MétaCan
Menu
Back to cohort
Record W3101635852 · doi:10.1115/1.4048744

Geometry-Based Thick Origami Simulation

2020· article· en· W3101635852 on OpenAlexafffund
Tsz-Ho Kwok

Bibliographic record

VenueJournal of Mechanical Design · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDNA origamiComputer scienceGeometric designVertex (graph theory)GeometryMechanical engineeringEngineeringEngineering drawingMathematicsTheoretical computer scienceGraph

Abstract

fetched live from OpenAlex

Abstract Origami is the art of creating a three-dimensional (3D) shape by folding paper. It has drawn much attention from researchers, and the designs that origami has inspired are used in various engineering applications. Most of these designs are based on familiar origami patterns and their known deformations, but origami patterns were originally intended for materials of near-zero thickness, primarily paper. To use the designs in engineering applications, it is necessary to simulate origami in a way that enables designers to explore and understand the designs while taking the thickness of the material to be folded into account. Because origami is primarily a problem in geometric design, this paper develops a geometric simulation for thick origami. The actuation, constraints, and assignment of mountain and valley folds in origami are also incorporated into the geometric formulation. The experimental results show that the proposed method is efficient and accurate. The method can successfully simulate a flat-foldable degree-four vertex, two different action origami, the bistable property of a waterbomb base, and the elasticity of non-rigid origami panels.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score0.387

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 head0.048
GPT teacher head0.257
Teacher spread0.209 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations13
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Mechanical DesignSame topicAdvanced Materials and MechanicsFrench-language works237,207