Automatic CFD analysis method for shape optimization
Bibliographic record
Abstract
This project presents an Automatic Computational Fluid Dynamics (CFD) analysis \nmethod for shape optimization of an aerodynamic profile -- It begins with an overview \nof basic concepts on shape optimization, geometry parameterization and objective \nfunctions -- It continues with an introduction to the current status of CFD simulation \nsoftware and types of solvers -- Then expands to optimization based on CFD analysis -- \nFollowing, a CFD-based method to optimize aerodynamic profiles under certain restrictions and scenarios is proposed -- Finally, the code implemented to automatically \nmodify a profile bound by a set of control points based on CFD analysis is described -- \nThe project was developed entirely at the EAFIT University’s Applied Mechanics Laboratory in Medellin, Colombia and is part of a collaboration effort in companionship \nwith the University of Aberta in Canada and Los Andes University in Bogota, Colombia
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".