Damage index correlation in massive granite-porous backfills under hydromechanical triaxial cyclic loading using acoustic emissions and X-ray computed tomography

The characterization accuracy of damage indices in massive and porous composite biomaterials under complex osmotic conditions has long been a challenge in engineering materials science. Establishing correlations between damage indices calculated using different methodologies is crucial to validate and improve defects characterizations. In this study, we investigated the damage index correlation of cylindrical massive granite-porous backfill structural composites under both dry and seepage conditions. A series of triaxial cyclic loading and unloading tests were conducted on specimens under hydromechanical conditions with varying osmotic pressures (0, 1, 3, 5, 7, and 9 MPa) and a confining pressure of 9 MPa involving acoustic emission monitoring and phase-based 3D nondestructive CT scanning. The results revealed the AE energy was lower under osmotic conditions compared to dry conditions. The AE Damage Index ( D A E ), defined by separating tensile and shear microcracking signals, significantly increased from 0.32 to 0.55 with rising osmotic pressure. 3D mesoscopic fracture visualization provided detailed insights into the fractures in granite and backfill interfaces. The number of small-angle cracks increased with osmotic pressure, and the crack inclination distribution range expanded from 63°- 85° to 49°–80°. The average crack angle showed a significant monotonic decrease with increasing osmotic pressure. An Energy Dissipation Damage Index ( D E D ) was defined, and its correlation with the D A E under dry conditions was modeled using a reciprocal function D E D = a / ( D A E + b σ 3 ) + c . This novel approach offers insights into the transition points between tensile and shear-dominated failure stages. Furthermore, an exponential function D V = a D A E b ( b < 0 ) was used to model the correlation between AE Damage Index and Visual Damage Index ( D V ) under osmotic conditions. The damage indices derived from different methods can be mathematically correlated, providing a comprehensive evaluation of material damage states. The study found the flow transition between different natural-human medias results in different damage mechanisms, which are all obey the correlation law. These damage mechanisms offered constructive recommendations for engineering applications based on varying ratios of osmotic pressure to confining pressure.

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Publication Details

Journal
Journal of Materials Research and Technology
Published
2024-10-09
DOI
https://doi.org/10.1016/j.jmrt.2024.10.058
Citations
5
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
1.35
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article

Damage index correlation in massive granite-porous backfills under hydromechanical triaxial cyclic loading using acoustic emissions and X-ray computed tomography

Shengwen Qi, John Kemeny, Songfeng Guo, Yuye Tan et al.
5 citations
Journal of Materials Research and Technology
Rock Mechanics and Modeling
1.35
article

Damage index correlation in massive granite-porous backfills under hydromechanical triaxial cyclic loading using acoustic emissions and X-ray computed tomography

Shengwen Qi, John Kemeny, Songfeng Guo, Yuye Tan, Weidong Song, Xin Yu, Bowen Zheng
article en
5 citations

Abstract

The characterization accuracy of damage indices in massive and porous composite biomaterials under complex osmotic conditions has long been a challenge in engineering materials science. Establishing correlations between damage indices calculated using different methodologies is crucial to validate and improve defects characterizations. In this study, we investigated the damage index correlation of cylindrical massive granite-porous backfill structural composites under both dry and seepage conditions. A series of triaxial cyclic loading and unloading tests were conducted on specimens under hydromechanical conditions with varying osmotic pressures (0, 1, 3, 5, 7, and 9 MPa) and a confining pressure of 9 MPa involving acoustic emission monitoring and phase-based 3D nondestructive CT scanning. The results revealed the AE energy was lower under osmotic conditions compared to dry conditions. The AE Damage Index ( D A E ), defined by separating tensile and shear microcracking signals, significantly increased from 0.32 to 0.55 with rising osmotic pressure. 3D mesoscopic fracture visualization provided detailed insights into the fractures in granite and backfill interfaces. The number of small-angle cracks increased with osmotic pressure, and the crack inclination distribution range expanded from 63°- 85° to 49°–80°. The average crack angle showed a significant monotonic decrease with increasing osmotic pressure. An Energy Dissipation Damage Index ( D E D ) was defined, and its correlation with the D A E under dry conditions was modeled using a reciprocal function D E D = a / ( D A E + b σ 3 ) + c . This novel approach offers insights into the transition points between tensile and shear-dominated failure stages. Furthermore, an exponential function D V = a D A E b ( b < 0 ) was used to model the correlation between AE Damage Index and Visual Damage Index ( D V ) under osmotic conditions. The damage indices derived from different methods can be mathematically correlated, providing a comprehensive evaluation of material damage states. The study found the flow transition between different natural-human medias results in different damage mechanisms, which are all obey the correlation law. These damage mechanisms offered constructive recommendations for engineering applications based on varying ratios of osmotic pressure to confining pressure.

Journal of Materials Research and TechnologyVol. 33
Arizona Geological Survey (US), University of Arizona (US), Chinese Academy of Sciences (CN), Institute of Geology and Geophysics (CN), University of Chinese Academy of Sciences (CN), University of Science and Technology Beijing (CN)
Sustainable cities and communities, Climate action
Openalex Percentile: Top 22%
Rock Mechanics and Modeling
1.35
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