• Journal of Korea Foundry Society
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• v.41 no.6
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• pp.550-557
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• 2021

With the advent of the fourth industrial revolution, the interest in the internet of things (IoT) in manufacturing is growing, even at foundries. There are several types of process data that can be automatically collected at a foundry, but considerable amounts of process data are still managed based on handwriting for reasons such as the limited functions of outdated production facilities and process design based on operator know-how. In particular, despite recognizing the importance of converting process data into big data, many companies have difficulty adopting these steps willingly due to the burden of system construction costs. In this study, the field applicability of IoT-based devices was examined by manufacturing devices and applying them directly to the site of a centrifugal foundry. For the centrifugal casting process, the temperature and humidity of the working site, the molten metal temperature, and mold rotation speed were selected as process parameters to be collected. The sensors were selected in consideration of the detailed product specifications and cost required for each process parameter, and the circuit was configured using a NodeMCU board capable of wireless communication for IoT-based devices. After designing the circuit, PCB boards were prepared for each parameter, and each device was installed on site considering the working environment. After the on-site installation process, it was confirmed that the level of satisfaction with the safety of the workers and the efficiency of process management increased. Also, it is expected that it will be possible to link process data and quality data in the future, if process parameters are continuously collected. The IoT-based device designed in this study has adequate reliability at a low cast, meaning that the application of this technique can be considered as a cornerstone of data collecting at foundries.

• Tunnel and Underground Space
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• v.32 no.1
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• pp.78-92
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• 2022

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.

• Journal of the Korean GEO-environmental Society
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• v.22 no.6
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• pp.5-15
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• 2021

One of the construction methods applied as a pier foundation type is a single type cast-in-place pile. In applying a pile bent system as a foundation type, the main concern in designing can be said to secure the lateral bearing capacity of pile structure in system. In addition, to increase the rigidity of the pile structure, a method of increasing the lateral bearing capacity by reinforcing the pile structure with a casing has been used. However, although the reinforcing effect and appropriate reinforcing length of casing may vary depending on the soil conditions, there is insufficient studies on this, and for this reason, the entire pile structure in a pile bent system is reinforced with a casing, in the field. In addition, if the length of the entire pile is reinforced with a casing, it may lead to delays in construction and increase in construction costs. That is, in order to more effectively reinforce the pile structure with a casing, it is necessary to study the lateral bearing characteristics of the reinforced pile structure in system. And it should be determined the appropriate reinforcing length of the casing from the evaluated bearing characteristics. Therefore, in this study, the lateral bearing characteristics of piles applied with the reinforcing length of casing for each condition were evaluated through a numerical analysis. And, based on the analysis results, the appropriate reinforcing length of casing was proposed. As a result of the study, it was found that in order to effectively increase the lateral bearing capacity of pile structure, the reinforcing length of casing should be applied twice the influence range of the bending behavior of the pile, 1/β.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.689-700
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• 2022

Layout work for building structures requires high precision to construct structural elements in the correct location. However, the accuracy and precision of the layout position are affected by the worker's skill, and productivity can be reduced when there is information loss and error. To solve this problem, it is necessary to automate the overall layout operation and introduce information technology, and layout process automation using construction robots can be an effective means of doing this. This study develops a prototype of an automated layout robot for building structures and evaluates its basic performance. The developed robot is largely composed of driving, marking, sensing, and control units, and is designed to enable various driving methods, and movement and rotation of the marking unit in consideration of the environment on structural work. The driving and marking performance experiments showed satisfactory performance in terms of driving distance error and marking quality, while the need for improvement in terms of some driving methods and marking precision was confirmed. Based on the results of this study, we intend to continuously improve the robot's performance and establish an automation system for overall layout work process.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.398-406
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• 2022

The outer membrane of Gram-negative bacteria is the outermost layer of cellular environment in which numerous biophysical and biochemical processes are in action sustaining viability. Advances in cell engineering enable modification of bacterial genetic information that subsequently alters membrane physiology to adapt bacteria to specific purposes. Surface display of a functional molecule on the outer membranes is one of strategies that directs host cells to respond to a specific extracellular matter or stimulus. While intracellular expression of a functional peptide or protein fused to a membrane-anchoring motif is commonly practiced for surface display, the method is not readily applicable to exogenous or large proteins inexpressible in bacteria. Chemical conjugation at reactive groups naturally occurring on the membrane might be an alternative, but often compromises fitness due to non-specific modification of essential components. Herein, we demonstrated two distinct approaches that enable site-specific decoration of the outer membrane with a fluorescent agent in Escherichia coli. An unnatural amino acid genetically incorporated in a surface-exposed peptide could act as a chemoselective handle for bioorthogonal dye labeling. A surface-displayed α-helical domain originating from a part of a selected heterodimeric coiled-coil complex could recruit and anchor a green fluorescent protein tagged with a complementary α-helical domain to the membrane surface in a site- and hetero-specific manner. These methods hold a promise as on-demand tools to confer new functionalities on the bacterial membranes.

