基于知识的优化NATM衬砌设计系统研究进展

IF 0.4 Q4 ENGINEERING, GEOLOGICAL Journal of the Korean Geosynthetic Society Pub Date : 2018-12-01 DOI:10.12814/JKGSS.2018.17.4.251
Ju-Sang Song, C. Yoo
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引用次数: 1

摘要

本文研究了海底隧道NATM二次衬砌优化设计系统的开发。海底隧道通常铺设在海水和由土壤或岩石组成的海底地面之下。该设计系统是通过人工神经网络系统预测衬砌构件受力,分析指定地基、施工和隧道条件下的合适断面的一系列过程。最后,本衬砌设计系统旨在连接海底隧道的自动设计。利用人工神经网络对衬砌构件的受力进行预测,并通过有限元分析进行计算,使设计人员无需进一步的有限元计算即可方便地确定衬砌尺寸。
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Development of Knowledge-based Study on Optimized NATM Lining Design System
This paper concerns the development of an optimized NATM secondary lining design system for a subsea tunnel. The subsea tunnel is normally laid down under the sea water and submarine ground which consists of soil or rock. The design system is the series of process which can predict lining member forces by ANN (artificial neural network system), analyze suitable section for the designated ground, construction and tunnel conditions. Finally, this lining design system aims to be connected for designing the subsea tunnel automatically. The lining member forces are predicted based on the ANN which was calculated by a FEM (finite element analysis) and it helps designers determine its lining dimension easily without any further FEM calculations.
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