Efficiency assessment of oxyhydrogen-enhanced engine tested experimentally with multiple fuel blends
Bibliographic record
Abstract
This paper presents the results of a set of experimental tests designed to study the effects of oxyhydrogen blending with the fuels of gasoline, propane, methane, ethanol and methanol on their thermodynamic efficiencies (including energy and exergy efficiencies and power outputs) and carbon dioxide, carbon monoxide, unburned hydrocarbons and nitrogen oxide emissions in a spark-ignition (SI) engine-driven power generator. Each fuel is blended with oxyhydrogen at volumetric ratios of 5 %, 10 %, 15 %, and 20 %. The results demonstrate that oxyhydrogen addition consistently improves engine performance and avoids incomplete combustion. For all tested fuels, an addition of oxyhydrogen leads to a significant reduction in carbon-based emissions, with specific carbon monoxide, unburned hydrocarbons, and carbon dioxide emissions for gasoline decreasing by up to 59 %, 55 % and 52 %, respectively. This is coupled with an increase in power output and thermodynamic efficiencies; methane blends, for instance, achieved a 17 % boost in power output and reached an energy efficiency of over 46 %. Also, these benefits are accompanied by a substantial increase in NO x emissions, for example, NO x emissions for gasoline rising from 10 g/kg fuel to 47.8 g/kg fuel, which is attributed to higher in-cylinder combustion temperatures. The findings reveal a critical trade-off between reducing carbon-based emissions and controlling NO x formation. This work provides a clear evidence-based analysis that underscores the potential of oxyhydrogen as an efficiency booster and decarbonization agent for SI engines, while also highlighting the crucial need for integrated NO x mitigation strategies for environmentally sustainable power generation. • The paper presents a comprehensive experimental work on oxyhydrogen combustion. • The oxyhydrogen use reduces gasoline CO emissions by up to 59 %. • A 20 % HHO addition boosts methane's energy efficiency by 7.5 %. • It helps increase power output for methane blends by about 17 %. • It lowers unburned hydrocarbon emissions for gasoline by up to 55 %.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".