Park, Chae-Rin;Heo, Gwang-Hee;Kim, Chung-Gil;Park, Jin-Yong;Ko, Byeong-Chan
Journal of the Korea institute for structural maintenance and inspection
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v.25
no.3
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pp.68-76
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2021
Storage racks have suffered huge losses due to earthquakes, but related research and regulations are relatively insufficient non-structural elements compared to the structural elements. In this study, we tried to experimentally analyze the behavioral characteristics of storage racks due to external force according to the fixing conditions of the column-foundations connection of storage racks. In general, the column-foundations connection of storage racks is installed according to the user's convenience without installation standards and regulations. For this reason, this study conducted a behavior analysis test on four full-scale storage racks with the condition of column-foundations connection of four typical storage racks. The behavior characteristics analysis test was performed by two-direction of the shake table with El-Centro seismic wave. To confirm the behavior characteristics according to the magnitude of the seismic load, 50% ~ 150% of the seismic waves were increased by 50% for each test. In addition, a resonance search test was conducted to confirm the natural frequency of each storage racks foundations fixing condition. Among the data obtained through the test, the displacement of the top layer and the permanent displacement after the test were compared for each condition to analyze the behavior characteristics of the column-foundations fixed conditions of the storage racks. As a result, the change of natural frequency was small in storage racks due to the change of the conditions of the foundations, and the behavior characteristics were changed due to the difference of the restoring force due to the change of the storage racks foundations condition rather than the influence of the natural frequency of the input load.
Choi, Jae Hee;Choi, Bong Jin;Kim, Nam Gyun;Lee, Chang Woo;Seo, Jun Pyo;Jun, Byong Hee
KSCE Journal of Civil and Environmental Engineering Research
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v.41
no.6
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pp.675-686
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2021
This study investigated the ground displacement occurring in a slope below a waste-rock dumping site and estimated the likelihood of a disaster due to a landslide. To start with, photogrammetry was conducted by unmanned aerial vehicles (UAVs) to investigate the size and extent of the ground displacement. From April 2019 to July 2020, the average error rate of the five UAV surveys was 0.011-0.034 m, and an elevation change of 2.97 m occurred due to the movement of the soil layer. Only some areas of the slope showedelevation change, and this was believed to be due to thegroundwater generated during rainfall rather than the effect of the waste-rock load at the top. Sensitivity analysis for LS-RAPID simulation was performed, and the simulation results were compared and analyzed by applying a digital elevation model (DEM) and a digital surface model (DSM)as terrain data with 10 m, 5 m, and 4 m grids. When data with high spatial resolution were used, the extent of the sedimentation of landslide material tended to be excessively expanded in the DEM. In contrast, in the result of applying a DSM, which reflects the topography in detail, the diffusion range was not significantly affected even when the spatial resolution was changed, and the sedimentation behavior according to the river shape could be accurately expressed. As a result, it was concluded that applying a DSM rather than a DEM does not significantly expand the sedimentation range, and results that reflect the site situation well can be obtained.
Park, Seong-Yong;Moon, Seong-Woo;Choi, Jaewan;Seo, Yong-Seok
The Journal of Engineering Geology
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v.31
no.4
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pp.701-718
/
2021
Geological field surveys and a series of laboratory tests were conducted to obtain data related to landslides in Sancheok-myeon, Chungju-si, Chungcheongbuk-do, South Korea where many landslides occurred in the summer of 2020. The magnitudes of various factors' influence on landslide occurrence were evaluated using logistic regression analysis and an artificial neural network. Undisturbed specimens were sampled according to landslide occurrence, and dynamic cone penetration testing measured the depth of the soil layer during geological field surveys. Laboratory tests were performed following the standards of ASTM International. To solve the problem of multicollinearity, the variation inflation factor was calculated for all factors related to landslides, and then nine factors (shear strength, lithology, saturated water content, specific gravity, hydraulic conductivity, USCS, slope angle, and elevation) were determined as influential factors for consideration by machine learning techniques. Minimum-maximum normalization compared factors directly with each other. Logistic regression analysis identified soil depth, slope angle, saturated water content, and shear strength as having the greatest influence (in that order) on the occurrence of landslides. Artificial neural network analysis ranked factors by greatest influence in the order of slope angle, soil depth, saturated water content, and shear strength. Arithmetically averaging the effectiveness of both analyses found slope angle, soil depth, saturated water content, and shear strength as the top four factors. The sum of their effectiveness was ~70%.
