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Applied Sciences
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The Advances of Rock Dynamics
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The Advances of Rock Dynamics

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

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 9371

Special Issue Editor

Dr. Tianhui Ma

E-Mail Website
Guest Editor
State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
Interests: rockburst; monitoring and early warning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is devoted to the research of rockburst-related technology. Rock dynamics are related to statics. The object studied by the latter is the force field response of rocks to the surrounding physical environment under static equilibrium conditions, ignoring the inertial effect of medium units. Rock dynamics research studies the effect of the impact load on rock. This research field is closely related to water conservation, hydropower, transportation, railway, energy, mining and construction engineering, protection engineering, and national defense construction. Although there have been no major breakthroughs in the study of rockburst mechanisms, continuous progress is being made in rockburst prediction and early warning systems.

Potential topics include, but are not limited to:

  1. Dynamic mechanical properties and the constitutive relation of rock;
  2. The propagation and attenuation law of stress wave in rock mass;
  3. Dynamic failure mechanisms and the numerical simulation of rock;
  4. Safety and protection in rock engineering;
  5. Dynamic stability analysis of rock caves, foundations, and slopes;
  6. Rock blasting technology;
  7. Study of the mechanism of rockbursts;
  8. Dynamic disaster monitoring of rock engineering;
  9. New techniques and methods for testing rock dynamic parameters;
  10. Other studies related to rock dynamics.

Prof. Dr. Tianhui Ma
Guest Editor

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.

Published Papers (6 papers)

