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Record W2534258050 · doi:10.11159/icsenm16.105

Analytical Approach to the Bond Strength of Plain Round Bars under Lateral Tensile Stresses

2016· article· en· W2534258050 on OpenAlexvenueno aff
Xue Zhang, Changming Lv, Zhimin Wu, Jinping Ou

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
FundersFundamental Research Funds for the Central UniversitiesScientific Research Fund of Liaoning Provincial Education DepartmentDepartment of Education of Liaoning Province
KeywordsUltimate tensile strengthBondMaterials scienceStructural engineeringBond strengthComposite materialGeotechnical engineeringGeologyEngineeringAdhesiveBusiness

Abstract

fetched live from OpenAlex

The bond strength of the plain round bar plays important role in the assessment of historical buildings and has been widely investigated.This paper presents an analytical approach to the bond strength of plain round bars embedded in concrete subjected to lateral tensile stresses.Based on the theory of elasticity, the contact condition of the bar/concrete interface is discussed, and an analytical solution for the ultimate bond strength is further derived.When the shrinkage of concrete, the geometric and mechanical parameters of bars and concrete are given, the analytical solution can be used to evaluate the ultimate bond strength of plain round bars subjected to uniaxial and biaxial lateral tensile stresses.153 pull-out specimens are used to verify the analytical solution.The results show that, the analytical predictions are in good agreement with the experimental values.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.181
Teacher spread0.175 · 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 designSimulation or modeling
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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