FEASIBILITY STUDY ON LONG-SPAN CLT-GLULAM COMPOSITE FLOORING SYSTEM CONNECTED WITH BAMBOO-TENON SHEAR CONNECTORS
Bibliographic record
Abstract
The rise of cross-laminated timber (CLT) became a cornerstone for the development of mass timber highrise buildings and for large applications of timber products in construction.The design of CLT floors is often hinged upon meeting the vibration and deflection requirements under serviceability limit states.As a result, thick and materialintensive sizes of floor members can result from the design to fulfil the minimum stiffness requirements.A long-span composite flooring system made of CLT panel and glulam ribs is a structurally optimized and cost-effective solution.In this paper, a feasibility study of a 12-meter composite flooring system consisting of CLT slab and glulam ribs jointed through bamboo-tenon shear connectors was conducted.The flooring system was designed to achieve performance objectives per the National Building Code of Canada, focusing on office spaces.Finite element modelling was used to investigate the behaviour of connectors under push-out shear forces.A parametric study of the shear connector was then carried out.Impacts of the material properties of mortise-tenon on the behaviour of the joints were discussed.Further, the structural performance of the composite system was investigated under several case scenarios.Specific design recommendations for adopting bamboo-tenon as the shear connector in composite systems were provided.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".