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Record W2153624780 · doi:10.1115/1.4006770

An Experimental Study on the Process Monitoring of Resin Transfer Molded Composite Structures Using Fiber Optic Sensors

2012· article· en· W2153624780 on OpenAlexaff
Mehmet Yıldız, Nazli Gulsine Ozdemir, Gökhan Bektaş, Casey Keulen, Talha Boz, Ege F. Sengun, Cem Öztürk, Yusuf́ Z. Menceloǵlu, Afzal Suleman

Bibliographic record

VenueJournal of Manufacturing Science and Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsUniversity of Victoria
FundersTürkiye Bilimsel ve Teknolojik Araştırma Kurumu
KeywordsMaterials scienceTransfer moldingComposite materialOptical fiberFiber Bragg gratingFiber optic sensorFiberComposite numberMolding (decorative)MoldOpticsOptoelectronicsWavelength

Abstract

fetched live from OpenAlex

Research conducted on in situ process monitoring of resin transfer molded composites with fiber optic sensors is presented. A laboratory scale resin transfer molding (RTM) apparatus was designed and built with the capability of embedding fiber optic sensors and visually observing the resin filling process. Both fiber Bragg grating (FBG) and etched fiber (EF) sensors are embedded into glass fiber reinforcements in the RTM mold and used to monitor the resin flow front and cure. The cure cycle of the resin system utilized in this work is also studied using a Fresnel reflection refractometer (FRR) sensor. The results of this study show that both the FBG and EF sensors can be used efficiently for flow and cure monitoring of the RTM process. The experimental results of the EF and FRR sensors agree with those of the FBG sensors for cure monitoring.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.285
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2012
Admission routes1
Has abstractyes

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