supported by the National Key Research and Development Program of China(Grant No.2023YFC3009400);the National Natural Science Foundation of China(Grant Nos.42307218 and U2239251).
The current deep learning models for braced excavation cannot predict deformation from the beginning of excavation due to the need for a substantial corpus of sufficient historical data for training purposes.To addres...
supported by grants from the National Natural Science Foundation of China(Nos.12172159 and 12362019).
Since the plasticity of soil and the irregular shape of the excavation,the efficiency and stability of the traditional local radial basis function(RBF)collocation method(LRBFCM)are inadequate for analyzing three-dimen...
the financial support provided by the National Natural Science Foundation of China(Grant No.52274105);the China Scholarship Council(Grant No.202306370184)。
In this study,a novel microwave-water cooling-assisted mechanical rock breakage method was proposed to address the issues of severe tool wear at elevated temperatures,poor rock microwave absorption,and excessive micro...
the funding support from the National Natural Science Foundation of China(Grant Nos.U23A2060,42177143 and 42277461).
Surrounding rock deterioration and large deformation have always been a significant difficulty in designing and constructing tunnels in soft rock.The key lies in real-time perception and quantitative assessment of the...
funded by the National Natural Science Foundation of China(Grant No.U23B20146);the Natural Science Foundation of Sichuan Province,China(Grant Nos.2024NSFSC0825 and 2022NSFSC0406);We are also grateful for the support provided by the China Scholarship Council(CSC).
Deep rocks encountered in underground engineering are frequently in complex in situ environments and experience both excavation disturbance during construction and cyclic loading throughout the long-term operation. Un...
Australian Research Council,Grant/Award Number:DP210100437;National Natural Science Foundation of China,Grant/Award Number:52274102;Graduate Research and Innovation Projects of Jiangsu Province,Grant/Award Number:KYCX21_2335。
In order to mitigate the risk of geological disasters induced by fault activation when roadways intersect reverse faults in coal mining,this paper uses a combination of mechanical models with PFC2D software.A mechanic...
supported by the Major Science and Technology Project of Shanxi Province,China(Grant No.20191101014);the National Natural Science Foundation of China(Grant No.52075068).
This study proposes an adaptive control strategy for unmanned mining shovel digging trajectory tracking based on radial basis function neural network(RBFNN)and a class of unmanned mining shovel time-varying systems wi...
Supported by Teaching and Research Project of Yangtze University(JY2022047).
Since the 18 th National Congress of the Communist Party of China,General Secretary Xi Jinping has emphasized that universities should address fundamental issues such as what kind of people does education cultivate.A ...
The financial support from the National Natural Science Foundation of China(Grant Nos.41831290,41907167 and 51708354);Natural Science Foundation of Zhejiang Province(Grant No.LTGS23E040001);Natural Science Foundation of Hunan Province(Grant No.2022JJ40521)is greatly appreciated.
When tunnel boring machines(TBMs)excavate through jointed rock masses,the cutting efficiency is strongly affected by the shear strength of joints,the mechanism of which,however,remains poorly understood.In this study,...
National Natural Science Foundation of China(Grant No.52108380);Natural Science Foundation of Jiangsu Province of China(No.BK20210721);Natural Science Foundation of Jiangsu Province of China(No.BK20230500).
Though a comprehensive in situ measurement project,the performance of a deep pit-in-pit excavation constructed by the top-down method in seasonal frozen soil area in Shenyang was extensively examined.The measured exca...