Pressure-Sensitive Paint Technology Applied to Low-Speed Automotive Testing
Bibliographic record
Abstract
<div class="htmlview paragraph">Pressure-sensitive paint (PSP) technology is a technique used to experimentally determine surface pressures on models during wind tunnel tests. The key to this technique is a specially formulated pressure-sensitive paint that responds to, and can be correlated with the local air pressure. Wind tunnel models coated with pressure-sensitive paint are able to yield quantitative pressure data on an entire model surface in the form of light intensity values in recorded images. Quantitative results in terms of pressure coefficients (Cp) are obtained by correlating PSP data with conventional pressure tap data. Only a small number of surface taps are needed to be able to obtain quantitative pressure data with the PSP method. This technique is gaining acceptance so that future automotive wind tunnel tests can be done at reduced cost by eliminating most of the expensive pressure taps from wind tunnel models. A significant advantage of PSP is a much higher spatial resolution mapping of the pressure field than that given by the discrete data available from pressure taps, even when the taps are closely spaced.</div> <div class="htmlview paragraph">Experiments were conducted with the main objective of determining whether PSP could produce useful results on an automotive model at low test velocities. These wind tunnel tests were performed on a 4/10 scale 1995 Ford Transit van. Results were obtained throughout the yaw range of -15° to+15 ° and between dynamic pressures of 16 psf and 60 psf (766 Pa and 2872 Pa). At higher dynamic pressures (above 40 psf or 1914 Pa), the PSP measurements can determine the model surface pressure distribution with ‘reasonable’ (±0.2 Cp with 95% confidence) quantitative accuracy. At lower dynamic pressures, the images have lower signal-to- noise ratios and thus decreased quantitative accuracy. However, the basic trends in the data seen at high dynamic pressures are also evident at low dynamic pressures. This indicates that PSP measurements are capable of qualitatively determining the model surface pressure distribution at dynamic pressures as low as 16 psf (766 Pa). PSP technology was also demonstrated to be very useful for flow diagnostics. A-pillar vortex regions, separated flow regions behind ‘backward-facing steps’, flow reattachment lines, and the effects of model changes and yaw angle could be identified from the PSP results.</div>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".