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Bowen Zhang, Guohua Zhang, Yuyong Jiao, Xingtong Wei, Song Du, Wei Wang. Estimation of Seepage-Erosion in Well-Graded Soils and its Application to Debris Flow Inrush. Journal of Earth Science. doi: 10.1007/s12583-026-0153-9
Citation: Bowen Zhang, Guohua Zhang, Yuyong Jiao, Xingtong Wei, Song Du, Wei Wang. Estimation of Seepage-Erosion in Well-Graded Soils and its Application to Debris Flow Inrush. Journal of Earth Science. doi: 10.1007/s12583-026-0153-9

Estimation of Seepage-Erosion in Well-Graded Soils and its Application to Debris Flow Inrush

doi: 10.1007/s12583-026-0153-9
Funds:

The financial support from the National Natural Science Foundation of China (No. 42277173,Grant No. U24A20599)

the National Science and Technology Major Project of China (Grant No. 2024ZD1004300)

  • Available Online: 10 Sep 2026
  • Debris flow inrush disasters have become a major challenge in underground engineering for the construction of tunnels in alteration zone. At present, there is a lack of effective methods for assessing the risk of debris flow inrush. Taking the debris flow inrush in Baofeng tunnel as a case study, the disaster process and characteristics of debris flow inrush are described based on field observations and geological analysis. It is found that the erosion potential is one of the main factors affecting the risk of debris flow inrush. Consequently, the coupled computational fluid dynamics and discrete element method (CFD-DEM) is used to simulate the seepage-erosion of sets of well-graded soils under different PSDs, hydraulic gradients and confining pressures. Based on the simulation results, models for estimating the final erosion ratio and evolution of PSD during the erosion process are established. The reliability of the models is verified by comparisons with both laboratory tests and engineering cases. It is also concluded that the erosion potential is proportional to the scale of debris flow inrush. The relevant results contribute to the assessment of debris flow inrush risks and can guide future research in developing early warning systems.

     

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      沈阳化工大学材料科学与工程学院 沈阳 110142

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