Precursory and damage characteristics of static and dynamic failures in granite under biaxial compression with different loading rates: Insight from sound signals

In deep rock engineering, rocks adjacent to excavation boundaries, subjected to biaxial compression, frequently encounter severe static and dynamic hazards induced by construction activities. These processes generate abundant sound signals associated with rock pre-failures, although the beneficial characteristics of these signals remain inadequately understood. Their potential drives us to comprehensively explore the precursory and damage characteristics of static (spalling) and dynamic (rockburst) failures in granite under biaxial compression with different loading rates using sound signals. Based on the characteristic analysis of sound signals in the time and frequency domains, we identified multiple precursors correlated with the rock failures and introduced a prediction method for determining the rock failure modes (spalling and rockburst). Subsequently, the strong effects of loading rate on the sound precursors were revealed. Moreover, the proposed sound-based damage constitutive model for granite under biaxial compression with different loading rates was proven to be feasible. Furthermore, the amplitude-frequency properties of sound signals produced by rock cracking under biaxial compression were uncovered. The research results of this study improve the prediction and warning of static-dynamic mechanisms driven rock failures under biaxial compression through sound monitoring technology.

Authors

Institutions

Publication Details

Journal
International Journal of Damage Mechanics
Published
2025-06-18
DOI
https://doi.org/10.1177/10567895251329702
Citations
1
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.86

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Precursory and damage characteristics of static and dynamic failures in granite under biaxial compression with different loading rates: Insight from sound signals

Peifeng Li, Guoshao Su, Salvatore Martino, Suoting Hu et al.
1 citations
International Journal of Damage Mechanics
Rock Mechanics and Modeling
0.86
article

Precursory and damage characteristics of static and dynamic failures in granite under biaxial compression with different loading rates: Insight from sound signals

Peifeng Li, Guoshao Su, Salvatore Martino, Suoting Hu, Zonghui Liu
article en
1 citations

Abstract

In deep rock engineering, rocks adjacent to excavation boundaries, subjected to biaxial compression, frequently encounter severe static and dynamic hazards induced by construction activities. These processes generate abundant sound signals associated with rock pre-failures, although the beneficial characteristics of these signals remain inadequately understood. Their potential drives us to comprehensively explore the precursory and damage characteristics of static (spalling) and dynamic (rockburst) failures in granite under biaxial compression with different loading rates using sound signals. Based on the characteristic analysis of sound signals in the time and frequency domains, we identified multiple precursors correlated with the rock failures and introduced a prediction method for determining the rock failure modes (spalling and rockburst). Subsequently, the strong effects of loading rate on the sound precursors were revealed. Moreover, the proposed sound-based damage constitutive model for granite under biaxial compression with different loading rates was proven to be feasible. Furthermore, the amplitude-frequency properties of sound signals produced by rock cracking under biaxial compression were uncovered. The research results of this study improve the prediction and warning of static-dynamic mechanisms driven rock failures under biaxial compression through sound monitoring technology.

International Journal of Damage MechanicsVol. 34(10)
Ministry of Education of the People's Republic of China (CN), Guangxi University (CN), Sapienza University of Rome (IT)
National Natural Science Foundation of China, China Scholarship Council
Sustainable cities and communities
Openalex Percentile: Top 29%
Rock Mechanics and Modeling
0.86
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.