Article
Engineering, Environmental
Guo-Feng Liu, Quan Jiang, Guang-Liang Feng, Dong-Fang Chen, Bing-Rui Chen, Zhou-Neng Zhao
Summary: This study proposed a method for early estimation of rockburst occurrence and scale based on microseismicity, using an established rockburst database, selection of typical rockburst samples, training of an artificial neural network (ANN) model, and dynamic updating. The method demonstrated reliable estimation of rockburst cases in drill-and-blast tunneling, providing a new approach for risk assessment and management.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Geosciences, Multidisciplinary
Ci Song, Runqiu Huang, Xiaolu Tang
Summary: This study assessed the impact of tunnel discharging on vegetation in the karst and non-karst areas during the construction of the Jinping II hydropower station in China. The results showed that while the overall vegetation remained largely unchanged, the vegetation in the karst area experienced a more significant decrease compared to the non-karst area. The research provides important insights for vegetation protection in large-scale underground construction worldwide.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Engineering, Civil
Diyuan Li, Zida Liu, Peng Xiao, Jian Zhou, Danial Jahed Armaghani
Summary: This paper investigates the drawbacks of neural networks in rockburst prediction and proposes a new method using Bayesian optimization and synthetic minority oversampling to optimize the feedforward neural network model. The method is proven to be accurate and effective through testing.
Article
Engineering, Electrical & Electronic
N. Safari, S. M. Mazhari, C. Y. Chung, S. B. Ko
Summary: This paper proposes a secure and accurate probabilistic model for predicting the transmission ampacity of overhead lines (OHL). The model is based on a deep learning architecture that utilizes various predictors and is trained using a customized cost function to consider security and minimize deviations. Experimental results validate the superiority of this model compared to existing prediction models.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Metallurgy & Metallurgical Engineering
Feng Guang-liang, Chen Bing-rui, Jiang Quan, Xiao Ya-xun, Niu Wen-jing, Li Peng-xiang
Summary: The study on excavation-induced microseismicity and rockburst occurrence in deep underground projects indicates the importance of these events in warning and analyzing rockburst occurrences. Differences in microseismicity and rockburst characteristics were found between parallel tunnels with different lithological conditions, emphasizing the complexity of predicting such events in deep tunnel projects.
JOURNAL OF CENTRAL SOUTH UNIVERSITY
(2021)
Article
Energy & Fuels
Jaewon Jung, Heechan Han, Kyunghun Kim, Hung Soo Kim
Summary: This study predicted the future potential of SHP using a climate change scenario and an artificial neural network model, showing a generally lower SHP potential compared to the past. This can serve as a basis for planning future energy supplies and reducing carbon emissions.
Article
Green & Sustainable Science & Technology
Alexandre Presas, David Valentin, Weiqiang Zhao, Carme Valero, Eduard Egusquiza
Summary: Hydraulic turbines, especially Francis turbines, face increasing fatigue issues, and using neural networks can reduce the complexity and cost of strain gauge testing.
Article
Geosciences, Multidisciplinary
Yong Fan, Xianze Cui, Zhendong Leng, Junwei Zheng, Feng Wang, Xiaole Xu
Summary: This research discussed the rockbursts that occurred during the construction of a diversion tunnel at Jinping II hydropower station and numerically described the brittle-ductile-plastic transition property of Jinping marble. The dynamic energy release process derived from the transient unloading of in-situ stress plays a crucial role in rockburst events.
FRONTIERS IN EARTH SCIENCE
(2021)
Article
Computer Science, Hardware & Architecture
Jinrui Zhang
Summary: This study designs a new multi-parameter monitoring platform using wireless sensor network, communication protocol, and Internet of things technology to predict and prevent rockburst accidents in deep coal mining. Two improvements are made to the Faster R-CNN model, resulting in better prediction performance. The experimental results demonstrate that the proposed system performs well in complex environments.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Engineering, Geological
Hongliang Tu, Hui Zhou, Yang Gao, Jingjing Lu, Hemant Kumar Singh, Chuanqing Zhang, Dawei Hu, Mingming Hu
Summary: The study conducted a probability analysis of deep-buried diversion tunnels using Monte Carlo simulation, with a case study of the Jinping II hydropower station diversion tunnels. The results showed that the vertical load and radial subgrade modulus are important factors affecting the safety of tunnel support structures.
