Experimental and numerical analysis on fire behaviour of loaded cross-laminated timber panels
Bibliographic record
Abstract
Cross-laminated timber is a relatively new engineered timber material that can be used in the design and construction of modern timber buildings. A key factor that raises concerns in the wide application of cross-laminated timber is the uncertainty of its fire performance. This article describes experimental and numerical investigations on the fire behaviour of loaded cross-laminated timber panels manufactured with Canadian hemlock. A total of 10 cross-laminated timber panels with different number and thickness of layers were tested under ambient and standard fire conditions to investigate the flexural capacity at ambient temperature, and temperature distribution, charring rate, fire resistance, mid-span deflection under fire exposure. Three-dimensional finite element model was developed using the Hashin criterion and cohesive elements to predict the failure of wood and adhesive, respectively. The thermal model implicitly considers the rapidly increased temperature of inner fresh timber after the protective charred layers have fallen off. The numerical model was validated with the results obtained from experimental tests and was found to have the ability to simulate the fire behaviour of loaded cross-laminated timber panels in reasonable accuracy.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".