• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.6
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• pp.35-43
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• 2017

The minimum reinforcement ratio is an important design factor to prevent a brittle failure in RC flexural members. A minimum reinforcement ratio is presented by assuming an effective depth of cross-section and moment arm lever in CDC and KHBDC. In this study, it suggests that a rational method for minimum reinforcement ratio is calculated by material model and force equilibrium. As results, a minimum reinforcement ratio using a p-r curve in KHBDC is evaluated about 52~80% of recent design code's value and it induces an economical design. And also, a ductility capacity in case of placing this minimum reinforcement amount is evaluated about 89% of recent design code's value, but ductility in a member is 7 or more, so it has a sufficient ductility capacity. Therefore, it is judged that a minimum reinforcement ratio using p-r curve has a theoretical rationality, safety and economy in a flexural member design.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.2
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• pp.40-48
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• 2016

To observe the rail-slab interaction in continuous welded railway(CWR) bridge when earthquake occurs, additional axial rail stresses and relative longitudinal displacements between rail and bridge deck were calculated with input of various load combinations and 3 different types of seismic loads to an analytical model. As results of analysis, it can be found that standard response spectrum proposed by Korea Rail(KR) network authority for earthquake design showed less additional axial rail stresses than allowable levels, but greater relative longitudinal displacement between rail and bridge deck, which means that adjustment of relative longitudinal displacement within a standard level is much more difficult than axial train stress. Additionally, if a large-scaled earthquake as occurred at Kobe, Japan comes up, then both of additional axial rail stress and relative displacement in rail-bridge deck may exceed allowable levels, which indicates to make proper design guides against sudden earthquake occurrence.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.4
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• pp.306-313
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• 2011

The damage tolerance analysis is required to guarantee the structural safety and the reliability for aircraft components. The damage tolerance method, which evaluate the life considering the initial crack, considers a fatigue design model of the aircraft main structure. The fatigue crack growth life should be calculated in damage tolerance analysis and the inspection time to define the replacement cycle. In this paper, the damage tolerance analysis is performed for a turbine wheel which has complex geometry. The equation of the stress intensity factor for complex geometry is hard to know, so that they are usually processed by finite element analysis which takes long time. To solve this problem, the stress intensity factors at specified crack are obtained by the FEA and the crack growth life is evaluated using the surrogate model which is generated by the regression analysis of the FEA data. From the results, the efficiency of the crack growth life calculation and the damage tolerance analysis could be increased by taking the surrogate model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.57-64
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• 2017

In order to reduce damages to major railroad components, which have the potential to cause interruptions to railroad services and safety accidents and to generate unnecessary maintenance costs, the development of rolling stock maintenance technology is switching from preventive maintenance based on the inspection period to predictive maintenance technology, led by advanced countries. Furthermore, to enhance trust in accordance with the speedup of system and reduce maintenances cost simultaneously, the demand for fault diagnosis and prognostic health management technology is increasing. The objective of this paper is to propose a highly reliable learning model using various machine learning algorithms that can be applied to critical rolling stock components. This paper presents a model for railway rolling stock component fault diagnosis and conducts a mechanical failure diagnosis of motor components by applying the machine learning technique in order to ensure efficient maintenance support along with a data preprocessing plan for component fault diagnosis. This paper first defines a failure diagnosis model for rolling stock components. Function-based algorithms ANFIS and SMO were used as machine learning techniques for generating the failure diagnosis model. Two tree-based algorithms, RadomForest and CART, were also employed. In order to evaluate the performance of the algorithms to be used for diagnosing failures in motors as a critical railroad component, an experiment was carried out on 2 data sets with different classes (includes 6 classes and 3 class levels). According to the results of the experiment, the random forest algorithm, a tree-based machine learning technique, showed the best performance.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.33-39
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• 2024

Inspecting cracks to determine a structure's condition is crucial for accurate safety diagnosis. However, visual crack inspection methods can be subjective and are dependent on field conditions, thereby resulting in low reliability. To address this issue, this study automates the detection of concrete cracks in image data using ResNet, FPN, and the Mask R-CNN components as the backbone, neck, and head of a convolutional neural network. The performance of the proposed model is analyzed using the intersection over the union (IoU). The experimental dataset contained 1,203 images divided into training (70%), validation (20%), and testing (10%) sets. The model achieved an IoU value of 95.83% for testing, and there were no cases where the crack was not detected. These findings demonstrate that the proposed model realized highly accurate detection of concrete cracks in image data.

• Journal of Food Hygiene and Safety
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• v.28 no.3
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• pp.217-221
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• 2013

This study developed predictive models for the kinetic behavior of Staphylococcus aureus on processed cheeses. Mozzarella slice cheese and cheddar slice cheese were inoculated with 0.1 ml of a S. aureus strain mixture (ATCC13565, ATCC14458, ATCC23235, ATCC27664, and NCCP10826). The inoculated samples were then stored at $4^{\circ}C$ (1440 h), $15^{\circ}C$ (288 h), $25^{\circ}C$ (72 h), and $30^{\circ}C$ (48 h), and the growth of all bacteria and of S. aureus were enumerated on tryptic soy agar and mannitol salt agar, respectively. The Baranyi model was fitted to the growth data of S. aureus to calculate growth rate (${\mu}_{max}$; ${\log}CFU{\cdot}g^{-1}{\cdot}h^{-1}$), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The growth parameters were further analyzed using the square root model as a function of temperature. The model performance was validated with observed data, and the root mean square error (RMSE) was calculated. At $4^{\circ}C$, S. aureus cell growth was not observed on either processed cheese, but S. aureus growth on the mozzarella and cheddar cheeses was observed at $15^{\circ}C$, $25^{\circ}C$, and $30^{\circ}C$. The ${\mu}_{max}$ values increased, but LPD values decreased as storage temperature increased. In addition, the developed models showed acceptable performance (RMSE = 0.3500-0.5344). This result indicates that the developed kinetic model should be useful in describing the growth pattern of S. aureus in processed cheeses.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.405-412
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• 2019

