3 citations · 3 across the 2 of their papers we have counts for
4 papers
AL-iGAN: An Active Learning Framework for Tunnel Geological Reconstruction Based on TBM Operational Data
Hao Wang, Lixue Liu, Xueguan Song +2
In tunnel boring machine (TBM) underground projects, an accurate description of the rock-soil types distributed in the tunnel can decrease the construction risk ({\it e.g.} surface…
The direct force correction based framework for general co-rotational analysis
Ziyun Kan, Kaijun Dong, Biaosong Chen +2
The use of nonlinear projection matrix in co-rotational (CR) analysis was pioneered by Rankin and Nour-Omid in 1990s (Computers & Structures, 30 (1988) 257-267; Comput. Methods App…
Real-time Forecast Models for TBM Load Parameters Based on Machine Learning Methods
Xianjie Gao, Xueguan Song, Maolin Shi +2
Because of the fast advance rate and the improved personnel safety, tunnel boring machines (TBMs) have been widely used in a variety of tunnel construction projects. The dynamic mo…
Geology prediction based on operation data of TBM: comparison between deep neural network and statistical learning methods
Maolin Shi, Xueguan Song, Wei Sun
Tunnel boring machine (TBM) is a complex engineering system widely used for tunnel construction. In view of the complicated construction environments, it is necessary to predict ge…