• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.71-79
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• 2021

In this study, a real-scale fuel-cell room of volume 1.36 m³ is constructed to confirm the explosion characteristics of hydrogen-air mixture gas in a hydrogen-powered house. A volume concentration of 40% is applied in the fuel-cell room as the worst-case scenario to examine the most severe accident possible, and two types of doors (made of plastic sheet and wood) are fabricated to observe their effects on the overpressure and impulse. The peak overpressure and impulse based on distance from the ignition source are experimentally observed and assessed. The maximum and minimum overpressures with a plastic-sheet door are about 20 and 6.7 kPa and those with a wooden door are about 46 and 13 kPa at distances of 1 and 5 m from the ignition source, respectively. The ranges of impulses for distances of 1-5 m from the ignition source are about 82-28 Pa·s with a plastic-sheet door and 101-28 Pa·s with a wooden door. The amount of damage to people, buildings, and property due to the peak overpressure and impulse is presented to determine the safe distance; accordingly, the safe distance to prevent harm to humans is about 5 m based on the 'injuries' class, but the structural damage was not serious.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.1
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• pp.31-38
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• 2018

Earthquake disasters that exceed the design criteria can pose significant threats to nuclear facilities. Seismic probabilistic safety assessment(PSA) is a probabilistic way to quantify such risks. Accordingly, seismic PSA has been applied to domestic and overseas nuclear power plants, and the safety of nuclear power plants was evaluated and prepared against earthquake hazards. However, there were few examples where seismic PSA was applied in case of a research reactor with a relatively small size compared to nuclear power plants. Therefore, in this study, seismic PSA technique was applied to actually completed research reactor to analyze its safety. Also, based on these results, the optimization study on the seismic capacity of the system constituting the research reactor was carried out. As a result, the possibility of damage to the core caused by the earthquake hazard was quantified in the research reactor and its safety was confirmed. The optimization study showed that the optimal seismic capacity distribution was obtained to ensure maximum safety at a low cost compared with the current design. These results, in the future, can expect to be used as a quantitative indicator to effectively improve the safety of the research reactor with respect to earthquakes.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.8-14
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• 2018

For the purpose of maintenance and prevention of earth fill dams against damage from natural hazards, automatic monitoring through various measuring instruments and resistivity survey has been carried out. Reservoirs and embankments have the structural vulnerability on the agricultural usages since most of them were built more than thirty years ago. The main aim to use monitoring method is to verify the safety and integrity of the dam. Resistivity survey can detect potential weaknesses, such as defective zones, anomalous seepages or internal erosion processes. Permanent resistivity monitoring systems were installed at a reservoir, which daily measurements have been taken every 6 hour. Using monitoring data for one year, anomalous seepage and structural defects were clarified for dam safety. Annual water level fluctuations are around 10 m. During their operation, reservoir dams are subject to a never-ending hydraulic load from the reservoir, which over the years may cause changes in the properties of the inner parts of the dam construction. Detailed analysis of the monitoring results was performed and showed that resistivities at most locations have been very stable over the full monitoring period excluding the effects of water fluctuation and seasons. To investigate the detectability of weak zone using the DC resistivity monitoring, numerical modeling with a simplified model for the drainage at a reservoir dam was also performed. The results showed that the seepage zone near drainage in a reservoir dam could be detected by resistivity response change.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.1
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• pp.104-114
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• 2000

This study was carried out to estimate current status of dust concentrations in the factories producing non-metallic products in Korea. Data were gathered from the environmental monitoring reports by 40 workplace environmental monitoring institutes and the questionnaire designed for the study by the authors. A total of 1838 dust samples from 368 plants were obtained from the reports and were analyzed with no data modifications. But data on asbestos, rock wool, and welding fumes were excluded in this evaluation. The factories were classified into eight groups according to the standard industrial classification scheme in Korea. The results of this study were as follows; 1. The factories included were glass, non-refractory ceramic, refractory ceramic ware, structural non-refractory clay and ceramic, cement and lime, articles of concretes, and stone. Mean(geometric mean) concentrations of total dust samples ranged from $1.75(0.84)mg/m^3$ to $5.87(2.84)mg/m^3$. Statistically significantly higher dust concentrations were found in the cement and lime industries compared with other industries. 2. The non-compliance rates were 15.2% in glass and 20.6% in other non-metallic mineral products industries. Although all institutions surveyed utilized the identical sampling and classification scheme for dusts as specified in the current occupational exposure limits, wide discrepancies were found in collecting samples and classifying dusts. Further problems were discovered in classifying dusts. A dust sample collected could be classified into any of the three groups regardless of silica content. The results of this study showed that dust concentrations in the non-metallic products industries varied widely. Also discovered was classification errors of dust types among workplace monitoring institutes. These errors could adversely affect the results of exposure assessments and the true nature of dust hazards. Further, no institutions performed respirable dust sampling and analysis of crystalline silica. In order to correct these malpractices, current standards of occupational exposure limits should be revised and tight supervision by the Ministry of Labour be suggested.

