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Grounding System Analysis and Design Considerations for Large Hydroelectric Power Plant

2012· article· en· W2000009953 on OpenAlexaff
Ye Xu Li, F. Dawalibi, Jin Xi

Bibliographic record

VenueAdvanced materials research · 2012
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsSafe Engineering Services & Technologies (Canada)
Fundersnot available
KeywordsHydroelectricityGroundEarthing systemElectrical conductorConductorEngineeringCurrent (fluid)Work (physics)Power (physics)Electrical engineeringReliability engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Grounding system analysis and design considerations for large hydroelectric power plant are analyzed and discussed in this paper. The main work that has been carried out includes: constructing adequate soil structures and analyzing the effects of the finite heterogeneous soil structure, the modeled river length and the water reservoir levels; conducting accurate fault current distribution calculations and studying the influence of circulating current on the touch and step voltages. The paper discusses the design of the grounding system and its safety performance while considering the impact of the circulating current and inductive coupling from cables and long parallel conductors inside the plant. Two practical examples have been provided in this paper. Furthermore, the paper demonstrates the effectiveness of using heterogeneous finite soil volumes to analyze large hydroelectric power stations and confirms that accurate grounding software packages are required to account for large circulating currents within the ground conductors and strong inductive coupling that exists between metallic elements within the substation. The results and discussions presented here can be used as a reference for engineers to analyze extensive grounding systems and to design appropriate grounding systems for large hydroelectric power plant.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.063
GPT teacher head0.322
Teacher spread0.260 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations2
Published2012
Admission routes1
Has abstractyes

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