MétaCan
Menu
Back to cohort
Record W3126998551 · doi:10.1109/tia.2021.3057349

Investigation of Seasonal Variations of Tower Footing Impedance in Transmission Line Grounding Systems

2021· article· en· W3126998551 on OpenAlexaffabout
Chenyang Wang, Xiaodong Liang, Emerson Adajar, Paul Loewen

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsUniversity of SaskatchewanManitoba Hydro
Fundersnot available
KeywordsGroundTowerTransmission lineEngineeringElectric power transmissionTransmission towerElectrical impedanceCharacteristic impedanceElectrical engineeringElectronic engineeringStructural engineering

Abstract

fetched live from OpenAlex

In the transmission line grounding system design, spatial and temporal/seasonal variations of tower footing impedance should be considered. However, in real life, only spatial variations are taken into account at the design stage, seasonal variations have not been included. In this article, seasonal variations of tower footing impedance of several types of transmission line grounding systems at Manitoba Hydro, Canada, are investigated through field measurements for a whole year. The industrial practice uses simulated tower footing impedances by the software current distribution, electromagnetic interference, grounding and soil structure analysis (CDEGS) in the design of transmission line grounding systems, however, the accuracy of simulated tower footing impedances as a critical design parameter has never been evaluated. In this article, this industrial practice is evaluated by comparing simulated and measured tower footing impedances for various transmission line grounding systems. The importance to use proper tower footing impedance for lightning conditions is also demonstrated.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.683
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.249
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on Industry ApplicationsSame topicLightning and Electromagnetic PhenomenaFrench-language works237,207