Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Zu-Yu Chen"'
Publikováno v:
Soils and Foundations, Vol 64, Iss 6, Pp 101526- (2024)
In earth-rockfill dams, roadbeds, airports, and other embankment projects, gradation information serves as the basis for evaluating the quality and suitability of fill materials. Addressing the limitations of existing image-based contour recognition
Externí odkaz:
https://doaj.org/article/d54c6d190eba4c9188b17727bb7eea90
Autor:
Jian-Bin Li, Zu-Yu Chen, Xu Li, Liu-Jie Jing, Yun-Pei Zhang, Hao-Han Xiao, Shuang-Jing Wang, Wen-Kun Yang, Lei-Jie Wu, Peng-Yu Li, Hai-Bo Li, Min Yao, Li-Tao Fan
Publikováno v:
Underground Space, Vol 11, Iss , Pp 26-45 (2023)
This review discusses the application scenarios of the machine learning-supported performance prediction and the optimization efficiency of tunnel boring machines (TBMs). The rock mass quality ratings, which are based on the Chinese code for geologic
Externí odkaz:
https://doaj.org/article/6ee45313cc174ddcb3143c04e25d6357
Autor:
Jian-Bin Li, Zu-Yu Chen, Xu Li, Liu-Jie Jing, Yun-Pei Zhangf, Hao-Han Xiao, Shuang-Jing Wang, Wen-Kun Yang, Lei-Jie Wu, Peng-Yu Li, Hai-Bo Li, Min Yao, Li-Tao Fan
Publikováno v:
Underground Space, Vol 11, Iss , Pp 1-25 (2023)
This review summarizes the research outcomes and findings documented in 45 journal papers using a shared tunnel boring machine (TBM) dataset for performance prediction and boring efficiency optimization using machine learning methods. The big dataset
Externí odkaz:
https://doaj.org/article/ba08dd1d5dc64e86a606eaa5f449942c
Publikováno v:
Underground Space, Vol 7, Iss 4, Pp 680-701 (2022)
This paper addresses the significance of preprocessing big data collected during a tunnel boring machine (TBM) excavation before it is used for machine learning on various TBM performance predictions. The research work is based on two water diversion
Externí odkaz:
https://doaj.org/article/ebcb53ec75c344359da4ac1ea9150123
Publikováno v:
In Ocean Engineering 15 September 2017 142:523-531
Publikováno v:
Waste Management. 103:159-168
Vertical wells are conventionally used to lower leachate levels or pressures in municipal solid waste (MSW) landfills. However, they are not always efficient or even effective, and in some circumstances retro-fitted horizontal wells represent a poten
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e38313de2211443ab6dd8c0e17032c0b
https://doi.org/10.1016/j.wasman.2019.12.035
https://doi.org/10.1016/j.wasman.2019.12.035
Publikováno v:
Rock Mechanics and Rock Engineering. 51:513-530
In this work, toppling failure of a jointed rock slope is studied by using the distinct lattice spring model (DLSM). The gravity increase method (GIM) with a sub-step loading scheme is implemented in the DLSM to mimic the loading conditions of a cent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ebb0ac2e07050141f47cfb1d8d862e6c
https://doi.org/10.1007/s00603-017-1323-y
https://doi.org/10.1007/s00603-017-1323-y
Publikováno v:
Engineering Geology. 203:83-98
Using measured data of over 100,000 discontinuities in 35 hydropower projects, this study conducts in-depth analyses on the statistical characteristics of geometric parameters of rock discontinuities and makes an improvement of Monte Carlo network si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4768b128514f366547476577ec7542c3
https://doi.org/10.1016/j.enggeo.2015.12.001
https://doi.org/10.1016/j.enggeo.2015.12.001
Publikováno v:
Proceedings of the 8th International Congress on Environmental Geotechnics Volume 2 ISBN: 9789811322235
This report describes a pilot test at Tianziling MSW landfill to assess the feasibility of lowering the leachate level using horizontal wells. Three horizontal wells S01, S02 and S03 (length 50 m, 56 m and 55 m, respectively) were successfully instal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf9bd20b42fc1a2a565e0e0b1f8ee4b8
https://doi.org/10.1007/978-981-13-2224-2_15
https://doi.org/10.1007/978-981-13-2224-2_15
