Neutron Radiography Study of Diesel Engine Exhaust Soot Depositions in a Exhaust Pipe With and Without Water Coolant
Bibliographic record
Abstract
An investigation was performed to study the soot deposition and its effect on heat transfer in a cooled cylindrical section. The soot layer thickness was measured using a non-destructive neutron radiography technique. Experiments were performed for a diesel exhaust mass flow rate of 20kg/hr or Reynolds number of approximately 9,000, initial inlet coolant temperatures of approximately 22 and 40°C, and exposure times from 1 to 3 hours. The results show that the nominal soot layer thickness was approximately uniform in the flow direction, hence, the thicker soot layer observed near the entrance by Ismail et al. [8] and de la Cruz et al. [9] was due to entrance effects. The deposited soot layer shows evidence of long wavy thickness variations that appears to be due to a soot re-entrainment and re-deposition moving bed type mechanism. The soot thickness increased and the long wavy variations persisted for larger soot thicknesses when the coolant temperature or wall temperature was lower. There was also evidence of larger soot thickness layer roughness for the lower wall temperature. These results could be due to an increase in the condensation of the vapour components at the lower wall temperature that may increase the soot adhesion. The heat transfer performance decreased faster for the lower coolant temperature, which is consistent with the soot deposition thickness measurement.
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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".