• Journal of Platform Technology
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• v.10 no.2
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• pp.10-19
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• 2022

Moving assistant devices for people who are difficult to move are becoming electric-powered and automated. These moving assistant devices are not suitable for moving stairs at which the height between floor surfaces is different because these devices are designed and manufactured for flatland moving. An electric-powered and automated moving assistant device should change direction or stop when it approaches stairs in a movement direction. If the user or automatic control system does not change direction or stop in time, a moving assistant device can roll over or collide with stairs. In this paper, we propose a stairs detection method by using oblique distance measured by one sensor tilted to flatland. The method proposed in this paper can detect upward or downward stairs by using a difference between a predicted and measured oblique distance in considering a tilted angle of a sensor for measuring an oblique distance and installation height of the sensor on a moving object. Before the device enters a stairs region, if our proposed method provides information about detected stairs to a device's controller, the controller can do adequate action to avoid the accident.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.11-20
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• 2022

The main purpose of this study is to investigate the applicability of the shear wave tomography technology as a non-destructive testing method to evaluate the debonding between the track concrete layer (TCL) and the hydraulically stabilized based course (HSB) of concrete slab tracks for the Korea high-speed railway system. A commercially available multi-channel shear wave measurement device (MIRA) is used to evaluate debonding defects in full-scaled mock-up test specimen that was designed and constructed according to the Rheda 200 system. A part of the mock-up specimen includes two artificial debonding defects with a length and a width of 400mm and thicknesses of 5mm and 10mm, respectively. The tomography images obtained by a MIRA on the surface of the concrete specimens are effective for visualizing the debonding defects in concrete. In this study, a simple image processing method is proposed to suppress the noisy signals reflected from the embedded items (reinforcing steel, precast sleeper, insert, etc.) in TCL, which significantly improves the readability of debonding defects in shear wave tomography images. Results show that debonding maps constructed in this study are effective for visualizing the spatial distribution and the depths of the debondiing defects in the railway concrete slab specimen.

• Journal of the Korea Institute of Building Construction
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• v.22 no.2
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• pp.161-169
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• 2022

The government [3] specifies steel pipe scaffolding as conventional scaffolding and is promoting the installation of system scaffolding, an integrated work platform, and avoidance of the use of steel pipe scaffolding as much as possible. However, in places where equipment cannot enter, such as power plants and plant sites, places the structure is complex, and places where scaffolding cannot be stacked on the ground, there is no choice but to install steel pipe scaffolding. When installing steel pipe scaffolding on an H-beam structure at a high place, the performance of the steel frame clamp is very important in order to form a work space which workers can work safely. In this study, the displacement magnitude and tensile load of members in each installation direction of the clamp for steel frame were verified through performance tests and structural analysis modeling. As a result, it was confirmed that the performance for each installation direction satisfies the safety certification standard tensile load of 10,000N. Although the performance value is satisfactory, deformation of the attachment pressing bolt was verified and was confirmed to have minimal deformation. Thus, to ensure the load is properly to the attachment body, the clamp for a steel frame must be installed in the direction in which the load is transmitted.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.39-59
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• 2022

We analyze the perceptions and requirements of early childhood teachers for artificial intelligence(AI) education to develop an AI education program for 5-year-olds. As for the research methodology, we conducted a survey and an in-depth interview to extract the AI educational elements centering on the analysis stage, the first stage of the ADDIE model. The research result is that first, it is necessary to design a curriculum that combines the contents of early childhood education and AI education to be naturally accepted as AI education for 5-year-olds. Second, an evaluation tool for AI education that can showcase the teacher's reflection should be developed systematically. Third, it is necessary to support a play-centered AI education support and environment for early childhood teachers. Lastly, it is essential to establish a system that can be continuously operated in the field of early childhood education in consideration of AI education in the non-curricular curriculum. It is expected that in the future, a play-oriented AI education program for 5-year-olds will be developed to spread awareness of AI education for infants and present an AI education approach for each age and stage of learners.