Transient analysis of soil resistivity influence on lightning generated magnetic field
Bibliographic record
Abstract
This paper proposes a full-wave analysis to consider the influence of soil resistivity on the magnetic field inside buildings hit directly by a lightning strike. An electromagnetic theory approach based on the method of moments is used. This method allows for a transient analysis and accounts for the effects of soil resistivity. Calculations are performed in the frequency domain for a simplified case where the lightning channel is modeled assuming a constant current along the channel. The model is selected for ease of comparisons with the examples described in the IEC 62305-4 standard. A time domain numerical analysis is carried out to estimate the influence of soil resistivity on the radiated magnetic field. The effect of the soil resistivity on both the resultant and on the time derivative of the magnetic field is investigated for a 2 m mesh grid-like spatial shield of 10x10x10 m located in horizontally layered soil structures. Examples of transient resultant magnetic field induced by a typical positive stroke on a building represented as a grid like shield are presented, emphasizing the impact of soil resistivity. It is shown that the transient electromagnetic field is moderately affected by soil resistivity changes which, therefore, can be, in some cases, neglected in the computation process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.001 | 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".