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Application of Geotechnical Engineering and Monitoring Technology in Sustainable Tunnels

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".

Deadline for manuscript submissions: closed (21 May 2024) | Viewed by 1364

Special Issue Editors


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Guest Editor
Department of Geotechnical Engineering, School of Mechanics and Civil Engineering, China University of Mining and Technology-Beijing, Beijing 100083, China
Interests: rock fragmentation; rock mechanics; blasting engineering; dynamic fracture; TBM; shaft and tunnel
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Guest Editor
State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Interests: rock mechanics; geological hazard monitoring; surrounding rock support; slope stability
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Civil Engineering, School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: rock mechanics; blasting engineering; dynamic fracture; experimental technique; numerical simulation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Applied Mechanics, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China
Interests: fracture mechanics; rock blasting; optical experimental technique; numerical simulation

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Guest Editor
State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: rock dynamics; seepage of fractured rock mass; stability control theory of underground engineering and disaster prevention and mitigation technology

Special Issue Information

Dear Colleagues,

The sustainable development of green and efficient tunnels and underground engineering is a new challenge faced by the industry. On the one hand, advanced geotechnical engineering construction technology is the basic guarantee. The mechanical performance and service life of tunnels and underground engineering during the operation period are affected by factors such as material degradation, accidental destructive loading, environmental erosion, and design defects, resulting in various hidden dangers that affect safety and normal use. In severe cases, it will pose a serious threat to the safe operation of infrastructure and people's lives and property. On the other hand, intelligent monitoring technology is the key principle. Integrated tunnel and underground engineering monitoring systems of space have been basically constructed, but further improvement is needed in front-end perception, data analysis, and processing, and the promotion and application of new technologies need to be strengthened. With the continuous progress of monitoring technology and research, achieving dynamic perception, accurate prediction, and intelligent management and maintenance during operation in the future of these fields will play a greater role.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Construction technology and equipment for large section tunnels;
  • New technology for tunnel blasting;
  • Intelligent and mechanized tunnel construction technology;
  • New monitoring and measurement technology for tunnels and underground engineering.

We look forward to receiving your contributions.

Prof. Dr. Liyun Yang
Prof. Dr. Zhigang Tao
Dr. Chenxi Ding
Dr. Peng Xu
Prof. Dr. Liyuan Yu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • geotechnical engineering
  • construction technology
  • monitoring technology
  • sustainable tunnels

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Published Papers (1 paper)

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Research

20 pages, 13314 KiB  
Article
Prediction Method of Rock Uniaxial Compressive Strength Based on Feature Optimization and SSA-XGBoost
by Huihui Xie, Peng Lin, Jintao Kang, Chenyu Zhai and Yuchao Du
Sustainability 2024, 16(19), 8460; https://doi.org/10.3390/su16198460 - 28 Sep 2024
Viewed by 757
Abstract
In order to establish an optimal model for reasonably predicting the uniaxial compressive strength (UCS) of rocks, a method based on feature optimization and SSA-XGBoost was proposed. Firstly, the UCS predictor system of rocks, considering petrographic and physical parameters, was determined based on [...] Read more.
In order to establish an optimal model for reasonably predicting the uniaxial compressive strength (UCS) of rocks, a method based on feature optimization and SSA-XGBoost was proposed. Firstly, the UCS predictor system of rocks, considering petrographic and physical parameters, was determined based on the systematic discussion of the factors affecting the UCS of rocks. Then, a feature selection method combining the RReliefF algorithm and Pearson correlation coefficient was proposed to further determine the optional input features. The XGBoost algorithm was used to establish the prediction model for rock UCS. In the process of model training, the Sparrow Search Algorithm (SSA) was used to optimize the hyperparameters. Finally, model evaluation was carried out to test the performance of the UCS prediction model. The method was applied and validated in a granitic tunnel. The results show that the proposed UCS prediction model can effectively predict the UCS of granitic rocks. Compared with simply adopting petrographic or physical parameters as the input features of the model, the UCS predictor considering petrographic and physical characteristics can improve the generalization ability of the SSA-XGBoost UCS prediction model effectively. The prediction method proposed in this study is reasonable and can provide some reference for establishing a universal method for accurately and quickly predicting the UCS of rocks. Full article
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