• Journal of the Korea Safety Management & Science
• /
• v.23 no.2
• /
• pp.31-36
• /
• 2021

This study aims to review observational methods for assessing postural loads such as OWAS, RULA and REBA, and to compare them, based on the literature survey. The literature was searched through academic database of ScienceDirect using the key words of observational methods, OWAS, RULA and REBA. The results exhibited that of the thee methods, RULA was cited in the literature and applied to manufacturing industries the most frequently. Although it has been known that RULA is appropriate for assessing upper body postures, it has been applied to healthcare and social work activities, agriculture, forestry, fishing, construction, mining and quarrying, which require unstable lower limb postures. The countries where more number of relevant studies have been carried out were USA, India, Brazil, UK, etc. It was recommended that of the three techniques, RULA may be better for assessing postural loads, because it evaluated postural loads more highly, irrespective of industry, work type and lower limb postures, and its assessment results had higher agreement rate with experts' assessments than those of OWAS and REBA. It is expected that the results of this study will be used as a guideline for selecting an appropriate observational method.

• Journal of the Architectural Institute of Korea Planning & Design
• /
• v.35 no.6
• /
• pp.39-46
• /
• 2019

In the 21st century, medical facility projects are required to operate appropriate digital technologies as the development of technology and the interests of various participants become more complex. In order for architects to successfully lead negotiations among various stakeholder groups, it is necessary to plan for effective communication through appropriate design reflecting their opinions and coordination of conflicts. For this purpose, building information modeling (BIM), which is a method of designing based on knowledge information related to medical facilities in the building database, can respond to change of order promptly and minimizes the occurrence of design errors can do. Recently, BIM technology and cloud computing technology in ICT have been combined and research on cloud BIM has been actively carried out. The use of cloud computing technology in BIM-based healthcare facility projects can effectively support decision making among project participants and has the advantage of sharing and collaborating on various forms of information generated during the design process, regardless of location and time. Therefore, the purpose of this study is to build of system that can support the design of medical facility using cloud computing technology in BIM.

• Korea Trade Review
• /
• v.44 no.4
• /
• pp.87-100
• /
• 2019

A country's participation in international technical standards development directly relates to its trade competitiveness. Many countries adopt international standards or influence their development process through the ISO/IEC. This study applies the ABCD Model to assess such activities through a constructed ITS index, not only in terms of 'level' of contribution but also in terms of 'process' participation that can give important implications related to the future potential influence of countries in standards development. Having examined seven countries, Korea showed the lowest score implying the need to enhance its performance in both 'international standards adoption' and 'internationalization of domestic standards'. Korea needs to more actively participate in currently on-going standards development processes, establish more offices that improve accuracy in the development, and consider participating in additional committees where domestic interests may potentially be at stake. Although KATS has improved greatly in regards to its relevant activities and database construction, a more active and specific plan must be made to allow its efforts to successfully influence Korea in international standards development. Confronted with strong challenges from directly competing countries in trade like China and Japan that showed better ITS scores, there is a need for Korea to step up its research and participation in this field.

• Steel and Composite Structures
• /
• v.38 no.6
• /
• pp.637-656
• /
• 2021

The component-based method is widely used to analyze the initial stiffness of joint in steel structures. In this study, an analytical component model for determining the column face stiffness of square or rectangular hollow section (SHS/RHS) subjected to tension was established, focusing on endplate connections. Equations for calculating the stiffness of the SHS/RHS column face in bending were derived through regression analysis using numerical results obtained from a finite element model database. Because the presence of bolt holes decreased the bending stiffness of the column face, this effect was calculated using a novel plate-spring-based model through numerical analysis. The developed component model was first applied to predict the bending stiffness of the SHS column face determined through tests. Furthermore, this model was incorporated into the component-based method with other effective components, e.g., bolts under tension, to determine the tensile stiffness of the T-stub connections, which connects the SHS column, and the initial rotational stiffness of the joints. A comparison between the model predictions, test data, and numerical results confirms that the proposed model shows satisfactory accuracy in evaluating the bending stiffness of SHS column faces.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.3
• /
• pp.148-154
• /
• 2021

We propose the AI Smart Factory Model for integrated management of production processes in this paper .It is an integrated platform system for the production of food packaging containers, consisting of a platform system for the main producer, one or more production partner platform systems, and one or more raw material partner platform systems while each subsystem of the three systems consists of an integrated storage server platform that can be expanded infinitely with flexible systems that can extend client PCs and main servers according to size and integrated management of overall raw materials and production-related information. The hardware collects production site information in real time by using various equipment such as PLCs, on-site PCs, barcode printers, and wireless APs at the production site. MES and e-SCM data are stored in the cloud database server to ensure security and high availability of data, and accumulated as big data. It was built based on the project focused on dissemination and diffusion of the smart factory construction, advancement, and easy maintenance system promoted by the Ministry of SMEs and Startups to enhance the competitiveness of small and medium-sized enterprises (SMEs) manufacturing sites while we plan to propose this model in the paper to state funding projects for SMEs.

