Development of Critical Load Cases Simulating the Effect of Downbursts and Torndos on Transmission Line Structures
Bibliographic record
Abstract
In the past decades, many failure incidents for transmission line structures were observed during High Intensity Wind (HIW) events, in the form of downbursts and tornados, in North America, Australia, and other locations around the globe. Examining design codes pertaining to this type of structures reveals the lack of procedures to determine the wind loading acting on transmission tower systems due to High Intensity events. A major challenge in the analysis and design of structures under HIW is the localized nature of these events, which makes the forces acting on the towers and lines dependent on the location and characteristics of the event. Motivated by the failure of number of transmission towers in Canada, an extensive research program was initiated at the University of Western Ontario (UWO) a decade ago and is still progressing with final aim for developing knowledge and information for designing transmission line structures to sustain HIW events. The current paper covers the two types of HIW events: tornados and downbursts. For each event, a literature review is provided followed by a summary of the outcomes of the research conducted at UWO and a description of the wind field. The main contribution in this paper is the introduction of procedures to account for the critical effects of HIW on transmission line structures. Using the knowledge gained from years of research on this subject, critical load cases and load profiles simulating the downburst and tornado configurations that are critical for transmission towers are identified and presented in a format that can be implemented in design codes and can be used by practitioners.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".