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Record W1971142069 · doi:10.1088/0960-1317/11/3/308

Simulation, dynamic testing and design of micromachined flexible joints

2001· article· en· W1971142069 on OpenAlexaff
H. Fettig, James Wylde, Ted Hubbard, Marek Kujath

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2001
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsNortel (Canada)Dalhousie University
Fundersnot available
KeywordsJoint (building)StiffnessStructural engineeringFinite element methodKinematicsDynamic simulationBeam (structure)Dynamic testingSurface micromachiningEngineeringRotation around a fixed axisBendingMaterials scienceMechanical engineeringAcousticsSimulationPhysicsFabrication

Abstract

fetched live from OpenAlex

This paper examines the simulation, dynamic testing and design of micromachined flexible joints. The objective is to mimic the kinematics of classical macro rotating and sliding joints with flexural micro joints. The joints consist of long slender beams that are folded in a variety of shapes: `I', `H', `X', `S', `U' and `V' shaped joints are considered. Finite element modelling simulations are used to simulate rotational, axial and out-of-plane stiffness and examine the effect of variations in joint length and beam angles. The simulation results are compared to a series of dynamic tests of polysilicon micromachined joints. The resonant frequencies of joint-mass systems were measured using a non-contact laser reflectance apparatus and the derived experimental rotational stiffnesses were found to agree with simulations. Design guidelines for the selection of the optimum joint shape and length for given functional requirements such as directional stiffness, selective compliance and range of motion are presented.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.634

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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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

Citations17
Published2001
Admission routes1
Has abstractyes

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