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Record W2066366227 · doi:10.1115/1.4001776

Variable Stiffness Spring Using Tensegrity Prisms

2010· article· en· W2066366227 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Mechanisms and Robotics · 2010
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTensegrityStiffnessSpring (device)Variable (mathematics)Mechanism (biology)Control theory (sociology)EngineeringVibrationCompliant mechanismStructural engineeringComputer scienceMathematicsControl (management)PhysicsMathematical analysisAcousticsArtificial intelligenceFinite element method

Abstract

fetched live from OpenAlex

A novel variable stiffness mechanism (i.e., variable spring) based on the concept of tensegrity structures is presented. Variable springs have extensive applications in noise and vibration control. The proposed method builds upon the prestress stiffness in tensegrities, which occurs along infinitesimal mechanisms and is fully controllable through force control in the members. A criterion is given to select a suitable tensegrity structure and an infinitesimal mechanism to develop a variable spring. Also, a mathematical model is developed for the stiffness components in an n-gon tensegrity prism. The variable components of the stiffness are then utilized to create a translational or rotational variable spring. In order to elaborate on the feasibility of the concept, a case study is presented on the engine mount of a vehicle. Parameters of a possible design of a variable stiffness mount are given, and the characteristics are compared with those of a conventional passive mount. This is followed by a detailed discussion on the properties of such a variable spring and the effects of various parameters.

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.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.249
Threshold uncertainty score0.252

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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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