• Geomechanics and Engineering
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• v.15 no.5
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• pp.1113-1124
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• 2018

Geological dynamic hazards during deep coal mining are caused by the failure of a composite system consisting of the rock and coal layers, whereas the joint in coal affects the stability of the composite system. In this paper, the compression test simulations for the rock-coal combined body with single joint in coal were conducted using $PFC^{2D}$ software and especially the effects of joint length and joint angle on strength and failure characteristics in a rock-coal combined body were analyzed. The joint length and joint angle exhibit a deterioration effect on the strength and affect the failure modes. The deterioration effect of joint length of L on the strength can be neglected with a tiny variation at ${\alpha}$ of $0^{\circ}$ or $90^{\circ}$ between the loading direction and joint direction. While, the deterioration effect of L on strength are relatively large at ${\alpha}$ between $30^{\circ}$ and $60^{\circ}$. And the peak stress and peak strain decrease with the increase of L. Additionally, the deterioration effect of ${\alpha}$ on the strength becomes larger with the increase of L. With the increase of ${\alpha}$, the peak stress and peak strain first decrease and then increase, presenting "V-shaped" curves. And the peak stress and peak strain at ${\alpha}$ of $45^{\circ}$ are the smallest. Moreover, the failure mainly occurs within the coal and no apparent failure is observed for rock. At ${\alpha}$ between $30^{\circ}$ and $60^{\circ}$, the secondary shear cracks generated in or close to the joint tips, cause the structural instability failure of the combined body. Therefore, their failure models present as a shear failure along partial joint plane direction and partially cutting across the coal body or a shear failure along the joint plane direction. However, at ${\alpha}$ of $60^{\circ}$ and L of 10 mm, the "V-shaped" shear cracks cutting across the coal body cause its final failure. While crack nucleations at ${\alpha}$ of $0^{\circ}$ or $90^{\circ}$ are randomly distributed in the coal, the failure mode shows a V-shaped shear failure cutting across the coal body.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.539-542
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• 2002

Crack sealing is a maintenance procedure that is commonly used to reduce pavement degradation. If cracks in pavements are not sealed, surface water penetration can reduce the strength of the sub-base layers, which can result in increased deflections of the pavement. Reduced strength of the sub-base also accelerates the deterioration of the surface, due to development of greater cracking and potholes. Crack sealing is performed to reduce water and debris penetration, thereby helping to maintain pavement structural capacity and limiting future degradation. The process of sealing cracks in pavements is however dangerous, costly, and labor-intensive operation. Labor turnover and training are increasing problems related to crack sealing crews, and as traffic volumes increase. Automating crack sealing can reduce labor and road user costs, improve work quality, and decrease worker exposure to roadway hazards. The main objective of this research is to develop an automated system for sealing cracks in pavement. Extension of the algorithms and tools presented in this research is also recommended for future study.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.162-171
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• 2004

Crack sealing is a maintenance procedure that is commonly used to reduce pavement degradation. If cracks in pavements are not sealed, surface water penetration can reduce the strength of the sub-base layers, which can result in increased deflections of the pavement. Reduced strength of the sub-base also accelerates the deterioration of the surface, due to development of greater cracking and potholes. Crack sealing is performed to reduce water and debris penetration, thereby helping to maintain pavement structural capacity and limiting future degradation. The process of sealing cracks in pavements is however dangerous, costly, and labor-intensive operation. Labor turnover and training are increasing problems related to crack sealing crews, and as traffic volumes increase. Automating crack sealing can reduce labor and road user costs, improve work quality, and decrease worker exposure to roadway hazards. The main objective of this research is to develop an automated system for sealing cracks in pavement. Extension of the algorithms and tools presented in this research is also recommended for future study.

• Korean Journal of Radiology
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• v.24 no.3
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• pp.235-246
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• 2023

Objective: It is difficult to predict the treatment response of tissue after stereotactic radiosurgery (SRS) because radiation necrosis (RN) and tumor recurrence can coexist. Our study aimed to predict tumor recurrence, including the recurrence site, after SRS of brain metastasis by performing a longitudinal tumor habitat analysis. Materials and Methods: Two consecutive multiparametric MRI examinations were performed for 83 adults (mean age, 59.0 years; range, 27-82 years; 44 male and 39 female) with 103 SRS-treated brain metastases. Tumor habitats based on contrast-enhanced T1- and T2-weighted images (structural habitats) and those based on the apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) images (physiological habitats) were defined using k-means voxel-wise clustering. The reference standard was based on the pathology or Response Assessment in Neuro-Oncologycriteria for brain metastases (RANO-BM). The association between parameters of single-time or longitudinal tumor habitat and the time to recurrence and the site of recurrence were evaluated using the Cox proportional hazards regression analysis and Dice similarity coefficient, respectively. Results: The mean interval between the two MRI examinations was 99 days. The longitudinal analysis showed that an increase in the hypovascular cellular habitat (low ADC and low CBV) was associated with the risk of recurrence (hazard ratio [HR], 2.68; 95% confidence interval [CI], 1.46-4.91; P = 0.001). During the single-time analysis, a solid low-enhancing habitat (low T2 and low contrast-enhanced T1 signal) was associated with the risk of recurrence (HR, 1.54; 95% CI, 1.01-2.35; P = 0.045). A hypovascular cellular habitat was indicative of the future recurrence site (Dice similarity coefficient = 0.423). Conclusion: After SRS of brain metastases, an increased hypovascular cellular habitat observed using a longitudinal MRI analysis was associated with the risk of recurrence (i.e., treatment resistance) and was indicative of recurrence site. A tumor habitat analysis may help guide future treatments for patients with brain metastases.