Effects of Notches on Surface Pressure Fluctuations Downstream of a Leading Edge Spoiler
Bibliographic record
Abstract
<div class="htmlview paragraph">Notched spoilers have been observed to be more effective than uniform spoilers to suppress the flow-induced cavity resonance of vehicles with open sunroofs. In this study, a few mechanisms possibly involved in buffeting suppression from notched spoilers were investigated experimentally and numerically. One objective was to investigate the spatial coherence and phase of the wall pressure fluctuations downstream of notched spoilers in comparison with the same quantities for uniform spoilers. Another objective was to gather detailed measured data to allow the verification of computer simulations of the flow over the notched spoiler. Experiments were performed to measure the velocity and wall pressure fields downstream of spoilers mounted on the rigid floor of a closed test section wind tunnel for different spoiler heights. Efforts were made to reproduce the spoiler and wind tunnel geometry and boundary conditions of the experimental set-up in the numerical simulations. The numerical investigation used the Lattice Boltzmann Method (LBM), with the so-called Very Large Eddy Simulation (VLES) viscosity turbulence model. The results of the numerical investigation were in satisfactory agreement with measured data at low frequencies, where buffeting is expected to occur. The results clearly showed that the notches act as streamwise vortex generators. They reduced spoiler drag, resulting in an upstream shift of the flow reattachment region. The results confirmed that the streamwise vortices break down the homogeneity of the leading edge cross-stream vortices predominantly responsible for the cavity excitation. This decreased the cross-stream coherence of the surface pressure field, thereby reducing the magnitude of the net equivalent excitation force acting over the surface downstream.</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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".