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Research

20 pages, 4820 KiB  
Article
Research on the Design of Coal Mine Microseismic Monitoring Network Based on Improved Particle Swarm Optimization
by Kaikai Wang, Chun’an Tang, Ke Ma and Tianhui Ma
Appl. Sci. 2022, 12(17), 8439; https://doi.org/10.3390/app12178439 - 24 Aug 2022
Cited by 2 | Viewed by 1313
Abstract
The quality of a mine’s microseismic network layout directly affects the location accuracy of the microseismic network. Introducing the microseismic probability factor Fe, the microseismic importance factor FQ, and the effective range factor FV, an improved particle [...] Read more.
The quality of a mine’s microseismic network layout directly affects the location accuracy of the microseismic network. Introducing the microseismic probability factor Fe, the microseismic importance factor FQ, and the effective range factor FV, an improved particle swarm algorithm with bacterial foraging algorithm is proposed to optimize the mine’s microseismic network layout and evaluation system based on the D-value optimization design theory. Through numerical simulation experiments, it is found that the system has the advantages of fast optimization speed and good network layout effect. Combined with the system application at Xiashijie Coal Mine in Tongchuan City, Shaanxi Province, the method in this paper successfully optimizes the layout of the 20-channel network, ensuring that the positioning error of key monitoring areas is controlled within 20 m, and the minimum measurable magnitude can reach −3.26. Finally, it is verified by blasting tests that the maximum spatial positioning accuracy of the site is within 12.2 m, and the positioning capability of the site network is more accurately evaluated. The relevant research can provide a reference for the layout of the microseismic monitoring network for similar projects. Full article
(This article belongs to the Special Issue The Advances of Rock Dynamics)
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17 pages, 3465 KiB  
Article
Experimental Study on Dynamic Mechanical Properties of Sandstone Corroded by Strong Alkali
by Qi Ping, Chen Wang, Qi Gao, Kaifan Shen, Yulin Wu, Shuo Wang and Shijia Sun
Appl. Sci. 2022, 12(15), 7635; https://doi.org/10.3390/app12157635 - 28 Jul 2022
Cited by 2 | Viewed by 1216
Abstract
In order to analyze the effect of different corrosion times on the dynamic compression mechanical properties of sandstone, the coal mine sandstone specimens are subjected to corrosion in NaOH solution with pH 11 for 0 d, 1 d, 3 d, 7 d, 14 [...] Read more.
In order to analyze the effect of different corrosion times on the dynamic compression mechanical properties of sandstone, the coal mine sandstone specimens are subjected to corrosion in NaOH solution with pH 11 for 0 d, 1 d, 3 d, 7 d, 14 d, and 28 d, and then, the impact compression tests and Brazilian splitting test are conducted using a split Hopkinson pressure bar apparatus. The study results show that sandstone specimen mass and the average density growth rate increases, with the corrosion time first rapidly increasing and then tending to level off the trend. The impact of the compression specimens on the dynamic stress–strain curve change law is basically the same, but the time gradient curve shape is different, and the line elastic deformation stage and plastic deformation stage curve difference gradually decreases. The specimen dynamic compressive strength and the dynamic elastic modulus with corrosion time are quadratic, and the exponential function declines the relationship. After corrosion of 28 d sandstone specimens, the dynamic compressive strength and dynamic elastic modulus are much lower than the uncorroded specimens. The average strain rate and the dynamic peak strain with the corrosion time extension are a quadratic function of the increasing relationship after the corrosion effect of the sandstone dynamic peak strain, and the average strain rate is significantly greater than the uncorroded specimens. With the corrosion time extension of sandstone specimens by the impact of damage degree being increased, the 14 d and 28 d specimen ruptures’ degree is much greater than other time gradients. The dynamic tensile strength of the split specimens decreases with increasing corrosion time; the dynamic peak strain increases quadratically; and the transmitted energy also decreases with increasing corrosion time. Full article
(This article belongs to the Special Issue The Advances of Rock Dynamics)
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21 pages, 5038 KiB  
Article
Research on Prediction of TBM Performance of Deep-Buried Tunnel Based on Machine Learning
by Tianhui Ma, Yang Jin, Zheng Liu and Yadav Kedar Prasad
Appl. Sci. 2022, 12(13), 6599; https://doi.org/10.3390/app12136599 - 29 Jun 2022
Cited by 4 | Viewed by 1243
Abstract
Based on the relevant data in the construction process of the south of the Qinling tunnel of the Hanjiang-to-Weihe River Diversion Project, this article obtains the main influencing factors of the tunnel boring machine (TBM) performance of the deep-buried tunnel. According to the [...] Read more.
Based on the relevant data in the construction process of the south of the Qinling tunnel of the Hanjiang-to-Weihe River Diversion Project, this article obtains the main influencing factors of the tunnel boring machine (TBM) performance of the deep-buried tunnel. According to the characteristics of deep-buried tunnel excavation, the random forest algorithm is used to select the features of the factors affecting the TBM penetration rate, and the four factors with large influence weights including total thrust, revolutions per minute, uniaxial compressive strength and volumetric joint count, are used as TBM penetration rate prediction models input parameters, which can improve the prediction accuracy and convergence speed of the model, and enhance the engineering practicality of the prediction model. Three types of TBM penetration rate prediction models are established: multiple regression model (MR), back propagation neural network model (BPNN) and support vector regression model (SVR). The prediction accuracy of the three models is compared and analyzed. The BPNN prediction model exhibits better prediction performance and generalization ability than the multiple regression model and SVR model, which manifest higher prediction accuracy and prediction stability. Full article
