Impingement of Supercooled Large Droplets via Reduced Order Models
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">The high computational cost of 3-D viscous turbulent aero-icing simulations is one of the main limitations to address in order to more extensively use computational fluid dynamics to explore the wide variety of icing conditions to be tested before achieving aircraft airworthiness. In an attempt to overcome the computational burden of these simulations, a Reduced Order Modeling (ROM) approach, based on Proper Orthogonal Decomposition (POD) and Kriging interpolation techniques, is applied to the computation of the impingement pattern of supercooled large droplets (SLD) on aircraft. Relying on a suitable database of high fidelity full-order simulations, the ROM approach provides a lower-order approximation of the system in terms of a linear combination of appropriate functions. The accuracy of the resulting surrogate solution is successfully compared to experimental and CFD results for sample 2-D problems and then extended to a typical 3-D case.</div></div>
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".