Calibration in a potential water jet of a five-hole pressure probe with embedded sensors for unsteady flow measurement
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Bibliographic record
Abstract
Investigations of the flow behavior are currently carried out experimentally on models of hydraulic turbines. Quantities such as unsteady velocity can be acquired using PIV or LDV techniques, static wall pressure using steady or unsteady pressure transducers and wall shear stress using hot-film anemometry. More rarely acquired however, the unsteady total pressure at different locations in the flowstream would give more information on the flow dynamics and would be a key component for setting boundary conditions for CFD simulations. Following the example of classical Pitot tubes, which can only give averaged pressure values though, we have developed a five-hole pressure probe with embedded sensors that can measure unsteady values of total pressure, local flow velocity and direction. The probe head is designed to have a minimum impact on the flowstream, and the miniature sensors are placed in a cross configuration compared to the probe's support axis. This paper focuses on the utilization of normalized calibration coefficients and their use for unsteady values, and on the justification for using our cross sensor repartition. The calibration setup is presented briefly, including a water potential jet that requires the calculation of specific calibration coefficients. Different phenomena were observed during experimentation. Their impact on the accuracy of the probe is analyzed. The probe's operation range for this particular calibration setup is discussed. Finally, we focus on the influence of the sensors repartition on the tridimensional shape of the calibration coefficients, and we provide a way to calculate the first approximate solution for the reverse calculus while the sensors are not aligned with the probe's arm.
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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 | 0.000 |
| 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) | 0.000 | 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 it