Energy evolution‐based damage quantification and failure prediction of fault zone tunnel lining concrete: A novel acoustic emission–strain energy coupling approach

Abstract This study proposes a methodology combining acoustic emission (AE) technology and strain energy evolution for quantifying damage and predicting the failure of tunnel lining concrete in active fault zones. The test specimens were prepared using the same concrete mix proportions as those used in an actual high‐altitude mountain tunnel project crossing active fault zones. The energy transformation mechanisms during concrete loading were analyzed through uniaxial compression testing integrated with AE monitoring. Results show a significant linear correlation between the AE cumulative absolute energy and the total strain energy, which effectively characterizes concrete damage evolution. Based on these findings, the change rate of AE cumulative absolute energy is proposed as a failure precursor indicator, providing an average advance warning time of 26.4% before concrete failure occurs. Additionally, energy‐based damage variables (the strain‐energy‐based damage variable, and the AE‐energy‐based damage variable, ) were established to accurately quantify concrete damage progression. Furthermore, an energy‐based stress–strain equation was developed to comprehensively describe the mechanical behavior of concrete. These research results provide theoretical foundations and technical support for safety monitoring and early warning systems for tunnel linings in active fault zones, with significant implications for improving tunnel safety in seismically active regions.

Authors

Institutions

Publication Details

Journal
Deep Underground Science and Engineering
Published
2026-08-26
DOI
https://doi.org/10.1002/dug2.70121
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Energy evolution‐based damage quantification and failure prediction of fault zone tunnel lining concrete: A novel acoustic emission–strain energy coupling approach

Mingliang Zhou, Hongwei Huang, Dongming Zhang, Shuaida Zhu et al.
Deep Underground Science and Engineering
Rock Mechanics and Modeling
article

Energy evolution‐based damage quantification and failure prediction of fault zone tunnel lining concrete: A novel acoustic emission–strain energy coupling approach

Mingliang Zhou, Hongwei Huang, Dongming Zhang, Shuaida Zhu, Shengjun Duo
article en

Abstract

Abstract This study proposes a methodology combining acoustic emission (AE) technology and strain energy evolution for quantifying damage and predicting the failure of tunnel lining concrete in active fault zones. The test specimens were prepared using the same concrete mix proportions as those used in an actual high‐altitude mountain tunnel project crossing active fault zones. The energy transformation mechanisms during concrete loading were analyzed through uniaxial compression testing integrated with AE monitoring. Results show a significant linear correlation between the AE cumulative absolute energy and the total strain energy, which effectively characterizes concrete damage evolution. Based on these findings, the change rate of AE cumulative absolute energy is proposed as a failure precursor indicator, providing an average advance warning time of 26.4% before concrete failure occurs. Additionally, energy‐based damage variables (the strain‐energy‐based damage variable, and the AE‐energy‐based damage variable, ) were established to accurately quantify concrete damage progression. Furthermore, an energy‐based stress–strain equation was developed to comprehensively describe the mechanical behavior of concrete. These research results provide theoretical foundations and technical support for safety monitoring and early warning systems for tunnel linings in active fault zones, with significant implications for improving tunnel safety in seismically active regions.

Deep Underground Science and Engineering
Tongji University (CN), China Railway Fifth Survey and Design Institute Group (CN)
Affordable and clean energy
Openalex Percentile: Top 17%
Rock Mechanics and Modeling
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.