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Record W1772081093 · doi:10.1002/9781118097298.weoc153

Molding: Liquid Composite Molding ( <scp>LCM</scp> )

2012· other· en· W1772081093 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

VenueWiley Encyclopedia of Composites · 2012
Typeother
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTransfer moldingThermosetting polymerMolding (decorative)Composite numberMoldComposite materialCompression moldingMaterials scienceThermoplasticFiber-reinforced compositeFabricationThermoplastic compositesThermoformingEngineering drawingEngineering

Abstract

fetched live from OpenAlex

Abstract Since many years, liquid composite molding (LCM) processes represent a well‐established class of manufacturing techniques for the fabrication of semistructural and structural fiber‐reinforced composite parts. All LCM variants share the same basic principle: arbitrary fiber reinforcement is placed in a mold. After closing, a liquid resin is injected. The part is then cured and demolded. LCM technology is mainly used to manufacture thermoset composites, but it can also be applied to thermoplastic composites. This article describes the main features of LCM technologies. Process variants are introduced, and main processing steps are illustrated using the example of the resin transfer molding (RTM) process. Particular attention is devoted to the mathematical description of the resin flow through fibrous preforms. Further technological aspects such as material selection criteria, mold design, and processing equipment are also considered.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.347
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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