• Journal of the Korean Society of Safety
• /
• v.12 no.4
• /
• pp.201-208
• /
• 1997

In order to improve the safety of nuclear power plant, we performed a human factors review for the CFMS(Critical Function Monitoring system) design of nuclear power plant. Three works were performed in this study. In first work, we developed human factors engineering program plan(HFEPP) and human factors engineering verification and validation plan (HFE-V & V plan) to effectively perform CFMS design and review. In second work, we identified human engineering discrepancies(HEDs) for CFMS design through human factors design review and proposed those resolutions. In the third work, we developed the evaluation and management methodology for identified KEDs. Methodology developed in this study can be used in other complex system as well as in CFMS design review.

• Journal of the Korean Society of Industry Convergence
• /
• v.22 no.5
• /
• pp.519-527
• /
• 2019

This study was conducted to present useful information on the utilization and productivity analysis of laminated modular multi-family housing. To this end, the process of site installation was investigated and analyzed through a prior study, and the monitoring survey was conducted through the site installation case of an stacked multi-family housing. Based on the above, the results of productivity analysis using the web-cyclone technique were also presented. However, the site installation process has limitations on generalisation because the process is not the same for each construction company, and also limits that require verification through application in the actual site of the web-cyclone model presented in this study.

• Proceedings of the KSR Conference
• /
• 2008.11b
• /
• pp.2040-2044
• /
• 2008

Recently, many safety measures are developing for the prevention of human error, which is main factors of railway accident. For the efficient management of human factors, many expertise on design, conditions, safety culture and staffing are required. But current safety management activities on safety critical works are focused on training, due to the limited resource and information. In order to establish railway human factors management, a systematic review model is required. Based on system engineering and nuclear industry model, a program review model is proposed in this study. The model includes operating experience review, task analysis, staffing and qualification, human reliability analysis, huma-system interface design, procedure development, training program, verification and validation, implementation and monitoring. Results can be applied for the review of safety measures relating to human factors.

• Nuclear Engineering and Technology
• /
• v.53 no.3
• /
• pp.888-893
• /
• 2021

The International Atomic Energy Agency has developed a tomographic imaging system for accomplishing the total fuel rod-by-rod verification time of fuel assemblies within the order of 1-2 h, however, there are still limitations for some fuel types. The aim of this study is to develop a deep learning-based denoising process resulting in increasing the tomographic image acquisition speed of fuel assembly compared to the conventional techniques. Convolutional AutoEncoder (CAE) was employed for denoising the low-quality images reconstructed by filtered back-projection (FBP) algorithm. The image data set was constructed by the Monte Carlo method with the FBP and ground truth (GT) images for 511 patterns of missing fuel rods. The de-noising performance of the CAE model was evaluated by comparing the pixel-by-pixel subtracted images between the GT and FBP images and the GT and CAE images; the average differences of the pixel values for the sample image 1, 2, and 3 were 7.7%, 28.0% and 44.7% for the FBP images, and 0.5%, 1.4% and 1.9% for the predicted image, respectively. Even for the FBP images not discriminable the source patterns, the CAE model could successfully estimate the patterns similarly with the GT image.

• Journal of Navigation and Port Research
• /
• v.45 no.5
• /
• pp.231-237
• /
• 2021

Enhancing the performance of maritime wireless communication has been highlighted by the issue of cell planning in the sea area because of lack of an appropriate Propagation Loss Model (PLM). To resolve the cell planning issue in vast sea areas, it was essential to develop the (PLM) matching the intended sea area. However, there were considerable gaps between the prediction of legacy PLMs and field measurement in propagation loss and there was a need to develop the adjusted PLM (A-PLM). Therefore, cell planning was performed on this adjusted model, including modification of the base station's location, altitude, and antenna azimuth to meet the quality objectives. Furthermore, in order to verify the availability of the cell planning, Communication Service Quality Monitoring System (CS-QMS) was developed in the LTE-Maritime project to collect LTE signal quality information from the onboard equipment at regular intervals and to ensure that the service quality was high enough to satisfy the goals in each designated grid. As a result of verification, the success rate of RSRP was 95.7% for the intensive management zone (IMZ) and 96.4% for the interested zone (IZ), respectively.

