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Record W4417441829 · doi:10.1139/cjce-2025-0182

Experimental and numerical analysis of the shear performance of trapezoidal dowel connectors in steel–UHPC composite beams

2025· article· en· W4417441829 on OpenAlexvenueno aff
Yifan Zhu, Xianhong Meng, Fadel Yessoufou, Tiange Gao

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsDowelBrittlenessShear (geology)Finite element methodCable glandNumerical analysisReinforcement

Abstract

fetched live from OpenAlex

This study investigates the shear performance of trapezoidal dowel connectors in steel–ultra-high-performance concrete (UHPC) composite beams through 15 push-out tests and complementary finite element simulations. The effects of dowel height, root width, and reinforcement ratio on shear resistance and failure modes were evaluated. Two distinct mechanisms were identified: steel dowel root shear failure, which dominated all experiments and most simulations, and UHPC dowel root shear-off, observed only in numerical analysis for extensive root widths. Test results showed that reducing the dowel height from 70 to 30 mm increased the ultimate shear capacity from 242 to 370 kN, while increasing the root width from 30 to 70 mm raised the capacity from 138 to 444 kN but triggered brittle UHPC failure. The reinforcement ratio (0.35%–0.75%) had a negligible influence. A simplified analytical formula for calculating shear capacity, assuming uniform load distribution, was proposed and validated against tests and simulations, with errors of less than 10%. Practical design recommendations for connector dimensions are also provided.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.004
GPT teacher head0.181
Teacher spread0.178 · 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 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
Published2025
Admission routes1
Has abstractyes

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