MétaCan
Menu
Back to cohort
Record W2997760111 · doi:10.4271/2019-01-2165

Evaluation of the Potential of Direct Water Injection in HCCI Combustion

2019· article· en· W2997760111 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 · 2019
Typearticle
Languageen
FieldChemical Engineering
TopicAdvanced Combustion Engine Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHomogeneous charge compression ignitionCombustionAutomotive engineeringEnvironmental scienceNuclear engineeringChemistryCombustion chamberEngineering

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">Homogeneous charge compression ignition (HCCI) is a part load, low-temperature combustion process which operates at lean mixtures and produces ultra-low NO<sub>X</sub> emissions. As opposed to SI engines that use a spark to control combustion timing, HCCI combustion is enabled by compression induced autoignition which is characterized by rapid global and spatial combustion yielding fuel efficiency benefits. This process is highly dependent on the in-cylinder state, including pressure, temperature and trapped mass. The absence of a direct combustion control proves to be a major challenge and results in unstable engine operation especially at the limits of the narrow operation range. In recent studies, direct water injection is used in HCCI combustion to stabilize combustion and increase the operation range. This paper outlines the thermodynamic influence and evaluation of the potential of water injection for HCCI combustion. Investigations were performed on two single cylinder research engines using different fuels to investigate the effect of direct water injection on HCCI combustion. In this work, the required energy to achieve autoignition is obtained using internal exhaust gas recirculation which is controlled via negative valve overlap. Steady state water injection timing, pressure and mass sweeps were performed to analyze the influence on HCCI combustion. Based on these single cylinder investigations, simulations were performed to simulate the effect of water on the amount of residual gas, in-cylinder temperature and rate of heat release. In addition, cyclic water injection investigations were performed, to separate the long term from the short term cooling effects. The results show a significant reduction of 44.5 % in NO<sub>X</sub> emissions when injecting water every cycle, and even a 12.2 % reduction when injecting water every 2 cycles. This trade-off between water consumption, combustion phasing and NO<sub>X</sub> emissions reduction can be useful for optimization in future control applications.</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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.939
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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