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Record W2128239748 · doi:10.5897/jmer.9000049

Utilization of demolished concrete, grog, hydrated lime and cement kiln dust in building materials

2011· article· en· W2128239748 on OpenAlexvenueno aff
H. M. Khater

Bibliographic record

VenueMechanical Engineering Research · 2011
Typearticle
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCementLimeCement kilnGrogKilnBrickWaste managementEnvironmental scienceClinker (cement)MetallurgyMaterials scienceAggregate (composite)MortarPortland cementComposite materialEngineering

Abstract

fetched live from OpenAlex

It is desirable to completely recycle concrete waste in order to protect natural resources and reduce environment pollution. In this paper, the studied reference  mix composed of demolished waste concrete/grog/hydrated lime in the ratio of (40/50/10, wt. %), while other mixes has cement kiln dust as a partial replacement of hydrated lime in the ratio from zero up to complete replacement. Both grog and burned cement kiln dust were obtained from firing clay materials as well as by-pass cement kiln dust at 850°C for 1 h with a heating rate of 5°C/min. Results of this study possess a method for recycling of demolished wastes in brick making as fine materials not in the traditional method that used it as aggregate. Waste concrete, grog, hydrated lime and by-pass cement dust can be used instead of the cement constituent of mortar and hydrated building brick making.   Key words: Demolished concrete, cement kiln dust, grog.

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 score0.001

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 integrity0.0000.000
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 head0.087
GPT teacher head0.294
Teacher spread0.208 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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