• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.152-161
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• 2023

In general, large-capacity hydrogen storage vessels, typically in the form of vertical cylindrical vessels, are constructed using steel materials. These vessels are anchored to foundation slabs that are specially designed to suit the environmental conditions. This anchoring method involves pre-installed anchors on top of the concrete foundation slab. However, it's important to note that such a design can result in concentrated stresses at the anchoring points when external forces, such as seismic events, are at play. This may lead to potential structural damage due to anchor and concrete damage. For this reason, in this study, it selected an vertical hydrogen storage vessel based on site observations and created a 3D finite element model. Artificial seismic motions made following the procedures specified in ICC-ES AC 156, as well as domestic recorded earthquakes with a magnitude greater than 5.0, were applied to analyze the structural behavior and performance of the target structures. Conducting experiments on a structure built to actual scale would be ideal, but due to practical constraints, it proved challenging to execute. Therefore, it opted for an analytical approach to assess the safety of the target structure. Regarding the structural response characteristics, the acceleration induced by seismic motion was observed to amplify by approximately ten times compared to the input seismic motions. Additionally, there was a tendency for a decrease in amplification as the response acceleration was transmitted to the point where the centre of gravity is located. For the vulnerable components, specifically the sub-system (support columns and anchorages), the stress levels were found to satisfy the allowable stress criteria. However, the concrete's tensile strength exhibited only about a 5% margin of safety compared to the allowable stress. This indicates the need for mitigation strategies in addressing these concerns. Based on the research findings presented in this paper, it is anticipated that predictable load information for the design of storage vessels required for future shaking table tests will be provided.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.1-8
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• 2010

The purpose of the study was to evaluate the influence of landscaping pavements on WBGT(Wet-Bulb Globe Temperature) of outdoor spaces that lack ventilation and shade at summer midday. The relative humidity(RH), dry-bulb temperature(DT) and globe temperature(GT) were recorded every minute from June to October 2009 at a height of 1.2m above ten experimental beds with different pavements, by a measuring system consisting of an electric humidity sensor(GHM-15), resistance temperature detector(RTD, Pt-100), standard black globe(${\phi} 150mm$) and data acquisition systems(National Instrument's Labview and Compact FieldPoint). Additionally, the surface dry-bulb temperatures also were recorded and compared. The area of each experimental bed was 1.5m(W)${\times}$2.0m(L) and ten different kinds of pavement were used including grass, grass+cubic stone, grass+porous brick, brick, stone panels, cubic stone, interlocking blocks, clay brick, naked soil, gravel and concrete. To prevent interference from ventilation, a 1.5m height cubic steel frame was established around each bed and each vertical side of the frame was covered with transparent polyethylene film. Based on the records of the hottest period from noon to 3 PM on 26 days with a peak dry-bulb temperature over $30^{\circ}C$ at natural condition, the wet-bulb temperature(WT) and WBGT were calculated and compared. The major findings were as follows: 1. The average surface DT was $40.1^{\circ}C$, which is $9^{\circ}C$ higher than that of the natural condition. The surface DT of the pavements with grass were higher than those of concrete and interlocking block. The peak DT of the surface almost every pavement rose to above $50^{\circ}C$ during the hottest time. 2. The averages of DT, WT and GT were $40.1^{\circ}C$, $27.5^{\circ}C$ and $49.1^{\circ}C$, and the peak values rose to $48.1^{\circ}C$, $45.8^{\circ}C$ and $59.5^{\circ}C$, respectively. In spite of slight differences that resulted according to pavements, no coherent differentiating factor could be found. 3. The average WBGT of grass was the highest at $34.3^{\circ}C$ while the others were similar in the range of around $33{\pm}1^{\circ}C$. Meanwhile, the peak WBGT was highest with stone panel at $47.9^{\circ}C$. Though there were some differences according to pavements, and while grass seemed to be worst in terms of WBGT, it seems difficult to say ablolutely that grass was the worst because the measurement was conducted without ventilation and shade during summer daytime hours only, which had temperatures that rose to a dangerous degree(above $45^{\circ}C$ WBGT), withering the grass during the hottest period. The average WBGT resulted also showed that the thermal environment of the pavement without ventilation and shade were at an intolerable level for humans regardless of the pavement type. In summary, the results of this study show that ventilation and shade are more important factor than pavement type in terms of outdoor thermal comfort in summer daylight hours.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.1
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• pp.61-71
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• 2010

