Spatially-Resolved Temperature Diagnostic for Supersonic Flow Using Cross-Beam Doppler-Limited Laser Saturation Spectroscopy
Bibliographic record
Abstract
Optical techniques for measuring the temperature in three-dimensional supersonic reactive flows have typically depended on lineshape measurements using single-beam laser absorption spectroscopy. However, absorption over extended path lengths in flows with symmetric, turbulent eddies can lead to systematically high extracted temperatures due to Doppler shifts resulting from flow along the absorption path. To eliminate these problems, Cross-Beam Saturation Absorption Spectroscopy (CBSAS) and Cross-Beam Inter-Modulated Fluorescence (CBIMF) have been developed which utilize two crossed and nearly copropogating laser beams.to record the spectral signal of an I2 ro-vibrational line in a small three-dimensional volume using a tunable CW dye laser. Temperature is extracted by fitting the recorded signal with a theoretical signal constructed from the Doppler-broadened hyperfine components of the ro-vibrational line. The CBIMF technique proved successful for extracting the temperature of an I2-seeded, Ar gas flow within a small, Mach 2, Laval nozzle where the overlap volume of the two 1 mm diameter laser beams was 2.4 mm3. At a test point downstream of the nozzle throat, the average temperature of 146 K +/- 1.5 K extracted from measurements of the I2 P(46) 17-1 spectral line compared favorably with the 138 K temperature calculated from isentropic, one-dimensional flow theory.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".