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2022 Vol.24, Issue 2 Preview Page

Research Paper

31 March 2022. pp. 217-230
Abstract
References
1
Anagnostou, G., Kovari, K. (1996), "Face stability conditions with earth-pressure-balanced shields", Tunnelling and Underground Space Technology, Vol. 11, No. 2, pp. 165-173. 10.1016/0886-7798(96)00017-X
2
Benardos, A.G., Kaliampakos, D.C. (2004), "Modelling TBM performance with artificial neural networks", Tunnelling and Underground Space Technology, Vol. 19, No. 6, pp. 597-605. 10.1016/j.tust.2004.02.128
3
Broere, W. (2001), Tunnel face stability and new CPT applications, Ph.D. Thesis, Delft University of Technology, Netherlands, pp. 5.
4
Broms, B.B., Bennermark, H. (1967), "Stability of clay at vertical opening", Journal of the Soil Mechanics and Foundations Division, Vol. 93, No. 1, pp. 71-94. 10.1061/JSFEAQ.0000946
5
Davis, E.H., Gunn, M.J., Mair, R.J., Seneviratine, H.N. (1980), "The stability of shallow tunnels and underground openings in cohesive material", Geotechnique, Vol. 30, No. 4, pp. 397-416. 10.1680/geot.1980.30.4.397
6
Gao, B., Wang, R., Lin, C., Guo, X., Liu, B., Zhang, W. (2021), "TBM penetration rate prediction based on the long short-term memory neural network", Underground Space, Vol. 6, No. 6, pp. 718-731. 10.1016/j.undsp.2020.01.003
7
Gao, X., Shi, M., Song, X., Zhang, C., Zhang, H. (2019), "Recurrent neural networks for real-time prediction of TBM operating parameters", Automation in Construction, Vol. 98, pp. 225-235. 10.1016/j.autcon.2018.11.013
8
Grima, M.A., Bruines, P.A., Verhoef, P.N.W. (2000), "Modelling tunnel boring machine performance by neuro-fuzzy methods", Tunnelling and Underground Space Technology, Vol. 15, No. 3, pp. 259-269. 10.1016/S0886-7798(00)00055-9
9
Hyun, K.C., Min, S., Choi, H., Park, J., Lee, I.M. (2015), "Risk analysis using fault-tree analysis (FTA) and analytic hierarchy process (AHP) applicable to shield TBM tunnels", Tunnelling and Underground Space Technology, Vol. 49, pp. 121-129. 10.1016/j.tust.2015.04.007
10
Jung, J.H., Kim, B.K., Chung, H., Kim, H.M., Lee, I.M. (2019), "A ground condition prediction ahead of tunnel face utilizing time series analysis of shield TBM data in soil tunnel", Journal of Korean Tunnelling and Underground Space Association, Vol. 21, No. 2, pp. 227-242. 10.9711/KTAJ.2019.21.2.227
11
Kim, D., Pham, K., Oh, J.Y., Lee, S.J., Choi, H. (2022), "Classification of surface settlement levels induced by TBM driving in urban areas using random forest with data-driven feature selection", Automation in Construction, Vol. 135. 10.1016/j.autcon.2021.104109
12
Kim, T.H., Kwak, N.S., Kim, T.K., Jung, S., Ko, T.Y. (2021), "A TBM data-based ground prediction using deep neural network", Journal of Korean Tunnelling and Underground Space Association, Vol. 23, No. 1, pp. 13-24. 10.7474/TUS.2013.23.1.013
13
Kirsch, A. (2010), Numerical Investigation of the Face Stability of Shallow Tunnels in Sand, Numerical Methods in Geotechnical Engineering, CRC Press, London, pp. 795-800. 10.1201/b10551-143
14
Leca, E., Dormieux, L. (1990), "Upper and lower bound solutions for the face stability of shallow circular tunnels in frictional material", Geotechnique, Vol. 40, No. 4, pp. 581-606. 10.1680/geot.1990.40.4.581
15
Mollon, G., Dias, D., Soubra, A.H. (2013), "Continuous velocity fields for collapse and blowout of a pressurized tunnel face in purely cohesive soil", International Journal for Numerical and Analytical Methods in Geomechanics, Vol. 37, No. 13, pp. 2061-2083. 10.1002/nag.2121
16
Santos Jr, O.J., Celestino, T.B. (2008), "Artificial neural networks analysis of Sao Paulo subway tunnel settlement data", Tunnelling and Underground Space Technology, Vol. 23, No. 5, pp. 481-491. 10.1016/j.tust.2007.07.002
17
Sharafat, A., Latif, K., Seo, J. (2021), "Risk analysis of TBM tunneling projects based on generic bow-tie risk analysis approach in difficult ground conditions", Tunnelling and Underground Space Technology, Vol. 111. 10.1016/j.tust.2021.103860
18
Zhang, C., Liang, M., Song, X., Liu, L., Wang, H., Li, W., Shi, M. (2022), "Generative adversarial network for geological prediction based on TBM operational data", Mechanical Systems and Signal Processing, Vol. 162. 10.1016/j.ymssp.2021.108035
Information
  • Publisher :Korean Tunneling and Underground Space Association
  • Publisher(Ko) :한국터널지하공간학회
  • Journal Title :Journal of Korean Tunnelling and Underground Space Association
  • Journal Title(Ko) :한국터널지하공간학회 논문집
  • Volume : 24
  • No :2
  • Pages :217-230
  • Received Date : 2022-02-21
  • Revised Date : 2022-03-17
  • Accepted Date : 2022-03-17