The attributes related to the health condition of RC deck slabs are analyzed to help us identify and rate the safety level of the bridges in this study. According to the related reports the state assessment for the outward aspects of bridges is the important and critical part for rating the overall structural safety. In this respect, the careful identification for the various state attributes make the field inspection and structural diagnosis very effective. This study analyzes the influence of the state attributes on evaluation classes and the relationship of them by the inductive reasoning, which raise the understanding and performance for evaluation work, and support the logical approach for the state assessment. ID3 algorithm applied to the case set which is constructed from the field reports indicates the main attributes and the precedence governing the assessment, and derives the decision hierarchy for the state assessment.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.2
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• pp.52-61
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• 2018

Urban heat islands occur due to increases in the extent of artificial surfaces such as concrete, asphalt and high-rise buildings. In this regard, research into the use of satellite thermal infrared images for thermal environment analysis of urban areas is being carried out. However, such analysis of the characteristics of individual land cover with low-resolution satellite images suffers from limitations because land cover patterns in urban areas are complicated. Recently, UAV has been widely used, which can compensate for this limitation as it is able to acquire high-resolution images. In this paper, the accuracy of UAV infrared images is verified and the applicability of UAV in urban thermal environment analysis is examined by comparing the results with land surface temperatures from Landsat 8 thermal images. The results show a high positive correlation of temperature values at 0.95, and no statistically significant difference between the two groups. Comparisons of land surface temperature according to land cover showed that the largest difference observed was $4.63^{\circ}C$ in the Used area, and UAV images with small cell units reflected various surface temperatures. Furthermore, it was possible to analyze the surface temperatures of various green spaces such as wetlands and street tree areas, which can lower surface temperatures in urban areas, with street tree shadows reducing surface temperatures by about $4-6^{\circ}C$. UAV can easily and rapidly measure the surface temperature of urban areas and is able to analyze various types of green spaces. Thus, this is an effective tool for thermal environment analysis in urban areas to aid in the design or management of urban green spaces, as it can allow for land cover and the effects of the various green spaces.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.2
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• pp.135-145
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• 2023

Aggregate is used to produce stable materials like concrete and asphalt and is fundamental to meet the social needs of housing, industry, road, energy and health. A total of 42.35 billion tons of aggregate were produced in 2021 worldwide, an increase of 0.91% compared to the previous year. Among them, 2 billion tons were produced in China, India, European Union and United States, making up to 71.75% of the share. South Korea has witnessed a constant increase in aggregate production, overtaking Mexico and Japan for seventh place with 390 million tons and 0.85% of the share. The industrial sand and gravel produced globally amounted to 352.66 million tons. The top seven countries with the highest production were China, United States, Netherlands, Italy, India, Turkey and France, and their production exceeded 10 million tons and held a share of 74.69%. Exports of natural rock recorded $21.68 billion in 2021, increased by $2.3 billion compared to the previous year, while exports of artificial rock increased by $2.66 billion to $13.59 billion. Exports of sand reached $1.71 billion with United States, Netherlands, Germany and Belgium being the four countries with the highest exports of sand. The four countries exported more than $100 million in sand and took up 57.70% of the total amount. Exports of gravel totaled $2.75 billion, with China, Norway, Germany, Belgium, France and Austria in the lead, making up to 48.30% of the total share. The aggregate quarry started to surge in the 1950s due to the change in people's lifestyle such as population growth, urbanization and infrastructure delvelopment. Demand for aggregate is also skyrocketing to prevent land reclamation and flood caused by sea-level rise. Demand for aggregate, which was around 24 gigatons in 2011, is expected to double to 55 gigatons in 2060. However, it is likely that aggregate extraction will heavily damage the ecosystem and the world will eventually face a shortage of aggregate followed by tense social conflict.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.617-628
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• 2022

A ground support pattern should be designed by properly integrating various support materials in accordance with the rock mass grade when constructing a tunnel, and a technical decision must be made in this process by professionals with vast construction experiences. However, designing supports at the early stage of tunnel design, such as feasibility study or basic design, may be very challenging due to the short timeline, insufficient budget, and deficiency of field data. Meanwhile, the design of the support pattern can be performed more quickly and reliably by utilizing the machine learning technique and the accumulated design data with the rapid increase in tunnel construction in South Korea. Therefore, in this study, the design data and ground exploration data of 48 road tunnels in South Korea were inspected, and data about 19 items, including eight input items (rock type, resistivity, depth, tunnel length, safety index by tunnel length, safety index by rick index, tunnel type, tunnel area) and 11 output items (rock mass grade, two items for shotcrete, three items for rock bolt, three items for steel support, two items for concrete lining), were collected to automatically determine the rock mass class and the support pattern. Three machine learning models (S1, A1, A2) were developed using two machine learning algorithms (SVR, ANN) and organized data. As a result, the A2 model, which applied different loss functions according to the output data format, showed the best performance. This study confirms the potential of support pattern design using machine learning, and it is expected that it will be able to improve the design model by continuously using the model in the actual design, compensating for its shortcomings, and improving its usability.