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Correlation of Rheological Properties to Durability and Strength of Hardened Concrete

2003· article· en· W2081666297 on OpenAlexaff
S.E. Chidiac, Omran Maadani, A. Ghani Razaqpur, Noel P. Mailvaganam

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsNational Research Council CanadaCarleton UniversityMcMaster University
Fundersnot available
KeywordsDurabilitySorptivityMaterials scienceRheologyCementFormworkCompressive strengthProperties of concreteComposite materialConsolidation (business)CrackingSuperplasticizerGeotechnical engineeringGeology

Abstract

fetched live from OpenAlex

Premature deterioration of concrete structures has created awareness and concern about the durability of concrete. Concrete mixtures used in the construction of residential basement walls and foundations have a high water to cement (w/c) ratio (w/c>0.6) and low cement content (<280kg/m3). The result is friable concrete with a highly porous surface layer and high potential for cracking. The defects have a direct impact on the durability of concrete. This experimental study examines the effects of three parameters—mix design, formwork, and consolidation—on the quality of the surface of high w/c concrete. The fresh concrete is characterized using its rheological properties—in particular, its yield stress and plastic viscosity. Pulse velocity, pull-off strength, and compressive strength were measured to evaluate the quality and the mechanical properties of the hardened concrete. The durability of the hardened concrete was evaluated by measuring its surface transport properties—namely, its air permeability and sorptivity. The results show that it is possible to correlate the rheological properties of fresh concrete to the mechanical and permeation properties of the hardened concrete.

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)0.002
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
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.198
Teacher spread0.187 · 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

Citations34
Published2003
Admission routes1
Has abstractyes

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