A study on the potential of skin heat exchangers for hybrid-electric aircraft
Why this work is in the frame
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Bibliographic record
Abstract
This study investigates the viability of Skin Heat Exchangers (SHXs) as an effective thermal management solution for hybrid-electric aircraft, with a focus on their aerodynamic and heat transfer performance. Using two-dimensional Computational Fluid Dynamics (CFD) simulations, the work evaluates various SHX configurations across different flight phases of a conceptual regional hybrid-electric aircraft (FutPrInt50), analysing the effects of surface heating on lift, drag, and convective heat transfer. A Gaussian Process Regression surrogate model is developed to predict SHX performance under varying atmospheric and operational conditions. At cruise, results reveal that heating the lower surface of the aerofoil enhances both aerodynamic efficiency and heat transfer capacity compared to an all-heated configuration by 10.9% and 9.9%, respectively, while a heated upper patch had the best average heat transfer potential by 7%, it suffered significantly in aerodynamic performance by -14.2%, compared to the next best configuration. However, SHX performance proved to be highly sensitive, with diminished cooling capacity of up to 54.3% during high-demand phases such as take-off and climb compared to cruise. The findings underscore SHXs as a promising, though insufficient stand-alone, thermal solution for hybrid-electric propulsion systems, indicating the need for complementary technologies in future aircraft designs. • Heating lower surface improves aerodynamic and heat transfer performance in cruise. • Heating upper surfaces improves heat transfer but hinders aerodynamic efficiency. • Skin heat exchangers can contribute to heat rejection in hybrid-electric aircraft.
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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 | 0.000 |
| 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) | 0.000 | 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