• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.128-140
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• 2021

This study applied the theory of Landscape Ecology to representative resources of Jeju Olle-gil, which is a representative subject of walking tourism, to identify ecological characteristics and to establish a technique for landscape ecological analysis of Olle-gil resources. Jeju Olle Trail type based on the biotope type, major land use, vegetation status around Olle Trail and roads were divided into 12 types. Based on the type of ecological tourism resource classification, the Jeju Olle-gil walking tourism resource classification was divided into seven types of natural resources and seven types of humanities resources, and each resource was characterized by Geotope, Biotope, and Anthropopope, just like the landscape ecology system. Geotope resources are strong in landscape characteristics such as coast and beach, rocks, bedrocks, waterfalls, geology and Jusangjeolli Cliff, Oreum and craters, water resources, and landscape viewpoints. The Biotope resources showed strong ecological characteristics due to large tree and protected tree, Gotjawal, forest road and vegetation communities, biological habitat, vegetation landscape view point. Antropotope include Culture of Jeju Haenyeo and traditional culture, potting and lighthouses, experience facilities, temples and churches, military and beacon facilities, other historical and cultural facilities, and cultural landscape views. Jeju Olle Trail The representative resources for each type of Jeju Olle Trail are coastal, Oreum, Gotjawal, field and Stonewall Fencing farming land, Jeju Village and Stone wall of Jeju. In order to learn about the components and various functions of the resources representing the Olle Trail's ecological culture, the landscape ecological technique was interpreted. Looking at the ecological and cultural characteristics of coastal, the coast includes black basalt rocks, coastal vegetation, coastal grasslands, coastal rock vegetation, winter migratory birds and Jeju haenyeo. Oreum is a unique volcanic topography, which includes circular and oval mountain bodies, oreum vegetation, crater wetlands, the origin and legend of the name of Oreum, the legend of the name of Oreum, the culture of grazing horses, the use of military purposes, the object of folk belief, and the view from the summit. Gotjawal features rocky bumps, unique microclimate formation, Gotjawal vegetation, geographical names, the culture of charcoal being baked in the past, and bizarre shapes of trees and vines. Field walls include the structure and shape of field walls, field cultivation crops, field wall habitats, Jeju agricultural culture, and field walls. The village includes a stone wall and roof structure built from basalt, a pavilion at the entrance of the village, a yard and garden inside the house, a view of the lives of local people, and an alleyway view. These resources have slowly changed with the long lives of humans, and are now unique to Jeju Island. By providing contents specialized for each type of Olle Trail, tourists who walk on Olle will be able to experience the Olle Trail in depth as they learn the story of the resources, and will be able to increase the sustainable use and satisfaction of Jeju Olle Trail users.

• Tunnel and Underground Space
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• v.15 no.4 s.57
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• pp.275-287
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• 2005

At the planning and design stages of a development of underground space or tunneling project, the information regarding ground conditions is very important to enhance economical efficiency and overall safety In general, the information can be expressed using RMR or Q-system and with the geophysical exploration image. RMR or Q-system can provide direct information of rock mass in a local scale for the design scheme. Oppositely, the image of geophysical exploration can provide an exthaustive but indirect information. These two types of the information have inherent uncertainties from various sources and are given in different scales and with their own physical meanings. Recently, RMR has been estimated in unsampled areas based on given data using geostatistical methods like Kriging and conditional simulation. In this study, simulated annealing(SA) is applied to overcome the shortcomings of Kriging methods or conditional simulations just using a primary variable. Using this technique, RMR and the image of geophysical exploration can be integrated to construct the spatial distribution of RM and to evaluate its uncertainty. The SA method was applied to solve an optimization problem with constraints. We have suggested the practical procedure of the SA technique for the uncertainty evaluation of RMR and also demonstrated this technique through an application, where it was used to identify the spatial distribution of RMR and quantify the uncertainty. For a geotechnical application, the objective functions of SA are defined using statistical models of RMR and the correlations between RMR and the reference image. The applicability and validity of this application are examined and then the result of uncertainty evaluation can be used to optimize the tunnel layout.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.547-560
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• 2023

Recently, research on predicting ground classification using machine learning techniques, TBM excavation data, and ground data is increasing. In this study, a multi-classification prediction study for uniaxial compressive strength (UCS) was conducted by applying random forest model based on a decision tree among machine learning techniques widely used in various fields to machine data and ground data acquired at three slurry shield TBM sites. For the classification prediction, the training and test data were divided into 7:3, and a grid search including 5-fold cross-validation was used to select the optimal parameter. As a result of classification learning for UCS using a random forest, the accuracy of the multi-classification prediction model was found to be high at both 0.983 and 0.982 in the training set and the test set, respectively. However, due to the imbalance in data distribution between classes, the recall was evaluated low in class 4. It is judged that additional research is needed to increase the amount of measured data of UCS acquired in various sites.

