Prediction of fracture and dilatancy in granite using acoustic emission signal cloud

The invisibility of fracture network evolution in the rock under triaxial compression seriously restricts the correlation modeling between dilatancy behavior and fracture interconnectivity. The key to solving such a challenge is strongly dependent on the accurate modeling of the spatial correlation...

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Main Authors: Dongjie Xue, Lan Lu, Lie Gao, Lele Lu, Cheng Chen
Format: Article
Language:English
Published: Elsevier 2021-10-01
Series:Journal of Rock Mechanics and Geotechnical Engineering
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1674775521000822
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author Dongjie Xue
Lan Lu
Lie Gao
Lele Lu
Cheng Chen
author_facet Dongjie Xue
Lan Lu
Lie Gao
Lele Lu
Cheng Chen
author_sort Dongjie Xue
collection DOAJ
description The invisibility of fracture network evolution in the rock under triaxial compression seriously restricts the correlation modeling between dilatancy behavior and fracture interconnectivity. The key to solving such a challenge is strongly dependent on the accurate modeling of the spatial correlation in fracture network, which could be indirectly re-constructed by the acoustic emission (AE) signal cloud. Considering the interaction of local fractures, a cube cluster approach is established to describe the spatial correlation. The evolutional cube clusters effectively present the geometric characteristics induced by the increasing dilatancy of fracture. Two descriptors (i.e. three-axis length sum and pore fraction) are introduced to correlate cluster model with dilatancy behavior. Most fitting results support the linear correlation between two descriptors and volumetric strain, which verifies the sensitiveness of the cube cluster model to dilatancy. More importantly, by the statistical analysis of cluster structure, the cluster model shows the potential of calculating fracture angle. Moreover, a comparison between dilatancy-based damage and porosity-based damage is made not to prove the best but provide an AE-based prediction of local damage evolution. Finally, four classical models for calculating fracture angle are compared. The deviations prove the huge difficulty of describing the development of the fracture network uniquely dependent on a fracture angle. The proximity of measured angle and cluster-based angle supports the effectiveness of predication by the cube cluster approach.
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spelling doaj.art-cc3b4bc6240c44aa8da7a46768cd5b622022-12-21T21:30:02ZengElsevierJournal of Rock Mechanics and Geotechnical Engineering1674-77552021-10-0113510591077Prediction of fracture and dilatancy in granite using acoustic emission signal cloudDongjie Xue0Lan Lu1Lie Gao2Lele Lu3Cheng Chen4School of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, 100083, China; State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing, 400030, China; Key Laboratory of Safety and High-efficiency Coal Mining, Anhui University of Science and Technology, Huainan, 232001, China; Corresponding author. School of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, 100083, China.School of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, 100083, ChinaSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, 100083, ChinaSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, 100083, ChinaSchool of Mechanics and Civil Engineering, China University of Mining and Technology, Beijing, 100083, ChinaThe invisibility of fracture network evolution in the rock under triaxial compression seriously restricts the correlation modeling between dilatancy behavior and fracture interconnectivity. The key to solving such a challenge is strongly dependent on the accurate modeling of the spatial correlation in fracture network, which could be indirectly re-constructed by the acoustic emission (AE) signal cloud. Considering the interaction of local fractures, a cube cluster approach is established to describe the spatial correlation. The evolutional cube clusters effectively present the geometric characteristics induced by the increasing dilatancy of fracture. Two descriptors (i.e. three-axis length sum and pore fraction) are introduced to correlate cluster model with dilatancy behavior. Most fitting results support the linear correlation between two descriptors and volumetric strain, which verifies the sensitiveness of the cube cluster model to dilatancy. More importantly, by the statistical analysis of cluster structure, the cluster model shows the potential of calculating fracture angle. Moreover, a comparison between dilatancy-based damage and porosity-based damage is made not to prove the best but provide an AE-based prediction of local damage evolution. Finally, four classical models for calculating fracture angle are compared. The deviations prove the huge difficulty of describing the development of the fracture network uniquely dependent on a fracture angle. The proximity of measured angle and cluster-based angle supports the effectiveness of predication by the cube cluster approach.http://www.sciencedirect.com/science/article/pii/S1674775521000822Fracture networkAcoustic emission (AE)Spatial correlationDilatancyDamageFracture angle
spellingShingle Dongjie Xue
Lan Lu
Lie Gao
Lele Lu
Cheng Chen
Prediction of fracture and dilatancy in granite using acoustic emission signal cloud
Journal of Rock Mechanics and Geotechnical Engineering
Fracture network
Acoustic emission (AE)
Spatial correlation
Dilatancy
Damage
Fracture angle
title Prediction of fracture and dilatancy in granite using acoustic emission signal cloud
title_full Prediction of fracture and dilatancy in granite using acoustic emission signal cloud
title_fullStr Prediction of fracture and dilatancy in granite using acoustic emission signal cloud
title_full_unstemmed Prediction of fracture and dilatancy in granite using acoustic emission signal cloud
title_short Prediction of fracture and dilatancy in granite using acoustic emission signal cloud
title_sort prediction of fracture and dilatancy in granite using acoustic emission signal cloud
topic Fracture network
Acoustic emission (AE)
Spatial correlation
Dilatancy
Damage
Fracture angle
url http://www.sciencedirect.com/science/article/pii/S1674775521000822
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AT liegao predictionoffractureanddilatancyingraniteusingacousticemissionsignalcloud
AT lelelu predictionoffractureanddilatancyingraniteusingacousticemissionsignalcloud
AT chengchen predictionoffractureanddilatancyingraniteusingacousticemissionsignalcloud