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3D printed bistable composite lattice shells with tailorable coiled geometries

2025· article· en· W4411196479 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueComposite Structures · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsBistabilityComposite numberMaterials scienceLattice (music)3d printedComposite material3D printingStructural engineeringOptoelectronicsEngineeringPhysicsBiomedical engineeringAcoustics

Abstract

fetched live from OpenAlex

This investigation presents, to the authors’ best knowledge, the first 3D printed continuous fiber-reinforced polymer composite deployable booms. The precise material placement capabilities of the fused filament fabrication (FFF) process are leveraged to produce cylindrical bistable slit tube booms with lattice architectures. The influences of fiber angles, lattice density, and initial shell curvature on the existence and form of stable coiled configurations as well as flexural rigidity properties are investigated. A computational procedure for automatically generating finite element models directly from material deposition paths is presented, with predicted shell behaviors showing strong agreement with experimental results using both homogenization and full-scale modeling approaches. Lattice shell architectures are revealed to exhibit higher flexural rigidity properties than continuum architectures on an equal-mass basis. Finally, bistable slit tube booms that can coil into unique stable configurations via the tailoring of material deposition paths are demonstrated.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.202
Teacher spread0.197 · 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