be given the authority to operate them to afford a sense of safety responsibility to the workers.

Heat is generated during the synthesis and mixing process of chemical compounds due to a change in activation energy during the reaction. A runaway reaction occurs when sufficient heat is not removed during the heat control process within a reactor, rapidly increasing the temperature, reaction speed, and rate of heat generation inside the reactor. A risk assessment was executed using an RC-1 (Reaction Calorimeter) during Friedel-Crafts acylation. Friedel-Crafts acylation runs the risk of rapid heat generation during Active Pharmaceutical Ingredient (API) manufacturing; it was used to confirm the risk of a runaway reaction at each synthesis stage and during the mixing process. This study used experimental data to develop a safety efficiency improvement plan to control the risks of runaway and other exothermic reactions, which was implemented at the production site of a chemical plant.

In Korea, more than half of work-related fatalities have occurred on construction sites. To reduce such occupational accidents, safety inspection by government agencies is essential in construction sites that present a high risk of serious accidents. To address this issue, this study developed risk prediction models of serious accidents in construction sites using five machine learning methods: support vector machine, random forest, XGBoost, LightGBM, and AutoML. To this end, 15 proactive information (e.g., number of stories and period of construction) that are usually available prior to construction were considered and two over-sampling techniques (SMOTE and ADASYN) were used to address the problem of class-imbalanced data. The results showed that all machine learning methods achieved 0.876~0.941 in the F1-score with the adoption of over-sampling techniques. LightGBM with ADASYN yielded the best prediction performance in both the F1-score (0.941) and the area under the ROC curve (0.941). The prediction models revealed four major features: number of stories, period of construction, excavation depth, and height. The prediction models developed in this study can be useful both for government agencies in prioritizing construction sites for safety inspection and for construction companies in establishing pre-construction preventive measures.

This study surveyed damage to small and medium-sized RC slab bridges, the largest in number in Korea. Four common types of damage were identified, and their static and dynamic structural behaviors were examined through structural analysis. The degree of damage was selected as an analysis parameter for three superstructures of RC slab bridges. After structural analysis, a damage assessment process was proposed that can be used as the basis for establishing maintenance yplans for these bridges. The results of the present study can be used for the safety management of RC slab bridges, classified as bridges suspected of safety flaws or requiring maintenance in load-carrying capacity tests.

The main purpose of accident analysis is to identify the causal factors and the mechanisms of those factors leading to the accident. However, current accident analysis techniques focus only on finding the factors related to the accident without providing more insightful results, such as structures or mechanisms. For this reason, preventive actions for safety management are concentrated on the elimination of causal factors rather than blocking the connection or chain of accident processes. This greatly reduces the effectiveness of safety management in practice. In the present study, a technique to model the correlational structure of accident risk factors is proposed by using the co-occurrence keyword network analysis technique. To investigate the effectiveness of the proposed technique, a case study involving a portable ladder fall accident is conducted. The results indicate that the proposed technique can construct the correlational structure model of the risk factors of a portable ladder fall accident. This proves the effectiveness of the proposed technique in modeling the correlational structure of accident risk factors.

Human error is often in part in the cause of accidents and the result of various factors in an organization. Accidents should be investigated to elucidate all causes. Therefore, to reduce accidents, it is necessary to identify which factors affect human error within the organization. In this study, five groups of influencing factors on human error were selected using previousresearch, and operational definitions were made based on them. In addition, a questionnaire for measuring latent variables by operational definition was developed as an observation variable, and responses were received from employees of chemical companies in Ulsan. Based on SEM (structural equation modeling) analysis, 1) confirmatory factor analysis of variables in the human error model, 2) reliability and validity of latent variables, 3) correlations among latent variables, 4) influencing coefficients among influence factors, and 5) the verification results of the paths that these influencing factors have on human error are introduced in this study.

This report documents the results of an at-power internal events Level 1 Probabilistic Safety Assessment (PSA) for a Korea research reactor (KRR). The aim of the study is to determine the accident sequences, construct an internal level 1 PSA model, and estimate the core damage frequency (CDF). The accident quantification is performed using the AIMS-PSA software version 1.2c along with a fault tree reliability evaluation expert (FTREX) quantification engine. The KRR PSA model is quantified using a cut-off value of 1.0E-15/yr to eliminate the non-effective minimal cut sets (MCSs). The final result indicates a point estimate of 4.55E-06/yr for the overall CDF attributable to internal initiating events in the core damage state for the KRR. Loss of Electric Power (LOEP) is the predominant contributor to the total CDF via a single initiating event (3.68E-6/yr), providing 80.9% of the CDF. The second largest contributor is the beam tube loss of coolant accident (LOCA), which accounts for 9.9% (4.49E-07/yr) of the CDF.

Korea Atomic Energy Research Institute (KAERI) has been operating an integral effects test facility, the Advanced Thermal-Hydraulic Test Loop for Accident Simulation (ATLAS), according to APR1400 for transient experimental and design basis accident simulation. Moreover, based on the experimental data, the domestic standard problem (DSP) program has been conducted in Korea to validate system codes. Recently, through DSP-05, the performance of the passive auxiliary feedwater system (PAFS) in the event of multiple steam generator tube rupture (MSGTR) has been analyzed. However, some errors exist in the reference input model distributed for DSP-05. Furthermore, the calculation results of the heat loss correlation for the secondary system presented in the technical report of the reference indicate that a large difference is present in heat loss from the target value. Thus, in this study, the reference model is corrected using the geometric information from the design report and drawings of ATLAS. Additionally, a new heat loss correlation is suggested by fitting the results of the heat loss tests. Herein, MSGTR-PAFS accident analysis is performed using MARS-KS 1.5 with the improved model. The steady-state calculation results do not significantly differ from the experimental values, and the overall physical behavior of the transient state is properly predicted. Particularly, the predicted operating time of PAFS is similar to the experimental results obtained by the modified model. Furthermore, the operating time of PAFS varies according to the heat loss of the secondary system, and the sensitivity analysis results for the heat loss of the secondary system are presented.