Galloping of a bundled conductor transmission line
Bibliographic record
Abstract
A useful design tool is developed for a bundle conductor or a single conductor of an electrical transmission line by using a three-degree-of-freedom, hybrid model.The model is adaptable because it incorpolates numerical mode shapes determined by employing the finite element technique to form lelevant matrices.On the other hand, it is quite computationally efflcient because analytical expressions are used to investigate the initiation and steady-state arnpli- tudes of galloping.The model accommodates not only intelactions of the vertical, horizontal and torsional movements but also non-linear aerodynamic loads, a non-uniform ice geometry, and distributed and discrete galloping control devices that cannot be considered in existing analytical modeis.By neglecting the sub-span motions between the conductors, a bundle is modelled as an equivalent single conductor so that the initiation conditions for galloping, peli- odic and quasi-periodic states and their stability conditions are considered by taking advantage of previous achievements for a single conductor.Numerical examples are presented to assess the accuracy of the results obtained flom the model in compalison with analogous data from a more sophisticated flnite element analysis.Parametric studies ale reported for limit cycle amplitudes with variations of the criticaÌ wind speed, wind speed above the critical wind speed, static tension and span length.Finally, the model is used to assess the effects of a hybrid, control damper to alleviate galloping by changing its parameters and providing guidelines for its application.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".