Flow velocity and temperature sensing using thermosensitive fluorescent polymer seed particles in water
Bibliographic record
Abstract
Particle image velocimetry (PIV) is an experimental technique that uses microscale particles as tracers to measure the velocity of a fluid flow. In this paper, we seek to extend this technique to simultaneously measure fluid temperature as well, by employing a novel class of thermosensitive polymer particles. Towards this aim, we designed a process to encapsulate highly fluorescent thermosensitive NBD-AE-co-poly(N-isopropylacrylamide) polymers into optically transparent poly(dimethylsiloxane) particles. These novel PIV particles enable direct measurement of water velocity while serving as temperature probes that increase their fluorescence intensity when the temperature rises above 32 °C. To demonstrate the ability of the particles to simultaneously serve as flow tracers and temperature sensors in water, we examine the flow velocity and temperature in the wake of a heated cylinder in a cross flow. Our results indicate the possibility of extending PIV to afford the spatial and temporal resolution of fluid velocity and temperature gradients in water, with potential application to the study of convection problems from life sciences to engineering.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".