Heat Transfer in Cone Calorimeter Tests of Generic Wall Assemblies
Bibliographic record
Abstract
It is critical for the construction industry to ensure that new building designs and materials, including wall and floor assemblies (e.g., a studded wall with insulation and drywall) provide an acceptable level of fire safety. A key fire safety requirement that is specified in building codes is the minimum fire resistance rating, which is a measure of the ability of an assembly to limit fire spread within a building. A manufacturer of building materials (e.g., insulation or drywall) is required to perform full-scale fire resistance furnace tests to determine the fire resistance ratings of assemblies that use their products. Fire resistance test facilities are very limited and these tests are very expensive to perform. Therefore, it can be difficult to properly assess the impact of changes to individual components on the overall fire performance of an assembly during the design process. As part of a project to develop methods of using small-scale fire test data to predict full-scale fire resistance test results, the heat transfer through scale models of common wall assembly designs was measured during cone calorimeter tests using an incident heat flux of 75 kW/m2. Wall assemblies consisting of single and double layers of 12.7 mm (1/2 in.) regular and lightweight gypsum board, and 15.9 mm (5/8 in.) type X gypsum board, along with mineral wool insulation and wood studs were tested. Temperature measurements made at various points within these assemblies are presented in this paper, and are discussed using results from thermal gravimetric analysis tests of the three types of gypsum board. Implications of this research to the development of heat transfer models and scaling relationships are also briefly discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".