Predicting distribution of aeolian vibration amplitude of undamped overhead transmission lines
Bibliographic record
Abstract
The most widely accepted estimation procedure of the severity of aeolian vibration is by calculating the maximum oscillation amplitudes of the conductor using Energy Balance Principle (EBP). However, the EBP is based on wind tunnel results where only one frequency is excited, while observations and experimental results show that multiple resonant modes are excited simultaneously. Furthermore, the required number of cycles of each amplitude level is not provided by current EBP-based methods. In this paper, vibration data from an experimental undamped ACSR Bersfort test line in Quebec, Canada, is recorded and analyzed. For each record of aeolian vibrations, amplitudes are fitted to a Rayleigh distribution based on the narrow-band assumption. The number of cycles and Rayleigh parameter are then related to wind conditions through a modified Strouhal frequency and EBP methodology. A statistical model is proposed to relate vibration profiles and wind input while considering wind turbulence intensity. The proposed method performs well and gives accurate estimates of both vibration amplitudes and number of cycles for ACSR Bersfort conductor. Physical and statistical theory is provided for each step of the method in order to extend the application of the method to other types of conductors or different line configurations. • Predicting the number of cycles for each amplitude level during aeolian vibration. • Modified Energy Balance Principle to accommodate turbulent wind conditions. • A statistical model linking detailed vibration profiles to maximum amplitude. • Validation through measurements from a test line featuring ACSR Bersfort conductor. • Detailed steps for broadening application to other ACSR line configurations.
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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) | 0.000 | 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 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".