Investigation of the explosion severity of multiphase hybrid mixtures
Bibliographic record
Abstract
Abstract This study presents an experimental investigation of the maximum explosion pressure (Pmax) and rate of pressure rise (dP/dt)max of dusts (lycopodium and brown coal), solvents (ethanol, isopropanol), gases (methane and hydrogen) as well as two‐ and three‐phase hybrid mixtures. Experiments were performed in a standard 20 L sphere with a 10‐J electrical igniter as an ignition source and a 60 ms ignition delay time. It was consistently noticed that the explosion severity of a dust and gas/spray hybrid mixture was higher than that of dust, but lower than either gas or solvent. The addition of a flammable gas/spray to a dust‐air mixture increases the maximum explosion pressure to some extent and significantly increases the maximum rate of the dust mixture pressure rise, even though the concentration of the flammable gas/vapor is below its lower explosion limit. For instance, lycopodium with maximum rate of pressure rise value of 272 bar/s increased to 322, 369, 410, and 504 bar/s when methane concentration of 1, 2, 3, and 4 vol% was respectively, added. These values of maximum rate of pressure rise further increased to 430, 460, 573, and 798 bar/s when a nonexplosible concentration of a third‐phase isopropanol (50% lower than the lower explosion limit) was added. From the findings of this research, it could be inferred that one cannot rely on the explosion severity of a single substance to ensure the safety of a process or system when substances with different states of aggregate are present.
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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) | 0.000 | 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 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".