Experimental Investigation of Compositely Connected Wood–Wood T-Beams and Shear Connections
Bibliographic record
Abstract
This study investigates the behavior of compositely connected wood–wood lumber T-beams in flexure to characterize the applicability of two analytical approaches in predicting the bending stiffness and assess the impact on the shear lag occurring in the flange. The shear connections consisted of glue-pressed and screw-glued configurations with PL Premium Max adhesive and 30° inclined screws at 100 mm spacing. Screw-glued and glue-pressed connections showed comparable behavior, achieved high strengths and stiffnesses, and remained linear up to 60%–80% of the maximum load. Inclined screw connections exhibited lower stiffness and remained linear up to approximately 60% of the maximum load. The glue-pressed and screw-glued T-beams showed a high degree of composite action despite the short span, while the inclined screw T-beams demonstrated more slip and a lower degree of composite action. Compression strain results across the top of the T-beam flange emphasized the shear lag behavior occurring within. The degree of reduction from the peak strain over the web is hypothesized to be influenced by the stiffness ratio between the web and flange, the degree of composite action achieved, and the perpendicular-to-grain properties of the flange. The gamma method and T-beam method showed good agreement with respect to the experimental stiffness results. Incorporating the shear lag effects observed in the flange in the material models is expected to result in a reduced flange width and decreased bending stiffness compared to current predictions. Based on the good agreement for dimensional lumber T-beams, the two models have potential for future implementation and analysis on mass timber composite elements.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".