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Record W2965968017 · doi:10.1177/1077546319867171

Analytical and experimental investigation of cable–beam system dynamics

2019· article· en· W2965968017 on OpenAlexaff
Mohammad Hadi Jalali, Geoff Rideout

Bibliographic record

VenueJournal of Vibration and Control · 2019
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCantileverBeam (structure)Structural engineeringBending stiffnessStiffnessEngineeringEquations of motionBendingPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

Interactions between cables and structures affect the design and nondestructive testing of electricity transmission lines, guyed towers, and bridges. An analytical model for an electricity pole beam–cable system is presented, which can be extended to other applications. A cantilever beam is connected to two stranded cables. The cables are modeled as tensioned Euler–Bernoulli beams, considering the sag due to self-weight. The pole is also modeled as a cantilever Euler–Bernoulli beam and the equations of motion are derived using Hamilton’s principle. The model was validated with a reduced-scale system in the laboratory and a setup was designed to accurately measure the bending stiffness of the stranded cable under tension. It is concluded that the bending stiffness and sag of the cable have a significant effect on the dynamics of beam–cable structures. By adding the cable to the pole structure, some hybrid modes emerge in the eigenvalue solution of the system. Modes with antisymmetric cable motion are sag-independent and the modes with symmetric cable motion are dependent on the cable sag. The effect of sag on the natural frequencies is more significant when the bending stiffness of the cables is higher.

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: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.213

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 head0.003
GPT teacher head0.187
Teacher spread0.183 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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