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Record W3120903610 · doi:10.1177/0954407020984599

Investigation of multi-event spark discharge strategy for lean methane-air combustion

2021· article· en· W3120903610 on OpenAlexaff
Hua Zhu, Xiao Yu, Liang Li, Ming Zheng, Graham T. Reader

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · 2021
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsIgnition systemElectromagnetic coilCombustionPartial dischargeOffset (computer science)Materials scienceVoltageMethaneNuclear engineeringAutomotive engineeringMechanicsElectrical engineeringComputer scienceAerospace engineeringChemistryEngineeringPhysics

Abstract

fetched live from OpenAlex

The characterization of the single-coil repetitive discharge and the dual-coil offset discharge was conducted in a constant volume combustion chamber to better understand the operating principle of the multi-event spark ignition strategies. A parametric study of the dual-coil offset discharge was carried out through electric and optical diagnosis to identify the effective operational parameters, including coil working frequency, charging voltage, and coil inductances. Combustion tests under both quiescent and flow conditions with methane-air mixture were performed to demonstrate the ignition capability of the dual-coil offset strategy. Test results have shown that constantly depositing spark energy through offset discharge is beneficial to secure flame kernel. However, the offset discharge strategy requires a high working frequency, an elevated charging voltage, and fast reacting coils to maintain the spark plasma channel under high background pressure and intensified flow conditions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.153
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.030
GPT teacher head0.265
Teacher spread0.235 · 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 teacher head, 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part D Journal of Automobile EngineeringSame topicPlasma Applications and DiagnosticsFrench-language works237,207