Experimental Study of Heat Flux in Propane Flash Fires
Bibliographic record
Abstract
Existing test methods for determining of thermal protection from fire offered by textiles are typically characterized by the exposure of specimens to a controlled flame and measurement of energy transferred through the specimen. The measured energy transfer is then used to differentiate materials or further processing (burn injury prediction) is used as a basis for comparison. The test conditions are set by measuring the energy transferred to the sensor or sensors in absence of a test specimen. In order to represent a potential hazard and provide good differentiation among tested materials, an exposure heat flux is required that allows for rapid and substantial increase in the temperature of the tested specimen. A specified heat flux of 80–84 kW/m2 is common in both bench-scale and full-scale tests. Because of the use of controlled flame and significant energy transfer rates involved in these tests, there is a common misconception that these test methods constitute a simulation of a particular hazard, especially with regard to the hazard of hydrocarbon flash fires. In order to provide a basis for comparing specified test conditions with real-world hazard conditions, a series of heat flux measurements were performed on propane-fueled flash fires in open air. In each test, an array of heat flux sensors was positioned around a propane source. A large fuel cloud was allowed to form and subsequently ignited using a pilot flame. These experiments were carried out outdoors and as such were subject to prevailing wind currents. Because of the potentially high variability, more than 50 separate fuel releases were undertaken. The output of the array of sensors was used to determine the intensity and duration of each flash fire event. In addition to the array of heat flux sensors, an instrumented mannequin was constructed to measure the heat flux incident on a human form within the flash fire. The results indicate that there was significant variability in the conditions in each fire due to the open air conditions creating unpredictable distribution of fuel and air. Flash fires occurred that were less severe and more severe than the conditions used in standardized laboratory testing.
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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) | 0.001 | 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 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".