SOLAS requires that ECDIS be installed on ships of more than 500 gross tonnage engaged in international navigation until the first inspection arriving after July 1, 2018. Several accidents related to the use of ECDIS have occurred with its installation as a new major navigation instrument. The 12 incident reports issued by MAIB, BSU, BEAmer, DMAIB, and DSB were analyzed, and the cause of accident was determined to be related to the operation of the navigator and the ECDIS system. The text was analyzed using the R-program to quantitatively analyze words related to the cause of the accident. We used text mining techniques such as Wordcloud, Wordnetwork and Wordweight to represent the importance of words according to their frequency of derivation. Wordcloud uses the N-gram model as a way of expressing the frequency of used words in cloud form. As a result of the uni-gram analysis of the N-gram model, ECDIS words were obtained the most, and the bi-gram analysis results showed that the word "Safety Contour" was used most frequently. Based on the bi-gram analysis, the causative words are classified into the officer and the ECDIS system, and the related words are represented by Wordnetwork. Finally, the related words with the of icer and the ECDIS system were composed of word corpus, and Wordweight was applied to analyze the change in corpus frequency by year. As a result of analyzing the tendency of corpus variation with the trend line graph, more recently, the corpus of the officer has decreased, and conversely, the corpus of the ECDIS system is gradually increasing.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.128-138
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• 2022

In this study, in order to apply ultra-high-strength concrete beams of 100 MPa or more manufactured by centrifugal molding as the superstructure of the avalanche tunnel, the purpose is to verify the structural safety of the corner rigid joint in which the centrifugal molded beam is integrated with the substructure, which is the negative moment area. A full-size specimen was manufactured, and loading tests and analysis studies were performed. In order to expect the same effect that the maximum moment occurs in the corner joint part of the upper slab end when the standard model of the avalanche tunnel is designed with a load combination according to the specification, a modified cantilever type structural model specimen was manufactured and the corner rigid joint was fixedly connected. A study was performed to determine the performance of the method and the optimal connection construction method. The test results demonstrated that the proposed connection system outperforms others. Despite having differences in joint connection construction type, stable flexural behavior was shown in all the tested specimens. The proposed method also outperformed the behavior of centrifugally formed beams and upper slabs. The behavior of the corner rigid joint analysis model according to the F.E. analysis showed slightly greater stiffness compared to the results of the experiment, but the overall behavior was almost similar. Therefore, there is no structural problem in the construction of the corner rigid joint between the centrifugally formed beam and the wall developed in this study.

• Journal of the Korea institute for structural maintenance and inspection
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• v.21 no.6
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• pp.185-195
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• 2017

In recent years, unexpected bridge fire accidents have increased because of augmenting the number of traffic volumes and hazardous materials by the increment in traffics and distribution business. Furthermore, in accordance with the effort of using the under space of bridges, the ratio of occupied by combustible materials like oil tanker or lorry has been increased. As a result, the occurrence of bridge fire has been growing drastically. In order to mitigate the accident of bridge fire, risk assessment of bridge fire has been studied, however, practical risk models considering safety from users' viewpoints were scarce. This study represented quantitative risk assessment model applicable to national road bridges in Korea. The primary factors with significant impacts on bridge fire accidents was chosen such as clearance height, materials of bridges, arrival time of fire truck and fire intensity. The selected factors were used for Fire Dynamics Simulation (FDS) and the peak temperature calculated by FDS in accordance with the fire duration and fire intensity. The risk assessment model in bridge fire reflected the FDS analysis results, the fire damage criteria, and the grade of fire truck arrival time was established. Response plans for bridge fire accidents according to the risk assessment output has been discussed. Lastly, distances between bridges and fire stations were calculated by GIS network analysis. Based on the suggested assessment model and methodology, sample bridges were selected and graded for the risk assessment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.595-601
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• 2020

During the safety inspection of nitrocellulose-made explosive containers stored for more than 10 years, cracks were found in the containers. Therefore, a failure cause analysis test was performed. First, the cause of failure through the failure tree analysis was conducted to select the factors that influenced failure. The changes in the properties of the container caused by the acceleration of the reaction were found to be the cause of the failure by confirming the influence on the environment and internal/external factors that may occur during storage. To confirm this, environmental tests, such as thermal shock test and vacuum thermal stability test, were performed using a naturally aged container to analyze the cause of failure, and an accelerated aging test was performed to reproduce the failure. Through this, the chemical reaction was accelerated by heat and charge, as in the result of the fault tree analysis, and it was confirmed that the physical properties of the container were changed. In addition, the service life of the container was estimated using the Arrhenius model for the storage life due to thermal aging.