Development of a glue bonded shear connections aimed for mass timber composites
Bibliographic record
Abstract
Mass timber composites (MTCs) generally require stiff glued connections to meet serviceability design criteria; however, achieving stiff glued connections without conventional pressing infrastructure can necessitate alternative gap filling adhesives. A readily available construction adhesive with potential for use with alternative pressing methods is investigated to develop the needed information for its commercial application in MTCs. The glue line thickness, surface coverage, three contact pressures, and how these parameters influence the load-slip curve of the connection when loaded in pure shear are investigated. The average glue line thickness ranged from 0.76 to 0.33 mm, with lower pressures having thicker glue lines and higher pressures having thinner glue lines. The planning precision was found to be more critical than clamping pressure for glue line thickness. Based on glue bond thickness testing and fabrication experience it is recommended to use 1.2–1.4 mm 2 of adhesive per mm width to create full coverage glue bonds without excessive adhesive squeeze out. When tested under pure shear, specimens were observed to fail with a mixture of wood and glue, with more glue failure present as the pressure was increased. The initial stiffness of the connection tended to increase with clamping pressure, while the strength tended to decrease. Two bi-linear data fit models are applied to determine the yield point and simplify the load-slip behaviour for use in design analysis. Overall, the 75% max load method better fit the behaviour and was simpler to apply. The shear strength and stiffness achieved experimentally across all pressures were comparable to other glue connection literature results, and when applied in the design of a 10 m long MTC ribbed panel all pressures achieved near fully composite action. Overall, the adhesive has shown to be an easy to apply and structurally viable connection alternative for MTCs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".