Characterization of the Soot Deposition Profiles in Diesel Engine Exhaust Gas Recirculation (EGR) Cooling Devices Using a Digital Neutron Radiography Imaging Technique
Bibliographic record
Abstract
<div class="htmlview paragraph">A non-destructive neutron radiography technique was used to measure the thickness of diesel soot deposited in the tubes of exhaust gas recirculation (EGR) cooling devices. Measurements were performed to characterize the fouling in single-tube and three-tube devices for laminar and turbulent flows. Measurements were also performed to characterize the effect that the design of the inlet header had on the deposition characteristics in the device. The analysis of the neutron images showed that the soot deposition in the single-tube device occurred at a faster rate for a turbulent flow than for a laminar flow. The deposition thickness decreased along the tubes for both flow regimes. More soot deposited in the center tube of the three-tube bundle for the expansion angle 45° inlet header suggesting there was an uneven distribution of the exhaust gas flow in the tube bundle. For the device with the expansion angle 60° inlet header the soot was approximately more evenly distributed along the tubes.</div>
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".