Lightning return-stroke transmission line model based on CN tower lightning data and derivative of heidler function
Bibliographic record
Abstract
The lightning discharge has been studied by many researchers for over a century. One of the most important parameters that is of interest to researchers (especially from the point of view of protection) is the lightning return-stroke current. In order to directly measure the lightning current one must know the exact location of lightning strikes, which can only be accomplished using instrumented tall towers, towers placed on elevated grounds or by rocket-triggered lighting experiments. In most investigations, the lightning current characteristics are determined from measured electric and magnetic fields through the usage of a lightning return-stroke model. In this paper, a lightning return-stroke transmission line (TL) model, based on the measured lightning return-stroke current derivative at the CN Tower is presented. Using the TL model along with the derivative of Heidler function, the paper focuses on the determination of the lightning current special temporal distribution along the current path during the lightning return-stroke phase. Current reflections resulting from the four main CN Towerpsilas structural discontinuities have been thoroughly studied and their proper values are determined and used in modeling of the current distribution along the CN Tower.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".