• Journal of the Korea Safety Management & Science
• /
• v.25 no.4
• /
• pp.87-94
• /
• 2023

This study analyzed and identified various causes of caustic alarms of 163 fire detectors that occurred from January 2019 to December 2021 at domestic semiconductor manufacturing plants equipped with about 30,000 fire detectors, and proposed a new non-fire prevention cause investigation plan by applying the NFPA 921 scientific methodology. The results of the study are as follows. First, in terms of necessary recognition and problem definition, an analog detector and an integrated monitoring system were proposed to quickly determine the location and installation space information of the fire detector. Second, in order to prevent speculative causes and errors in various analyses in terms of data analysis and hypothesis establishment, non-fire reports were classified into five by factor and defined, and the causes of occurrence by factor were classified and proposed. Finally, in terms of hypothesis verification and final hypothesis selection, a non-fire prevention improvement termination process and a final hypothesis verification sheet were proposed to prevent the cause from causing re-error.

• Korean Journal of Computational Design and Engineering
• /
• v.20 no.4
• /
• pp.420-430
• /
• 2015

Operator Training Simulators (OTSs) provide macroscopic training environment for plant operation. They are equipped with simulation systems for the emulation of remote monitoring and controlling operations. OTSs typically provide 2D block diagram-based graphic user interface (GUI) and connect to process simulation tools. However, process modeling for OTSs is a difficult task. Furthermore, conventional OTSs do not provide real plant field information since they are based on 2D human machine interface (HMI). In order to overcome the limitation of OTSs, we propose a new type of plant training system. This system has the capability required for collaborative training between operators and field workers. In addition, the system provides 3D virtual training environment such that field workers feel like they are in real plant site. For this, we designed system architecture and developed essential functions for the system. For the verification of the proposed system design, we implemented a prototype training system and performed experiments of collaborative training between one operator and two field workers with the prototype system.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.5
• /
• pp.1643-1653
• /
• 2014

This paper presents the design and implementation of a wind-solar hybrid power system for LED street lighting and an isolated power system. The proposed system consists of photovoltaic modules, a wind generator, a storage system (battery), LED lighting, and the controller, which can manage the power and system operation. This controller has the functions of maximum power point tracking (MPPT) for the wind and solar power, effective charging/discharging for the storage system, LED dimming control for saving energy, and remote data logging for monitoring the performance and maintenance. The proposed system was analyzed in regard to the operation status of the hybrid input power and the battery voltage using a PSIM simulation. In addition, the characteristics of the proposed system's output were analyzed through experimental verification. A prototype was also developed which uses 300[W] of wind power, 200[W] of solar power, 60[W] LED lighting, and a 24[V]/80[Ah] battery. The control system principles and design scheme of the hardware and software are presented.

• Journal of the Korean Institute of Gas
• /
• v.24 no.5
• /
• pp.10-19
• /
• 2020

Valve leak accidents in petrochemistry plants and gas utilities cause human and property damage. The main reason why happen gas inhalation, poisoning, fire and explosion accidents is gas valve leakage. To prevent gas leakage, inspectors check the facilities in the field. And they are at risk of gas leak accidents. So we applied IoT-based risk assessment, monitoring and automatic control system. It can detect both internal and external gas leakage, do real-time monitoring of industrial valve in the plant by using hybrid sensor. As the new safety management system for industrial valve is developed, it needs method to evaluate device performance and environmental components for the system. This study is about development of method to verify performance of the explosion-proofed hybrid sensing system include gas detector and optical fiber sensor supporting wire and wireless communication.

• Journal of the Korean Institute of Gas
• /
• v.18 no.3
• /
• pp.53-59
• /
• 2014

In this study, we suggest a system to build the monitoring model for compressed natural gas (CNG) stations, operated in only non-stationary modes, and perform the real-time monitoring and the abnormality diagnosis using principal component analysis (PCA) that is suitable for processing large amounts of multi-dimensional data among multivariate statistical analysis methods. We build the model by the calculation of the new characteristic variables, called as the major components, finding the factors representing the trend of process operation, or a combination of variables among 7 pressure sensor data and 5 temperature sensor data collected from a CNG station at every second. The real-time monitoring is performed reflecting the data of process operation measured in real-time against the built model. As a result of conducting the test of monitoring in order to improve the accuracy of the system and verification, all data in the normal operation were distinguished as normal. The cause of abnormality could be refined, when abnormality was detected successfully, by tracking the variables out of the score plot.