INTERNATIONAL JOURNAL OF GEOMECHANICS
(2021)
Article
Computer Science, Artificial Intelligence
Meichang Zhang
Summary: This paper studied the rockburst risk prediction method based on particle swarm algorithm and neural network, using BP neural network for impact risk assessment and optimizing connection weights with PSO algorithm to improve accuracy; Experimental results show that the evaluation accuracy of the PSO-BP model is increased by 15% compared with the standard BP model.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Geosciences, Multidisciplinary
Peiyuan Li, Yin Yu, Daning Huang, Zhi-Hua Wang, Ashish Sharma
Summary: Heatwaves have catastrophic consequences and accurate predictions are crucial for climate preparedness. This paper proposes a heatwave prediction algorithm based on a novel deep learning model, GNN, which provides real-time warnings of regional heatwaves with high accuracy and low computation costs. The interpretable structure of the GNN framework helps unravel spatiotemporal patterns and enrich understanding of climate dynamics and causal influences. This framework can be extended to detect and predict other extreme climate events, requiring further studies.
GEOPHYSICAL RESEARCH LETTERS
(2023)
Article
Environmental Sciences
Chunchi Ma, Wenjin Yan, Weihao Xu, Tianbin Li, Xuefeng Ran, Jiangjun Wan, Ke Tong, Yu Lin
Summary: Microseismic monitoring can capture microseismic signals released from rock mass fractures to evaluate the development of geological disasters. However, the low signal-to-noise ratio of these signals due to complex environmental factors makes effective information extraction challenging. Therefore, denoising and detection are crucial for processing microseismic signals and extracting source information.
Article
Automation & Control Systems
Xovee Xu, Ting Zhong, Fan Zhou, Rongfan Li, Goce Trajcevski, Qinggang Meng
Summary: Landslides are hazardous events that result from geological (and meteorological) factors, causing extensive ground movements. Remote sensing technology allows for precise and continuous monitoring of terrain, facilitating the study and analysis of land deformations for prediction purposes.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Civil
Xinyu Wu, Zhiyong Chen, Chuntian Cheng, Shuai Yin, Huaying Su
Summary: A deep neural network SSDP (DNN-SSDP) method is proposed to solve the problem of multiple reservoir operations. The method combines DNN, SSDP, and simulation to improve the efficiency of the solution by using a small-scale and irregularly distributed state set.
JOURNAL OF HYDROLOGY
(2022)
Article
Engineering, Mechanical
Wenjing Niu, Xia-Ting Feng, Guangliang Feng, Yaxun Xiao, Zhibin Yao, Wei Zhang, Lei Hu
Summary: Rockbursts are complex dynamic engineering failures encountered in deep tunnels, and microseismic warning and safety control can reduce the damage and occurrence of rockburst failures. This study analyzes the behavior and microseismicity of rockbursts of different intensities, clarifies the factors and causes for rockburst warning, and establishes a method for selecting microseismic information for rockburst warning. The proposed method has been successfully applied in a tunnel for rockburst warning, effectively identifying over 85% of rockburst hazards.
ENGINEERING FAILURE ANALYSIS
(2022)
Article
Geochemistry & Geophysics
Yang Yu, Guang-liang Feng, Chang-jie Xu, Bing-rui Chen, Da-xin Geng, Bi-tang Zhu
Summary: This study investigates the quantitative threshold of energy fractal dimension for immediate rock burst warning in deep tunnels based on the cases of rock bursts in Jinping Hydropower Station in China. A calculation method for energy fractal dimension in deep linear tunnels associated with microseismic monitoring is proposed. The mechanism analysis assesses the distribution range and evolution of energy fractal dimension during the development of rock bursts. The results provide a guide for establishing a dynamic warning system and scientific basis for prediction, warning, and risk-control standards of rock burst disasters during the excavation of deep tunnels.
