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Brittleness evaluation of gas-bearing coal based on statistical damage constitution model and energy evolution mechanism
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作者 XUE Yi WANG Lin-chao +5 位作者 LIU Yong RANJITH P G CAO Zheng-zheng SHI Xu-yang GAO Feng KONG Hai-ling 《Journal of Central South University》 2025年第2期566-581,共16页
Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a ... Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions. 展开更多
关键词 gas pressure statistical damage constitutive model energy evolution mechanism brittleness evaluation gas bearing coal
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Energy evolution mechanism and failure criteria of jointed surrounding rock under uniaxial compression 被引量:26
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作者 LI Peng CAI Mei-feng 《Journal of Central South University》 SCIE EI CAS CSCD 2021年第6期1857-1874,共18页
The object of this article is to investigate the energy evolution mechanism and failure criteria of cross-jointed samples containing an opening during deformation and failure based on the uniaxial compression test and... The object of this article is to investigate the energy evolution mechanism and failure criteria of cross-jointed samples containing an opening during deformation and failure based on the uniaxial compression test and rock energy principle.The results show that the energy evolution characteristics of the samples correspond to a typical progressive damage mode.The peak total energy,peak elastic energy,and total input energy of the samples all first decrease and then increase with an increase of half of the included angle,reaching their minimum values when this angle is 45°,while the dissipated energy generally increases with this angle.The existence of the opening and cross joints can obviously weaken the energy storage capacity of the rock,and the change in the included angle of the cross joint has a great influence on the elastic energy ratio of the sample before the peak stress,which leads to some differences in the distribution laws of the input energy.The continuous change and the subsequent sharp change in the rate of change in the energy consumption ratio can be used as the criteria of the crack initiation and propagation and the unstable failure of the sample,respectively. 展开更多
关键词 energy evolution mechanism failure criteria jointed rock mass cross joint uniaxial compression
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Test selection and optimization for PHM based on failure evolution mechanism model 被引量:8
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作者 Jing Qiu Xiaodong Tan +1 位作者 Guanjun Liu Kehong L 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2013年第5期780-792,共13页
The test selection and optimization (TSO) can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management (PHM) systems. Traditionally, TSO mainly focuse... The test selection and optimization (TSO) can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management (PHM) systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability (DFT) to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model (FEMM) for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm (ASAGA) is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level. 展开更多
关键词 test selection and optimization (TSO) prognostics and health management (PHM) failure evolution mechanism model (FEMM) adaptive simulated annealing genetic algorithm (ASAGA).
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