Combining computational fluid dynamics (CFD) with experimental fluid dynamics (EFD) and flight fluid dynamics (FFD) via gappy proper orthogonal decomposition
Why this work is in the frame
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Bibliographic record
Abstract
In the aerospace industry, experiments and flight tests are expensive, often inaccurate and incomplete. On the other hand, numerical results require validation, verification and can be computationally expensive. By means of Reduced Order Modelling (ROM), the computational cost can be reduced drastically and a more complete investigation of a continuous design space can be provided. Moreover, the ROM framework allows CFD simulations to be combined with Experimental Fluid Dynamics (EFD) and even Flight Fluid Dynamics (FFD) results through a multidimensional database. Since CFD data is much denser than EFD or FFD datasets, and the ROM framework requires input snapshots of same dimension, these datasets need to be enriched.The "Gappy" Proper Orthogonal Decomposition (POD) is an extension of the POD method that allows consideration of incomplete datasets and can be used to enrich the experimental results to the size of the companion CFD simulations. The reconstructed results can then be used within the ROM framework for a real-time exploration of a design space. The goal of this thesis is to implement the Gappy POD in order to be used in the ROM framework developed at McGill CFD Laboratory for various applications, such as aerodynamic flows and in-flight icing computations.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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