Spatial response and prediction model for blasting-induced vibration in a deep double-line tunnel

Excessive blasting-induced vibration during drilling-and-blasting excavation of deep tunnels can trigger geological hazards and compromise the stability of both the rock mass and support structures. This study focused on the deep double-line Sejila Mountain tunnel to systematically analyze the spatial response of blasting-induced vibration and to develop a prediction model through field tests and numerical simulations. The results revealed that the presence of a cross passage significantly altered propagation paths and the spatial distribution of blasting-induced vibration velocity. The peak particle velocity (PPV) at the cross-passage corner was amplified by approximately 1.92 times due to wave reflection and geometric focusing. Blasting-induced vibration waves attenuated non-uniformly across the tunnel cross-section, where PPV on the blast-face side was 1.54–6.56 times higher than that on the opposite side. We propose an improved PPV attenuation model that accounts for the propagation path effect. This model significantly improved fitting accuracy and resolved anomalous parameter ( k and α ) estimates in traditional equations, thereby improving prediction reliability. Furthermore, based on the observed spatial distribution of blasting-induced vibration, optimal monitoring point placement and targeted vibration control measures for tunnel blasting were discussed. These findings provide a scientific basis for designing blasting schemes and vibration mitigation strategies in deep tunnels.

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Publication Details

Journal
International Journal of Mining Science and Technology
Published
2025-12-03
DOI
https://doi.org/10.1016/j.ijmst.2025.11.009
Citations
1
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.86
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article

Spatial response and prediction model for blasting-induced vibration in a deep double-line tunnel

Yongan Ma, Haibin Wang, Haibo Li, Lili Meng et al.
1 citations
International Journal of Mining Science and Technology
Rock Mechanics and Modeling
0.86
article

Spatial response and prediction model for blasting-induced vibration in a deep double-line tunnel

Yongan Ma, Haibin Wang, Haibo Li, Lili Meng, Chong Yu, Changjian Wang
article en
1 citations

Abstract

Excessive blasting-induced vibration during drilling-and-blasting excavation of deep tunnels can trigger geological hazards and compromise the stability of both the rock mass and support structures. This study focused on the deep double-line Sejila Mountain tunnel to systematically analyze the spatial response of blasting-induced vibration and to develop a prediction model through field tests and numerical simulations. The results revealed that the presence of a cross passage significantly altered propagation paths and the spatial distribution of blasting-induced vibration velocity. The peak particle velocity (PPV) at the cross-passage corner was amplified by approximately 1.92 times due to wave reflection and geometric focusing. Blasting-induced vibration waves attenuated non-uniformly across the tunnel cross-section, where PPV on the blast-face side was 1.54–6.56 times higher than that on the opposite side. We propose an improved PPV attenuation model that accounts for the propagation path effect. This model significantly improved fitting accuracy and resolved anomalous parameter ( k and α ) estimates in traditional equations, thereby improving prediction reliability. Furthermore, based on the observed spatial distribution of blasting-induced vibration, optimal monitoring point placement and targeted vibration control measures for tunnel blasting were discussed. These findings provide a scientific basis for designing blasting schemes and vibration mitigation strategies in deep tunnels.

International Journal of Mining Science and TechnologyVol. 36(1)
Institute of Rock and Soil Mechanics (CN), University of Chinese Academy of Sciences (CN), Shandong Jianzhu University (CN)
Openalex Percentile: Top 22%
Rock Mechanics and Modeling
0.86
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