Heat release rate and emissions regimes of stratified pilot-ignited direct-injection natural gas combustion
Bibliographic record
Abstract
Natural gas (NG) is an attractive fuel for heavy-duty internal combustion engines because of its potential for reduced CO 2 , particulate, and NO X emissions and lower cost of ownership. Pilot-ignited direct-injected NG (PIDING) combustion uses a small pilot injection of diesel to ignite a main direct injection of NG. Recent studies have demonstrated that increased NG premixing is a viable strategy to increase PIDING indicated efficiency and further reduce particulate and CO emissions while maintaining low CH 4 emissions. However, it is unclear how the combustion strategies relate to one another, or where they fit within the continuum of NG stratification. The objective of this work is to present a systematic evaluation of pilot combustion, NG combustion, and emissions behavior of stratified-premixed PIDING combustion modes that span from fully-premixed to non-premixed conditions. A sweep of the relative injection timing, [Formula: see text], of NG and pilot diesel was performed in a heavy-duty PIDING engine with [Formula: see text] = 140–220 bar, [Formula: see text] = 0.47–0.71, and a constant NG energy fraction of 94%. Apparent heat release rate and emissions analyses identified interactions between the pilot fuel and NG, and qualitatively characterized the impact of NG stratification on combustion and emissions. Changes in the [Formula: see text] resulted in six distinct PIDING combustion regimes, for all considered injection pressures and equivalence ratios: (i) RIT-insensitive premixed, (ii) stratified-premixed (early-cycle injection), (iii) NG jet impingement transition, (iv) stratified-premixed (late-cycle injection), (v) variable premixed fraction, and (vi) minimally-premixed. Parametric definitions for the bounds of each regime of combustion were valid for the wide range of [Formula: see text] and [Formula: see text] investigated, and are expected to be relevant for other PIDING engines, as previously identified regimes agree with those identified here. This conceptual framework encompasses and validates the findings of previous stratified PIDING investigations, including optimal ranges of operation that provide significantly increased efficiency and lower emissions of incomplete combustion products.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".