Effective technique to analyze transmission line conductors under high intensity winds
Bibliographic record
Abstract
An effective numerical technique to calculate the reactions of a multi-spanned transmission line conductor system, under arbitrary loads varying along the spans, is developed. Such variable loads are generated by High Intensity Wind (HIW) events in the form of tornadoes and downburst. First, a semi-closed form solution is derived to obtain the displacements and the reactions at the ends of each conductor span. The solution accounts for the nonlinearity of the system and the flexibility of the insulators. Second, a numerical scheme to solve the derived closed-form solution is proposed. Two conductor systems are analyzed under loads resulting from HIW events for validation of the proposed technique. Non-linear Finite Element Analyses (FEA) are also conducted for the same two systems. The responses resulting from the technique are shown to be in a very good agreement with those resulting from the FEA, which confirms the technique accuracy. Meanwhile, the semi-closed form technique shows superior efficiency in terms of the required computational time. The saving in computational time has a great advantage in predicting the response of the conductors under HIW events, since this requires a large number of analyses to cover different potential locations and sizes of those localized events.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".