Evaluation of the fall-off of gypsum board in lightweight and mass timber constructions and implications in fire resistance
Bibliographic record
Abstract
: This review study investigates the fall-off behavior of gypsum board (GB) in Lightweight Wood (LW) assemblies by synthesizing a comprehensive dataset compiled from previously conducted full-scale fire resistance tests. To address the inherent variability and scatter in the existing experimental data, this study incorporates detailed analyses and statistical modeling to discover consistent trends. A few quantitative findings are as follows: adding a second layer of 12.7 mm Type X GB increased the fall-off time to over 60 minutes, improving the fire resistance duration from an average of 50 minutes with a single layer to 68 minutes with 2 layers. On the other hand, insulated floors experienced accelerated GB degradation in 1-layer GB floors. Reducing the resilient channel spacing from 610 mm to 406 mm increased the fall-off time by approximately 10% for 2-layer GB floors. In a single layer of GB, the onset of wood charring was around 10.7 minutes before the GB fell off, while in 2-layered GB floors, the charring began 6.4 minutes after the face layer's fall-off. These findings extend beyond LW systems, offering potential solutions for mass timber (MT) structures where practical and economical GB encapsulation can facilitate fire safety in such structures. This study evaluates the GB protection design equations in international codes showing that these equations are conservative for single-layer GB but within the average range of the experimental results.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".