Post-peak dependence analysis in statistical damage constitutive modeling of brittle rocks

Accurately simulating the post-peak behavior of brittle rocks remains a challenge for statistical damage constitutive models. This study investigates the sensitivity of post-peak simulation to model components by evaluating combinations of three strength criteria and three micro-element strength distributions against triaxial test data from five rock types. Results indicate that the probability distribution of micro-element strength governs simulation accuracy, while the strength criterion exerts minimal influence. Based on these findings, a relative brittleness index-based method for selecting the optimal distribution is proposed, along with a dual-parameter collaborative correction method. Validation shows that this approach significantly enhances the fit to experimental post-peak curves, eliminates criterion-induced interference in parameter adjustment, and remains effective across multiple distribution modes. The proposed method offers a solution for improving the reliability of damage models in predicting brittle rocks failure.

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Publication Details

Journal
Scientific Reports
Published
2026-04-26
DOI
https://doi.org/10.1038/s41598-026-49872-7
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

Post-peak dependence analysis in statistical damage constitutive modeling of brittle rocks

Dongping Zhu, Yixiao Shen, Yongyi Li, Peidong Zhu et al.
Scientific Reports
Rock Mechanics and Modeling
article

Post-peak dependence analysis in statistical damage constitutive modeling of brittle rocks

Dongping Zhu, Yixiao Shen, Yongyi Li, Peidong Zhu, Chao Zhang, Hao Zhou
article en

Abstract

Accurately simulating the post-peak behavior of brittle rocks remains a challenge for statistical damage constitutive models. This study investigates the sensitivity of post-peak simulation to model components by evaluating combinations of three strength criteria and three micro-element strength distributions against triaxial test data from five rock types. Results indicate that the probability distribution of micro-element strength governs simulation accuracy, while the strength criterion exerts minimal influence. Based on these findings, a relative brittleness index-based method for selecting the optimal distribution is proposed, along with a dual-parameter collaborative correction method. Validation shows that this approach significantly enhances the fit to experimental post-peak curves, eliminates criterion-induced interference in parameter adjustment, and remains effective across multiple distribution modes. The proposed method offers a solution for improving the reliability of damage models in predicting brittle rocks failure.

Scientific Reports
Hunan University of Science and Technology (CN), China Railway Construction Corporation (China) (CN), China Railway Group (China) (CN), University of Hong Kong (HK)
China Postdoctoral Science Foundation
Openalex Percentile: Top 8%
Rock Mechanics and Modeling
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