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Record W2895511020 · doi:10.1061/9780784415153.ch07

Longitudinal Forces on Transmission Towers due to Non-Symmetric Downburst Ground Wire Loads

2018· article· en· W2895511020 on OpenAlexaff
Amal Elawady, Ashraf El Damatty

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsWestern University
Fundersnot available
KeywordsThunderstormTowerElectric power transmissionStructural engineeringTransmission towerOblique caseWind engineeringNonlinear systemSpan (engineering)Transmission (telecommunications)GeologyEngineeringMeteorologyPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

Downburst thunderstorms are localized high-intensity wind events that are formed by an intensive downdraft of cold air that impinges on the ground causing high radial wind speeds. Spatial localization of downbursts causes unique oblique load cases on long-span structures such as transmission lines that do not occur during synoptic winds. This loading scenario causes an unsymmetrical wind loading along the spans of the cables, resulting in an unbalanced longitudinal force acting on the transmission tower of interest. This longitudinal force is highly nonlinear; it depends on the material and geometrical properties of the cables. Therefore, a nonlinear analysis should be conducted considering the various possibilities of downburst-cable configurations and the cable material and geometrical properties. This paper focuses on developing a simplified and manual approach to estimate this damaging longitudinal force, which develops in ground wires of transmission lines.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.238
Teacher spread0.228 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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