Page 40 - MSAM-4-3

Materials Science in Additive Manufacturing Numerical simulation of plasma WAAM for Ti-6Al-4V

different welding conditions, making it inefficient and Writing – original draft: Martin Bielik
resource-intensive. Future research should explore Writing – review and editing: Martin Bielik and Ernst
data-driven approaches, such as machine learning, Kozeschnik
regression analysis, or optimization algorithms,
to improve calibration efficiency and prediction Ethics approval and consent to participate
accuracy. Not applicable.
(iv) Assuming temperature-independent thermal
boundary conditions throughout the welding process Consent for publication
introduces potential inaccuracies. These parameters
are not only temperature-dependent but also Not applicable.
influenced by building height and geometry, requiring Availability of data
adaptive calibration approaches to improve model
accuracy. Data will be made available from the corresponding author
(v) Melt pool dynamics are not explicitly modeled in the upon reasonable request.
present simulation framework, limiting the ability to
capture fluid flow effects, temperature gradients, and Further disclosure
solidification phenomena. Oversimplified thermal The paper is based on the thesis of the first author,
models can misrepresent cooling rates, affecting the Martin Bielik. (https://repositum.tuwien.at/
microstructure evolution and mechanical properties handle/20.500.12708/15047).
of the deposited material. Future work should integrate
computational fluid dynamics with FE simulations References
to improve the accuracy of weld pool dynamics, 1. DIN EN ISO/ASTM 52900:2022-03. Additive Fertigung-
solidification modeling, and heat transfer predictions. Grundlagen-Terminologie Additive Manufacturing-General
(vi) The results of this study can be extended to multi- Principles-Fundamentals and Vocabulary (ISO/ASTM
pass welding simulations to facilitate the prediction 52900:2021); 2022.
of residual stresses, distortion fields, and thermal
cycles in complex AM components. Coupled thermo- doi: 10.31030/3290011
mechanical simulations can optimize toolpath 2. Bielik M. Thermo-Mechanical Analysis of Plasma-Based
strategies and welding parameters, reducing the Additive Manufacturing of Ti-6Al-4V Components Using
need for extensive experimental testing. Model Simufact Welding. Master’s Thesis. TU Wien; 2020.
enhancements can be tested, and different numerical Available from: https://repositum.tuwien.at/
approaches can be compared to improve computational handle/20.500.12708/15047 [Last accessed 2025 Mar 30].
efficiency and result accuracy.
3. Bielik M, Meuthen J, Ariza-Galvan E, et al. Plasma Metal
Acknowledgments Deposition in Aerospace Applications Enabling a Cost-
Efficient Technology for High Tech Industries. Metal Additive
The authors acknowledge TU Wien Bibliothek for financial Manufacturing Conference (MAMC), Vienna; 2020.
support through its Open Access Funding Programme.
4. Wallis C, Neubauer E, Kitzmantel M, et al. Investigations of
Funding plasma metal deposition (PMD) of 6061 and 7075 aluminum
alloys for aerospace and automotive applications. BHM Berg
Not applicable Hüttenmänn Monats. 2023;168(5):209-218.
Conflict of interest doi: 10.1007/s00501-023-01345-4
5. Li JZ, Alkahari MR, Rosli NA, Hasan R, Sudin MN,
The authors declare they have no competing interests.
Ramli FR. Review of wire arc additive manufacturing for 3D
Author contributions metal printing. Int J Autom Technol. 2019;13(3):346-353.
doi: 10.20965/ijat.2019.p0346
Conceptualization: Martin Bielik, Erich Neubauer, and
Ernst Kozeschnik 6. Gierth M, Henckell P, Ali Y, Scholl J, Bergmann JP. Wire
Investigation: Martin Bielik arc additive manufacturing (WAAM) of aluminum alloy
Methodology: Martin Bielik AlMg5Mn with energy-reduced gas metal arc welding
Resources: Erich Neubauer, Michael Kitzmantel, Ingo (GMAW). Materials. 2020;13(12):2671.
Neubauer, and Ernst Kozeschnik doi: 10.3390/ma13122671

Volume 4 Issue 3 (2025) 13 doi: 10.36922/MSAM025140021