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Record W3000585605 · doi:10.1115/1.4046029

Modeling and Analysis of a Planar Soft Panel Continuum Mechanism

2020· article· en· W3000585605 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 · 2020
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsToronto Metropolitan University
FundersNational Natural Science Foundation of China
KeywordsStaticsKinematicsStiffnessPlanarCompliant mechanismMechanism (biology)CurvatureClassical mechanicsComputer scienceControl theory (sociology)PhysicsStructural engineeringEngineeringGeometryFinite element methodMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Continuum mechanisms have drawn wide attention to scholars due to their salient advantages including compliance and dexterity. In this paper, a planar continuum mechanism made of soft panels is proposed. This mechanism has a reduced degree-of-freedom (DOF) compared with some existing continuum mechanisms capable of 3D motion. However, it can meet some application requirements in the field of robot and aerospace due to its characteristics of small stiffness in the motion plane and large stiffness perpendicular to the motion plane. Besides, a combined kinematics and statics modeling approach is presented for this mechanism by using the classical beam theory and a constrained optimization method. In order to ensure the model accuracy, a hybrid approach is proposed to consider gravity depending on the deformation under study. By comparing our results with those from the commonly used constant-curvature method, it is shown that our model is more accurate in predicting the deformation shapes.

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: none
Teacher disagreement score0.803
Threshold uncertainty score0.358

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 head0.027
GPT teacher head0.216
Teacher spread0.189 · 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