• Tunnel and Underground Space
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• v.23 no.4
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• pp.319-325
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• 2013

The objective of this study is to assess risks which might occur in connection with the storage of the highly compressed air in underground opening. Risk factors were selected throughout literature survey and analysis for the characteristic of CAES. Large risk factors were categorized in three components; planning and design phase, construction phase, and operation & maintenance phases. Large category was composed of 8 medium risk groups and 24 sub-risks. AHP technique was applied in order to analyze the questionnaires answered by experts and high-risk factors were selected by evaluating the relative importance of risks. AHP analysis showed that the operation & maintenance phases are the highest risk group among three components of large category and the highest risk group of eight medium risk groups is risk associated with the quality and safety. Risk having the highest risk level in 24 sub-risks is evaluated to be a failure of tightness security of inner containment storing compressed air.

• Tunnel and Underground Space
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• v.19 no.4
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• pp.275-286
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• 2009

In order to establish the causes and measures for technical risks that occur in various ground conditions when a subsea tunnel is excavated, it is important to configure expected risk scenarios. In addition, when the risk scenarios are classified because the scenario that occurs along all tunnel route and the scenario limited to some area are considered together, a logical framework with systematic and organized responses can be provided for project managements. In this research, project risk scenarios and management elements were configurated, and the project schedule was established for the management techniques to the risk scenario. The risk scenarios expected in a subsea tunnel were classified into a common risk scenario and a special risk scenario, and the concept which can combine with the project management elements was derived.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.2
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• pp.125-133
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• 2014

In this study, TBM selection methods to meet soil and site conditions were presented. Factors and excavation equipment affecting TBM selection by soil and environmental condition were selected and classified. Weights between equipment and influencing factors selected were calculated by applying the AHP (Analytic Hierarchy Process) method. The results of the analysis influence factors, Ground condition was a major factor in objective factors and strength was a major factor in the hard condition of criteria factors and water pressure was a major factor in the soft ground condition of criteria factors. In Environment condition, existence of adjacent structures was evaluated more important than existence of feasible site. Lastly, Adequacy was verified through the deduction of results that coincide with input equipment by applying derived weights to actual site conditions.

• The Journal of Engineering Geology
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• v.21 no.1
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• pp.15-24
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• 2011

To clarify the distribution of joints and fracture zones in the Cheongju granitic mass, we analyzed drill-core and geophysical well-logging data obtained at two boreholes located 30 m from each other. Lithological properties were investigated from the drill-core data and the samples were classified based on the rock mass rating (RMR) and on rock quality designation (RQD). Subsurface discontinuities within soft and hard rocks were examined by geophysical well-logging and cross-hole seismic tomography. The velocity structures constructed from seismic tomography are well correlated with the profile of bedrock depth, previously mapped from a seismic refraction survey. Dynamic elastic moduli, obtained from full waveform sonic and ${\gamma}-{\gamma}$ logging, were interrelated with P-wave velocities to investigate the dynamic properties of the rock mass. Compared with the correlation graph between elastic moduli and velocities for hard rock at borehole BH-1, the correlation points for BH-2 data showed a wide scatter. These scattered points reflect the greater abundance of joints and fractures near borehole BH-2. This interpretation is supported by observations by acoustic televiewer (ATV) and optical televiewer (OTV) image loggings.

• The Journal of Engineering Geology
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• v.16 no.1 s.47
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• pp.85-96
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• 2006

This study was conducted to suggest a method to determine weighting values of each parameter of the RMR system considered with geologic characteristics of a study area. This study reviewed the weighting values of the RMR system for the Cretaceous sedimentary rocks distributed in Ulsan area. Based on the data of field survey at the study area, a multiple regression analysis was used to set up an optimal weighting values of the RMR parameters. For the multiple regression analysis, each parameter of the RMR and the slope gradient were regarded as the independent variable and the dependent variable, respectively. The analysis result suggested a modified weighting values of the RMR parameters as follows; 30 for the intact strength of rock; 18 for RQD; 8 for spacing of discontinuities; 32 for the condition of discontinuities; and 12 for ground water.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.209-227
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• 2023

The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.