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Record W2600173581 · doi:10.1680/jcoma.16.00058

Role of test method in detection of alkali–silica reactivity of concrete aggregates

2017· article· en· W2600173581 on OpenAlexaff
Muhammad Junaid Munir, Safeer Abbas, Asad Ullah Qazi, Moncef L. Nehdi, Syed Minhaj Saleem Kazmi

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Construction Materials · 2017
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsWestern University
Fundersnot available
KeywordsAlkali–silica reactionAggregate (composite)Reactivity (psychology)MortarMaterials scienceAlkali–aggregate reactionComposite materialScanning electron microscopeCompressive strengthAlkali metalFlexural strengthChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The risk of alkali–silica reaction of concrete aggregates in many parts of the world remains largely unexplored. In particular, a suitable approach for testing aggregates with marginal to moderate alkali–silica reactivity has not been clearly identified. In this study, the mineralogical compositions of aggregates from five different quarries were investigated. Mortar bar expansion for these aggregates was tested as per the guidelines of both C 227 and C 1260. Although the tested aggregate sources proved non-reactive under ASTM C 227 test conditions, ASTM C 260 identified one group of aggregates as potentially reactive. Scanning electron microscopy imaging confirmed that two sources of aggregates were reactive. The compressive and flexural strength test results of aged specimens with reactive aggregates indicated that the strength reduction of those subjected to 1 month of ASTM C 260 exposure was similar to those of specimens under 6 months of ASTM C 227 exposure. Based on the experimental results, it appears that aggregates with potential alkali–silica damage may be characterised as non-reactive if the appropriate test method is not adopted. The findings indicate that the ASTM C 1260 procedure is more effective in determining the reactivity potential of marginally to moderately reactive aggregates.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 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

Citations43
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Civil Engineers - Construction MaterialsSame topicConcrete and Cement Materials ResearchFrench-language works237,207