Failure analysis of a transmission tower during a microburst
Bibliographic record
Abstract
This paper focuses on assessing the failure of one of the transmission towers that collapsed in Winnipeg, Canada, as a result of a microburst event. The study is conducted using a fluid-structure numerical model that was developed in-house. A major challenge in microburst-related problems is that the forces acting on a structure vary with the microburst parameters including the descending jet velocity, the diameter of the event and the relative location between the structure and the jet. The numerical model, which combines wind field data for microbursts together with a non-linear finite element formulation, is capable of predicting the progressive failure of a tower that initiates after one of its member reaches its capacity. The model is employed first to determine the microburst parameters that are likely to initiate failure of a number of critical members of the tower. Progressive failure analysis of the tower is then conducted by applying the loads associated with those critical configurations. The analysis predicts a collapse of the conductors cross-arm under a microburst reference velocity that is almost equal to the corresponding value for normal wind load that was used in the design of the structure. A similarity between the predicted modes of failure and the post event field observations was shown.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".