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Record W2016070437 · doi:10.1139/l03-027

A novel method for determining effective length factors for solid round steel leg members of guyed lattice towers with cross-bracing

2003· article· en· W2016070437 on OpenAlexvenueno aff
Yongcong Ding, Faouzi Ghrib, Sudip Bhattacharjee, Murty K. S. Madugula

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBracingStructural engineeringWeldingStiffnessTowerEngineeringBucklingLattice (music)Finite element methodBracePhysicsMechanical engineering

Abstract

fetched live from OpenAlex

A novel method is presented for determining the effective length factors (K factors) for solid round steel leg (vertical) members in all-welded guyed communication towers with cross-bracing. Deflections due to an arbitrary load were used to determine the restraining moments and rotational stiffness of the legs. Using the closed-form solution for buckling of a column with rotational restraint at both ends, K factors were computed. From the study it is found that the K factors varied from 0.61 to 1.00, depending on the relative sizes of the leg and bracing members. An expression for estimating the effective length factors for solid round steel leg members of all-welded guyed lattice towers with cross-bracing is developed.Key words: cross-bracing, effective length factor (K factor), finite element analysis, guyed lattice tower, solid round steel leg member, welded tower.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.012
GPT teacher head0.255
Teacher spread0.243 · 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.

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

Citations0
Published2003
Admission routes1
Has abstractyes

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