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Record W2030187489 · doi:10.1139/l06-132

Detecting the fracture process zone in concrete using scanning electron microscopy and numerical modelling using the nonlocal isotropic damage model

2007· article· en· W2030187489 on OpenAlexvenueno aff
H Hadjab-Souag, J.-F. Thimus, Mohamed Chabaat

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsFinite element methodIsotropyFracture (geology)Scanning electron microscopeMaterials scienceConstitutive equationCrackingBrittlenessProcess (computing)Characterization (materials science)Structural engineeringComposite materialComputer scienceOpticsPhysicsEngineering

Abstract

fetched live from OpenAlex

This paper deals with two aspects of the characterization of the fracture process zone (FPZ) in quasi-brittle materials such as concrete. An overview is given of the possibility of using a destructive technique, such as the scanning electron microscope, and a numerical model, such as the nonlocal isotropic damage model (NLIDM), to detect FPZ characteristics, e.g., length and width of the FPZ. The fracture of concrete requires the consideration of progressive damage, which is usually modelled by a constitutive law and can be studied by a numerical method. The object-oriented finite element method (OOFEM) has recently been used in damage studies, and thus the FPZ is calculated on the basis of one of the damage models (the NLIDM). The results obtained from the experimental investigation are similar to those obtained using the NLIDM, which has proven to be a useful tool for analysis of the cracking process.Key words: object-oriented finite element method, nonlocal isotropic damage model, fracture process zone, scanning electron microscope.

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)0.001
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 score0.520
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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
Published2007
Admission routes1
Has abstractyes

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