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Velocity tomography of cross-sectional damage evolution along rock longitudinal direction under uniaxial loading
Graphical abstract Display Omitted
Highlights The damage pattern of the loaded rock exhibits end effects. Tomography visualizes the damage evolution of the loaded rocks in a 3D manner. Heterogeneity is explicitly considered when analyzing the damage evolution of the rock sample. Kalman filter-based tomography can invert the rock damage evolution and simultaneously obtain the velocity model’s uncertainty.
Abstract Rock pillars in rock engineering are affected by the stress concentration, which is uneven and can lead to potential instability after loading disturbance. In this paper, considering the heterogeneity of the rock, time-dependent velocity tomography based on the Kalman filter system is adopted to invert the velocity evolution of the rock monitored via acoustic emission (AE) under diverse stresses. Furthermore, the tomography uncertainty is investigated to validate the experimental accuracy of the loaded rock. The experimental results show that Kalman filter-based tomography can characterize the damages of the loaded rock, which is influenced by the distance from the sample’s end and heterogeneity of the rock. The rock damage and its growth rate increase when the loading increases or the cross section approaches the mid-waistline. The model uncertainty analysis demonstrates that the velocity tomography based on the Kalman filter has a high precision. Our study shows that for evaluating the stability of bearing rock pillars, we can simplify the rock pillar as a uniaxial loading rock and need to consider the rock’s heterogeneity for understanding the damage distribution and evolution of the loaded rock.
Velocity tomography of cross-sectional damage evolution along rock longitudinal direction under uniaxial loading
Graphical abstract Display Omitted
Highlights The damage pattern of the loaded rock exhibits end effects. Tomography visualizes the damage evolution of the loaded rocks in a 3D manner. Heterogeneity is explicitly considered when analyzing the damage evolution of the rock sample. Kalman filter-based tomography can invert the rock damage evolution and simultaneously obtain the velocity model’s uncertainty.
Abstract Rock pillars in rock engineering are affected by the stress concentration, which is uneven and can lead to potential instability after loading disturbance. In this paper, considering the heterogeneity of the rock, time-dependent velocity tomography based on the Kalman filter system is adopted to invert the velocity evolution of the rock monitored via acoustic emission (AE) under diverse stresses. Furthermore, the tomography uncertainty is investigated to validate the experimental accuracy of the loaded rock. The experimental results show that Kalman filter-based tomography can characterize the damages of the loaded rock, which is influenced by the distance from the sample’s end and heterogeneity of the rock. The rock damage and its growth rate increase when the loading increases or the cross section approaches the mid-waistline. The model uncertainty analysis demonstrates that the velocity tomography based on the Kalman filter has a high precision. Our study shows that for evaluating the stability of bearing rock pillars, we can simplify the rock pillar as a uniaxial loading rock and need to consider the rock’s heterogeneity for understanding the damage distribution and evolution of the loaded rock.
Velocity tomography of cross-sectional damage evolution along rock longitudinal direction under uniaxial loading
Zheng, Qiangqiang (author) / Qian, Jiawei (author) / Zhang, Haijiang (author) / Chen, Yukuan (author) / Zhang, Shihuai (author)
2023-11-11
Article (Journal)
Electronic Resource
English
British Library Online Contents | 2018
|Concrete Damage under Fatigue Loading in Uniaxial Compression
British Library Online Contents | 2017
|Concrete Damage under Fatigue Loading in Uniaxial Compression
Online Contents | 2017
|Concrete Damage under Fatigue Loading in Uniaxial Compression
Online Contents | 2017
|