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Record W1970845827 · doi:10.1177/0731684404029360

Laser Transmission Welding of Semicrystalline Thermoplastics - Part II: Analysis of Mechanical Performance of Welded Nylon

2004· article· en· W1970845827 on OpenAlexaff
Val A. Kagan, G. P. Pinho

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2004
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Selection and Properties
Canadian institutionsMagna International (Canada)
Fundersnot available
KeywordsMaterials scienceLaser beam weldingComposite materialWeldingUltimate tensile strengthMolding (decorative)Nylon 6Nylon 66Plastic weldingPolymerFiller metalArc welding

Abstract

fetched live from OpenAlex

Selecting thermoplastics for a wide industrial application (automotive, appliances, lawn and garden, power tools, etc.) strongly depends on the plastic material composition, part design, processing (molding and welding) conditions. The structure of used thermoplastics, mechanical properties and composition (reinforcements, fillers, additives, pigments, etc.) may have the greater influence and need to be characterized for optimum material selection for the laser transmission welding (LTW) application. To provide a guide to nylon based thermoplastics selection for LTW applications we have evaluated the influence of specific material composition factors and properties, such as fiber-glass, mineral filler, impact modifier content, and color/pigment version on the Near InfraRed (NIR) transmission characteristics, including the laser wavelength (1.06 mm). The results of an optical characterization of nylon 6 based thermoplastics are discussed in the Part I of this report to ANTEC’ 2000 (Kagan, V. A., Bray, R. B. and Kuhn, W. P., ‘‘Laser Transmission Welding of Semi-Crystalline Thermoplastics - Part I: The Magical Solution, Proceedings of the SPE 58th Annual Technical Conference and Exhibits (ANTEC’2000)). The mechanical performance (tensile strength at room temperature conditions) of nylon welded joints was evaluated in terms of the influence of transmission laser welding technology parameters (laser power, welding speed, laser beam spot sizes, clamp pressure, etc.) and thermoplastic composition (reinforcements, fillers, additives, pigments, etc.). Technical results of this comprehensive evaluation (optical properties of nylon 6 based plastics and mechanical performance of welded joints) will assist plastic parts designers and technologists in selecting nylon based thermoplastics and developing new products using LTW technology. The purpose of Part II of this report is to increase understanding within the plastics engineering community regarding the usefulness and possible applicability of LTW technology for nylon made components.

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)0.000
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
Metaresearch0.0000.000
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)0.0010.000

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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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

Citations52
Published2004
Admission routes1
Has abstractyes

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