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Record W2765627290 · doi:10.5539/mer.v7n2p6

Dynamic Characteristics of Hanging Truss Having Shape Memory Alloy Wires

2017· article· en· W2765627290 on OpenAlexvenueno aff
Xuan Zhang, Kazuyuki HANAHARA, Yukio Tada

Bibliographic record

VenueMechanical Engineering Research · 2017
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsSMA*Shape-memory alloyTrussStructural engineeringVibrationVibration isolationStiffnessBracingMaterials scienceAttenuationComputer scienceEngineeringAcousticsComposite materialBracePhysicsOptics

Abstract

fetched live from OpenAlex

In this study, we discuss the dynamics of a type of hanging truss structural system consisting of rigid and wire members, part of which are SMA (shape memory alloy) wires. This kind of truss structure has the capability of vibration isolation and absorption. Characteristics of zero compressive stiffness of wire members, SMA wire members and hanging configuration of the structure itself contribute to the effect of vibration isolation. The hysteretic loop of SMA wires plays a significant role in vibration attenuation. Mathematical models for this kind of dynamic problem are developed. Calculation process is introduced to take into account the mechanical characteristics of SMA and wire members. Dynamic characteristics are discussed; simultaneously, the effects of vibration isolation and attenuation have been confirmed. On the basis of the numerical calculations, advantages of combinations of various types of wire members, including the truss units having no bracing wires have been demonstrated.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.025
GPT teacher head0.292
Teacher spread0.267 · 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 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

Citations3
Published2017
Admission routes1
Has abstractyes

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