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Record W2023669034 · doi:10.1139/l05-062

Compressive strength of solid round steel members strengthened with rods or angles

2006· article· en· W2023669034 on OpenAlexfundvenueno aff
Cindy Kumalasari, Yongcong Ding, Murty K. S. Madugula, Faouzi Ghrib

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBracingRodStructural engineeringCompressive strengthFinite element methodMaterials scienceReinforcementEngineeringBraceComposite material

Abstract

fetched live from OpenAlex

Results of an experimental investigation of the compressive strength of solid round steel bracing members of lattice communication towers strengthened with rods or angles are presented in this paper. The reinforcing rods or angles were connected to the bracing members with clamps or U-bolts. The sizes of reinforcing members were in accordance with industry practice. Finite element models that used a modified static Riks method were built to compute the compressive strength of the members. The results from finite element analysis agree closely with the experimental failure loads. On the basis of the test results and the finite element analysis, a simplified design procedure is proposed to determine the compressive strength of solid round bracing members strengthened with rods or angles.Key words: angles, compressive strength, lattice tower, reinforcement, rods, bracing member, strengthening.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.184
Teacher spread0.178 · 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 designBench or experimental
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

Citations5
Published2006
Admission routes2
Has abstractyes

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