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Record W2203713882 · doi:10.1139/t2012-035

Strength and deformation behavior of red sandstone under multi-stage triaxial compression

2012· article· en· W2203713882 on OpenAlexvenueno aff
Sheng‐Qi Yang

Bibliographic record

VenueCanadian Geotechnical Journal · 2012
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsGeotechnical engineeringOverburden pressureGeologyDeformation (meteorology)Triaxial shear testStage (stratigraphy)Compression (physics)Geological Strength IndexMaterials scienceComposite materialPetrologyRock mass classificationShear (geology)

Abstract

fetched live from OpenAlex

Based on multi-stage triaxial experimental results of red sandstone with circumferential deformation control, the influence of confining pressure on strength and deformation behavior of red sandstone under multi-stage triaxial compression is investigated. The results show that the confining pressure has an obvious effect on the deformation parameters of red sandstone under multi-stage triaxial compression. A multi-stage triaxial compression experiment with only one specimen can be used to confirm the peak strength of rock under different confining pressures. Under single-stage and multi-stage triaxial compression, the peak strength behavior of red sandstone agrees better with the nonlinear Hoek–Brown criterion than the linear Mohr–Coulomb criterion. However, the difference between single-stage and multi-stage triaxial strength changes with different post-peak deformation values, and the reason for the difference, is discussed. To predict single-stage triaxial strength using the obtained multi-stage triaxial strength with only one specimen, a new method is put forward to revise multi-stage triaxial strength of red sandstone, which testifies to being reasonable. The concluding remarks are very useful and significant for deep geotechnical and underground structural engineering.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.331

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 head0.038
GPT teacher head0.261
Teacher spread0.224 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations24
Published2012
Admission routes1
Has abstractyes

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