Transient analysis of power transmission towers above lossy ground with frequency dependent electrical parameters considering the water content of soil
Bibliographic record
Abstract
Adequate soil modeling is fundamental to assessing the grounding impedance of the grounding system and the transient responses in power systems. This paper aims to investigate three soil models with electrical parameters varying with frequency and water content, namely Smith-Longmire, Scott, and Messier models, and their impact on the ground potential rise (GPR) waveforms of vertical grounding rods. Besides that, the transient induced voltages across the string of insulators induced are also investigated for lightning currents representative first, and subsequent return strokes are employed. The harmonic grounding impedance (HGI) is calculated for rods of 3, 15, and 30 m buried in frequency-dependent (FD) soil model using commercial electromagnetic software (FEKO) with the Method of Moments (MoM) for a range of 100 Hz to 10 MHz. Simulation results show a significant modification of the calculated HGI beyond a particular frequency. The induced transient GPR waveforms show a notable reduction in their voltage peaks when the FD soil model is compared with those computed using the frequency-independent (FI) soil model. Finally, a backflashover analysis is carried out that demonstrates its dependence on the rod length, water content, and the specific soil model employed.
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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".