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Record W7116060219 · doi:10.1016/j.rockmb.2025.100287

Experimental Study on Hydro-Mechanical Behavior and Damage Evolution in Tunnel Surroundings with Different Lithologies

2025· article· en· W7116060219 on OpenAlexaff

Bibliographic record

VenueRock Mechanics Bulletin · 2025
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of Alberta
FundersChina Scholarship Council
KeywordsDolomiteLithologyPermeability (electromagnetism)BrittlenessCarbonateRock mass classificationCarbonate rockDeformation (meteorology)

Abstract

fetched live from OpenAlex

Understanding the mechanical properties of surrounding rocks is essential for the safe construction of tunnels. This study investigates dolomite and sandstone from the Yuxi section of the Central Yunnan Water Diversion Project as research subjects. Through a series of laboratory tests, we compared the differences between dolomite and sandstone in terms of microstructure, water absorption characteristics, mechanical properties, and failure behaviors. A damage constitutive model was also developed to predict the damage state of rocks under specific stress conditions. The results show that sandstone, although stronger in the dry state, develops pronounced water driven pore enlargement, rapid permeability growth during unloading, and significant strength loss, which together increase the susceptibility to seepage induced failure and water inrush. Dolomite exhibits fracture controlled porosity, irreversible permeability reduction under stress cycling, and a brittle to ductile transition under water weakening, which promotes localized deformation and hidden instability near the tunnel boundary. The proposed model reproduces these distinct damage paths and provides a quantitative link between microstructure, saturation, and macroscopic failure. Based on these mechanisms, lithology targeted measures are recommended, including double gradient grouting and sealing systems in dolomite sections and high energy absorption anchoring with strict water control in sandstone sections. The findings supply a mechanism based design basis for tunnels in interbedded carbonate clastic formations in Southwest China. • Experimental comparison reveals strength-permeability differences between dolomite and sandstone under varying water contents. • Developed an AE-based damage model calibrated with Weibull statistics and the Drucker–Prager failure criterion. • Recommend lithology-tailored construction: double-gradient grouting for dolomite, high-NPR anchoring for sandstone tunnels.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.241
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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