A compact in-blade five hole pressure probe for local inflow study on a horizontal axis wind turbine
Bibliographic record
Abstract
Understanding local inflow conditions on a wind turbine blade on an operating wind turbine can further understanding of aerodynamic variations and help predict loads on the turbine. Turbine blades are generally designed with a two-dimensional steady approach, however the real wind conditions are highly three-dimensional (3D) and unsteady. Detailed measurements are not common for validating aerodynamic models. The aim of this theoretical and experimental study is to build, calibrate, install and test a compact in-blade five hole pressure probe system to be used to retrieve these measurements. Wind tunnel calibration of the five hole pressure probe has been successfully completed using an automated traversing system over a ±45° range, with 5° increments. Error analysis showed that the multi-zone pressure coefficient data reduction approach is the most suitable for this application. This approach not only extends the measurable local inflow angles up to ±70°, but also it allows any reference pressure for differential pressure readings. A new data acquisition system (DAQ) internal to a rotating small wind turbine blade section was developed. Space limitations resulted in a custom built DAQ of very contained dimensions. This included, among others, five pressure transducers on a printed circuit board, a 16 bit analog to digital converter, an Arduino microcontroller, and a Bluetooth transceiver to transmit the data wirelessly to the main computer. The new blade section was designed and 3D-printed in such a way that the DAQ instrumentation could be easily accessed and, at the same time, had an acceptable structural solidity. A series of tests were conducted on a 3.4 m diameter wind turbine in a large scale wind tunnel in order to assess the correct functioning of the probe system. As expected, the inflow measurement obtained while the turbine was operating under yawed conditions showed a periodically oscillating inflow vector. The period of this variation was the same as the period of the rotor rotation.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".