Mechanical property reconstruction and damage evolution of rock-like materials for deep argillaceous sandstone under multiple similarity constraints

Physical model tests of deep underground rock masses require rock-like materials that reproduce multiple mechanical properties and failure behaviour simultaneously, yet conventional proportioning commonly treats mixture selection and damage characterization separately. This study proposes an integrated framework for multidimensional property reconstruction and damage characterization of deep argillaceous sandstone. Sixteen river sand-cement-gypsum mixtures were evaluated through unit-weight measurements, uniaxial compression, Brazilian splitting, and variable-angle shear tests. Compatibility with prototype targets was quantified using the root-mean-square relative errors of compressive strength, tensile strength, elastic modulus, cohesion, and unit weight, and a Weibull model with an initial-compaction correction was used to describe progressive failure. The results show asynchronous responses of strength, stiffness, shear resistance, and unit weight to mixture composition. The 100:10:10 mixture achieved the minimum overall deviation of 7.85%, with measured-to-target ratios of 0.98, 1.00, 0.95, 1.17, and 1.01, respectively. The damage model reproduced the post-compaction response, peak transition, and post-peak softening, with R 2 values of 0.951–0.994 and normalized root-mean-square errors of 2.39%-6.54%. The framework advances rock-like material design from single-property matching to coordinated reconstruction of multidimensional mechanical response and progressive failure.

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Journal
Scientific Reports
Published
2026-10-30
DOI
https://doi.org/10.1038/s41598-026-77612-4
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

Mechanical property reconstruction and damage evolution of rock-like materials for deep argillaceous sandstone under multiple similarity constraints

Baojun Chen, Wenping Li, Dong Zhu, Enyuan Wang et al.
2 links
Scientific Reports
Rock Mechanics and Modeling
article

Mechanical property reconstruction and damage evolution of rock-like materials for deep argillaceous sandstone under multiple similarity constraints

Baojun Chen, Wenping Li, Dong Zhu, Enyuan Wang, Boyuan Yu, Xiaofei Liu, Yutong Chao, Xuwen Ku, Qiming Zhang
article en

Abstract

Physical model tests of deep underground rock masses require rock-like materials that reproduce multiple mechanical properties and failure behaviour simultaneously, yet conventional proportioning commonly treats mixture selection and damage characterization separately. This study proposes an integrated framework for multidimensional property reconstruction and damage characterization of deep argillaceous sandstone. Sixteen river sand-cement-gypsum mixtures were evaluated through unit-weight measurements, uniaxial compression, Brazilian splitting, and variable-angle shear tests. Compatibility with prototype targets was quantified using the root-mean-square relative errors of compressive strength, tensile strength, elastic modulus, cohesion, and unit weight, and a Weibull model with an initial-compaction correction was used to describe progressive failure. The results show asynchronous responses of strength, stiffness, shear resistance, and unit weight to mixture composition. The 100:10:10 mixture achieved the minimum overall deviation of 7.85%, with measured-to-target ratios of 0.98, 1.00, 0.95, 1.17, and 1.01, respectively. The damage model reproduced the post-compaction response, peak transition, and post-peak softening, with R 2 values of 0.951–0.994 and normalized root-mean-square errors of 2.39%-6.54%. The framework advances rock-like material design from single-property matching to coordinated reconstruction of multidimensional mechanical response and progressive failure.

Scientific Reports
China University of Mining and Technology (CN), Jiangsu Vocational Institute of Architectural Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 23%
Rock Mechanics and Modeling
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