Determination of trajectories of metallic spheres settling in non‐newtonian fluids
Bibliographic record
Abstract
Abstract A “videogrammetric” system to measure the trajectory of small metallic spheres falling through a slurry‐filled tank has been developed to support fluid dynamics research. The system used two low‐cost video cameras and a combination of commercially available and custom‐built software for the image acquisition, the measurement and tracking of the spheres in the imagery and the photogrammetric operations. After a review of relevant literature and a description of the system, this paper reports on an extensive testing regime conducted to gauge the performance of the system. The results show that it achieved object space coordinate precision and accuracy better than the required figure of 1 mm. Simulation‐based analyses, to quantify the sensitivity of refraction corrections in object space to the accuracy of the three refractive indices and distance parameters involved in the system, are also reported. The results of these tests demonstrated that some parameters need only be specified to about 56% of their true value whereas others must be accurate to better than 2%. Finally, results from two examples in sphere trajectory determination are presented and analysed.
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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) | 0.001 | 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".