Predicting the thermal response of gypsum board subjected to a constant heat flux
Bibliographic record
Abstract
Abstract Models are available to predict the fire‐resistance ratings of wood‐frame assemblies protected by gypsum board. These models have been developed to predict the performance of assemblies exposed to a standard fire test in which temperatures increase monotonically. In an ongoing effort to model the fire resistance of light‐frame wood floor assemblies, in this study, a number of improvements over past heat transfer models have been made in an attempt to simulate assembly performance in any arbitrary fire exposure. For this purpose, the heat transfer analysis has been coupled with a mass transfer analysis. The calcination of gypsum board and pyrolysis of wood are now modelled using an Arrhenius expression. In order to evaluate the accuracy of the model, a series of cone calorimeter experiments have been conducted in an effort to generate experimental data under well‐defined boundary conditions. Comparisons between test results and the predictions from a one‐dimensional heat and mass transfer analysis are encouraging with excellent agreement in predicting the point at which gypsum board is fully calcinated. A lack of material property data, particularly the permeability of gypsum board, remains a limiting factor in further improvement of the accuracy of the model. Copyright © 2008 John Wiley & Sons, Ltd.
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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".