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Record W3177450342 · doi:10.4271/2021-01-5068

Design of a Compact Composite Prepreg Tape Dispensing Device

2021· article· en· W3177450342 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

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2021
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsMiller Group (Canada)
Fundersnot available
KeywordsComposite numberMaterials scienceComputer scienceComposite material

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">The design of a compact composite prepreg tape dispensing device is presented. This device supplies composite prepreg plies to manual and robotic composite prepreg layup processes for producing composite laminates. It is able to de-reel a spool of prepreg tape, remove the backing paper, cut the tape into plies at specified lengths, and place the plies for pickup. It provides a compact and economic tape supplying solution to the composite manufacturing industry. A prototype device was created and tested. With an overall footprint of 20 3/8 inches (517.5 mm) by 50 5/8 inches (1285.9 mm) and a mass of 35 lb (15.9 kg), the device was compact enough and functioned well in a tabletop layup workspace. The prepreg tape dispensing process was successfully carried out. The tape cutting accuracy of the prototype device achieved 1/22 inches (1.2 mm) on average with a standard deviation of 1/13 inches (2.0 mm). The tape delivery positioning accuracy achieved 1/32 inches (0.8 mm) on average with a standard deviation of 3/68 inches (1.1 mm) in the longitudinal direction, and 1/80 inches (0.3 mm) on average with a standard deviation of 1/38 inches (0.7 mm) in the transverse direction. The test results verify the capability of the presented technique in producing prepreg plies with sufficient accuracy and consistency.</div></div>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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