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http://dx.doi.org/10.9711/KTAJ.2016.18.2.195

A knowledge-based study on design of NATM lining for subsea tunnels  

Sin, Chunwon (Dept. of Global Construction Engineering, Sungkyunkwan University)
Woo, Seungjoo (Dept. of Global Construction Engineering, Sungkyunkwan University)
Yoo, Chungsik (Dept. of Civil and Environmental Engineering, Sungkyunkwan University)
Publication Information
Journal of Korean Tunnelling and Underground Space Association / v.18, no.2, 2016 , pp. 195-211 More about this Journal
Abstract
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.
Keywords
NATM lining; ANN; Subsea tunnels;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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