Bibliographic record
Abstract
The international standard ISO 5660 Cone Calorimeter test is widely used in fire research and for modeling, but not so often in legislation or requirements on products. The available acceptance criteria for products in different countries and codes have therefore been compiled and are presented in tables. Some research studies have also been included. There are several national standards with different designation based on ISO 5660 for fire testing according to the Cone Calorimeter, for example, ASTM E1354 in the US, AS/NZS 3837 in Australia, and New Zealand. Part 1 is most used and heat exposure at 50 kW/m2 is preferred in research and for expressing acceptance criteria, see Table 1. In a few cases, heat exposure at 25 kW/m2 is utilized, see Table 2. Part 4 uses a larger cone heater and allows larger specimens 150 × 150 mm compared to 100 × 100 mm for the other parts. National versions of ISO 5660-4 are used in Canada as CAN/ULC-S135 and in the US as ASTM E2965. New Zealand A separate standard on mass loss rate is also available as ISO 17554. It may be used for industry production control. Acceptance criteria for general classification of building products are used in New Zealand as direct test data, see Table 1. Australia uses indices based on Cone Calorimeter data, and direct test data only for Bushfire resisting timber, see Table 2. The codes IBC and IFC use acceptance criteria for special products like water resistive barriers, children's playground structures, and plastic rubbish containers. The same is true for the NFPA standards 1, 101 and 5000. In the European standard EN 16755 and in New Zealand, the Cone Calorimeter is used specifically for fire retardant treated wood products before and after weathering, see Table 1. The main parameter used in acceptance criteria is peak heat release rate (HRR) in kW/m2. For non-combustibility total heat release (THR) in MJ/m2 is added in Japan and Korea. Canada and NFPA 220 use THR for non-combustibility but measured at different heat exposures and slightly different cone heaters, see Table 3. Table 4 presents two research studies with the aim to determine acceptance criteria based on extensive fire testing. The study by Wade aimed at creating performance-based criteria and is used as background verification for the legislation in New Zealand and the one by Tsantaridis et al focused on wood products. Fire retardant wood products Euroclass B Fire retardant wood products Euroclass C Wood products Euroclass D Thanks to Marc Alam, Jungmin Choi, Christian Dagenais, Mark Dietenberger, Andrew Dunn, Marc Janssens, Koichi Yoshida, Jason Smart, Kuma Sumathipala, Yongho Yoo and Colleen Wade for useful information. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
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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".