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Record W1157126761 · doi:10.1299/jmsesdm.2012.8.251

EC1-1 A Control Strategy Analysis for Clean and Efficient Combustion in Compression Ignition Engines(EC: Engine Control,General Session Papers)

2012· article· en· W1157126761 on OpenAlexaff
Usman Asad, Ming Zheng, Jimi Tjong, Meiping Wang

Bibliographic record

VenueThe Proceedings of the International symposium on diagnostics and modeling of combustion in internal combustion engines · 2012
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsHomogeneous charge compression ignitionCombustionAutomotive engineeringDiesel cycleExhaust gas recirculationDiesel engineIgnition systemCompression ratioInternal combustion engineDiesel fuelHydrogen internal combustion engine vehicleComputer scienceEnvironmental scienceCombustion chamberEngineeringChemistryAerospace engineering

Abstract

fetched live from OpenAlex

In this work, the pathways and challenges for enabling the clean and efficient combustion are first identified with extensive engine tests on a high compression ratio single-cylinder diesel engine. The engine load and emission trade-offs are analyzed for different fuel injection strategies, intake boost, injection pressure and exhaust gas recirculation. The identified challenges are then analyzed to define the requisite control strategies for improving the stability and combustion efficiency of such clean combustion processes. Moreover, the critical issue of switching in multi-mode combustion on-the-fly is also addressed and empirically demonstrated for the seamless transition from the single-injection to multi-injection modes in 3 consecutive engine cycles without leaving low temperature combustion. To further demonstrate the robustness of the control system, the use of ethanol in a dual-fuel configuration with a diesel pilot-injection is demonstrated to extend the load limit of clean combustion. This research intends to advance the control methodologies for application of the clean combustion modes over the engine operating regime.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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.

Study designSimulation or modeling
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

Citations5
Published2012
Admission routes1
Has abstractyes

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