Estimating wind velocity and direction using sparse sensors on a cylinder
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
Using finite pressure measurements on a cylinder, we are able to estimate both the oncoming wind speed and direction of uniform flow over a cylinder at Reynolds numbers 20 000<Re<120 000. While reduced-order methods, such as proper orthogonal decomposition with QR factorization, require at least nine sensors to estimate the oncoming wind speed and direction with <10% error, other methods, such as probabilistic approaches or curve-fitting, can achieve similar results with as few as five sensors. A utility function, based on the Kullback–Leibler divergence, is used to determine the locally optimal location of the sensors to accurately estimate inlet conditions. It was found that sensor arrangement also plays a significant role, with unevenly distributed sensors being preferable than evenly distributed sensors. These techniques, when paired with existing flow field estimation approaches, allow the user to predict the surrounding flow field from any oncoming direction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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