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Record W2096148403 · doi:10.1139/t00-105

Dual role of microcracks: toughening and degradation

2001· article· en· W2096148403 on OpenAlexvenueno aff
G. Mallikarjuna Rao, C.R.L. Murthy

Bibliographic record

VenueCanadian Geotechnical Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceAcoustic emissionTougheningComposite materialNucleationCeramicDegradation (telecommunications)Ultrasonic sensorStress (linguistics)ThermalFracture (geology)AcousticsToughness

Abstract

fetched live from OpenAlex

One of the methods of improving the mechanical properties of ceramics is to introduce a defective structure that acts as a restraint for the propagation of cracks. In the present study a detailed investigation was carried out by introducing a defective structure in rock to determine if there is any improvement in properties similar to ceramics. Granite was chosen for the investigation, and the microcracks were introduced by a heating and cooling cycle. Uniaxial compression tests have shown that granite thermally treated to 200°C shows the highest strength, and the strength of granite treated to 400°C is comparable to that of unheated granite. Both ultrasonic images and acoustic-emission monitoring show that for thermally treated samples the stress-induced microcrack and macrocrack nucleation and their growth are retarded. The variations in mechanical properties are explained based on the concept of toughening and degradation. Uniaxial compression tests on unheated and thermally treated granite samples have clearly established the dual role of microcracks, which operate in the toughening and degradation mechanisms.Key words: thermal treatment, microcrack, inelastic strain, ultrasonic C-scan imaging, acoustic emission, toughening.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score0.296

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 head0.008
GPT teacher head0.190
Teacher spread0.182 · 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
Published2001
Admission routes1
Has abstractyes

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