Application of the antenna theory model to a tall tower struck by lightning
Bibliographic record
Abstract
The interaction of lightning with the 553‐m high CN Tower in Toronto is modeled using the antenna theory model. A simple lossless wire structure is used to represent the tower. The return‐stroke channel is modeled as a lossy vertical antenna attached to the tower top. The lossy antenna and the wire structure representing the tower are assumed to be fed at their junction point by a voltage source. The voltage waveform of this source is selected so that the source current resembles a typical lightning current waveform not influenced by the presence of the tall strike object. An electric field integral equation in the time domain is employed to calculate the lightning return stroke current distribution along the CN Tower and along the lightning channel. The equation is solved numerically using the method of moments. The lightning current flowing in the tower at the 474‐m level above ground, predicted by the antenna theory (AT) model, compares favorably with the measurements conducted at the CN Tower. Once the temporal and spatial distributions of the current along the tower and along the lightning channel are determined, the corresponding remote electromagnetic fields are computed. Waveshapes of model‐predicted electric and magnetic fields at a distance of 2 km from the tower are in good agreement with measurements. The contribution of the tower to the electric and magnetic fields at 2 km is about four to five times the contribution of the lightning channel.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".