Contribution to IPW2 by Studying Single and Multi-Layer Icing in 2D, 2.5D and 3D
Bibliographic record
Abstract
This paper presents the three ice accretion cases from the 2nd AIAA Ice Prediction Workshop carried out by Polytechnique Montreal, using the in-house ice accretion software, CHAMPS (CHApel MultiPhysics Software). The simulations employ minimally a 2D multilayer approach for all the cases. Moreover, multilayer 2.5D and single-layer 3D simulations are performed for the 3D cases. Globally, the numerically obtained ice shapes satisfactorily reproduce the experimental ice volume and limits. The incorporation of 2.5D simulations offers a favorable balance between computational complexity and accuracy. These results demonstrate a good agreement with 3D ice shapes and an improvement over the 2D results. A stochastic ice accretion model, firstly integrated without updating flow, droplet trajectories, and surface thermodynamic exchanges, exhibits satisfying predictive capabilities by capturing the lower form of the 2D rimed ice case. The experimental variability is also captured by superimposing results from repeated runs. Then, preliminary results with a laminar multilayer approach for the stochastic model are shown for the last test case, well capturing the global aspect of the rimed ice shape.
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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 | 0.000 | 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 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".