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Record W1493916601 · doi:10.1109/appeec.2014.7066170

Realistic and accurate model for analyzing substation grounding systems buried in various backfill material

2014· article· en· W1493916601 on OpenAlexaff
Jie Liu, F. Dawalibi, N. Mitskevitch, Marc-André Joyal, Sharon Tee

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsSafe Engineering Services & Technologies (Canada)
Fundersnot available
KeywordsComputationFinite element methodGroundEarthing systemBoundary value problemBoundary (topology)GridGeotechnical engineeringComputer scienceGround-penetrating radarEngineeringGeologyStructural engineeringAlgorithmMathematicsElectrical engineeringMathematical analysis

Abstract

fetched live from OpenAlex

The design of a substation grounding system that is surrounded by a number of backfill material (finite volumes of soil) with distinct resistivity values, such as a thin surface layer of crushed rock and paved surfaces is particularly complicated. The effects of such arbitrary finite volumes of backfill material and heterogeneous soil have been studied in this paper. The numerical solution of a boundary element based method and the exact analytical solution for a hemispheroidal soil model are used in this study. Computation results for a realistic case are presented by comparing several approaches. The analysis demonstrates that it is necessary to model such arbitrary volumes accurately in order to determine the grid GPR, touch and step voltages realistically and to avoid unsafe or costly designs.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.271
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2014
Admission routes1
Has abstractyes

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