Tailoring Ethanol High Temperature Ignition by Means of Chemical Additives and Water Content
Bibliographic record
Abstract
The quest for sustainable alternatives to fossil fuels leads to a growing diversification of the molecular structures of fuel sources. Since ignition is a vital property in the choice of an engine combustion concept, the ability to tailor the ignition behavior of various fuel sources by means of fuel additives is expected to aid the development of fuel-flexible engines. Ethanol is one of the biofuels with a potential to play an important role in the transportation fuel mix of the future. One of the final processes during ethanol production involves distillation in order to minimize the water content. Using wet ethanol in combustion engines could lead to a reduction in the energy consumption during fuel processing. An understanding of fundamental combustion properties of ethanol in the presence of water vapor such as ignition behavior is expected to aid in the design of efficient engine combustion processes. In this work, the effect of two esters, isopropyl nitrate (IPN) and isopropyl formate (IPF), on the high temperature shock ignition of ethanol is investigated. Furthermore, the ignition of wet ethanol is investigated in order to shed light on the effect of water vapor content on the ignition chemistry of ethanol. New ethanol ignition data at 10 atm are also reported. Experiments are carried out in a shock tube at average pressures of 2, 10 and 12 atm over a temperature range of 949-1650 K. The ethanol and ethanol/additives are mixed with oxygen and argon. Ignition delay times are obtained behind reflected shock waves by means of pressure and light emission profiles. It is observed that while IPN addition to ethanol results in shorter ignition delay times, IPF addition leads to longer delay times. In case of water addition, it is found that for the same post-reflected temperatures and pressure, shorter ignition delay times are observed. However, this effect must be considered together with other physical processes of wet ethanol combustion such as heating and vaporization.
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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) | 0.003 | 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".