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Correlations between Different Hardened Properties of High-Strength Self-Consolidating Concrete Including Palm Oil Fuel Ash

2011· article· en· W1992597363 on OpenAlexaff
Md. Safiuddin, Md. Abdus Salam, Mohd Zamin Jumaat

Bibliographic record

VenueApplied Mechanics and Materials · 2011
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPortland cementMaterials sciencePalm oilUltimate tensile strengthCompressive strengthFlexural strengthCementYoung's modulusComposite materialPorosityFly ashWater reducerWaste managementEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

Palm oil fuel ash is considered as an agro-waste material in Malaysia. Various investigations have been conducted on the use of palm oil fuel ash as a supplementary cementing material for concrete. In the present study, palm oil fuel ash was used as a partial replacement of normal portland cement to produce high-strength self-consolidating concrete. In total, twenty (20) self-consolidating concrete mixes were prepared by varying water to binder ratio, palm oil fuel ash content, and high-range water reducer dosage. Palm oil fuel ash was used by replacing 0–30% of normal portland cement by weight at the water to binder ratios ranging from 0.25 to 0.40. The compressive, splitting tensile and flexural strengths, modulus of elasticity, ultrasonic pulse velocity, and porosity of various self-consolidating concrete mixes were investigated. However, the correlations between the hardened properties of concrete were emphasized in this study. The experimental findings revealed that strong correlations exist between different hardened properties of high-strength self-consolidating 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 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 categoriesMeta-epidemiology (narrow)
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 score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.034
GPT teacher head0.202
Teacher spread0.169 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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