Bibliographic record
Abstract
Convectional free flame combustion causes the temperature rise in the vicinity of the flame to be very steep, resulting in high temperatures, consequently NOx formation enhances. The fact is that the thermal conductivity of gases are very low, i.e., poor thermal conductors. Combustion in porous media elevates this problem by enhancing heat conduction and thermal radiation from the flame zone, which reduces the flame temperature and NOx formation. Also, heat transfer from the free flame to a load is mainly by convection, while heat transfer is by convection and radiation from combustion zone in porous medium to a load. Moreover, it is easy to stabilize the flame in a porous medium, where the thermophysical properties of the porous medium can engineered for specific application. Most of the work is done on flat type porous burner, where the axial flow of gaseous fuel air mixture forces through a layer of porous medium. In this report a concept of cylindrical porous burner is introduced, where the fuel air mixture is forced to flow radially. Mathematical models and simulation results are introduced for both burners, axial and radial flow burners. Preliminary results of the comparison between the thermal performances between the mentioned burners are discussed. The results revealed that the cylindrical burner has superiority over the convectional flat burner. The cylindrical burner has a wide range stability limits and may produce less NOx than the flat type burners.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".