Recently, with the development of deep learning technology, researches to apply a deep learning algorithm to analyze unstructured data such as text and images are being actively conducted. Text classification has been studied for a long time in academia and industry, and various attempts are being performed to utilize data characteristics to improve classification performance. In particular, a hierarchical relationship of labels has been utilized for hierarchical classification. However, the top-down approach mainly used for hierarchical classification has a limitation that misclassification at a higher level blocks the opportunity for correct classification at a lower level. Therefore, in this study, we propose a methodology for classifying hierarchical data using the autoencoder-based deeply supervised network that high-level classification does not block the low-level classification while considering the hierarchical relationship of labels. The proposed methodology adds a main classifier that predicts a low-level label to the autoencoder's latent variable and an auxiliary classifier that predicts a high-level label to the hidden layer of the autoencoder. As a result of experiments on 22,512 academic papers to evaluate the performance of the proposed methodology, it was confirmed that the proposed model showed superior classification accuracy and F1-score compared to the traditional supervised autoencoder and DNN model.
Journal of the Korea Society of Computer and Information
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v.27
no.12
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pp.59-68
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2022
This paper presents a method for 1:1 verification by comparing the similarity between the given real product image and the drawing image. The proposed method combines two existing CNN-based deep learning models to construct a Siamese Network. After extracting the feature vector of the image through the FC (Fully Connected) Layer of each network and comparing the similarity, if the real product image and the drawing image (front view, left and right side view, top view, etc) are the same product, the similarity is set to 1 for learning and, if it is a different product, the similarity is set to 0. The test (inference) model is a deep learning model that queries the real product image and the drawing image in pairs to determine whether the pair is the same product or not. In the proposed model, through a comparison of the similarity between the real product image and the drawing image, if the similarity is greater than or equal to a threshold value (Threshold: 0.5), it is determined that the product is the same, and if it is less than or equal to, it is determined that the product is a different product. The proposed model showed an accuracy of about 71.8% for a query to a product (positive: positive) with the same drawing as the real product, and an accuracy of about 83.1% for a query to a different product (positive: negative). In the future, we plan to conduct a study to improve the matching accuracy between the real product image and the drawing image by combining the parameter optimization study with the proposed model and adding processes such as data purification.
Yokjido is a 15-km2 inhabited island located at the tip of the southeastern coast of the Korean Peninsula. Its forest is mostly composed of substitutional vegetation. Our aim was to provide basic information necessary for the conservation and management of the forest vegetation in Yokjido. We classified the types of existing vegetation using methods of the Zurich-Montpellier school of phytosociology. The resulting vegetation map shows the dominant tree species in the top canopy-layer. A total of 8 vegetation types were identified, which were arranged into a vegetation unit hierarchy of 2 communities, 4 sub-communities, 6 variants, and 2 subvariants. Evaluations of each type showed large and small differences in floristic composition, which reflect anthropogenic influences, site conditions, succession stages, and the establishment period. Moreover, vegetation types differed significantly in terms of species diversity indices; in particular, overall species richness, species diversity, and species evenness tended to increase significantly as the elevation increased. The herbaceous plant species showed the highest positive (+) correlation to x. These results were consistent with those of McCain, who reported that species diversity increases in mountainous areas with relatively low elevations due to the mid-domain effect. The forest succession in Yokjido will potentially enter a mixed-forest stage and then proceed to become an all-evergreen broad-leaved forest.
A pile is a structural element that is used to transfer external loads from superstructures and has been widely utilized in construction fields all over the world. The method of installing a pile into the ground should be selected based on geotechnical conditions, location, site status, environmental factors, and construction costs, among others. It can be divided into two types: direct hammering and preboring. The direct hammering method installs a pile into the bearing layer, such as rock, using a few types of hammer, generating a considerable amount of pile driving-induced vibration. The vibration from pile driving influences adjacent structures and the ground; therefore, quantitatively investigating the effects of vibration is inevitably required. In this study, two-dimensional dynamic numerical modeling and analysis are performed using the finite difference method to investigate the influence on the adjacent slope, including temporary supporting system. Time-dependent loading induced by pile driving is estimated and used in the numerical analysis. Consequently, large surface displacement is estimated due to surface waves and less wave deflection, and refraction at the surface. The total displacement decreases with the increase of the distance from the source. However, lateral displacement at the top of the slope shows a larger value than vertical displacement, and the overall displacement tends to be concentrated near the face of the slope.
