• Land and Housing Review
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• v.12 no.4
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• pp.103-117
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• 2021

With the current rapid changes in population and technology, the long-lastig housing certification system is a means of prolonging the physical and functional lifespan of a building. The certification requires differentiation between the structure and infill elements to allow for variability and ease of repairs. This works well with prefabricated houses so this study investigated the possibility of applying the long-lastig housing certification requirements to apartment construction using off-site construction (OSC) methods focused on the installation of bathrooms (plumbing and toilet) that differ from the traditional wet method. This study examined three different sized floor plans at 22 m², 46 m², and a combined one resulting in 69 m². The larger 69 m² plan utilized a removeable non-load bearing wall to increase flexibility in the layout of the floorplan. The apartments are constructed of steel reinforced concrete composite columns on a 9 m × 10.5 m grid with integrated slabs. The exterior and interior infill walls are all non-load bearing with some containing plumbing. This separation of the structure and infill walls can help meet some of the criteria in the long-lastig housing certification, particularly with the ease of repairs. Technologies that facilitate the replacement of infill elements that contain plumbing and other building services can benefit the nation by reducing carbon emissions and therefore tax incentives should be introduced to increase the adoption of the proposed construction methods.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.4
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• pp.468-475
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• 2019

An end-line flame arrester allows free venting in combination with flame protection for vertical vent applications. End-line flame arresters are employed in various fields, especially in shipping. In flame arresters, springs are essential parts because the spring load and the spring's elasticity determine the hood opening moment. In addition, the spring has to work under a high-temperature condition because of the burning gas flame. Therefore, it is necessary to analyze the mechanical load and elasticity of the spring when the flame starts to appear. Based on simulations of the working process of a specific end-line flame arrester, a thermal and structural analysis of the spring is performed. A three-dimensional model of a burned spring is built using computational fluid dynamics (CFD) simulation. Results of the CFD analysis are input into a finite element method simulation to analyze the spring structure. The research team focused on three cases of spring loads: 43, 93, and 56 kg, correspondingly, at 150 mm of spring deflection. Consequently, the spring load was reduced by 10 kg after 5 min under a $1,000^{\circ}C$ heat condition. The simulation results can be used to predict and estimate the spring's load and elasticity at the burning time variation. Moreover, the obtained outcome can provide the industry with references to optimize the design of the spring as well as that of the flame arrester.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.111-121
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• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.632-645
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• 2021

Satellite sea surface temperature (SST) composites provide important data for numerical forecasting models and for research on global warming and climate change. In this study, six types of representative SST composite database were collected from 2007 to 2018 and the characteristics of spatial structures of SSTs were analyzed in seas around the Korean Peninsula. The SST composite data were compared with time series of in-situ measurements from ocean meteorological buoys of the Korea Meteorological Administration by analyzing the maximum value of the errors and its occurrence time at each buoy station. High differences between the SST data and in-situ measurements were detected in the western coastal stations, in particular Deokjeokdo and Chilbaldo, with a dominant annual or semi-annual cycle. In Pohang buoy, a high SST difference was observed in the summer of 2013, when cold water appeared in the surface layer due to strong upwelling. As a result of spectrum analysis of the time series SST data, daily satellite SSTs showed similar spectral energy from in-situ measurements at periods longer than one month approximately. On the other hand, the difference of spectral energy between the satellite SSTs and in-situ temperature tended to magnify as the temporal frequency increased. This suggests a possibility that satellite SST composite data may not adequately express the temporal variability of SST in the near-coastal area. The fronts from satellite SST images revealed the differences among the SST databases in terms of spatial structure and magnitude of the oceanic fronts. The spatial scale expressed by the SST composite field was investigated through spatial spectral analysis. As a result, the high-resolution SST composite images expressed the spatial structures of mesoscale ocean phenomena better than other low-resolution SST images. Therefore, in order to express the actual mesoscale ocean phenomenon in more detail, it is necessary to develop more advanced techniques for producing the SST composites.

• Geophysics and Geophysical Exploration
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• v.26 no.1
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• pp.18-30
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• 2023

Submarine mud volcanos are topographic features that resemble volcanoes, and are formed due to eruptions of fluidized or gasified sediment material. They have gained attention as a source of subsurface heat, sediment, or hydrocarbons supplied to the surface. In the continental slope of the Canadian Beaufort Sea, mud volcano exists at various water depths. The MV420, is an active mud volcano erupting at a water depth of 420 meters, and it has been the subject of extensive study. The Korea Polar Research Institute(KOPRI) collected high-resolution seismic data and heat flow data around the caldera of the mud volcano. By analyzing the multi-channel seismic data, we confirmed the reverse-polarity reflector assumed by a gas hydrate-related bottom simulating reflector(BSR). To further elucidate the relationship between the BSR and gas hydrates, as well as the thermal structure of the mud volcano, a numerical geothermal model was developed based on the steady-state heat equation. Using this model, we estimated the base of the gas hydrate stability zone and found that the BSR depth estimated by multi-channel seismic data and the bottom of the gas hydrate stability zone were in good agreement., This suggests the presence of gas hydrates, and it was determined that the depth of the gas hydrate was likely up to 50 m, depending on the distance from the mud conduit. Thus, this depth estimate slightly differs from previous studies.

