Thermal properties of lightweight‐framed construction components at elevated temperatures
Bibliographic record
Abstract
Abstract Fire resistance behaviour of lightweight‐framed assemblies is determined by defining the thermal and structural performances of the assembly when exposed to fire. To adequately model thermal behaviour in a lightweight wood‐framed assembly, thermal properties of the components of the assembly at elevated temperatures must be well defined. This paper presents results of measurements of thermal properties at elevated temperatures of construction materials commonly used to build lightweight wood‐framed assemblies that were conducted at the National Research Council of Canada since 1990. The test results, in graphical form, are given as a function of temperature for thermal conductivity, specific heat, mass loss and thermal expansion/contraction for wood, gypsum and insulation. In addition, the effects of temperature on the thermal conductivity, specific heat, mass loss and thermal expansion/contraction of these materials are discussed. Finally, in addition to providing a resource of information, this paper also identifies the additional thermal property tests required to complete the matrix of information. Copyright © 2005 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| 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".