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Record W4308012205 · doi:10.1680/jstbu.22.00181

Effect of loss of bond on the behaviour of RC beams under service load conditions

2022· article· en· W4308012205 on OpenAlexaboutno aff
Emmanouil Vougioukas, Gerasimos M. Kotsovos, Apostolos Roulias, Michael D. Kotsovos

Bibliographic record

VenueProceedings of the Institution of Civil Engineers - Structures and Buildings · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsStructural engineeringReinforced concreteReinforcementFlexural strengthBuilding codeCode (set theory)Code of practiceBondComputer scienceEngineeringConstruction engineering

Abstract

fetched live from OpenAlex

Deviation of the flexural reinforcement spacing from code specifications appears to underly the cause of the loss of bond (LoB) between concrete and steel that preceded the unexpected collapse of the top-floor balcony of a building under service load conditions on 15 October 2021 in Athens. Although rare, LoB has also been identified as the cause of collapse of buildings under similar conditions in the UK and Canada. However, the codes of practice for reinforced concrete (RC) design neither make reference to the effect of LoB on structural behaviour, nor include LoB in the parameters that the formulae currently used for assessing load-carrying capacity are dependent on. In view of this, a description of the effect of LoB on the function of RC beams is provided in this paper and this description is used as the basis for the derivation of a formula linking LoB with load-carrying capacity. The validity of the proposed formula is verified using published experimental information on the subject. The proposed formula is used for the structural assessment of the collapsed balcony, taking into account the design details, physical state and loading conditions of structural members similar to the one that collapsed.

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 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 score0.267
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

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 head0.006
GPT teacher head0.211
Teacher spread0.206 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Civil Engineers - Structures and BuildingsSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207