Performance of a drop-in biofuel emulsion on a single-cylinder research diesel engine
Bibliographic record
Abstract
Current targets in reducing CO2 and other greenhouse gases as well as fossil fuel depletion have promoted the research for alternatives to petroleum-based fuels. Pyrolysis oil (PO) from biomass and waste oil is seen as a method to reduce life-cycle CO2, broaden the energy mix and increase the use of renewable fuels. The abundancy and low prices of feedstock have attracted the attention of biomass pyrolysis in order to obtain energy-dense products. Research has been carried out in optimising the pyrolysis process, finding efficient ways to convert the waste to energy. However, the pyrolysis products have a high content in water, high viscosity and high corrosiveness which makes them unsuitable for engine combustion. Upgrading processes such as gasification, trans-esterification or hydro-deoxynegation are then needed. These processes are normally costly and require high energy input. Thus, emulsification in fossil fuels or alcohols is being used as an alternative. In this research work, the feasibility of using PO-diesel emulsion in a single-cylinder diesel engine has been investigated. In-cylinder pressure, regulated gaseous emissions, particulate matter, fuel consumption and lubricity analysis reported. The tests were carried out of a stable non-corrosive wood pyrolysis product produced by Future Blends Ltd of Milton Park, Oxfordshire, UK. The product is trademarked by FBL, and is a stabilized fraction of raw pyrolysis oil produced in a process for which the patent is pending. The results show an increase in gaseous emissions, fuel consumption and a reduction in soot. The combustion was delayed with the emulsified fuel and a high variability was observed during engine operation.
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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".