• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.1
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• pp.59-76
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• 2020

As a continuous increase in demand for the transportation infrastructure in the metropolitan area, the renovation of existing metropolitan and urban railway lines for the rapid transport system requires the construction of sidetrack that can operate local and express trains simultaneously. However, the construction of sidetrack after stopping the operation of the existing subway line causes a lot of economic losses, therefore it is essential to study the tunnel enlargement scheme during the operation of the existing subway tunnel. Accordingly, in this paper, basic research on the enlargement plan of the existing subway tunnel was carried out for the renovation of the existing subway line. In order to investigate the method for the sidetrack construction, the Government Complex Gwacheon station on the Gwacheon line of subway line 4 was selected as a virtual research station. Subsequently, four construction plans including tunnel cross-sectional plan for each section were reviewed and constructability and economic feasibility were compared. Finally, the stability assessment was conducted for the selected construction plan which was considered to be relatively unstable by 3-D full numerical analysis considering the sidetrack construction process.

• Geophysics and Geophysical Exploration
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• v.23 no.4
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• pp.230-242
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• 2020

We performed a magnetotelluric (MT) survey to delineate the geological structures below the depth of 20 km in the Gyeongju area where an earthquake with a magnitude of 5.8 occurred in September 2016. The measured MT data were severely distorted by electrical noise caused by subways, power lines, factories, houses, and farmlands, and by vehicle noise from passing trains and large trucks. Using machine-learning methods, we classified the MT time series data obtained near the railway and highway into two groups according to the inclusion of traffic noise. We applied three schemes, stochastic gradient descent, support vector machine, and random forest, to the time series data for the highspeed train noise. We formulated three datasets, Hx, Hy, and Hx & Hy, for the time series data of the large truck noise and applied the random forest method to each dataset. To evaluate the effect of removing the traffic noise, we compared the time series data, amplitude spectra, and apparent resistivity curves before and after removing the traffic noise from the time series data. We also examined the frequency range affected by traffic noise and whether artifact noise occurred during the traffic noise removal process as a result of the residual difference.