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A knowledge-based study on design of NATM lining for subsea tunnels
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 Title & Authors
A knowledge-based study on design of NATM lining for subsea tunnels
Sin, Chunwon; Woo, Seungjoo; Yoo, Chungsik;
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This paper concerns a study of a knowledge-based NATM tunnel lining design for subsea tunnels. Concept for tunnel automation designing system, the development of Artificial Neural Network based technology of the tunnel design system, the learning process and verification of the technology forecasting member forces were described. The design system is the series of process which can predict segmental lining member forces by ANN(artificial neural network system), analyze suitable section for the designated ground, construction and tunnel conditions using a FEM(finite element analysis). The lining member forces are predicted based on the ANN quickly and it helps designers determine its segmental lining dimension easily.
NATM lining;ANN;Subsea tunnels;
 Cited by
Beale, M.H., Hagan, M.T., Demuth, H.B. (2013), Neural Network Toolbox User's Guide, Mathwork Inc.

European Committee for Standardization, (2004). "Eurocode 2: design of concrete structures - part 1-1: general rules and rules for buildings".

Garson, G.D. (1991), "Interpreting neural-network connection weights", AI Expert, Vol. 6, No. 7, pp. 47-51.

Lim, S.B. (1997), "Evaluation of dynamic damage adjacent to a blasthole in tunnel excavations", Kyunghee Univ. PhD dissertation.

Midas users manual version 2012+ (2012), MIDAS IT Co., Ltd.

Ministry of Land, Transport and Maritime Affairs (2012), "Standard concrete construction specification 2012".

Park, E.S., Shin, H.S., Hong, E.S. (2007), "Trends of investigation and design for subsea tunnels", KSCE Tunnel Committee Special Conference 27th Dec. pp. 29-41.

Shin, H.S. (2011), "Technology aspects of subsea tunnels", Proceedings of the Korean Society for Rock Mechanics Conference 2011.9, pp. 35-43.

Terzaghi, K. (1943), "Theoretical soil mechanics", J. Wiley & Sons, New York.

Yoo, C.S., Choi, J.H. (2014), "Prediction of TBM tunnel segment lining forces using ANN technique", Journal of Korean Tunnelling and Underground Space Association, Vol. 16, No. 1, pp. 13-24. crossref(new window)

Yoo, C.S., Kim, S.B., Yoo, K.H. (2008), Development of IT-based tunnel design system, Journal of Korean Tunnelling and Underground Space Association, Vol. 10, No. 2, pp. 153-166.

Yoo, C.S., Kim, J.M., Kim, J.H. (2005), Application of Information Technology in Tunnel Design - A case study, Journal of Korean Tunnelling and Underground Space Association pp. 105-116.

Yang, Y., Zhang, Q. (1997), "A hierarchical analysis for rock engineering using artificial neural networks", Rock Mechanics and Rock Engineering, Vol. 30, Issue 4, pp. 207-222. crossref(new window)

Yang, Y., Zhang, Q. (1998), "The application of neural networks to rock engineering system (RES)", Rock Mechanics and Mining Sciences, Vol. 35, Issue 6, pp. 727-745. crossref(new window)