Investigating Humidity Effects on Small Offroad Engine SI Performance and Emissions
Bibliographic record
Abstract
Collaborative research outlined in this paper documents recent engine and emission performance of a newer, more robust small SI engine across a sweeping range of relative humidity (RH) having fixed intake air temperature and pressure. The experimental results will show that power correction references to SAE J1349 as well as humidity correction (Kh) reference in EPA 40 CFR §1065 may generically be applied, but do not accurately compensate for the extent of correction required. The test results shared from this particular performance testing of a Kohler KT745 carbureted engine develops the case for a more diverse and less conservative approach to a one-size-fits all strategy related to humidity corrections within the small SI testing community. Moreover, humidity effects for both observed and corrected power, as well as emission corrected constituents (not just NOx) are generally greater than would otherwise be assumed from the literature. From these results, facilities without intake air humidity management may unknowingly bias brake specific emissions of both HC+NOx and CO family emission limits (FELs). Moreover, in defining family emission limits with NOx only correction, general performance repeatability in certifications as well as production line testing (PLT) results throughout the year may contribute to a wider deviation in engine-to-engine emission variability and power than might normally be expected. The following results are specifically for rich engine operation of an air-cooled engine, and subsequent results for stoichiometric air-cooled engine relative humidity effects would need to be discussed separately.
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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 | 0.001 |
| 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) | 0.002 | 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".