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Record W4390344580 · doi:10.3390/ma17010166

Damage Generated and Propagated by the AAR Reactive Aggregate from Kingston, Ontario, Canada

2023· article· en· W4390344580 on OpenAlexaffabout
Cassandra Trottier, Leandro Sanchez

Bibliographic record

VenueMaterials · 2023
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAlkali–silica reactionAggregate (composite)Materials scienceAlkali–aggregate reactionComposite materialCementEttringiteForensic engineeringPortland cementEngineering

Abstract

fetched live from OpenAlex

It remains unclear in the literature what the cause of the so-called alkali-carbonate reaction (ACR) damage to concrete is. However, expansion and cracks as distress features are often attributed to the alkali-silica reaction (ASR). Therefore, this work aims to assess the damage to concrete generated and propagated by the so-called ACR-susceptible reactive aggregate through mechanical testing (i.e., the direct shear test), microscopy (the damage rating index-DRI), and other techniques. Distinct induced expansion levels (i.e., 0%, 0.05%, 0.12%, and 0.20%) were selected to compare the distress caused by ACR to concrete affected by ASR. The results show that the behavior of ACR, namely, as captured through the DRI, is inconsistent with that of ASR, thus attesting to ACR being a distinct distress mechanism. The damage captured through mechanical testing does not distinguish ACR from ASR; however, microscopy reveals that cracks in the cement paste are the main damage mechanism. The proportions of cracks in the cement paste are 40-50% of the total number of cracks, whereas open cracks in the aggregates normally characterizing ASR represent only up to 20% of the total 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
Threshold uncertainty score0.999

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)0.0020.000

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 head0.012
GPT teacher head0.204
Teacher spread0.192 · 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 designBench or experimental
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

Citations2
Published2023
Admission routes2
Has abstractyes

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