Research on mechanical properties and acoustic emission characteristics of rock beams with different lithologies and thicknesses

Zhao, Tianfeng; Zhang, Peng-fei; Guo, Wei‐yao; Xiao, Ya-xun; Zhao, Yongqiang; Sun, Xin

doi:10.1590/1679-78256711

Cited by 5 publications

(2 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The estimation of rock compressive strength typically involves various geotechnical in-situ or laboratory tests, including the uniaxial compressive strength (UCS) test 9 , Schmidt hammer test 10 , point-load test 11 , beam bending test 12 , ring shear test 13 , and triaxial compression test 14 . Among these, both UCS and point-load tests play a pivotal role in ore crusher design and the evaluation of rock strength for mining purposes.…”

Section: Introductionmentioning

confidence: 99%

Azarshahr travertine compression strength prediction based on point-load index (Is) data using multilayer perceptron

Mao,

Licai,

Feng

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Azarshahr County in the northwest of Iran is predominantly covered by Azarshahr travertine, a prevailing sedimentary rock. This geological composition has led to extensive open-pit mining activities, particularly in the western and southwestern parts of the county. The rock's drillability and resistance to excavation play a pivotal role in determining its overall durability and hardness, crucial factors that influence the mining process. These attributes are intimately tied to the compressive strength of the rock. Accurate assessment of rock strength is vital for devising reliable excavation methodologies at mining sites. However, conventional approaches for analyzing rock strength have limitations that undermine the precision of strength estimations. In response, this study endeavors to leverage artificial intelligence techniques, specifically the Multilayer Perceptron (MLP), to enhance the prediction of travertine's compressive strength. To formulate a robust model, a comprehensive database containing data from 150 point-load index (Is) tests on Azarshahr travertine was compiled. This dataset serves as the foundation for the development of the MLP-based predictive model, which proves instrumental in projecting rock compressive strength. The model's accuracy and efficacy were rigorously assessed using the Receiver Operating Characteristic (ROC) curve, employing both training and testing datasets. The modeling outcomes reveal impressive results. The estimated R-squared coefficient attained an impressive value of 0.975 for axial strength and 0.975 for diametral strength. The overall accuracy, as indicated by the Area Under the Curve (AUC) metric, stands at an impressive 0.968. These exceptional performance metrics underscore the efficacy of the MLP model in accurately predicting compressive strength based on the point-load index of samples. The implications of this study are substantial. The predictive model, empowered by the MLP approach, has profound implications for excavation planning and drillability assessment within the studied region's travertine deposits. By facilitating accurate forecasts of rock strength, this model equips mining endeavors with valuable insights for effective planning and execution.

show abstract

Section: Introductionmentioning

confidence: 99%

Azarshahr travertine compression strength prediction based on point-load index (Is) data using multilayer perceptron

Mao,

Licai,

Feng

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Several joints, fissures, and structural planes exist in rock masses because of geological tectonics and mining activities [1][2][3]. Crack propagation and coalescence are the primary reasons for the failure of engineering rock masses, which may cause dynamic instability of the roadway [4][5][6][7][8]. Therefore, research on the crack propagation and failure characteristics of jointed rock materials is necessary to clarify the failure mechanism of fractured rocks.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Behaviors and AE Characteristics of Brittle Coal Specimens with Different Fissure Angles

Guo

Zhang

et al. 2022

Geofluids

Self Cite

View full text Add to dashboard Cite

Uniaxial compression tests were performed on coal specimens with five fissure angles to study the mechanical behaviors and acoustic emission (AE) characteristics of fractured coals. AE and video monitoring techniques were used to examine crack propagation in the fractured specimens. The stress–strain curves, mechanical properties, and cracking processes at different fissure angles were analysed. The AE counts and dominant frequency characteristics, during the failure processes of the specimens, were investigated. In addition, five types of AE signals were classified according to the AE spectral frequency analysis, and low-frequency–high-energy signals were used to accurately predict the brittle fracture processes of the fractured specimens. Finally, a comparison with sandstone specimens revealed the influence of primary cracks on the strength of brittle coal specimens containing preexisting fissures under uniaxial compression. The test results are helpful to elucidate the mechanical behavior and failure mechanism in underground engineering, such as hydraulic slotting in mines.

show abstract

Failure prediction and microcracks development based on acoustic emission and energy evolution for different rocks treated with freeze–thaw weathering

Ullah,

Zhou,

Cai

et al. 2023

Bull Eng Geol Environ

View full text Add to dashboard Cite

Research on mechanical properties and acoustic emission characteristics of rock beams with different lithologies and thicknesses

Cited by 5 publications

References 32 publications

Azarshahr travertine compression strength prediction based on point-load index (Is) data using multilayer perceptron

Azarshahr travertine compression strength prediction based on point-load index (Is) data using multilayer perceptron

Mechanical Behaviors and AE Characteristics of Brittle Coal Specimens with Different Fissure Angles

Failure prediction and microcracks development based on acoustic emission and energy evolution for different rocks treated with freeze–thaw weathering

Contact Info

Product

Resources

About