MétaCan
Menu
Back to cohort
Record W2048068366 · doi:10.4271/2013-01-0283

Low Temperature Combustion Strategies for Compression Ignition Engines: Operability limits and Challenges

2013· article· en· W2048068366 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2013
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsOperabilityIgnition systemHomogeneous charge compression ignitionCombustionCompression (physics)Automotive engineeringComputer scienceAutoignition temperatureNuclear engineeringCombustion chamberMaterials scienceEngineeringAerospace engineeringChemistry

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Low temperature combustion (LTC) strategies such as homogeneous charge compression ignition (HCCI), smokeless rich combustion, and reactivity controlled compression ignition (RCCI) provide for cleaner combustion with ultra-low NOx and soot emissions from compression-ignition engines. However, these strategies vary significantly in their implementation requirements, combustion characteristics, operability limits as well as sensitivity to boundary conditions such as exhaust gas recirculation (EGR) and intake temperature. In this work, a detailed analysis of the aforementioned LTC strategies has been carried out on a high-compression ratio, single-cylinder diesel engine. The effects of intake boost, EGR quantity/temperature, engine speed, injection scheduling and injection pressure on the operability limits have been empirically determined and correlated with the combustion stability and performance metrics. For dual-fuel combustion of diesel-ethanol (RCCI), the pilot-to-main fuelling ratio and pilot timing/quantity variations have been investigated to identify high-efficiency or high-load operation. The factors affecting the real-world application of these LTC strategies have been identified, the challenges needed to overcome have been highlighted and their effects on the engine performance quantified.</div></div>

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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