Real-time forecasting of brittle rock failure: a robust acoustic emission approach validated on a large experimental dataset

Abstract Accurate and real-time forecasting of brittle rock failure remains a major challenge in geotechnical engineering and mining safety. In this study, a novel failure forecasting method based on acoustic emission (AE) monitoring was proposed and validated using a large experimental dataset of 403 sandstone specimens subjected to uniaxial compression. A new early warning indicator, WI b —the b-value change rate per unit time—was developed to capture the frequency and amplitude of b-value fluctuations, which intensify as microcracking evolves toward macroscopic failure. WI b was computed continuously during loading, and a statistically adaptive threshold was established using the evolving mean and standard deviation of WI b . The results demonstrated that WI b consistently escalated before failure in all specimens, with warning signals occurring at loads averaging 76.7% of the ultimate compressive strength. Sensitivity analyses confirmed the robustness of the method across variations in b-value calculation parameters and AE sensor configurations. Importantly, WI b and its threshold were calculated solely from real-time data without requiring knowledge of the full loading path, ensuring practical applicability. The proposed approach offers a physically meaningful and operationally viable solution for real-time rock failure forecasting and has potential for integration into field-scale AE or microseismic monitoring systems.

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Publication Details

Journal
GeoEnergy Communications
Published
2026-01-13
DOI
https://doi.org/10.1007/s44421-025-00014-1
Citations
1
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
18.34

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article

Real-time forecasting of brittle rock failure: a robust acoustic emission approach validated on a large experimental dataset

Chaodong Xi, Fuqiang Gao, Zhiguo Lu, Wenju Liu et al.
1 citations
GeoEnergy Communications
Rock Mechanics and Modeling
18.34
article

Real-time forecasting of brittle rock failure: a robust acoustic emission approach validated on a large experimental dataset

Chaodong Xi, Fuqiang Gao, Zhiguo Lu, Wenju Liu, Lei Yang, Rui Wu
article en
1 citations

Abstract

Abstract Accurate and real-time forecasting of brittle rock failure remains a major challenge in geotechnical engineering and mining safety. In this study, a novel failure forecasting method based on acoustic emission (AE) monitoring was proposed and validated using a large experimental dataset of 403 sandstone specimens subjected to uniaxial compression. A new early warning indicator, WI b —the b-value change rate per unit time—was developed to capture the frequency and amplitude of b-value fluctuations, which intensify as microcracking evolves toward macroscopic failure. WI b was computed continuously during loading, and a statistically adaptive threshold was established using the evolving mean and standard deviation of WI b . The results demonstrated that WI b consistently escalated before failure in all specimens, with warning signals occurring at loads averaging 76.7% of the ultimate compressive strength. Sensitivity analyses confirmed the robustness of the method across variations in b-value calculation parameters and AE sensor configurations. Importantly, WI b and its threshold were calculated solely from real-time data without requiring knowledge of the full loading path, ensuring practical applicability. The proposed approach offers a physically meaningful and operationally viable solution for real-time rock failure forecasting and has potential for integration into field-scale AE or microseismic monitoring systems.

GeoEnergy CommunicationsVol. 2(1)
China University of Mining and Technology (CN), China Coal Technology and Engineering Group Corp (China) (CN), China Coal Research Institute (China) (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 3%
Rock Mechanics and Modeling
18.34
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Real-time forecasting of brittle rock failure: a robust acoustic emission approach validated on a large experimental dataset — Chaodong Xi, Fuqiang Gao, et al. · GeoEnergy Communications (2026) | TGRS Research Map | TGRS