Effect of joint coalescence coefficient on rock bridge formation of slope based on finite difference method

A method combining finite difference method (FDM) and k -means clustering algorithm which can determine the threshold of rock bridge generation is proposed. Jointed slope models with different joint coalescence coefficients( k ) are constructed based on FDM. The rock bridge area was divided through k -means algorithm and the optimal number of clusters was determined by sum of squared errors (SSE) and elbow method. The influence of maximum principal stress and stress change rate as clustering indexes on the clustering results of rock bridges was compared by using Euclidean distance. The results show that using stress change rate as clustering index is more effective. When the joint coalescence coefficient is less than 0.6, there is no significant stress concentration in the middle area of adjacent joints, that is, no generation of rock bridge. In addition, the range of rock bridge is affected by the coalescence coefficient ( k ), the relative position of joints and the parameters of weak interlayer.

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Publication Details

Journal
Transactions of Nonferrous Metals Society of China
Published
2025-10-01
DOI
https://doi.org/10.1016/s1003-6326(25)66892-0
Citations
2
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
1.73
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article

Effect of joint coalescence coefficient on rock bridge formation of slope based on finite difference method

Hang Lin, Su Li, Yi Tang
2 citations
Transactions of Nonferrous Metals Society of China
Rock Mechanics and Modeling
1.73
article

Effect of joint coalescence coefficient on rock bridge formation of slope based on finite difference method

Hang Lin, Su Li, Yi Tang
article en
2 citations

Abstract

A method combining finite difference method (FDM) and k -means clustering algorithm which can determine the threshold of rock bridge generation is proposed. Jointed slope models with different joint coalescence coefficients( k ) are constructed based on FDM. The rock bridge area was divided through k -means algorithm and the optimal number of clusters was determined by sum of squared errors (SSE) and elbow method. The influence of maximum principal stress and stress change rate as clustering indexes on the clustering results of rock bridges was compared by using Euclidean distance. The results show that using stress change rate as clustering index is more effective. When the joint coalescence coefficient is less than 0.6, there is no significant stress concentration in the middle area of adjacent joints, that is, no generation of rock bridge. In addition, the range of rock bridge is affected by the coalescence coefficient ( k ), the relative position of joints and the parameters of weak interlayer.

Transactions of Nonferrous Metals Society of ChinaVol. 35(10)
Central South University (CN)
Openalex Percentile: Top 14%
Rock Mechanics and Modeling
1.73
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