Ethanol diesel dual fuel clean combustion with FPGA enabled control
Bibliographic record
Abstract
Sophisticated engine controls have progressively become vital enablers for implementing clean and efficient combustion. The low temperature combustion in diesel engines is a viable combustion mode that offers ultra-low nitrogen oxides and dry soot emissions, yet only feasible under tightly controlled operating conditions. In this work, the dual fuel application of ethanol and diesel is studied for clean and efficient combustion. A set of real-time controllers has been configured to control the common-rail pressure and injection events, in concert with the use of two fuels in a high compression ratio diesel engine. An improved control algorithm has been implemented into the field programmable gate array devices to promptly execute the injection commands of the port and direct injection events. Such reliable and prompt control of fuel injection has been identified as critical to safely enable simultaneously low nitrogen oxides and soot combustion, especially when excessive or inadequate rate of exhaust gas recirculation is imminent. High load clean combustion was achieved with the improved control system.
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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 | 0.001 |
| 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 | 0.001 |
| 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".