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Record W2947809539

Assessment of the effect of residual stresses on the mechanical behavior of steel lattice transmission towers

2018· article· en· W2947809539 on OpenAlexfundno aff
Geneviève Gravel, Kahina Sad Saoud, Sébastien Langlois

Bibliographic record

VenueKnowledge UdeS (Institutional Deposit of the University of Sherbrooke) · 2018
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaHydro-Québec
KeywordsResidual stressResidualStructural engineeringMaterials scienceForensic engineeringEngineeringMetallurgyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Abstract: Power transmission lines predominantly involve lattice towers, which are typically composed of steel angle members connected together by means of bolted joints. An effective design of such structures requires the consideration of a range of complex phenomena likely to affect either the carrying capacity or the failure mode. In practice, simple numerical models are combined with standard design equations to consider these effects. A few advanced numerical models reported in the literature deal with eccentricities, stiffness of the connections, and joint slippage. However, the impact of residual stresses on the global behavior of lattice towers is not addressed in prior works. In this work, the influence of residual stresses is studied numerically using the finite element software Code_Aster. The proposed model employs multi-fibre beam elements to model the elastoplastic angle members, and discrete elements to represent the bolted connections. Both the connection eccentricity and the rotational stiffness of connections are modeled. The associated problem is solved in an incremental way, so as to deal with geometric and material nonlinearities, and the results are compared with experimental tests. Considering residual stresses in advanced models is an important step for the numerical evaluation of the failure of lattice towers.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.276

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 studies0.0000.001
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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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Same venueKnowledge UdeS (Institutional Deposit of the University of Sherbrooke)Same topicVibration and Dynamic AnalysisFrench-language works237,207