Investigation of effect of heat exchanger size on power output in low-temperature difference Stirling engines
Bibliographic record
Abstract
The Stirling engine is capable of converting any source of thermal energy into kinetic energy, which makes it an attractive option for utilizing low-temperature sources such as geothermal or waste heat below 100 °C. However, at these low temperatures, the effects of losses are proportionally higher due to the lower thermal potential available. One such significant loss is excess dead volume, wherein a significant contributor is the heat exchangers. The heat exchangers must be selected to optimize power output by minimizing the dead volume loss while maximizing the heat transfer to and from the engine. To better understand what the optimal geometry of the heat exchanger components is, a Stirling engine is modelled using a third-order commercial modelling software (Sage) and trends of engine properties of power, temperature, and pressure for different heat exchanger geometries are observed. The results indicate that there is an optimum heat exchanger volume and geometry for low temperature Stirling engines. This optimum is also affected by other engine properties, such as regenerator size and engine speed. These results provide insight into the optimal geometry of these components for low-temperature Stirling engines, as well as providing design guidance for future engines to be built.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".