• The Journal of Engineering Geology
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• v.20 no.1
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• pp.47-60
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• 2010

This study is focused on the analysis of tunnel behavior to estimate the stability on tunnel design. An estimation method was proposed as a hybrid consideration, which contains the displacement analysis by 3D numerical simulation, the maximum displacement obtained after field measurement, and an assessment of tunnel stability using a deformation analysis proposed by Sakurai(1988, 1997). The points of case study by Sakurai(1988, 1997) were replotted considering his analysis. From the new analysis of the tunnel case study, the trend line for analyzed points is analogized, which curve is divided into stable, unstable and failure zone. To evaluate the estimation method, a special shape of railway tunnel was selected, which are the Inchon international airport rail way connected to subway line 9 in Gimpo, Korea. The point s of upper and below track on the Inchon international airport rail way were satisfied to the stability of tunnel after reinforcing. Also the points shows the higher apparent Young's modulus, which resulted from improvement on shear strength by the micro silica grouting and the supporting of umbrella method. Therefore, if new analysis used, proper tunnel reinforcing method could be selected according to tunnel strain and geological property.

• Geomechanics and Engineering
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• v.37 no.6
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• pp.599-614
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• 2024

To evaluate the safety status of deteriorated segments in a submarine shield tunnel during its service life, a seepage model was established based on a cross-sea shield tunnel project. This model was used to study the migration patterns of erosive ions within the shield segments. Based on these laws, the degree of deterioration of the segments was determined. Using the derived analytical solution, the internal forces within the segments were calculated. Lastly, by applying the formula for calculating safety factors, the variation trends in the safety factors of segments with different degrees of deterioration were obtained. The findings demonstrate that corrosive seawater presents the evolution characteristics of continuous seepage from the outside to the inside of the tunnel. The nearby seepage field shows locally concentrated characteristics when there is leakage at the joint, which causes the seepage field's depth and scope to significantly increase. The chlorine ion content decreases gradually with the increase of the distance from the outer surface of the tunnel. The penetration of erosion ions in the segment is facilitated by the presence of water pressure. The ion content of the entire ring segment lining structure is related in the following order: vault < haunch < springing. The difference in the segment's rate of increase in chlorine ion content decreases as service time increases. Based on the analytical solution calculation, the segment's safety factor drops more when the joint leaks than when its intact, and the change rate between the two states exhibits a general downward trend. The safety factor shows a similar change rule at different water depths and continuously decreases at the same segment position as the water depth increases. The three phases of "sudden drop-rise-stability" are represented by a "spoon-shaped" change rule on the safety factor's change curve. The issue of the poor applicability of indicators in earlier studies is resolved by the analytical solution, which only requires determining the loss degree of the segment lining's effective bearing thickness to calculate the safety factor of any cross-section of the shield tunnel. The analytical solution's computation results, however, have some safety margins and are cautious. The process of establishing the evaluation model indicates that the secondary lining made of molded concrete can also have its safety status assessed using the analytical solution. It is very important for the safe operation of the tunnel and the safety of people's property and has a wide range of applications.

• Archives of design research
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• v.19 no.4 s.66
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• pp.61-70
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• 2006

The functions and roles in the various fields of modern society are changing into the unified and multiplex structure, which is simultaneous and virtual communication environments beyond physical space and time, by the digital IT technology. The urban traffic system is also being intellectualized in order to solve urban traffic problems and convenient services by using digital IT technology. The bus, which is the one of the most common public transportation, are suffering in the decrease of bus service quality and the bus passengers rate because of the development of other public transportation systems such as the subway and electric railway and by rapidly increasing private cars. By recognizing these problems, many domestic and overseas cities are promoting to introduce the Bus Information System (BIS) to improve service quality of buses through the intelligent traffic system. According to the construction of this new information system called the Bus Information System (BIS), the new bus stop configuration system and design plans are being required to solve the existing bus stop information system. Therefore, this research was conducted to suggest an effective BIS configuration system plan and synthetic design goals based on the investigation the problems of the information system and the BIS configuration system for Busan city. Also, this research are conducted the below actions as follows: First, the literature survey was conducted, such as theoretical documents on the bus stop and the Bus Information System(BIS), Also, the design trend of the BIS was examined through domestic and overseas BIS cases studies. Scondly, the problems related to the information system in Busan city bus stops were investigated to investigate the present state and problems of the Bus Information System (BIS). Finally, as a result of this research, the effective BIS configuration system plan and design approach methods of bus stops were proposed for by Busan city based on the above investigation results.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.