MétaCan
Menu
Back to cohort

SMA in Mitigation of Extreme Loads in Civil Engineering: Damping Actions in Stayed Cables

2011· article· en· W2028385433 on OpenAlexaff
Vicenç Torra, A. Isalgué, C. Auguet, Guillem Carreras, F.C. Lovey, Patrick Terriault, Lamine Dieng

Bibliographic record

VenueApplied Mechanics and Materials · 2011
Typearticle
Languageen
FieldMaterials Science
TopicShape Memory Alloy Transformations
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsSMA*DamperShape-memory alloyStructural engineeringOscillation (cell signaling)EngineeringMaterials scienceComputer scienceComposite material

Abstract

fetched live from OpenAlex

Reliable use of Shape Memory Alloys (SMA) in mitigation of extreme load effects requires a deep study of the SMA behavior according to the necessities of the application. Damping the oscillations induced by one storm of three or four days with a strong wind and/or rain usually requires more than one million of working cycles. A SMA damper is checked in to two realistic cables of ELSA and of IFSTTAR. The measurements establish that the SMA damping device reduces drastically the oscillation amplitude. Technical suggestions for the preparation of the dampers built by several SMA wires of NiTi with 2.46 mm of diameter are included. The choice of appropriate length and the choice of the number of required SMA wires are suggested. Moreover, a suitable simulation by proprietary SMA routine inside ANSYS is included.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.046
GPT teacher head0.221
Teacher spread0.175 · 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

Citations20
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueApplied Mechanics and MaterialsSame topicShape Memory Alloy TransformationsFrench-language works237,207