Startseite Thermal modeling and analysis of laser transmission welding of polypropylene: process mechanics and parameters
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Thermal modeling and analysis of laser transmission welding of polypropylene: process mechanics and parameters

  • Ghulam Anwer ORCID logo EMAIL logo und Bappa Acherjee ORCID logo
Veröffentlicht/Copyright: 13. Dezember 2024
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Abstract

Laser transmission welding efficiently welds polymers by precisely applying concentrated heat with a laser beam, making it a widely used, non-contact, contamination-free, automated, and fast polymer joining method in automotive, medical, and electrical industries. This study presents a three-dimensional finite element model simulating the laser transmission welding of polypropylene, a widely utilized engineering thermoplastic with superior mechanical properties and exceptional chemical resistance. The primary objectives are to analyze thermal phenomena, predict parameters such as weld temperature and weld pool size, and conduct a thorough parametric analysis. The finite element model incorporates a volumetric heat source within COMSOL® Multiphysics, incorporating a radiative beam in an absorbing media interface, while considering key thermal factors such as conduction, convection, and radiation. Experimental tests are conducted to validate the developed thermal model. The paper deepens comprehension of the mechanics behind laser transmission welding of polypropylene, providing insights into the impact of process parameters on the thermal field and weld pool size.


Corresponding author: Ghulam Anwer, Department of Production & Industrial Engineering, Birla Institute of Technology: Mesra, Ranchi 835215, India, E-mail:

Acknowledgments

The authors gratefully acknowledge the Central Instrumentation Facility (CIF) of BIT Mesra, Ranchi, India. The authors also would like to acknowledge I-STEM, Indian Institute of Science, Bengaluru, India for providing access to COMSOL® Multiphysics 6.0 for the simulation work carried out in this research.

  1. Research ethics: Authors know the purpose, benefits, and funding behind this study.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Ghulam Anwer: investigation, methodology, formal analysis, writing – original draft. Bappa Acherjee: conceptualization, writing – review & editing, supervision.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

  6. Research funding: This research is partially supported by the Science and Engineering Research Board, DST, New Delhi, India, Grant Number CRG/2022/004102.

  7. Data availability: The data that support the findings of this study are available in the manuscript. Missing data, if any, that support the findings of this study are available from the corresponding author, upon reasonable request.

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Received: 2024-02-09
Accepted: 2024-04-09
Published Online: 2024-12-13
Published in Print: 2024-11-26

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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