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Record W2504028702 · doi:10.1177/8756087916663031

Thermal wrinkling behavior of formable decorative film laminates

2016· article· en· W2504028702 on OpenAlexaff
Ganesh Balamurugan, Rohan N. Pukadyil, Mahdy M Malayery, Michael R. Thompson, J. Vlachopoulos, Kent E. Nielsen, Frank A. Brandys

Bibliographic record

VenueJournal of Plastic Film & Sheeting · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceComposite materialViscoelasticityWrinkleThermalStiffnessSubstrate (aquarium)Layer (electronics)Thermodynamics

Abstract

fetched live from OpenAlex

This paper focuses on wrinkle development in decorative film laminates during heating operations with the goal to understand their driving factors and develop strategies to overcome such defects. The study looked at temperature and heating rate effects on the wrinkling behavior of a commercial black-out film laminated onto a metal substrate. The 135℃ threshold temperature identified for our film under which no wrinkles formed, related to the stiffness of its different construction layers. Heating rate was also noted by this study to be an important parameter in wrinkling; values between 1℃ and 350℃/min were tested. It was possible to exceed the threshold temperature stated above without wrinkling when the heating rate was sufficiently low (closer to 1℃/min, though less than 50℃/min was often sufficient depending on the final temperature). The heating rate effect is believed to be related to the time-dependent viscoelastic response of the compliant layer in relation to building thermal stresses.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.345

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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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 designBench or experimental
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

Citations2
Published2016
Admission routes1
Has abstractyes

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