• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.549-555
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• 2023

Jacking force loss management inside the PSC Box girder of a common high-speed railway is a very important feature in girder performance, and requires detailed management during the maintenance of the girder. This study aimed to analyze the timing of re-tension prediction of PSC Box girder based on the reduction level of the packing force inside the girder and the results of the tension loss measured without the train load test. As a result of predicting the timing of re-tension according to the level of tension reduction of the PSC Box Girder, the Jacking Force Loss curve was gently analyzed before the structure reached 17 years after confirmed completion, and 17 years later, it was found that the jacking force loss curve progressed rapidly. The results confirmed that the tension of the structure decreases with the service life increase, but considerably decreases as the structure ages. Therefore, more data and research on tension loss of facilities over 20 years are much required.

• The Journal of Bigdata
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• v.7 no.2
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• pp.139-152
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• 2022

Engineering's work area for plants is a technical area that directly affects productivity, performance, and quality throughout the lifecycle from planning, design, construction, operation and disposal. Using the different types of data that occur to make decisions is important not only in the subsequent process but also in terms of cyclical cost reduction. However, there is a lack of systems to manage and analyze these integrated data. In this paper, we developed a knowledge base-based plant engineering analysis platform that can manage and utilize data. The platform provides a knowledge base that preprocesses previously collected engineering data, and provides analysis and visualization to use it as reference data in AI models. Users can perform data analysis through the use of prior technology and accumulated knowledge through the platform and use visualization in decision-support and systematically manage construction that relied only on experience.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.334-334
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• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.132-133
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• 2021

In recent years, energy harvesting from natural sources and waste heat has been attracting more attention from researchers in response to ever-growing energy demands, high energy prices, and climate-change-mitigation purposes. It is also an important step towards future sustainable energy usages. In thermal dynamic cycles, expanders are playing as the most important equipment for waste heat recovery and energy harvesting as well. As a kind of expander, the bladeless turbine has a promising future and more widely using owning its advantages on relatively long life, good off-design performance, easy operation cleaning and maintenance, a simple structure, no blade corrosion, and low manufacturing costs. There are numerous studies about using the Tesla Turbine as a key technology for energy harvesting in a wide range of applications and conditions. They are presented to help identify technologies that have sufficient potential for applicating to our life and marine industrial engineering. This review paper, initially, presents an overview of current studies both theoretical and experimental of Tesla Turbine usage for waste heat recovery alongside its challenges and investigation on the effect of its configuration, working fluid selection as well. To conclude, future perspectives besides possible ways of transforming waste heat energy to electricity or work, which leads to circular energy, are discussed. The ambition of this paper is to act as a first-hand reference, through the well-defined possible directions, to the young researchers and senior scientists.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.155-161
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• 2023

In this paper, we present a WebRTC-based emergency video call system structure that builds a service system in a constant monitoring environment to increase the usability and stability of elevator emergency call devices. The proposed system provides a smooth call environment between the emergency call system in the elevator and maintenance managers in case of an emergency, performs rapid response processing to elevator emergency calls through monitoring of the target elevator, and handles any emergency calls that may occur in the physical space of the elevator. The purpose is to build an environment that can implement low-latency, real-time video call services of voice and video by overcoming the physical constraints required for video calls. To this end, we have established a service environment based on OpenAPI, which is currently used in various fields and its performance has been proven, and provides video calls and emergency situation dissemination through rapid messaging by providing low-latency call quality. The presented system structure will be able to provide a basis for expanding various functions and constructing a reliable service environment and intelligent model for the elevator system through combination with the elevator control panel and various devices.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.376-385
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• 2023

Fishing boat capsizing accidents account for more than half of all capsize accidents. These can occur for a variety of reasons, including inexperienced operation, bad weather, and poor maintenance. Due to the size and influence of the industry, technological complexity, and regional diversity, fishing ships are relatively under-researched compared to commercial ships. This study aimed to predict the rolling motion time series of fishing boats using an image-based deep learning model. Image-based deep learning can achieve high performance by learning various patterns in a time series. Three image-based deep learning models were used for this purpose: Xception, ResNet50, and CRNN. Xception and ResNet50 are composed of 177 and 184 layers, respectively, while CRNN is composed of 22 relatively thin layers. The experimental results showed that the Xception deep learning model recorded the lowest Symmetric mean absolute percentage error(sMAPE) of 0.04291 and Root Mean Squared Error(RMSE) of 0.0198. ResNet50 and CRNN recorded an RMSE of 0.0217 and 0.022, respectively. This confirms that the models with relatively deeper layers had higher accuracy.

