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http://dx.doi.org/10.9711/KTAJ.2019.21.2.227

A ground condition prediction ahead of tunnel face utilizing time series analysis of shield TBM data in soil tunnel  

Jung, Jee-Hee (School of Civil, Environmental and Architectural Engineering, Korea University)
Kim, Byung-Kyu (School of Civil, Environmental and Architectural Engineering, Korea University)
Chung, Heeyoung (School of Civil, Environmental and Architectural Engineering, Korea University)
Kim, Hae-Mahn (School of Civil, Environmental and Architectural Engineering, Korea University)
Lee, In-Mo (School of Civil, Environmental and Architectural Engineering, Korea University)
Publication Information
Journal of Korean Tunnelling and Underground Space Association / v.21, no.2, 2019 , pp. 227-242 More about this Journal
Abstract
This paper presents a method to predict ground types ahead of a tunnel face utilizing operational data of the earth pressure-balanced (EPB) shield tunnel boring machine (TBM) when running through soil ground. The time series analysis model which was applicable to predict the mixed ground composed of soils and rocks was modified to be applicable to soil tunnels. Using the modified model, the feasibility on the choice of the soil conditioning materials dependent upon soil types was studied. To do this, a self-organizing map (SOM) clustering was performed. Firstly, it was confirmed that the ground types should be classified based on the percentage of 35% passing through the #200 sieve. Then, the possibility of predicting the ground types by employing the modified model, in which the TBM operational data were analyzed, was studied. The efficacy of the modified model is demonstrated by its 98% accuracy in predicting ground types ten rings ahead of the tunnel face. Especially, the average prediction accuracy was approximately 93% in areas where ground type variations occur.
Keywords
Artificial neural network (ANN); Autoregressive integrated moving average (ARIMA) model; Time delay neural network (TDNN); Ground condition prediction; Earth pressure-balanced (EPB) shield TBM;
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Times Cited By KSCI : 1  (Citation Analysis)
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