Transient Three-Dimensional Measurement of Ice Crystal Accretion Using a Plenoptic Camera
Bibliographic record
Abstract
Monitoring the three-dimensional formation of ice layers on airfoils during icing wind tunnel experiments is extremely challenging. For the first time, this paper demonstrates the use of a single plenoptic camera to perform transient, nonintrusive in situ measurements of ice crystal accretion. Experiments have been conducted in the Altitude Icing Wind Tunnel at the National Research Council of Canada under different icing conditions to assess the potential of the new technique. Using the camera in a close-up configuration, the results show the evolution of the three-dimensional shape of the accreted ice in high spatial and temporal resolution and in absolute metric units. The computed surface meshes allow for a detailed analysis in terms of ice shape, surface area, and ice volume. Posttest shapes are compared to measurements taken using a commercial laser scanner. Although not rated for ice surfaces, this device is used as a reference to compare the detailed surface structure after registering the data sets. The results of the two methods are in good agreement and show a mean relative deviation of the plenoptic camera of about 0.15 mm.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".