Performance and emission analysis of cassava peel waste pyrolysis oil-hydrogen-diesel blends in a compression ignition engine
Bibliographic record
Abstract
As the world moves away from fossil fuels and embraces sustainable energy sources, the need for sustainable fuels for transportation becomes paramount. This study investigates the effects of pyrolysis oil derived from cassava peel waste (CPO), hydrogen (H), and diesel (D) blends as a partial substitute for low-displacement compression ignition engines. We tested three blends – CPO25, CPO25H5, and CPO25H10 – against neat diesel operation at engine speeds of 3400 rpm, 3600 rpm, and 3800 rpm and torques of 4 Nm, 6 Nm, and 8 Nm. Our findings reveal that while energy efficiency decreased with CPO25 compared to D100 operation, adding H2 increased energy efficiency. The highest increase was 7.8 % for CPO25H5 and 16 % for CPO25H10 compared to CPO25. Exergy efficiency also decreased with CPO25 compared to D100, but adding H2 compensated for this reduction. The highest increase was 8.0 % for CPO25H5 and 17 % for CPO25H10 compared to D100. CPO25H10 showed an increase of 8.1 % in combustion pressure and 9.9 % in heat release rate compared to CPO25. Emissions analysis also revealed that CO emissions were considerably lower with CPO and H2 than with D100, with the highest decrease of 11 % with CPO25H10. CO2 and hydrocarbon emissions followed the same trend as CO. Although NOx emissions slightly increased, the benefits of using pyrolysis oil-H2-diesel blends as a partial substitution fuel for low-displacement compression ignition engines are evident.
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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 | 0.001 | 0.001 |
| 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".