(This article belongs to the Special Issue The Advances of Rock Dynamics)
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16 pages, 2965 KiB  
Article
Mine-Microseismic-Signal Recognition Based on LMD–PNN Method
by Qiang Li, Yingchun Li and Qingyuan He
Appl. Sci. 2022, 12(11), 5509; https://doi.org/10.3390/app12115509 - 29 May 2022
Cited by 3 | Viewed by 1364
Abstract
The effective recognition of microseismic signal is related to the accuracy of mine-dynamic-disaster precursor-information processing, which is a difficult method of microseismic-data processing. A mine-microseismic-signal-identification method based on LMD energy entropy and the probabilistic neural network (PNN) is proposed. First, the Local-Mean-Decomposition (LMD) [...] Read more.
The effective recognition of microseismic signal is related to the accuracy of mine-dynamic-disaster precursor-information processing, which is a difficult method of microseismic-data processing. A mine-microseismic-signal-identification method based on LMD energy entropy and the probabilistic neural network (PNN) is proposed. First, the Local-Mean-Decomposition (LMD) method is used to decompose the mine microseismic signal. Considering the problem of vector redundancy, combined with the correlation-coefficient method, the energy entropy of the effective product-function component (PF) is extracted as the feature vector of mine-microseismic-signal classification. Furthermore, the probabilistic neural network (PNN) is used for learning and training, and the blasting-vibration signal and the coal–rock-mass-rupture signal are effectively identified. The test results show that the recognition accuracy of the PNN is up to 90%, the calculation time and classification effect of the PNN are better, and the recognition accuracy is increased by 15% and 7.5%, respectively, compared with the traditional PBNN and GRNN. This method can accurately and effectively identify the microseismic signals of mines and has good generalization performance. Full article
(This article belongs to the Special Issue The Advances of Rock Dynamics)
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20 pages, 8964 KiB  
Article
Numerical Studies on Rockbursts in Tunnels with High In Situ Stresses and Geothermally Rich Areas
by Zhonglian Luo, Jiaming Li, Shibin Tang, Xiaoshuang Li and Leitao Zhang
Appl. Sci. 2022, 12(10), 5108; https://doi.org/10.3390/app12105108 - 19 May 2022
Cited by 1 | Viewed by 1237
Abstract
To further understand the stress evolution and rockburst occurrence mechanism in geothermally rich areas in the Sichuan–Tibet railway project, this work presents a theoretical study of the influence of temperature change on the failure of rock, conducts numerical studies of the temperature and [...] Read more.
To further understand the stress evolution and rockburst occurrence mechanism in geothermally rich areas in the Sichuan–Tibet railway project, this work presents a theoretical study of the influence of temperature change on the failure of rock, conducts numerical studies of the temperature and stress evolution in the surrounding rock during high-temperature tunnel excavation, and further studies the possibility of rockbursts under high in situ stress and high-temperature conditions. Rockbursts occur frequently at the junction of a face and tunnel wall, and ventilation and cooling of tunnels reduce the stress and sometimes reduce the possibility of rockbursts. Continuous cooling leads to a larger tensile stress and the possibility of failure of wall rock. In addition, the influence of the convection heat transfer coefficient, in situ stress and fault effect on the stress distribution and possibility of rockbursts are also discussed in detail. The results are beneficial for the prevention and control of rockbursts in high in situ stress and geothermally rich areas. Full article
(This article belongs to the Special Issue The Advances of Rock Dynamics)
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15 pages, 8677 KiB  
Article
Dynamic Evolution Characteristics of Oil–Gas Coupling Fractures and Dynamic Disaster of Coal Mass in Coal and Oil Resources Co-Storage Areas
by Yawu Shao, Yonglu Suo, Jiang Xiao, Yuan Bai, Tao Yang and Siwei Fan
Appl. Sci. 2022, 12(9), 4499; https://doi.org/10.3390/app12094499 - 29 Apr 2022
Cited by 4 | Viewed by 1106
Abstract
The dynamic evolution characteristics of fracture are crucial to analyzing the development of coal and rock mass instability, gas diffusion law, and dynamic disaster prediction. These characteristics affect coal rock fractures and gas-induced disaster channels. Based on the experimental results, we found the [...] Read more.
The dynamic evolution characteristics of fracture are crucial to analyzing the development of coal and rock mass instability, gas diffusion law, and dynamic disaster prediction. These characteristics affect coal rock fractures and gas-induced disaster channels. Based on the experimental results, we found the following: In areas rich in both coal and oil, the coal mass damage due to high-pressure oil diffusion was inversely correlated with the distance of the coal mass from the disaster source. Moreover, as the coal mass became closer to the disaster source in the abandoned oil well, the average CT number reduced, mechanical performance diminished, fracture volume ratio increased, and capacity of the oil and gas storage improved. The four-dimensional analysis of the rock evolution and strength grade showed that coal mass stress, fracture propagation, and AE incidents were characterized by a low-strength compression stage featured by tensile fractures, medium-strength elastic stage with shear fractures replacing tensile fractures, and high-strength rapid fracture stage with rapid growth in shear fracture quantity and intensity. The dynamic conversion between coal mass instability disaster in coal and oil resources co-storage areas and oil and gas disaster was clarified. We propose high strength, high RA, and low AF of AE incidents in the rapid fracturing stage as the qualitative warning factors for the fracture of coal mass and the occurrence of oil and gas disaster. Full article
(This article belongs to the Special Issue The Advances of Rock Dynamics)
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