Article
Geosciences, Multidisciplinary
Chengcheng Gao, Manqing Lin, Yongxiong Lu, Dianji Zhang, Guangliang Feng, Xiaoshuai Liang
Summary: This paper investigates the failure process of phosphate rock under different loading rates by conducting infrared radiation and uniaxial compression tests. The results show that the higher the loading rate, the more pronounced the high-temperature zone and high-temperature point of phosphate rock during the loading process. As the loading rate increases, the energy release time of phosphate rock before damage decreases, resulting in more energy stored in the rock and ultimately leading to greater damage.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Geosciences, Multidisciplinary
Yang Yu, Da-Cheng Zhao, Guang-Liang Feng, Da-Xin Geng, Hao-Sen Guo
Summary: This study investigates the energy evolution and acoustic emission characteristics of layered sandstone under anchorage during deformation and failure. The results show that anchoring increases the energy storage capacity of sandstone and improves its toughness. The spatial distribution of acoustic emission events and damage in the anchored sandstone is more uniform. The changes in B and D values can be used as precursors to instability and failure.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Construction & Building Technology
Guang-Liang Feng, Bing-Rui Chen, Ya-Xun Xiao, Quan Jiang, Peng-Xiang Li, Hong Zheng, Wei Zhang
Summary: This study investigates the characteristics of microseismicity in deep tunnels constructed within alternating soft-hard strata and proposes a warning method for rockbursts based on the observed data. The findings provide valuable insights for understanding and predicting rockbursts in deep tunnels with complex lithologies.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2022)
Article
Geochemistry & Geophysics
Peiyang Yu, Peng-Zhi Pan, Guangliang Feng, Zhaofeng Wang, Shuting Miao
Summary: Understanding the time-dependent characteristics of Beishan granite after excavation is crucial for ensuring the long-term stability and disaster control of the high-level radioactive waste repository. Experimental results show that the unloading path significantly affects the instantaneous volume deformation, but has minor effects on creep strain. The axial and lateral creep strain are mainly determined by creep fracture potential, which can be evaluated using a unified time-dependent fracture potential index. A damage mechanical model based on time-dependent subcritical crack growth theory reveals that strain hardening dominates the granite creep process and the strain softening effect is enhanced with increasing fracture potential index.
Article
Metallurgy & Metallurgical Engineering
Jian-cong Zhang, Quan Jiang, Guang-liang Feng, Shao-jun Li, Shu-feng Pei, Ben-guo He
Summary: This study investigated the geological characteristics and crack patterns of columnar jointed basalt, and developed a method to simulate irregular polygonal crack patterns. The results revealed that geometric irregularity significantly affects the mechanical properties of columnar jointed rock mass.
JOURNAL OF CENTRAL SOUTH UNIVERSITY
(2022)
Article
Engineering, Geological
Fuqiang Ren, Chun Zhu, Manchao He, Junlong Shang, Guangliang Feng, Jinwen Bai
Summary: By conducting true triaxial unloading rockburst tests, the difference between static-driven and dynamically triggered rockbursts was examined. The study compared and analyzed the rockburst characteristics, intensities, and precursors of three different types of rockbursts. The findings suggest that the increment f (alpha) parameter and stress drop can be used for long-term monitoring and short-term prediction of rockbursts.
