Zobrazeno 1 - 8
of 8
pro vyhledávání: '"LiuJie Jing"'
Autor:
Qinglong Zhang, Yanwen Zhu, Rui Ma, Sanlin Du, Kun Shao, Liujie Jing, Yongsheng Zhang, Qingbin Li
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Existing tunnel boring machine (TBM) construction presents certain shortcomings. These include difficulty in comprehensive perception of information, poor timelines of information transmission and storage systems, significant effects of traditional d
Externí odkaz:
https://doaj.org/article/10020da110864461868ff3f6a88e5e61
Publikováno v:
Frontiers in Earth Science, Vol 10 (2023)
In order to improve the digging efficiency of tunnel boring machine (TBM) in high-strength and highly abrasive formations, high-pressure water jet-assisted tunnel boring machine rock breaking technology has been developed and applied in steps. In thi
Externí odkaz:
https://doaj.org/article/29f02cc765db44fd86bc758516da09c7
Publikováno v:
Science China Technological Sciences. 66:751-770
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::176134ae4dd066b668a6dd201c96c0c8
https://doi.org/10.1007/s11431-022-2290-7
https://doi.org/10.1007/s11431-022-2290-7
Publikováno v:
Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards. 17:127-147
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f0064cf549824c251adf60ac662ff54
https://doi.org/10.1080/17499518.2023.2184834
https://doi.org/10.1080/17499518.2023.2184834
Publikováno v:
Arabian Journal of Geosciences. 13
In the tunnel boring machine (TBM) excavation process, the accurate prediction of the TBM performance, especially the penetration rate, is of great significance to the in time planning, cost control, and safety judgment. In this paper, we propose a p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::112112b515344da153d730928b9d48ad
https://doi.org/10.1007/s12517-020-05305-x
https://doi.org/10.1007/s12517-020-05305-x
Akademický článek
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Autor:
Lipeng Liu, Yufei Zhao, Feng Shangxin, Hua Luo, Shanyong Wang, Zuyu Chen, Liujie Jing, Daosheng Ling
Publikováno v:
Tunnelling and Underground Space Technology. 110:103636
This work explores the potential for predicting TBM performance using deep learning. It focuses on a 17.5-km-long tunnel excavated for the Yingsong Water Diversion Project in Northeastern China with its 728 days’ continuous monitoring of mechanical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95e9c938b9e44712d51b5a77ecc25cfa
https://doi.org/10.1016/j.tust.2020.103636
https://doi.org/10.1016/j.tust.2020.103636
Publikováno v:
Tunnelling and Underground Space Technology. 108:103700
The Yinsong Water Diversion Project in China’s northeast region contains a 20 km long tunnel section, which was drilled by a tunnel boring machine (TBM) and monitored in real time to generate continuously measured data. During the tunnel constructi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::61615f45228ad00d66efa9dd312ed9df
https://doi.org/10.1016/j.tust.2020.103700
https://doi.org/10.1016/j.tust.2020.103700