Review of Span and Gust Factors for Transmission Line Design
Bibliographic record
Abstract
Current criteria for the calculation of synoptic wind load effects on transmission line components are based on Davenport's gust response factors, which take into account the different response of structures and long spans of wires to turbulent wind. The gust factors include resonant components that imply possible dynamic amplifications of the wind effect on the structures and wires, although the wire resonant response is generally ignored because of high aerodynamic damping. Although the gust response factor equations were derived for 1-hour mean wind records, the factors are being applied for winds with different sampling intervals but with reference to 10-minute winds. The conversion is based on Durst's velocity ratio curve, which was not derived from records of extreme winds but from low velocity storms. Due to these differences, and also other simplifications, there could be errors in calculated line or component reliability of at least one order of magnitude. While line design weather loading conditions are derived from synoptic wind records, it is well known within the industry that most line or structure failures are induced by non-synoptic storms, such as downdrafts or tornadoes generated by thunderstorms. Field evidence from these storms indicate that the 1-hour mean factors, even when extrapolated to very short-interval gusts, do not explain the observed effects and therefore new span and gust factors are needed for design. The paper reviews the basic concepts and history of span and gust factors and the impact of some of the current assumptions and simplifications. It also focuses on recent research on the actual effects of non-synoptic storms and the new factors that are derived from these experiences.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".