ROCK MECHANICS AND ROCK ENGINEERING
(2023)
Editorial Material
Chemistry, Multidisciplinary
Guang-Liang Feng, Sanichiro Yoshida, Giuseppe Lacidogna
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Environmental
Yang Yu, Jun Wang, Guang-Liang Feng, Da-Xin Geng, Hao-Sen Guo
Summary: The deterioration characteristics and damage principle of limestone under the coupling action of aqueous chemical solution and consecutive loading-unloading cycles were investigated. Laboratory cyclic consecutive loading-unloading test combined with acoustic emission monitoring was used to study the mechanics of limestone under different chemical corrosion conditions. The results showed that limestone exhibited more significant deterioration in peak strain and peak strength with lower pH acid and longer corrosion time. The quality, longitudinal wave velocity, and through-crack size of limestone were also affected by the acidic solution. The results provide experimental reference for evaluating the long-term stability of engineering rock mass.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2023)
Article
Mining & Mineral Processing
Haosen Guo, Qiancheng Sun, Guangliang Feng, Shaojun Li, Yaxun Xiao
Summary: The damage-fracture evolution of deep rock mass has distinct characteristics, as revealed by field tests in 2400-meter deep tunnels. The evolution of the excavation damaged zone depth is consistent with that of the fractured zone depth. The research results provide valuable insights for the monitoring and support design of future construction projects.
INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY
(2023)
Article
Metallurgy & Metallurgical Engineering
Guang-liang Feng, Jin-gang Ma, Bing-rui Chen, Ya-xun Xiao, Quan Jiang, Peng-xiang Li, Man-qing Lin
Summary: Rockburst hazards caused by excavation in deep TBM tunnels are a threat to construction safety. This study investigated the characteristics and intensity identification of rockburst events in deep TBM tunnels based on 43 events in the Neelum-Jhelum hydropower station in Pakistan. The study established a criterion for identifying rockburst intensity using the quantitative parameter of microseismic energy. The results showed a nonlinear relationship between rockburst intensity and microseismic energy, and the criterion was validated in the project as reliable for advance warning of rockburst events in deep TBM tunnels.
JOURNAL OF CENTRAL SOUTH UNIVERSITY
(2023)
Article
Mathematics, Interdisciplinary Applications
Xiu-yang Liu, Ding-ping Xu, Shu-qian Duan, Huai-sheng Xu, Guang-liang Feng, Shi-li Qiu, Quan Jiang
Summary: Exploring the mechanical properties and crack characteristics of granites at the grain scale is important to understand brittle failures in deep-buried hard rocks. This study derived the microscopic mechanical properties of granite minerals and discussed the relationship between these properties. A parameter calibration process was proposed to reduce randomness in the calibration process. The study also discussed the microcrack evolution and crack characteristics of different minerals in granite. The results reveal the crucial role of intragranular cracks in the failure process of brittle rocks.
COMPUTATIONAL PARTICLE MECHANICS
(2023)
Article
Engineering, Geological
Yaxun Xiao, Shujie Chen, Liu Liu, Guangliang Feng, Junbo Zhou, Dongbo Hou, Shaojun Li, Jianing Guo
Summary: This paper proposes a novel method based on instantaneous phase difference intensity (IPDI) for accurately determining the S-wave arrival time of microseismic signals in tunnels. The IPDI method can correctly determine the arrival time of S-waves even when they are overlapped by P-waves. The method was successfully applied to microseismic monitoring in a deeply buried tunnel, improving the accuracy of locating rockburst and microseismic events.
ROCK MECHANICS AND ROCK ENGINEERING
(2023)
Article
Engineering, Geological
Liu Guo-feng, Feng Kun, Yan Chang-gen, Feng Guang-liang, Xu Ding-ping, Zhou Chi
Summary: This study proposes a probabilistic evaluation method for excavation unloading response of rock slopes considering the uncertainty of mechanical parameters. The method is applied to analyze a cutting slope along the Beijing-Qinhuangdao expressway under construction. Probabilistic statistical models of rock mass mechanical parameters are constructed based on laboratory tests and geological survey data, and the simulation analysis is carried out to obtain probability distributions of slope safety factor, displacement, and plastic zone. The results show the applicability of the proposed method.
ROCK AND SOIL MECHANICS
(2023)
