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Record W1965098199 · doi:10.1680/macr.13.00044

Effect of partially hydrated cementitious materials on early-age shrinkage of ultra-high-performance concrete

2013· article· en· W1965098199 on OpenAlexaff
Ahmed Soliman, Moncef L. Nehdi

Bibliographic record

VenueMagazine of Concrete Research · 2013
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsShrinkageCementitiousMaterials sciencePrecast concreteCompressive strengthComposite materialSuperplasticizerReduction (mathematics)CementStructural engineeringEngineering

Abstract

fetched live from OpenAlex

The effect of adding partially hydrated cementitious materials (PHCM) on the early-age shrinkage of ultra-high-performance concrete (UHPC) is investigated. UHPC mixtures incorporating a shrinkage-reducing admixture (SRA) are also tested for comparison. Combined effects of PHCM and SRA in reducing early-age shrinkage are explored. Results indicate a significant improvement in the early-age compressive strength of UHPC mixtures due to PHCM addition. SRA was effective in reducing shrinkage; however, PHCM achieved excellent early-age shrinkage reduction when used alone or combined with SRA. PHCM mitigates undesirable behaviour induced by SRA, including setting time delays and reduction in mechanical properties. The addition of PHCM provides an ecological and economic technique for producing precast and cast-in-place self-restraining shrinkage concrete. Indeed, unused/returned concrete can be recycled in new mixtures to enhance mechanical strength and resistance to shrinkage, and to mitigate set retardation effects.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.270
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2013
Admission routes1
Has abstractyes

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