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Record W2330664838 · doi:10.1061/9780784479414.042

Examination of Yawed Wind Loading on Transmission Towers

2015· article· en· W2330664838 on OpenAlexaff
T. G. Mara, Roberto H. Behncke

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsTowerDragAerodynamicsStructural engineeringTransmission lineEngineeringWind tunnelMarine engineeringTransmission towerWind engineeringElectric power transmissionLine (geometry)ConductorAerospace engineeringElectrical engineeringMathematicsGeometry

Abstract

fetched live from OpenAlex

Guyed and self-supported transmission towers are typically comprised of two unique geometries: the vertical tower body and the horizontal conductor support cross-arm. Much research has been directed towards the evaluation of aerodynamic coefficients of the compact and symmetric geometry often used in the vertical portion of towers, however, much less information is available for cross-arm or non-symmetric sections. Wind tunnel tests carried out on a typical tower cross-arm design indicate that the drag loads vary significantly with wind direction, and exhibit a relationship which differs from the design procedure in the current (3rd Edition) of ASCE Manual of Practice No. 74: Guidelines for Electrical Transmission Line Structural Loading (ASCE-74). Two additional methods are presented, which show better agreement with the experimental data: the IEC equation for yawed wind (which was recommended in the 2nd Edition of ASCE-74); and a modified version of the yawed wind formula in ASCE-74. These approaches have been proposed for the upcoming edition of ASCE-74. The implications of the different equations are shown with reference to the wind loading on the structure only, as well as the overall tower-line system. The results are also compared with those obtained using PLS-TOWER. The paper reviews how force coefficients (i.e., drag coefficients) are developed and applied in wind load calculations, and describes the implications of the current and proposed approaches to yawed wind loads.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.186

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.217
Teacher spread0.201 · 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 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

Citations9
Published2015
Admission routes1
Has abstractyes

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