Impact of Frequency-Dependent Soil Models on Grounding System Performance for Direct and Indirect Lightning Strikes
Bibliographic record
Abstract
The goal of this article is to investigate the effect of frequency-dependent soil models on the performance of grounding electrodes subjected to lightning strikes. Several soil models are examined while accounting for the variation of soil resistivity and permittivity as a function of the lightning current frequency spectrum. The analysis is performed for a homogeneous soil and a two-layer horizontally stratified soil. The impact of the frequency-dependent soil parameters on the ground potential rise (GPR) of simple grounding electrodes subjected to lightning is analyzed and discussed. The analysis is performed in the frequency domain and in the time domain. A wind turbine and its grounding system are also considered in this article. Special attention is given to the case of indirect lightning, rarely mentioned in the literature. The GPR of the grounding electrodes is examined when the frequency dependence of the soil is taken into account and the lightning channel is located at close distances to the electrodes. Indeed, the level of induced electromagnetic fields caused by a nearby lightning channel can still be too high and potentially dangerous. The computations are performed using an efficient Method of Moments (MoM) numerical tool based on surface-wire integral equations for a stratified medium in the frequency range from dc to several MHz. Numerical results demonstrate that the frequency dependency of the soil parameters results in a decrease of the potential rise of the grounding electrodes, with respect to the case where the parameters are assumed constant.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".