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Record W4396828982 · doi:10.1155/2024/1234797

Experimental Investigation on the 3D Printing of Nylon Reinforced by Carbon Fiber through Fused Filament Fabrication Process, Effects of Extruder Temperature, and Printing Speed

2024· article· en· W4396828982 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

VenueInternational Journal of Polymer Science · 2024
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsÉcole de Technologie Supérieure
FundersUniversity of Northampton
KeywordsMaterials sciencePlastics extrusionFabricationComposite materialProtein filamentProcess (computing)Fused filament fabricationFiber3D printingNylon 6PolymerComputer science

Abstract

fetched live from OpenAlex

This study investigated how the extruder temperature, printing speed, and specimen geometry interact during a tensile test of continuous carbon fiber‐reinforced nylon matrix composites produced by the fused deposition modelling (FDM) process. The investigation utilized statistical techniques. For this purpose, tensile examinations were done on manufactured samples using a testing apparatus. The study’s objective is to identify the most efficient specimen geometry for tensile testing result optimization and to maximize the 3D printing process’s capability for producing complex, freeform patterns in these composites. In this study, the input parameters required for the response surface methodology (RSM) were varying extruder temperature (240‐255°C) and printing speed (60‐80 mm/s), and experimental responses included modulus, elongation at break, and weight. The findings of the regression analysis showed output responses are influenced by both input variables. The results showed that the strength of the samples was significantly influenced by the input parameters. To draw the surface and residual plots, the software of design expert software was used. The interaction between the two input variables suggests raising the extruder temperature and decreasing printing speed, which leads to printing heavier samples. Inversely, the diversity between the forecasted and real responses for the optimal specimens is less than 10% which is assumed to be acceptable for the design of experiments (DOE). The analysis took into account the lower and upper ranges of the input variable with the goal of enhancing both the most modulus and fracture elongation while simultaneously degrading the weight of the specimens. To achieve this objective, the extruder temperature and printing speed are between 240 and 250°C and 65 and 75 mm/s, respectively.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.277

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 head0.011
GPT teacher head0.248
Teacher spread0.238 · 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