Experimental and Numerical Investigations of Groove Connections for a Novel Timber-Concrete-Composite System
Bibliographic record
Abstract
The development of hybrid structures is constantly being pushed forward because of the need for more efficient components that incorporate multiple functions. Structural requirements lead to state-of-the-art timber-concrete-composite (TCC) floor systems, which consist of a concrete layer on top of timber beams or decks. In bending, the TCC concrete layer is in compression and the timber is in tension. When multifunctionality requirements such as building physics or fire protection are added, other solutions of the structural form of hybrid systems can emerge that challenge common engineering conceptions. This paper presents research on the connection system of a novel TCC setup that integrates thermal and fire protection functionality, in which timber beams are placed at the top and a concrete layer at the bottom. The results from full-scale bending tests, and shear and tension tests on a subsection of the system, show that the grooves cut into the timber beams transmit the shear forces and sufficiently connect the concrete deck vertically to the timber. Subsequently, the structural behavior was numerically modeled and the agreement between experimental and numerical results allow for the validated model to be used for geometric optimizations, and predicting the performance of optimized systems.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".