Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In order to improve the fatigue test accuracy and efficiency of full-scale structure of wind turbine blades, an effective load matching method for full-scale structure fatigue test of wind turbine blades under biaxial loading is proposed. The blade biaxial loading fatigue test scheme is designed. The transfer matrix method is used to calculate the test bending moment under biaxial loading. The particle swarm optimization algorithm is designed to optimize the position and mass of the excitation device in the flap-wise and edgewise directions and the position, mass and quantity of the fixed counterweight. Based on this, the calculation model of the test bending moment and the data of the target bending moment are integrated into the particle swarm optimization algorithm to achieve the optimal matching of the biaxial loading fatigue test load, Finally, a numerical example is given to verify it. The results show that this method can make the test load closer to the target load, further accelerate the popularization of biaxial loading fatigue test, and provide a certain theoretical reference and application value for engineering practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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