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Record W2987933154 · doi:10.1080/20550340.2019.1686820

Heat transfer analysis of automated fiber placement of thermoplastic composites using a hot gas torch

2019· article· en· W2987933154 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

VenueAdvanced Manufacturing Polymer & Composites Science · 2019
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceComposite materialThermoplasticThermocoupleResidual stressHeat deflection temperatureHeat transferComposite numberCrystallinityMechanics

Abstract

fetched live from OpenAlex

With more and more use of composites in engineering applications, the need for automated composites manufacturing is evident. The use of automated fiber placement (AFP) machine for the manufacturing of thermoplastic composites is under rapid development. In this technique, a moving heat source (hot gas torch, laser, or heat lamp) is melting the thermoplastic composite tape and consolidation occurs in situ. Due to the rapid heating and cooling of the material, there are many issues to be addressed. First is the development of the temperature distribution in different directions which gives rise to temperature gradients. Second is the quality of the bond between different layers, and third is the rate of material deposition to satisfy industrial demand. This paper addresses the first issue. The temperature distribution affects the variation in crystallinity, and residual stresses throughout the structure as it is being built. The result is the distortion of the composite laminate even during the process. In order to address this problem, first the temperature distribution due to a moving heat source needs to be determined. From the temperature distribution, the development and distribution of crystallinity, residual stresses and deformation of the structure can then be determined. As the first phase of the work, this paper investigates the temperature distribution due to a moving heat source for thermoplastic composites, without considering the material deposition. A finite difference (FD) code based on energy balance approach is developed to predict the temperature distribution during the process. Unidirectional composite strips are manufactured using AFP and fast-response K-type thermocouples (response time of 0.08 s, as compared to normal thermocouples with response time of 0.5 s) are used to determine the thermal profiles in various locations through the thickness of the composite laminate subjected to a moving heat source. It is shown that temperature variations measured experimentally during the heating pass, using thermocouples embedded into the composite substrate, underneath layers of the composite material, are consistent with the generated thermal profiles from the numerical model. The temperature distribution, in both the direction of the tape and through-thickness direction can be predicted numerically.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.237
Teacher spread0.227 · 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