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Record W2765237418 · doi:10.1680/jmacr.17.00189

Thermal properties of fibre-reinforced alkali-activated concrete in extreme temperatures

2017· article· en· W2765237418 on OpenAlexafffund
Jose Goncalves, Yaman Boluk, Vivek Bindiganavile

Bibliographic record

VenueMagazine of Concrete Research · 2017
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsMaterials scienceThermal conductivityComposite materialHeat capacityPolypropyleneAlkali metalThermalAtmospheric temperature rangeDrop (telecommunication)ThermodynamicsChemistry

Abstract

fetched live from OpenAlex

The thermal conductivity and specific heat capacity of paste and concrete prepared with alkali-activated fly ash were investigated. Along with a reference plain concrete mix, two other mixes were reinforced with a blend of steel and polypropylene fibres to examine the role of fibre reinforcement on the thermal constants. The mixtures were exposed to a range of extreme temperatures in the sub-zero and elevated regimes, from −30°C to 300°C, for a duration of 2 h. The thermal constants were measured using the transient plane source method on a hot-disc thermal analyser system. The results showed that there was no phase change in the alkali-activated system within the range of exposures. The thermal conductivity increased with a drop in ambient temperature, especially in the sub-zero regime. Adding fibres tended to lower the thermal conductivity, probably due to the finer pore size and consequent lowering of the freezing point of water. The specific heat capacity was found to rise with an increase in ambient temperature. A rule-of-mixtures approach was found to closely approximate the thermal constants at room temperature.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.099
GPT teacher head0.307
Teacher spread0.209 · 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.

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

Citations9
Published2017
Admission routes2
Has abstractyes

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