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Record W2990232350 · doi:10.1115/detc2019-97094

Geometric Simulation for Thick Origami

2019· article· en· W2990232350 on OpenAlexaff
Tsz-Ho Kwok

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceGeometric designBistabilityDNA origamiGeometric modelingEngineering drawingMechanical engineeringEngineeringMaterials science

Abstract

fetched live from OpenAlex

Abstract Origami is an art that creates a three-dimensional (3D) shape only by folding. This capability has drawn much research attention recently, and its applied or inspired designs are utilized in various engineering applications. Most current designs are based on the existing origami patterns and their known deformation, but origami patterns are universally designed for zero-thickness like a paper. To extend the designs for engineering applications, simulation of origami is needed to help designers explore and understand the designs, and the simulation must take the material thickness into account. With the observation that origami is mainly a geometry design problem, this paper develops a geometric simulation for thick origami, similar to a pseudo-physics approach. The actuation, constraints, and mountain/valley assignments of origami are also incorporated in the geometric formulation. Experimental results show that the proposed method is efficient and accurate. It can simulate successfully the bistable property of a waterbomb base, two different action origami, and the elasticity of origami panels when they are not rigid.

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: Empirical · Consensus signal: none
Teacher disagreement score0.838
Threshold uncertainty score0.210

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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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
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

Citations1
Published2019
Admission routes1
Has abstractyes

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