Rail tank cars exposed to fires: experimental analyses of thermal conditions imposed to a railcar engulfed in crude oil fires (Series 1-3 Tests)
Bibliographic record
Abstract
A series of 2-m pool fire experiments were performed to better evaluate the comparative thermal hazard between different crude oils as a result of pool fires, which could occur as a consequence of an accident in the land transport of crude oils. In order to assess the thermal conditions to which a rail tank car could be exposed, a calorimeter designed to simulate a 1/10th scale tank car was placed above a 2-m diameter pool fire fueled by heptane in Series 1 tests, Bakken crude oil from North Dakota in Series 2 tests and diluted bitumen (dilbit) crude oil from Alberta in Series 3 tests. The calorimeter was instrumented to measure the total heat flux at various locations along its surface. The crude oils used in the testing program were specially handled to ensure no change in its composition over the course of the testing program, from the time of fuel acquisition to the time of fire testing. In conjunction with the fire testing, a fuel characterization study was conducted to enable the study of fire effects in relation to fuel properties. The burning behaviours of the fuels were observed by measuring the burning rate, flame height and heat release rate (HRR), the flame surface emissive powers (SEP) and the incident heat fluxes away from the fire. Overall, the Bakken crude oil and heptane fires displayed continuous steady burning throughout the test while the dilbit crude oil fires displayed unsteady burning behaviour, which was mainly caused by the fuel composition containing a larger fraction of heavy end hydrocarbons than the Bakken crude oil and heptane. The total heat flux measured by the calorimeter indicated that the measurements were uneven around the circumference of the calorimeter. The average heat flux to the calorimeter from the Bakken and dilbit crude oil fires was higher than that from the heptane fires although the measured HRRs of the Bakken and dilbit crude oil pool fires were less than those of the heptane pool fires. The main reason for the increased heating of the object in particular by the Bakken and dilbit crude oil fires is that the total heat flux to the object is mostly affected by radiative heat exposure from the flame, and the Bakken and dilbit crude oil fires have higher radiative heat fraction. The study also investigated the effects of test parameters on fire characteristics. These parameters include the effect of fuel types, the presence and placement of a calorimeter engulfed in the fire, fuel feed temperature, and allowing the fuel to burn down. The results indicate that there was no significant effect of “fuel supply temperature” and “fuel to burn down (i.e., non-continuous fuel feed)”. The higher fuel supply temperature increased the burn rate by about 10% for the heptane and Bakken crude oil tests. For the dilbit crude oil fires, due to the non-steady burning behaviour, the impact of the calorimeter was difficult to capture. Allowing the fuel to burn down, rather than maintaining a constant fuel level in the pool pan, resulted in minimal effect on average values of the mass burning rate and general fire characteristics of the Bakken crude oil pool fires. For the dilbit crude oil, the fuel compositional effect on the burning behaviour was observed in both continuous and non-continuous fuel feeding. The non-uniform burning behaviour became easier to discern when there was no continuous fuel feed into the fuel pan.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".