Journal of the Korean Institute of Landscape Architecture
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v.51
no.5
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pp.70-83
/
2023
Recently, the Korea Forest Service has implemented a planning project about wind corridor forests as a response measure to climate change. Based on this, research on wind corridors has been underway. For the creation of wind corridor forests, a preliminary evaluation of the wind corridor function is necessary. However, currently, there is no evaluation index to directly evaluate and spatially distinguish the types of wind corridors, and analysis is being performed based on indirect indicators. Therefore, this study proposed a method to evaluate and classify wind corridors by utilizing heat deficit analysis as an evaluation index for cold air generation. Heat deficit was analyzed using a cold air analysis model called Kaltluftabflussmodell_21 (KLAM_21). According to the results of the simulation analysis, the wind path was functionally classified. The top 5% were classified as cold-air generating Areas (CGA), and the bottom 5% as cold-air vulnerable Areas (CVA). In addition, the cold-air flowing Areas (CFA) were classified by identifying the flow of cold air moving from the cold air generation area. It is expected that the methodology of this study can be utilized as an evaluation method for the effectiveness of wind corridors. It is also anticipated to be used as an evaluation index to be presented in the selection of wind corridor forest sites.
Journal of Korean Society of Environmental Engineers
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v.27
no.9
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pp.978-988
/
2005
A three-dimensional dynamic model was applied to Lake Paldang, Han River in this study. The model was calibrated and verified using the data measured under different ambient conditions. The model results were in reasonable agreements with the field measurements in both calibration and verification. Utilizing the validated model, we analyzed the spatial and temporal distributions of temperature, current, residence time, and spreading pattern of incoming flows within the lake. Relatively low velocity and high temperature were computed at the surface layer in the southern region of the Sonae island. The longest residence time within the lake was predicted in the southern region of the Sonae island and the downstream region of the South Branch. This can be attributed to the fact that the back currents caused by the dam blocking occur mainly in these regions. Vertical thermal profiles indicated that the thermal stratifications would be occurred feebly in early summer and winter. During early spring and fall, it appeared that there would be no discernible differences at the vertical temperature profiles in the entire lake. The vertical overturns, however, do not occur during these periods due to an influence of high discharge flows from the dam. During midsummer monsoon season with high precipitation, the thermal stratification was disrupted by high incoming flow rates and discharges from the dam and very short residence time was resulted in the entire lake. In this circulation patterns, the plume of the Kyoungan stream with smallest flow rate and higher water temperature tends to travel downstream horizontally along the eastern shore of the south island and vertically at the top surface layer. The model results suggest that the Paldang lake should be a highly hydrodynamic water body with large spatial and temporal variations.
Nutrient fluxes and sediment oxygen demands (SOD) were measured with intact sediment cores collected from three stations in the downstream of Nagdong River. The sediments were subjected to controlled oxic and hypoxic conditions and temperature gradients (from $10^{\circ}C$ to $30^{\circ}C$) of the overlying waters in laboratory batch system. The effect of temperature and labile layer thickness of the sediment on SOD were examined. $PO_4\;^{3-}$ and $NH_4\;^+$ fluxes were elevated above $20^{\circ}C$ and large mobilities were observed when they were coupled with a hypoxic and high-temperature condition. In the well oxygenated conditions, $PO_4\;^{3-}$ fluxes were negative or negligible but $NH_4\;^+$ fluxes ranged from 1.3 mg N $m^{-2}\;hr^{-1}$ to 2.3 $m^{-2}\;hr^{-1}$. Temperature quotients($Q_{10}$) of $PO_4\;^{3-}$ fluxes were 3.7 ${\sim}$ 7.3 ranges to have the most high values. $PO_4\;^{3-}$ and $NH_4\;^+$ fluxes had the logarithmic increase with temperature, while $NO_3\;^-$ was negatively absorbed to the sediment and linearly correlated with the temperature. $SiO_2$ fluxes showed no difference among oxic and hypoxic conditions and sediment texture. The nutrient fluxes would be closely correlated with pore water chemistry of sediments and activated by the top sediment layer composition such as labile organic matters or algal detritus. The ecological implications of the nutrient fluxes were discussed in terms of sources and sinks of nutrients coupled to algal productions in the Nagdong River.
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