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Applied Sciences
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Application of Artificial Intelligence in Rock Mass Engineering
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Application of Artificial Intelligence in Rock Mass Engineering

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

Deadline for manuscript submissions: 31 May 2025 | Viewed by 4091

Special Issue Editors

Prof. Dr. Jun Zheng

E-Mail Website
Guest Editor
Department of Civil Engineering, Zhejiang University, Hangzhou 310058, China
Interests: geotechnical engineering; engineering geology; geological hazards; slope engineering; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Dr. Mingming He

E-Mail Website
Guest Editor
School of Civil Engineering and Architecture, Xi’an University of Technology, Xi’an 710048, China
Interests: unconventional rock mechanical behavior; stability of deep tunnels; geotechnical deep learning and artificial intelligence; digital drilling technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This exclusive collection aims to showcase the latest advancements, cutting-edge research and practical applications of artificial intelligence (AI) in the field of rock mass engineering. The Special Issue will encompass a wide array of topics related to the integration of AI techniques in rock mass engineering, including, but not limited to: (1) AI-based predictive modeling for rock behavior and geomechanical analysis, (2) machine learning algorithms for rock mass classification and characterization, (3) deep learning applications in rock mass deformation and stability analysis, (4) AI-driven optimization and decision-making in rock engineering projects, (5) virtual reality and simulation technologies using AI for rock mass visualization and analysis, (6) application of AI in acquiring and modeling geometric parameters of rock masses, (7) AI-driven rock mass sensing and measurement techniques and (8) data processing and intelligent monitoring systems for sensor data in rock engineering

Dr. Jun Zheng
Dr. Mingming He
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

  • rock mass
  • machine learning
  • discontinuity detection
  • rock engineering
  • deep learning
  • big data
  • artificial intelligence

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Published Papers (2 papers)

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Research

20 pages, 10843 KiB  
Article
Experimental and Numerical Simulations on the Mechanical Characteristics of Soil–Rock Mixture in Uniaxial Compression
by Zhenping Zhang, Xiaodong Fu, Qian Sheng, Shuo Wang and Yuwei Fang
Appl. Sci. 2024, 14(22), 10485; https://doi.org/10.3390/app142210485 - 14 Nov 2024
Viewed by 890
Abstract
Soil–rock mixture is a common geo-material found in natural deposit slopes and various constructions, such as tunnels, hydropower stations, and subgrades. The complex mechanical characteristics of soil–rock mixture arise from its multi-phase compositions and cooperative interactions. This paper investigated the mechanical properties of [...] Read more.
Soil–rock mixture is a common geo-material found in natural deposit slopes and various constructions, such as tunnels, hydropower stations, and subgrades. The complex mechanical characteristics of soil–rock mixture arise from its multi-phase compositions and cooperative interactions. This paper investigated the mechanical properties of soil–rock mixture, focusing on the influence of rock content, and soil–rock interface strength was discussed. Specimens with varying rock contents were subjected to uniaxial compression tests. The results indicated that rock content, as a key structural parameter, significantly controls the crack propagation trends. As rock content increases, the initial structure of the soil matrix is damaged, leading to the formation of a weak-strength soil–rock interface. The failure mode transitions from longitudinal cracking to multiple shear fractures. To analyze the strength of the soil–rock interface from a mesoscopic perspective, simulations of soil–rock mixture specimens with irregular rock blocks were conducted using the particle discrete element method (PDEM). At the meso-scale, the specimen with 30% rock content exhibited a complex particle displacement distribution, with differences in the direction and magnitude of displacement between soil and rock particles being critical to the failure modes of the specimen. As the soil–rock interface strength increased from 0.1 to 0.9, the distribution of force chains within the specimen shifted from a centralized to a more uniform distribution, and the thickness of force chains became increasingly uniform. The strength responses of the soil–rock mixture under uniaxial compression condition were discussed, revealing that the uniaxial compression strength (UCS) of soil–rock mixture decreases exponentially with increasing rock content. An estimation formula was developed to characterize the UCS of soil–rock mixture in relation to rock content and interface strength. The findings from both the experiments and simulations can provide valuable insights for evaluating the stability of deposit slopes and other constructions involving soil–rock mixture. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in Rock Mass Engineering)
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26 pages, 7890 KiB  
Article
Investigation of the Rock-Breaking Mechanism of Drilling under Different Conditions Using Numerical Simulation
by Xinxing Liu, Hao Kou, Xudong Ma and Mingming He
Appl. Sci. 2023, 13(20), 11389; https://doi.org/10.3390/app132011389 - 17 Oct 2023
Cited by 2 | Viewed by 2311
Abstract
The interaction between the drill bit and rock is a complex dynamic problem in the process of drilling and breaking rock. In this paper, the dynamic process of drilling and breaking rock is analyzed using ABAQUS software. The rock-breaking mechanism of drilling is [...] Read more.
The interaction between the drill bit and rock is a complex dynamic problem in the process of drilling and breaking rock. In this paper, the dynamic process of drilling and breaking rock is analyzed using ABAQUS software. The rock-breaking mechanism of drilling is revealed according to the stress–strain state of the rock and the force of the drill bit. The effect of the size of the drill bit and the characteristics of the rock mass on the drilling parameters is studied during the drilling process. The results show that both thrust force and torque show a linear increase with the increasing drilling speed under each fixed rotational speed. The drill bit size has minimal impact on the correlation coefficient of the relationship curves between thrust force, torque, and rotation speed. The drilling results in a soft–hard interlayered rock formation show that there are significant differences in thrust force and torque during the drilling process of different rock types. Whether transitioning from a soft rock layer to a hard rock layer or vice versa, the relationship between thrust force and torque is distinctly manifested whenever there is a change in rock quality. The thrust force and torque increase correspondingly with the increase in confining pressure. When subjected to lateral pressure, thrust force and torque gradually increase with the rising confining pressure. Vertical drilling exhibits a larger increase in thrust force and torque compared to horizontal drilling. The thrust force and torque increase more significantly with the rise in confining pressure compared to lateral pressure. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in Rock Mass Engineering)
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