Analysis of an Internal Combustion Engine Using Porous Foams for Thermal Energy Recovery
Bibliographic record
Abstract
Homogeneous and complete combustion in internal combustion engines is advantageous. The use of a porous foam in the exhaust gas in an engine cylinder for heat recovery is examined here with the aim of reducing engine emissions. The internal combustion engine with a porous core regenerator is modeled using SOPHT software, which solved the differential equations for the thermal circuit in the engine. The engine thermal efficiency is observed to increase from 43% to 53% when the porous core regenerator is applied. Further, raising the compression ratio causes the peak pressure and thermal efficiency to increase, e.g., increasing the compression ratio from 13 to 15 causes the thermal efficiency and output work to increase from 53% to 55% and from 4.86 to 4.93 kJ, respectively. The regenerator can also be used as a catalytic converter for fine particles and some other emissions. The regenerator oxidizes unburned hydrocarbons. Meanwhile, heat recovered from the exhaust gases can reduce fuel consumption, further reducing pollutant emissions from the internal combustion engine.
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 | 0.001 |
| 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".