• Convergence Security Journal
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• v.24 no.1
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• pp.35-42
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• 2024

Multi-tenancy architecture plays a crucial role in cloud-based services and applications, and data isolation within such environments has emerged as a significant security challenge. This paper investigates various data isolation methods including schema-based isolation, logical isolation, and physical isolation, and compares their respective advantages and disadvantages. It evaluates the practical application and effectiveness of these data isolation methods, proposing security considerations and selection criteria for data isolation in the development of multi-tenant websites. This paper offers important guidance for developers, architects, and system administrators aiming to enhance data security in multi-tenancy environments. It suggests a foundational framework for the design and implementation of efficient and secure multi-tenant websites. Additionally, it provides insights into how the choice of data isolation methods impacts system performance, scalability, maintenance ease, and overall security, exploring ways to improve the security and stability of multi-tenant systems.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.2
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• pp.155-162
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• 2023

In nuclear power plants, the flow rate information is a major indicator of the performance of rotating equipment such as pumps, and is a very important one required for facility operation and maintenance. To measure a flow rate, various types of methods have been developed and used. Among them, the differential pressure type using orifice and the direct doppler type using ultrasonic waves are the most commonly used. However, these flow rate measurement methods have limitations in installation, conditions and status of the measuring part, etc. To solve this problem, we have studied a new technique for measuring flow rate from scratch. In this paper, we have devised a technique to estimate the flow rate using an average moving velocity of large-scale eddy in turbulence that occurs in the piping flow field. The velocity of the large-scale eddy can be measured using the pressure fluctuation signals on the inner surface of the pipe. To estimate the flow rate, at first a cross-correlation function is applied to the two pressure fluctuation signals located at different positions in the down stream for calculating the time delay between the moving eddies. In order to validate the proposed flow rate estimation method, CFD analyses for the internal turbulence flow in pipe are conducted with a fixed flow condition, where the pressure fluctuation signals on the pipe inner surface are simulated. And then the average flow velocity of the large scale eddy is to be estimated. The estimated flow velocity is turned out to be similar to the fixed (known) flow rate.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.23-34
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• 2024

This research aims to assess the flexural bonding efficacy of polymer-cement composites(PCCs) in mending cracks within reinforced concrete(RC) structures. The study involved infilling PCCs into cement mortar cracks of varying dimensions, followed by evaluations of enhancements in flexural adhesion and strength. The findings indicate that the flexural bond performance of PCCs in crack repair is influenced by the cement type, polymer dispersion, and the polymer-to-binder ratio. Specifically, the use of ultra-high early strength cement combined with silica fume resulted in an up to 19.0% improvement in flexural bond strength compared to the application of ordinary Portland cement with silica fume. It was observed that the augmentation in flexural strength of cement mortar filled with PCCs was significantly more dependent on the depth of the crack rather than the width. Furthermore, PCCs not only acted as repair agents but also as reinforcement materials, enhancing the flexural strength to a certain extent. Consequently, this study concludes that PCCs formulated with ultra-high early strength cement, various polymer dispersions, silica fume, and a high polymer-to-binder ratio ranging from 60% to 80% are highly effective as maintenance materials for crack filling in practical settings.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.35-42
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• 2024

This research explores the potential of methyl methacrylate(MMA) as a material for road repair applications. It specifically examines two MMA formulations, referred to as type A and type B, in relation to their performance on concrete substrates. The evaluation criteria included drying time, tensile bond strength, and resistance to alkali. The condition of the substrate surface was varied across three curing environments: constant temperature and humidity(R), immersion in water(W), and immersion in water with chloride ions(N). The findings indicate that type B MMA exhibits a quicker drying time and superior resistance to alkali compared to type A. While type A demonstrated greater tensile bond strength, it failed to maintain adhesion with the concrete base. Based on the parameters tested in this study, type B MMA emerges as the more favorable option for road repair contexts. Nonetheless, the study underscores the necessity for additional testing on asphalt substrates to fully assess the material's durability and applicability for long-term road maintenance.