Characterization of Temperature Sensitive Paint for Application in Hypersonic Ludwieg Tubes at the University of Tennessee
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2022-1660.vid A fast-response temperature sensitive paint has been selected for use in the University of Tennessee Space Institute’s Ludwieg Tubes. The paint is based on a ruthenium complex called ru(phen) which produces fluorescence under ultraviolet excitation that correlates to temperature, with a response time suitable for hypersonic test facilities with sub-second steady state run times. This work presents benchtop characterization of the temperature sensitive paint and initial tests in the Mach 4 Ludwieg Tube. The luminescent intensity of the paint is observed at various surface temperatures produced by contact with heated air flows and compared to control measurements to establish accuracy and repeatability. Highly linear correlation between the luminescent signal and the control measurement is observed, demonstrating that the paint functions with the expected quality as reported in literature. Mach 4 flow experiments are conducted on a painted 6-degree half-angle cone with a cylindrical protruding shock generator, and thermal disturbances are successfully captured.
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 | 0.000 |
| 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) | 0.004 | 0.001 |
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".