Heat release rates of modern residential furnishings during combustion in a room calorimeter
Bibliographic record
Abstract
Summary Results are presented from a number of fire experiments that were conducted in a room environment to study the fire characteristics of typical residential furnishings and assist in the design of a subsequent phase of a project involving fully furnished room fire experiments. The experiments were conducted in a 16‐m2 test room (with dimensions 3.8 m wide × 4.2 m long × 2.4 m high), which had a 1.5 × 1.5‐m window opening. The furnishings tested included mattresses, bed clothes, bed assemblies, upholstered seating furniture, clothing arrangements, books, plastic audio/video media and storage cases, toys, shoes, and a computer workstation setup. The smoke (gaseous products of combustion) from the room was collected using a hood system in order to measure the heat release rate (HRR) and optical density of the smoke. The test room was instrumented with load cells, heat flux gauges, thermocouples and velocity probes in order to take the following measurements: mass loss, total heat flux on gauge‐installed flush with the internal surfaces (floor, walls, and ceiling), temperatures at numerous locations, and gas velocities in the window opening. Twin‐size mattresses produced peak HRRs of approximately 3800 kW, and the maximum room temperature was approximately 980°C. The HRRs of bed assemblies of various sizes and configurations ranged from 1800 kW for a twin‐size bed to 6250 kW for a bunk bed. The maximum temperature and heat flux recorded in the experiments were 1071°C and 221 kW/m2, respectively. Upholstered chairs and sofas had HRRs ranging from 630 kW for an ottoman to 3360 kW for a two‐seat sofa. In tests with clothing, toys, shoes, books, a computer workstation, and CD/DVD media, the peak HRRs ranged from 440 kW for a bookcase to 2045 kW for toys. Furnishings containing a large proportion of rigid thermoplastic plastics, such as shoes and media cases, produced very dense smoke even at low HRRs. The effect of parameters such as bed clothes, mattress type, foundation type, bed assembly and chair size, material composition, and fuel package arrangement was evident in the results. Because the room dimensions and wall lining materials remained constant, temperatures were linearly proportional to the peak HRR (and exposure time) until the ventilation limit (approximately 4100 kW) was reached. Copyright © 2014 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".