Two-dimensional lagrangian velocity field measurement based on femtosecond laser-induced cyano chemiluminescence technique
Bibliographic record
Abstract
• Through the regulation experiment of molecular fluorescence intensity and lifetime, a synergistic optimum was identified. This enabled a novel imaging acquisition method, combining single femtosecond laser molecular tagging with multiple camera exposures, to capture multiple fluorescence displacement segments in one frame for Lagrangian displacement tracking in a supersonic flow. • An inversion algorithm utilizing the characteristics of luminous lines in images is proposed. It computes 2D velocity vectors by discretizing luminous lines into interrelated points, enabling the reconstruction of the 2D Lagrangian velocity field from molecular tagging displacement images. • Velocity measurements of the jet flow field at the Laval nozzle outlet, with a gas source pressure of 0.7 MPa, validated the feasibility of the velocity measurement method. A preliminary assessment of the measurement results was also carried out. The assessment revealed that in a 530 m/s supersonic flow field, the relative uncertainty of the axial velocity was merely 0.11 %. Measurements of the Lagrangian velocity field in supersonic flows can help to gain a deeper understanding of the internal structure of the flow field, thus supporting aspects of fluid dynamics research and design optimization for engineering applications. However, the measurement technology of the multidimensional Lagrangian velocity field in the supersonic flow field needs to be further improved, especially in the inversion algorithm used to reconstruct the velocity field. Here, we report the two-dimensional Lagrangian velocity field reconstruction of the supersonic flow field by the Femtosecond Laser-Induced Cyano Chemiluminescence (FLICC) technique. The femtosecond laser self-focuses into a filament and then interacts with CH 4 /N 2 gas in the flow field and induces a chemical reaction that generates CN molecular luminescent tagging lines with strong fluorescence intensity and long lifetime. The luminous line moves with the flow in the flow field. The displacement of the luminous line is tracked, and an image of luminous lines is obtained using an Intensified Charge-Coupled Device (ICCD) camera with multiple exposures. Based on the line shapes and displacements of the luminous lines in the image, the luminous lines are discretized into multiple sets of interrelated representation points. These points are then used to calculate the axial and radial velocity components and subsequently reconstruct the 2D velocity field. The relative uncertainty of the axial velocity obtained by this method is 0.11 % in a supersonic flow field with a speed of 530 m/s.
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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 | 0.001 |
| 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".