Toward Real-Time Aero-Icing Simulation for Complete Aircraft Configurations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
3D fully viscous turbulent aero-icing flow simulation is still computationally demanding for industry, especially when parametric studies are needed. In order to make such compute-intensive simulations more affordable, this work presents a reduced order modeling, based on the “Proper Orthogonal Decomposition” (POD) method to predict a wider swath of flow fields and ice shapes based on a limited number of “snapshots” obtained from complete high-fidelity CFD computations. The procedure of the POD approach is to first decompose the fields into modes, using the snapshots, and then to reconstruct the field and/or ice shapes using those decomposed modes for other conditions. This results in much shorter calculation times, from 1/600 th to 1/1000 th the full 3D ones, drastically reducing the computational cost and providing a more complete map of the performance degradation of an iced aircraft over a wide range of flight and weather conditions.
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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