MétaCan
Menu
Back to cohort
Record W2971888669 · doi:10.1016/j.jrmge.2019.04.005

Deformation and failure characteristics and fracture evolution of cryptocrystalline basalt

2019· article· en· W2971888669 on OpenAlexfundno aff
Zhenjiang Liu, Chuanqing Zhang, Chunsheng Zhang, Yang Gao, Hui Zhou, Zhaorong Chang

Bibliographic record

VenueJournal of Rock Mechanics and Geotechnical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
FundersAtomic Energy of Canada LimitedYouth Innovation Promotion Association of the Chinese Academy of SciencesYalong River Joint FundChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsBasaltMaterials sciencePebbleComposite materialGeologyGeotechnical engineeringGeochemistry

Abstract

fetched live from OpenAlex

Cryptocrystalline basalt is one of the two major types of rocks exposed in the super large-scale underground powerhouse in Baihetan hydropower station in China. The rock of this type shows various site-specific mechanical responses (e.g. fragmentation, fracturing, and relaxation) during excavation. Using conventional triaxial testing facility MTS 815.03, we obtained the stress–strain curves, macroscopic failure characteristics, and strength characteristics of cryptocrystalline basalt. On this basis, evolution of crack initiation and propagation was explored using the finite-discrete element method (FDEM) to understand the failure mechanism of cryptocrystalline basalt. The test results showed that: (1) under different confining stresses, almost all the pre-peak stress–strain curves of cryptocrystalline basalt were linear and the post-peak stresses decreased rapidly; (2) the cryptocrystalline basalt showed a failure mode in a form of fragmentation under low and medium confining stresses while fragmentation-shear coupling failure dominated at high confining stresses; and (3) the initial strength ratio (σci/σf, where σci and σf are the crack initiation strength and peak strength, respectively) ranged from 0.45 to 0.55 and the damage strength ratio (σcd/σf, where σcd is the crack damage strength) exceeded 0.9. The stress–strain curve characteristics and failure modes of cryptocrystalline basalt could be reflected numerically. For this, FDEM simulation was employed to reveal the characteristics of cryptocrystalline basalt, including high σcd/σf values and rapid failure after σcd, with respect to the microscopic characteristics of mineral structures. The results showed that the fragmentation characteristics of cryptocrystalline basalt were closely related to the development of tensile cracks in rock samples prior to failure. Moreover, the decrease in degree of fragmentation with increasing confining stress was also correlated with the dominant effect of confining stress on the tensile cracks.

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: none
Teacher disagreement score0.619
Threshold uncertainty score0.552

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 head0.003
GPT teacher head0.170
Teacher spread0.167 · 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

Citations43
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Rock Mechanics and Geotechnical EngineeringSame topicRock Mechanics and ModelingFrench-language works237,207