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Record W2790876129 · doi:10.1177/1045389x17754254

Utilizing tension reduction in a dielectric elastomer actuator to produce compression for physiological application

2018· article· en· W2790876129 on OpenAlex
Hamza Edher, Louise Maupas, Sunraaj Nijjer, Armaghan Salehian

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Intelligent Material Systems and Structures · 2018
Typearticle
Languageen
FieldEngineering
TopicDielectric materials and actuators
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooUniversity of Auckland
KeywordsActuatorCompression (physics)Materials scienceVoltageElastomerSmart materialMechanical engineeringEngineeringElectrical engineeringComposite material

Abstract

fetched live from OpenAlex

A common prophylaxis against peripheral vascular diseases utilizes pneumatic active compression systems. Although effective, traditional active compression systems require the use of an air compressor and pump and are, therefore, ill-suited for ambulatory use. The current work introduces a novel approach to developing an ambulatory smart material–based active compression system. The actuation system is composed of a belt-like mechanism connected in conjunction with a multi-layered dielectric elastomer actuator. The belt mechanism allows compression to be applied directly with voltage application. By doing so, the proposed design limits the period during which the actuator should be charged and improves system power efficiency and lifetime. An analytical model which defines the pre-compression exerted by the actuation system before voltage application is presented and validated experimentally. Experimental results for the belt mechanism characterization, dielectric elastomer actuator characterization and actuation system testing are presented. Through experimental testing, it is shown that the initial pre-compression can be fine-tuned by varying the parameters of the system as defined in the analytical model, and that the pre-compression has little effect on the consequent actuation output amplitudes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.351

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 head0.015
GPT teacher head0.255
Teacher spread0.240 · 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