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Record W2903903986 · doi:10.4271/2019-01-0063

Spray Characterization of Gasoline Direct Injection Sprays Under Fuel Injection Pressures up to 150 MPa with Different Nozzle Geometries

2019· article· en· W2903903986 on OpenAlexaff
Akichika Yamaguchi, Lucien Koopmans, Arjan Helmantel, Fabian Peng Kärrholm, Petter Dahlander

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2019
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsVolvo (Canada)
Fundersnot available
KeywordsNozzleGasolineMaterials scienceSpray characteristicsGasoline direct injectionCharacterization (materials science)Fuel injectionComposite materialSpray nozzleNuclear engineeringAutomotive engineeringPetroleum engineeringWaste managementMechanical engineeringEngineeringNanotechnology

Abstract

fetched live from OpenAlex

Maximum fuel injection pressures for GDI engines is expected to increase due to positive effects on emissions and engine-efficiency. Current GDI injectors have maximum operating pressures of 35 MPa, but higher injection pressures have yielded promising reductions in particle number (PN) and improved combustion stability. However, the mechanisms responsible for these effects are poorly understood, and there have been few studies on fuel sprays formed at high injection pressures. This paper summarizes experimental studies on the properties of sprays formed at high injection pressures. The results of these experiments can be used as inputs for CFD simulations and studies on combustion behavior, emissions formation, and combustion system design. The experiments were conducted using an injection rate meter and optical methods in a constant volume spray chamber. Injection rate measurements were performed to determine the injectors’ flow characteristics. Spray imaging was performed using a high-speed video camera. Several spray properties such as the liquid spray penetration, spray plume angle, and the spray breakup point were determined as functions of the fuel injection pressure and injected fuel mass by image post-processing. The impact of fuel pressure on spray droplet size was also investigated using two-component Phase Doppler Interferometry. Piezoelectric injectors for diesel engines were used with modified nozzles that produce sprays resembling those generated in gasoline engines. Experiments were performed with fuel injection pressures ranging from 20 to 150 MPa, and chamber pressures of 0.1 and 0.6 MPa. In addition, four different nozzles with three different nozzle configurations and either 6 or 10 holes were used to determine how hole geometry affects spray formation. The study’s key findings are that increasing the fuel injection pressure advances spray breakup and creates smaller droplets, improving mixture formation and accelerating evaporation. The nozzle type and the ambient pressure both significantly affect aspects of spray behavior such as spray tip development.

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 score0.002
Threshold uncertainty score0.008

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)0.0020.000

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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

Citations36
Published2019
Admission routes1
Has abstractyes

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