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Advances in Sustainable Geotechnical Engineering: 2nd Edition
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Advances in Sustainable Geotechnical Engineering: 2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: 20 November 2024 | Viewed by 1620

Special Issue Editors

Prof. Dr. Helin Fu

E-Mail Website
Guest Editor
School of Civil Engineering, Central South University, Changsha 410075, China
Interests: tunnel and underground engineering; geotechnical engineering; tunnel construction; special geological environment
Special Issues, Collections and Topics in MDPI journals
Dr. Zhen Huang

E-Mail Website
Guest Editor
School of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China
Interests: tunnel engineering; prefabricated tunnel; geotechnical engineering; underground structure safety; numerical simulation; tunnel construction; special geological environment
Special Issues, Collections and Topics in MDPI journals
Dr. Jiabing Zhang

E-Mail Website
Guest Editor
School of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China
Interests: tunnel; freeze–thaw damage; rock mechanics; creep characteristics; numerical simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

this special issue is devoted to publishing research results of important geotechnical problems involved in the field of tunnel and underground engineering. In recent years, with the rapid economic development and population increases in various countries, new tunnel projects have begun construction. However, the geological environment of a tunnel structure is complex and changeable. Landslides, collapses, rock piles, unsymmetrical strata, karst, high stress, high-strength strata, loose strata, soft soil sections, special rock and soil, strong permeable strata, and other unfavorable geological environments are often encountered. Various unfavorable geological environments have led to frequent engineering accidents, which has brought great challenges to tunnel construction. This special issue mainly focuses on the important geotechnical problems involved in the design and construction of highways, railways, subways, and municipal tunnels, but it is not limited to tunnels in the above fields. High-quality research papers and engineering cases focusing on low-carbon environmental protection technology, energy-saving and consumption reduction technology, advanced methods, machine learning technology, artificial intelligence methods, etc., applied in tunnels are welcome.

Prof. Dr. Helin Fu
Dr. Zhen Huang
Dr. Jiabing Zhang
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. Applied Sciences 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

  • tunnel engineering
  • tunnel excavation stability
  • large deformations of surrounding rock
  • special geological environment
  • waterproofing and drainage of tunnels
  • deep rock mass
  • special rock and soil
  • trenchless technology
  • intelligent prediction method
  • intelligent monitoring technology
  • carbon-saving technology
  • green construction method
  • machine learning technology

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Published Papers (2 papers)

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16 pages, 2442 KiB  
Article
Low Stress Level and Low Stress Amplitude Fatigue Loading Simulation of Concrete Components Containing Cold Joints under Fatigue Loading
by He-Lin Fu, Huang-Shi Deng, Yi-Min Wu, Yi-Bo Zhao and Cheng-Da Xie
Appl. Sci. 2024, 14(17), 7709; https://doi.org/10.3390/app14177709 - 31 Aug 2024
Viewed by 484
Abstract
Concrete linings containing cold joint defects may crack or detach under the aerodynamic fatigue loading generated by high-speed train operation, which posing a serious threat to the normal operation of high-speed trains. However, there is currently no simulation method specifically for fatigue damage [...] Read more.
Concrete linings containing cold joint defects may crack or detach under the aerodynamic fatigue loading generated by high-speed train operation, which posing a serious threat to the normal operation of high-speed trains. However, there is currently no simulation method specifically for fatigue damage of concrete linings containing cold joints. Based on the Roe-Siegmund cycle cohesive force model, a cohesive force fatigue damage elements were developed. A large dataset was constructed through numerical simulation software to build a BP neural network for back-calculated parameter of cohesive force fatigue damage elements. By combining experimental data, fatigue damage parameters corresponding to different pouring interval cold joints were back-calculated. These back-calculated parameters were then incorporated into the numerical model to compare simulation results with experimental results to validate the applicability of cohesive force fatigue damage elements and back propagation neural networks (BP neural network). The research results show that the difference between the fatigue life and fracture process calculated by numerical simulation and experimental data is small, verifying the applicability of the method proposed in this paper. The pouring interval directly affects the initial strength of the cold joint interface and the starting conditions of fatigue damage. The possibility of fatigue damage and fracture of concrete components containing cold joints increases with the increase of pouring interval, while the variability of fatigue life decreases with the increase of pouring interval. Interface strength and thickness are the main factors affecting the possibility of fatigue damage occurrence and the variability of fatigue life. The research results can be used to analyze the damage and cracking status of concrete linings containing cold joints under aerodynamic fatigue loading. Full article
(This article belongs to the Special Issue Advances in Sustainable Geotechnical Engineering: 2nd Edition)
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19 pages, 27369 KiB  
Article
A New Approach for Discontinuity Extraction Based on an Improved Naive Bayes Classifier
by Guangyin Lu, Xudong Zhu, Bei Cao, Yani Li, Chuanyi Tao and Zicheng Yang
Appl. Sci. 2024, 14(5), 2050; https://doi.org/10.3390/app14052050 - 29 Feb 2024
Viewed by 775
Abstract
An increasing number of methods are being used to extract rock discontinuities from 3D point cloud data of rock surfaces. In this paper, a new method for automatic extraction of rock discontinuity based on an improved Naive Bayes classifier is proposed. The method [...] Read more.
An increasing number of methods are being used to extract rock discontinuities from 3D point cloud data of rock surfaces. In this paper, a new method for automatic extraction of rock discontinuity based on an improved Naive Bayes classifier is proposed. The method first uses principal component analysis to find the normal vectors of the points, and then generates a certain number of random point sets around the selected training points for training the classifier. The trained, improved Naive Bayes classifier is based on point normal vectors and is able to automatically remove noise points due to various reasons in conjunction with the knee point algorithm, realizing high-precision extraction of the discontinuity sets. Subsequently, the individual discontinuities are segmented using a hierarchical density-based spatial clustering method with noise application. Finally, the PCA algorithm is used to complete the orientation by plane fitting the individual discontinuities. The method was applied in two cases, Kingston and Colorado, and the reliability and advantages of the new method were verified by comparing the results with those of previous research, and the discussion and analysis determined the optimal values of the relevant parameters in the algorithm. Full article
(This article belongs to the Special Issue Advances in Sustainable Geotechnical Engineering: 2nd Edition)
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