• Economic and Environmental Geology
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• v.45 no.2
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• pp.71-78
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• 2012

Illite-smectite mixed layers (I-S) occurring authigenically in diagenetic and hydrothermal environments reacts toward more illite-rich phases as temperature and potassium ion concentration increase. For that reason, I-S is often used as geothermometry and/or geochronometry at the field of hydrocarbons or ore minerals exploration. Generally, I-S shows X-ray powder diffraction (XRD) patterns of ultra-thin lamellar structures, which consist of restricted numbers of sillicate layers (normally, 5 ~ 15 layers) stacked in parallel to a-b planes. This ultra-thinness is known to decrease I-S expandability (%S) rather than theoretically expected one (short-stacking effect). We attempt here to quantify the short stacking effect of I-S using the difference of two types of expandability: one type is a maximum expandability ($%S_{Max}$) of infinite stacks of fundamental particles (physically inseparable smallest units), and the other type is an expandability of finite particle stacks normally measured using X-ray powder diffraction (XRD) ($%S_{XRD}$). Eleven I-S samples from the Geumseongsan volcanic complex, Uiseong, Gyeongbuk, have been analyzed for measuring $%S_{XRD}$ and average coherent scattering thickness (CST) after size separation under 1 ${\mu}m$. Average fundamental particle thickness ($N_f$) and $%S_{Max}$ have been determined from $%S_{XRD}$ and CST using inter-parameter relationships of I-S layer structures. The discrepancy between $%S_{Max}$ and $%S_{XRD}$ (${\Delta}%S$) suggests that the maximum short-stacking effect happens approximately at 20 $%S_{XRD}$, of which point represents I-S layer structures consisting of ca. average 3-layered fundamental particles ($N_f{\approx}3$). As a result of inferring the $%S_{XRD}$ range of each Reichweite using the $%S_{XRD}$ vs. $N_f$ diagram of Kang et al. (2002), we can confirms that the fundamental particle thickness is a determinant factor for I-S Reichweite, and also that the short-stacking effect shifts the $%S_{XRD}$ range of each Reichweite toward smaller $%S_{XRD}$ values than those that can be theoretically prospected using junction probability.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• The Journal of the Petrological Society of Korea
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• v.6 no.2
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• pp.77-85
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• 1997

The Early Proterozoic reworked rock association occurs within the Preacmbrian high grade metamorphic rocks in the area of Daqingshan, Inner Molgolia. In this association, the various large scale ductile deformation belts, form a nappe structure where the foliation steeply dips to north and the lineation ($340^{circ}-30^{\circ}$) plunges at $45^{\circ}55^{\circ}$. This result indicates the subduction/extension with northern part thrusting over the southern part at high angle. The southern subducted microlithon has the characteristics of prograde metamorphism. The northern thrusted microlithon shows the evidence of retrograde metamorphism with decreasing pressure and increasing temperature. The main rock types of Early Proterozoic Moyites are biotite adamellite and syenogranites occurring in the form of small batholiths or stocks and alkali-feldspar granites in veins. The biotite adamellites are progressively contacted with the Archean and Early Proterozoic rocks and contain a great deal of enclaves of metamorphosed rocks, suggesting an anatexis origin. The geochemical characteristics of moyites show the typical features of anatexis granite. At middle to late Early Proterozoic time, the continent-continent collision formed the large scale thrusting and imbrication of Archean basement rocks. According to the mineral assemblage and thermobarometer of Paria et al. (1988) give the following P-T condition : up-faulted block; $700-710^{\circ}C$, 0.72-0.78 Gpa (early stage) and $600^{\circ}C$, 0.44 Gpa (late stage), footwall block; $620^{\circ}C$, 0.8 Gpa (early stage), $620-840^{\circ}C$, 0.64-0.45 Gpa (peak) and $620-630^{\circ}C$, 0.35Gpa (late stage). These results suggest a clockwise P-T-t path (jin et al., 1991, 1994). According to the depth-temperature model in the comperature subduction zone and the experimental data of Wyllie et al. (1983), we propose a tectonic-magmatic-thermal model to account for metamorphism-anatexis of moyite occurring in subduction-shear zone.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.853-860
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• 2022

The purpose of this study is to suggest an improvement plan for the calculation method of the engineer standard wage rate (ESWR) and to compute a reasonable ESWR. To this end, an adequacy review of theESWR calculation criteria was conducted along with an extensive engineering industry survey. The survey results were analyzed using an effective response sample of 748 companies out of 1,000 survey samples extracted by stratifying the 5,879 survey population. The main results were as follows. ①When calculating the engineering service fee, the prime contractor's engineer wage is suitable for the ESWR. The ESWR can be estimated by the formula 'average wage÷[1-proportion of subcontract orders×(1-subcontract rate)].' ② The field survey showed that the number of monthly working days was 20.35-20.54 days at 99 % confidence interval, which was significantly different from the current standard (22 days). In addition, as a result of a legal review of the ESWR criteria, it was found that the number of working days should be calculated in accordance with the Labor Standards Act after 2022. ③ Applying government guidelines, the time difference between the wage survey and the ESWR application can be corrected by the past ESWR increase rate for a specific period. ④ Using modeling based on the analysis above, the current ESWR was 13.5-14.5 % lower than the appropriate level. A lower ESWR was driven by the non-reflection of subcontract structure (4.1 %), overestimation of monthly work days (6.8-7.8 %), and application of past wage (2.6 %). The proposed model is expected to be widely used in policy making, as it can provide a useful framework for calculating the standard wage rate in similar industries as well as calculating appropriate engineering fees.