Electromagnetic Fields at Very Close Range From a Tower Struck by Lightning in Presence of a Horizontally Stratified Ground
Bibliographic record
Abstract
In this paper, we present an analysis of electromagnetic fields generated by a lightning return stroke to a tall tower in presence of a horizontally stratified two-layer ground. The electromagnetic fields are evaluated at a distance of 50 m from the tower for two observation points above and below the ground surface, by using the finite-difference time-domain method. The developed numerical model is validated using available experimental data obtained at the CN Tower in Toronto. To illustrate and discuss the effect of the soil stratification on the electromagnetic fields, we adopt two different cases characterized, respectively, by an upper layer less conductive than the lower level, and vice versa. The obtained results show, for the considered distance range (50 m), that the electromagnetic fields above ground at such close distance are nearly insensitive to the ground stratification. However, the underground electromagnetic fields are markedly affected by the properties of the soil layers. In the presence of a lower layer of higher conductivity, the horizontal electric field is characterized by a faster rise time, a significant decrease in amplitude and a bipolar wave-shape compared to that in the case of a homogeneous ground with the upper-layer characteristics. On the other hand, the presence of a lower layer with lower conductivity results in an increase of the peak value of the underground horizontal electric field.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".