• Geomechanics and Engineering
• /
• v.30 no.2
• /
• pp.107-121
• /
• 2022

Coal pillar assessment is of broad importance to underground engineering structure, as the pillar failure can lead to enormous disasters. Because of the highly non-linear correlation between the pillar failure and its influential attributes, conventional forecasting techniques cannot generate accurate outcomes. To approximate the complex behavior of coal pillar, this paper elucidates a new idea to forecast the underground coal pillar stability using combined unsupervised-supervised learning. In order to build a database of the study, a total of 90 patterns of pillar cases were collected from authentic engineering structures. A state-of-the art feature depletion method, t-distribution symmetric neighbor embedding (t-SNE) has been employed to reduce significance of actual data features. Consequently, an unsupervised machine learning technique K-mean clustering was followed to reassign the t-SNE dimensionality reduced data in order to compute the relative class of coal pillar cases. Following that, the reassign dataset was divided into two parts: 70 percent for training dataset and 30 percent for testing dataset, respectively. The accuracy of the predicted data was then examined using support vector classifier (SVC) model performance measures such as precision, recall, and f₁-score. As a result, the proposed model can be employed for properly predicting the pillar failure class in a variety of underground rock engineering projects.

• Nuclear Engineering and Technology
• /
• v.54 no.4
• /
• pp.1363-1373
• /
• 2022

The recent seismic events that occurred in South Korea have increased the interest in the re-evaluation of the seismic capacity of nuclear power plant (NPP) equipment, which is often conservatively estimated. To date, various approaches-including the Bayesian method proposed by the United States (US) Electric Power Research Institute -have been developed to quantify the seismic capacity of NPP equipment. Among these, the Bayesian approach has advantages in accounting for both prior knowledge and new information to update the probabilistic distribution of seismic capacity. However, data availability and region-specific issues exist in applying this Bayesian approach to Korean NPP equipment. Therefore, this paper proposes to construct an earthquake experience database by combining available earthquake records at Korean NPP sites and the general location of equipment within NPPs. Also, for the better representation of the seismic demand of Korean earthquake datasets, which have distinct seismic characteristics from those of the US at a high-frequency range, a broadband frequency range optimization is suggested. The proposed data construction and seismic demand optimization method for seismic capacity re-evaluation are demonstrated and tested on a 480 V motor control center of a South Korea NPP.

• Advances in concrete construction
• /
• v.14 no.1
• /
• pp.15-34
• /
• 2022

The use of waste rubber in concrete can reduce natural aggregate consumption and improve some technical properties of concrete. Although there are several equations for estimating the mechanical properties of concrete containing waste rubber, limited numbers of machine learning-based models have been proposed to predict the mechanical properties of rubbercrete. In this study, an extensive database of the mechanical properties of rubbercrete was gathered from a comprehensive survey of the literature. To model the mechanical properties of rubbercrete, M5P tree and linear gene expression programming (LGEP) methods as two machine learning techniques were employed to achieve reliable mathematical equations. Two procedures of input variable selection were considered in this study. The crucial component ratios of rubbercrete and concrete age were assumed as the input variables in the first procedure. In contrast, the volumes of the coarse and fine waste rubber and the compressive strength of concrete without waste rubber were considered the second procedure of the input variables. The results show that the models obtained by LGEP are more accurate than those achieved by the M5P model tree and existing traditional equations. Besides, the volumes of the coarse and fine waste rubber and the compressive strength of concrete without waste rubber are better predictors of the mechanical properties of rubbercrete compared to the first procedure of input variable selection.

• Journal of Korea Society of Industrial Information Systems
• /
• v.15 no.1
• /
• pp.25-36
• /
• 2010

Recently, digitizing technologies for conservation and restoration of tangible intangible cultural properties are coming into spotlight. Because cultural properties are easy to be lost and damaged over the years, After construction of cultural assets database we can reconstruct the cultural asset making use of the reverse engineering when needed, and implement digital contents such as computer graphics, 3D virtural realization, hologram, etc. So in this paper, we scrutinize visual and technical factors occurring in different types of digital restoration of cultural properties, and present problems and improvements, and try to research technological prowess and visual mechanism.

• Nuclear Engineering and Technology
• /
• v.55 no.9
• /
• pp.3164-3182
• /
• 2023

The CRUD on the fuel cladding under the pressurized water reactor (PWR) operating condition causes several issues. The CRUD can act as thermal resistance and increases the local cladding temperature which accelerate the corrosion process. The hideout of boron inside the CRUD results in axial offset anomaly and reduces the plant's shutdown margin. Recently, there are efforts to revise the acceptance criteria of emergency core cooling systems (ECCS), and additionally require the modeling of the thermal resistance effect of the CRUD during the performance analysis. There is an urgent need for the evaluation of the effect of the CRUD deposition on the cladding heat transfer under PWR operating conditions, but the experimental database is very limited. The experimental facility called DISNY was designed and constructed to analyze the CRUD-related multi-physical phenomena, and the performance analysis of the constructed DISNY facility was conducted. The thermal-hydraulic and water chemistry conditions to simulate the CRUD growth under PWR operating conditions were established. The design characteristics and feasibility of the DISNY facility were validated by the MARS-KS code analysis and separate performance tests. In the current study, detailed design features, design validation results, and future utilization plans of the proposed DISNY facility are presented.