Theoretical modeling of pull-out stiffness of glued-in single rod in timber
Bibliographic record
Abstract
Glued-in rods (GIRs) have emerged as an innovative solution for timber connections, offering superior pull-out performance and aesthetic benefits. However, existing design methods for predicting the GIR pull-out stiffness are either excessively complex or fail to provide accurate predictions because they neglect critical deformation components. This study proposes a theoretical model for predicting the pull-out stiffness of GIRs in timber based on the Timoshenko and Volkersen theories to develop a simple and accurate approach. The model considers both rod tensile deformation and timber shear deformation, representing the GIR behavior more comprehensively. To validate the proposed model, pull-out tests were conducted on GIR specimens with various configurations, including different rod diameters (16, 19, and 24 mm), anchorage lengths (200, 300, and 400 mm), and non-bonded lengths (0 and 80 mm). The theoretical predictions concurred with the experimental results for all the configurations. The model effectively captured the influence of geometric parameters on the GIR stiffness, revealing the increased stiffness with larger rod diameters and a marginal decrease with the increasing anchorage length. Non-bonded regions reduced the pull-out stiffness. Compared with the existing models, the proposed approach offers a balance between simplicity and accuracy, making it more suitable for practical applications. This study contributes to the understanding of GIR behavior and provides a valuable tool for engineers and designers. Further experimental investigations are required to validate the proposed model over a wide range of material properties and geometric configurations. • Developed a simplified, accurate theoretical model for glued-in rod pull-out stiffness. • Combined Timoshenko's and Volkersen's theories for comprehensive deformation analysis. • Validated model through experimental research across various GIR configurations. • Explored impact of geometrical factors on glued-in rod pull-out stiffness. • Provides a practical tool for engineers to optimize high-performance timber connections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".