Numerical Study of the Geometry Effect of Notched Connections in Mass Timber Panel-Concrete Composite Floors
Bibliographic record
Abstract
A mass timber panel-concrete (MTPC) composite floor system consists of a timber panel in the tensile zone, a concrete layer in the compression zone, and shear connectors between timber and concrete. The notched connections that are cut in timber and connected with concrete by the interlocking effect are often classified as the best type of connection system in terms of stiffness and load-carrying capacity. To study the effect of notch geometry to the performance of notched connections and composite beams, 2D finite element models are built in ABAQUS in this study. The concrete portion is modelled with concrete damaged plasticity model while the timber portion is modelled with Hashin’s failure criteria. The effective bending stiffness and ultimate bending capacity of the composite beam under uniformly distributed load are obtained from the finite element models and are compared with the well-known Gamma method in Eurocode 5 and strut-and-tie model. Good agreement between finite element model in the elastic range and strut-and-tie model was achieved. However, due to the assumptions made in the Gamma method, it was found that this simplified design method is not capable of describing MTPC composite floors with discrete notched 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".