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Record W2077052586 · doi:10.2514/1.21462

Investigation of Active Flow Control on Diesel Engine Aftertreatment

2008· article· en· W2077052586 on OpenAlexafffund
Ming Zheng, Graham T. Reader, Meiping Wang

Bibliographic record

VenueJournal of Propulsion and Power · 2008
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsOverheating (electricity)Diesel fuelAutomotive engineeringEnvironmental scienceTransient (computer programming)ThermalDiesel engineVolumetric flow rateExhaust gasFlow (mathematics)Materials scienceEngineeringMechanicsWaste managementComputer scienceThermodynamicsElectrical engineering

Abstract

fetched live from OpenAlex

Theoretical studies are performed with one-dimensional transient modeling techniques to analyze the thermal behavior of the diesel aftertreatment systems when active flow control schemes are applied. The combined use of activegas flowandactivefueling-controlschemesareidentifiedtobecapableofshiftingtheexhaustgastemperature, flow rate, and oxygen concentration to more favorable windows for the filtration, conversion, and regeneration processes. Several external fuel-supplying techniques are applied and analyzed with various heat distribution patterns and exhaust flow control parameters. The analysis indicates that the active flow control schemes have fundamental advantages in optimizing the converter thermal management that includes supplemental heating, thermal retention, thermal recuperation, and overheating protection. Modeling validation analyses with selected experiments are also reported.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.223
Teacher spread0.210 · 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

Citations3
Published2008
Admission routes2
Has abstractyes

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