Bending Stiffness and Load–Deflection Response Prediction of Mass Timber Panel–Concrete Composite Floor System with Mechanical Connectors
Bibliographic record
Abstract
Mass timber panel–concrete (MTPC) composite floor systems are currently the preferred choice of designers for multistory modern mass timber construction. An analytical model for one-way-acting composite panels has been developed to predict the effective bending stiffness and load–deflection response of MTPC composite floor systems by considering the elastic-plastic behavior of interlayer connectors and the presence of a soft acoustic layer between concrete and timber. One-way-acting composite floor panels were tested under four-point bending and vibration with various configurations to validate the developed stiffness prediction model and investigate the influence of different parameters. The experiments showed that the model can predict the effective bending stiffness of MTPC composite systems within 10% of the bending test values in the elastic range and 14% of the modal test results. The so-called gamma method, commonly used for designing composite systems, provides predictions within 12% of the test bending stiffness, on average. Although both the gamma and proposed methods yield similar results, the proposed method is more comprehensive and less restrictive in terms of the underlying assumptions that underpin the method. The proposed model is also capable of predicting the postyielding load–deflection response of the composite system. A comparison of the predicted and tested load–deflection responses indicates a reasonable agreement between the two, although the predicted effective bending stiffness tends to be higher. The predictive capability of the model for the postyielding response can be further improved by considering the influence of cracking in concrete slabs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".