Computing Tower-Footing Grounding Impedance and GPR curves of Grounding Electrodes Buried in Multilayer Soils
Bibliographic record
Abstract
Grounding systems are essential to dissipate fault currents into soil to guarantee safe conditions to personnel and equipment. In this context, several approaches have been employed to calculate tower-footing grounding impedance either in the frequency or time domain. In the Transmission Line Model (TLM), vertical or horizontal electrodes are represented by distributed parameters along its length. and its impedance are calculate by analytical equations. However, for counterpoise electrodes there are no analytical formulae to estimate its tower-footing grounding impedance. To tackle this issue, numerical methods have been employed to assess the tower-footing grounding impedance in any various arrangements. In this article, a comparison between the grounding impedance obtained by the TLM and numerical Method of Moments (MoM) is carried out in order to verify the accuracy of the numerical method. Then, grounding impedances of counterpoise electrodes and the Grounding Potential Rising (GPR) are calculated for different configurations of a multi-layer soil. It can be noted that grounding impedance of counterpoise electrodes as well as the peaks of the GPR curves are strongly modified by the presence of multi-layer soil and electrode length.
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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) | 0.000 | 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 | 0.000 | 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".