Performance Prediction of a Practical Low-Pressure-Ratio Highly Efficient Split-Cycle Recuperated Engine
Why this work is in the frame
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Bibliographic record
Abstract
<div>Split-cycle recuperated engines are promising candidates to compete with hydrogen-based fuel cells for high-duty cycles. They can potentially achieve similar, or even higher, efficiencies at the cost of historically cheap piston engines. However, existing approaches are either limited in efficiency or difficult to develop, mainly because of the challenges around the high-temperature expansion piston. This article presents a practical architecture of a low-pressure-ratio, recuperated split-cycle engine with a contact-free expansion piston using labyrinth seals supported by thermodynamics and numerical modeling. The engine operates under a regenerative dual Brayton cycle to combine the benefits of constant pressure heat recuperation and near-constant volume combustion. Thermodynamics results reveal pre-compressing the residual mass in the expansion cylinder before intake is crucial. A 0D transient model integrating main losses is implemented to explore the design space and maximize efficiency through a numerical design of experiments. The blowby in the expansion cylinder is the main loss but remains acceptable for relatively tight clearances. An indicated efficiency of 60% is predicted for a cycle pressure of 20 bar and an expansion piston exhaust temperature of 1250 K. The predicted indicated power density of 6.5 kW/L is relatively low but in the range of micro-combined-heat-power diesel engines.</div>
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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 it