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Record W2129426600 · doi:10.1139/l2012-025

Constitutive flow models for characterizing the rheology of fresh mortar and concrete

2013· article· en· W2129426600 on OpenAlexafffundvenue
S.E. Chidiac, F. Mahmoodzadeh

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaMcMaster University
KeywordsRheologyMortarConstitutive equationMaterials scienceExperimental dataFlow (mathematics)MechanicsParticle (ecology)Bingham plasticGeotechnical engineeringComposite materialStructural engineeringEngineeringMathematicsGeologyPhysicsFinite element methodStatistics

Abstract

fetched live from OpenAlex

Constitutive equations for fresh mortar and fresh concrete provide the characterization of the mixture’s flow and the quantification of the rheological properties. This paper presents a constitutive material model for mortar and concrete that builds on previous research. It postulates that (a) the shear stress is the sum of three components: static interaction between particles, dynamic interaction between particles, and collision of particles; and (b) the cell is a representative volume of the mixture. For fresh concrete, the effects of particle collisions are negligible due to high concentration, and the equation reduces to the Bingham model. Experimental data reported in the literature was employed to evaluate the predictive capabilities of the constitutive equations. The model results are found to compare very well with the measured experimental data and the difference is within the measurement errors.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.177
Teacher spread0.167 · 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 routes3
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicInnovations in Concrete and Construction MaterialsFrench-language works237,207