Fostering Composite Structures of UHPC and Timber
Bibliographic record
Abstract
Timber-Concrete Composite (TCC) structures are emerging in bridge and multi-storey buildings as they allow optimizing multiple performances, such as the structural stiffness and strength, enchanted vibration behavior, improved durability, and lower environmental impact in terms of carbon dioxide emission. The composite action consists of a couple of axial forces that significantly contribute to the resistant moment. This work aims at fostering the use of UHPFRC slab for TCC structures by taking advantage of the high compressive strength and shear resistance. In particular, two kinds of TCC structures are considered: (i) UHPFRC slab connected to a GLULAM (Glued Laminated) timber beam; (ii) UHPFRC slab connected with a Cross Laminated Timber slab. The threefold methodology consists of : (i) a multi-criteria design optimization, which considers vibrational effect and long term deflection; (ii) experimental characterization of shear behavior by push-out tests; (iii) vibrational and structural tests on four point bending tests on long span TCC beams; (iv) non-linear Finite-Element analysis. The present results show the important potentials of UHPFRC for reducing the weight and increasing the slenderness of TCC structures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".