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Record W2562603376

STR-924: EFFECT OF LOW TEMPERATURE ON THE SHEAR-FATIGUE PERFORMANCE OF REINFORCED CONCRETE BEAMS

2016· article· en· W2562603376 on OpenAlexfundno aff
M. Mehdi Mirzazadeh, Martin Noël, Mark F. Green

Bibliographic record

VenueScholarship@Western (Western University) · 2016
Typearticle
Languageen
FieldEngineering
TopicFire effects on concrete materials
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaTransport Canada
KeywordsShear (geology)Structural engineeringReinforced concreteMaterials scienceComposite materialEngineering
DOInot available

Abstract

fetched live from OpenAlex

This paper investigates the fatigue behaviour of a reinforced concrete beam (without shear reinforcement) at low temperature (-20°C) compared to a similar beam tested near room temperature (+16°C). Two large-scale steel reinforced beams (200 mm x 400 mm x 4200 mm) were fabricated and tested. The beams had temperature differentials over their depth to simulate solar radiation and in-service temperature of the bridges. The beams were cyclically loaded to failure with a stress range representing the ratio of live to dead loads found in most bridges. This study showed that low temperature increased the fatigue life of the reinforced concrete beam by 51%, and changed the mode of failure of the beam from shear fatigue failure at room temperature to flexural fatigue failure at low temperature. It was observed that the low and room temperature beams maintained 65% and 31% of their original flexural rigidity indicating that low temperature mitigated the stiffness degradation of the reinforced concrete caused by fatigue loading. The strains in the tensile reinforcement of the low temperature beam were much lower than the room temperature beam which could be due to the higher strength of concrete and reduction in concrete softening at low temperature which resulted in lower stresses in the tensile reinforcement. The findings of this study show that the contribution of concrete under either static or cyclic load becomes much higher at low 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)0.001
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 score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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