Fuel Tank and Charcoal Canister Fire Hazards during EVAP System Leak Testing
Bibliographic record
Abstract
<div class="htmlview paragraph">The combination of on-board diagnostics and evaporative emission control (EVAP) systems has led to a growing need to identify and repair leaks in automotive EVAP systems. The normal leakfinding method involves purging the system with a smoke fluid, usually air or nitrogen containing an oil aerosol and then looking for a visual indication of the leak. The purge flow used to distribute smoke through the system displaces substantial amounts of fuel vapor from the tank vapor space and can also raise the oxygen level inside the fuel system. If any ignition source is present, the formation of flammable mixtures both inside and outside the vehicle systems can lead to a flash fire hazard associated with leak finding procedures. Currently available fire statistics (such as NFPA) are not sufficiently detailed to attribute service shop fires to specific testing procedures. However, concern over anecdotal reports of flash fires has led to a study of flammable mixture formation during evap system testing. This paper describes a set of experimental and modeling studies aimed at better understanding fuel vapor behavior and associated fire hazards of EVAP system leak testing.</div> <div class="htmlview paragraph">The first phase of the project involved experimental measurement and Computational Fluid Dynamics (CFD) modeling of fuel vapour / air mixture distribution in a tank vapour space with an imposed flow rate typical of leak testing equipment. Initial fuel vapor concentrations, (and thus the quantity of vapor expelled during the initial purge), depend strongly on fuel volatility and temperature. In addition, purge flow rates in the vicinity of 10 litres/minute can produce substantial quantities of flammable mixture inside the fuel system. The quantity of purged vapor available for an external flash fire is highest for high volatility gasoline while the quantity of flammable mixture formed inside the fuel system tends to be highest for low volatility gasoline.</div> <div class="htmlview paragraph">The second phase of the project examined charcoal canister behavior with typical leak test flows imposed through the EVAP system. A basic model of canister behavior was established by measuring butane working capacity and gasoline working capacity under standard test conditions. Further experimental tests examined the fuel vapour concentrations leaving a pre-loaded charcoal canister with an imposed purge flow. Test results showed substantial release rates of fuel-rich gasoline vapor during early stages of testing and a long period of flammable vapor emission with prolonged testing. Ignition tests confirmed the flammability and flame characteristics of the mixture leaving the canister.</div> <div class="htmlview paragraph">Recommended procedures to limit the flammable mixtures formed during leak-testing are discussed in the paper.</div>
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".