• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.5
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• pp.431-449
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• 2022

As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.4
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• pp.1-17
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• 2018

This study was conducted to interpret the landscape of Songge Byeoleop(Korean villa) garden at Jogyedong, Bukhansan near Seoul which was built in the mid 17C. to restore through the literature reviews and field surveys. The results were as follows; Songge Byeoleop garden was a royal villa, constructed at King Injo24(1646) of Joseon dynasty by prince Inpyeong(麟坪大君), Lee, Yo(李?, 1622~1658), the third son of King Injo who was a brother of King Hyojong. It was a royal villa, Seokyang-lu under Mt. Taracsan of Gyendeokbang, about 7km away in the straight line from main building. It was considered that the building system was a very gorgeous with timber coloring because of owner's special situation who was called the great prince. The place of Songge Byeoleop identity and key landscape of the place were consisted with Gucheon waterfall and the sound of the water with multi-layered waterfall which might be comparable to the waterfall of Yeosan in China. After the destruction of the building, the place was used for the royal tomb quarry, but there was a mark stone for forbidden quarry. The Inner part of Songge Beoleop, centered with Jogedongcheon, Chogye-dong, composted beautifully with the natural sceneries of Gucheon waterfall, Handam and Changbeok, and artificial structures, such as Bihong-bridge, Boheogak, Yeonghyudang and Gyedang. In addition, the existing Chinese characters, 'Songge Beoleop' and 'Gucheoneunpog' carved in the rocks are literary languages and place markings symbolizing with the contrast of the different forests and territories. They gave the names of scenery to the rock and gave meaning to them. Particularly, Gucheon waterfall which served as a visual terminal point, is a cascade type with multi-staged waterfall. and the lower part shows the topographical characteristics of the Horse Bowl-shaped jointed with port-holes. On the other hand, the outer part is divided into the spaces for the main entrance gate, a hanging bridge character, a bridge connecting the inside and the outside, and Yeonghyudang part for the purpose of living. Also in the Boheogak area, dual view frame structures are made to allow the view of the four sides including the width and the perimeter of the villa. In addition, at the view point in Bihong-bridge, the Gucheon water fall divides between the sacred and profane, and crosses the Bihong-bridge and climbs to the subterranean level.