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Record W1520293668 · doi:10.1109/iecec.1997.656749

The effect of exhaust gas recirculation on the combustion noise level of an indirect injection diesel engine

2002· article· en· W1520293668 on OpenAlexaff
C.E. Bowen, Graham T. Reader, I.J. Potter

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsExhaust gas recirculationCombustionNoise (video)Automotive engineeringDiesel engineExhaust gasEnvironmental scienceDiesel fuelInternal combustion engineDiesel exhaustWaste managementEngineeringComputer scienceChemistry

Abstract

fetched live from OpenAlex

A pollutant that has not yet received as much public or regulatory attention as gaseous or solid particulate emissions is engine generated noise. Excessive levels of noise can, however, be as harmful to human health and the environment as noxious gases. In a well-designed engine, mechanical noise can be kept to a minimum but the combustion process itself still generates noise, "combustion noise". Thus, if the combustion process is modified for exhaust emission control it can be expected that the level of noise generated by combustion will also be affected, albeit not necessarily adversely. As exhaust gas recirculation (EGR) is becoming an essential technology for NO/sub x/ emission control in diesel engines, and, as this technique modifies the combustion process, it is important that the effects of using EGR on noise generation be identified.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.046
GPT teacher head0.253
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2002
Admission routes1
Has abstractyes

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