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Record W4400476708 · doi:10.1002/suco.202400081

Anchorage and lap capacity of plain surface and square twisted bars in existing R.C. Structures: A comprehensive approach

2024· article· en· W4400476708 on OpenAlex
John Cairns, Lisa R. Feldman, Fabrizio Palmisano

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStructural Concrete · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsExpression (computer science)Structural engineeringEngineeringSquare (algebra)ReinforcementCode (set theory)Test dataComputer scienceMathematicsSet (abstract data type)Geometry

Abstract

fetched live from OpenAlex

Abstract Although plain round or square section reinforcement is no longer used in new construction, there are many older structures still in service built with such bars. In recognition of the need for guidance on the assessment of load‐carrying capacity of structures reinforced with such bars, design codes are now introducing or re‐introducing provisions to assess the capacity of laps and anchorages of such reinforcement. The authors have contributed to the introduction of design rules in the fib Model Code 2020. This paper describes the derivation of these provisions. Starting from the form of expression proposed earlier by the authors, the data from which these proposals are derived is specified and modifications in interpretation preparatory to a statistical analysis are outlined. A rigorous multivariate statistical procedure is then employed firstly to determine a mean strength expression for the capacity of anchorages and laps which is then validated against test data. Further statistical analysis is subsequently used to determine a design expression using the approach outlined in EN 1990, taking appropriate account scatter in test data. Finally, some comparisons are presented between the assessment expressions proposed and design provisions that were in place when these types of bars were in common use. Areas where earlier design provisions may be non‐conservative are identified.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
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 integrity0.0000.001
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 head0.031
GPT teacher head0.259
Teacher spread0.228 · 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