Open Access
| Issue |
MATEC Web Conf.
Volume 417, 2025
2025 RAPDASA-RobMech-PRASA-AMI Conference: Bridging the Gap between Industry & Academia - The 26th Annual International RAPDASA Conference, joined by RobMech, PRASA and AMI, co-hosted by CSIR and Tshwane University of Technology, Pretoria
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| Article Number | 06006 | |
| Number of page(s) | 15 | |
| Section | Computational & Data-driven Modelling | |
| DOI | https://doi.org/10.1051/matecconf/202541706006 | |
| Published online | 25 November 2025 | |
- A.H. Alami, et al., Additive manufacturing in the aerospace and automotive industries: Recent trends and role in achieving sustainable development goals. Ain Shams Eng. J. 14, 1-18 (2023) https://doi.org/10.1016/j.asej.2023.102516 [Google Scholar]
- H.A. Colorado, C.A. Cardenas, E.I. Gutierrez-Velazquez, J.P. Escobedo, S.N. Monteiro, Additive manufacturing in armor and military applications: research, materials, processing technologies, perspectives, and challenges. J. Mat. Res. Technol. 27, 3900-3913 (2023) https://doi.org/10.1016/j.jmrt.2023.11.030 [Google Scholar]
- L. Chen, N.P.H. Ng, J. Jung, S.K. Moon, Additive Manufacturing for Automotive Industry: Status, Challenges and Future Perspectives, in Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management. 2023. Singapore (2023) [Google Scholar]
- Y. Xu, et al., Experimental analysis of the multiaxial failure stress locus of commercially pure titanium at low and high rates of strain. Int. J. Impact Eng. 170, 1-17 (2022) https://doi.org/10.1016/j.ijimpeng.2022.104341 [Google Scholar]
- P. Muthuswamy, Influence of powder characteristics on properties of parts manufactured by metal additive manufacturing. Lasers Manuf. Mater. Process. . 9, 312-337 (2022) https://doi.org/10.1007/s40516-022-00177-3 [Google Scholar]
- F.A. Talebi, et al., Spreadability of powders for additive manufacturing: A critical review of metrics and characterisation methods. Particuology. 93, 211-234 (2024) https://doi.org/10.1016/j.partic.2024.06.013 [Google Scholar]
- A.S. Tehrani, M.H. Korayem, S. Shao, M. Haghshenas, N. Shamsaei, Ti-6Al-4V powder characteristics in laser powder bed fusion: the effect on tensile and fatigue behavior. Addit. Manuf. 51, (2022) https://doi.org/10.1016/j.addma.2021.102584 [Google Scholar]
- J. Li, Z. Hao, Y. Shu, J. He, Fabrication of spherical Ti-6Al-4V powder for additive manufacturing by radio frequency plasma spheroidization and deoxidation using calcium. J. Mat. Res. Technol. 9, 14792-14798 (2020) https://doi.org/10.1016/j.jmrt.2020.10.054 [Google Scholar]
- Ji., L., C. Wang, W. Wu, C. Tan, G. Wang, X.-M. Duan, Spheroidization by Plasma Processing and Characterization of Stainless Steel Powder for 3D Printing. Metall. Mater. Trans. A. 48, 4831-4841 (2017) https://doi.org/10.1007/s11661-017-4240-5 [Google Scholar]
- L.A. Dobrzanski, L.B. Dobrzanski, A.D. Dobrzanska-Danikiewicz, M. Kraszewska, Manufacturing powders of metals, their alloys and ceramics and the importance of conventional and additive technologies for products manufacturing in Industry 4.o stage. Arch. Mater. Sci. Eng. 102, 13-41 (2020) https://doi.org/10.5604/01.3001.0014.1452 [Google Scholar]
- N. Nkhasi, W.d. Preez, H. Bissett, Plasma spheroidization and characterisation of commercial titanium grade 5 powder for use in metal additive manufacturing, in Proceedings of the RAPDASA-RobMech-PRASA-AMI Conference. 2023. CSIR International Convention Centre in Pretoria, South Africa: EDP Sciences (2023) [Google Scholar]
- X. Zhang, X. Hou, Z. Hao, P. Wang, Y. Shu, J. He, Research on Spheroidization of Tungsten Powder from Three Different Raw Materials. Materials. 15, 1-12 (2022) https://doi.org/10.3390/ma15238449 [Google Scholar]
- Y.L. Li, T. Ishigaki, Spheroidization of Titanium Carbide Powders by Induction Thermal Processing. J. Am. Ceram. Soc. 84, 1929-1936 (2001) [Google Scholar]
- H. Hou, Z. Ji, Z. Xie, H. Jin, Spheroidizing mechanisms and simulation of spherical silica in Oxygen-Acetylene flame. Adv. Powder Technol. 29, 789-795 (2018) https://doi.org/10.1016/j.apt.2017.12.018 [Google Scholar]
- J.B. Tong, X. Lu, C.C. Liu, Z.Q. Pi, R.J. Zhang, X.H. Qu, Numerical simulation and prediction of radio frequency inductively coupled plasma spheroidization. Appl. Therm. Eng. 100, 1198-1206 (2016) https://doi.org/10.1016/j.applthermaleng.2016.02.108 [Google Scholar]
- L. Xin, Z. Lang-ping, Z. Bing, Z. Rui-jie, H. Xin-bo, Q. Xuan-hui, Simulation of flow field and particle trajectory of radio frequency inductively coupled plasma spheroidization. Comput. Mater. Sci. 65, 13-18 (2012) https://doi.org/10.1016/j.commatsci.2012.06.008 [Google Scholar]
- J. He, L. Bai, H. Jin, F. Yuan, Optimization of tungsten particles spheroidization with different size in thermal plasma reactor based on numerical simulation. Powder Technol. 302, 288-297 (2016) https://doi.org/10.1016/j.powtec.2016.08.067 [Google Scholar]
- A. Seya, A. Kolesnikov, J. Van Der Walt, H. Bissett, Simulation of the effect of evaporation and gas composition during plasma spheroidization, in Proceedings of the RAPDASA-RobMech-PRASA-CoSAAMI Conference. 2022. Somerset West, South Africa: EDP Sciences (2022) [Google Scholar]
- B.L. Smith, The difference between traditional and CFD validation benchmark experiments. Nucl. Eng. Des. 312, 42-47 (2017) https://doi.org/10.1016/j.nucengdes.2016.10.007 [Google Scholar]
- J. Slotnick, et al., CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences. (2014); Available from: ntrs.nasa.gov/citations/20140003093. [Google Scholar]
- M.J. Berger, M.J. Aftosmis, D. Marshall, S.M. Murman, Performance of a new CFD flow solver using a hybrid programming paradigm. J. Parallel Distrib. Comput. 65, 414-423 (2005) [CrossRef] [Google Scholar]
- G. Calzolari, W. Liu, Deep learning to replace, improve, or aid CFD analysis in built environment applications: A review. Build. Environ. 206, 1-12 (2021) https://doi.org/10.1016/j.buildenv.2021.108135 [Google Scholar]
- S. Calcaterra, G. Campana, L. Tomesani, Prediction of mechanical properties in spheroidal cast iron by neural networks. J. Mater. Process. Technol. 104, 74-80 (2000) [Google Scholar]
- R.P. Cherian, L.N. Smith, P.S. Midha, A neural network approach for selection of powder metallurgy materials and process parameters. AI Eng. 14, 39-44 (2000) [Google Scholar]
- T.A. Choudhury, N. Hosseinzadeh, C.C. Berndt, Using Artificial Neural Network to Predict the Particle Characteristics of an Atmospheric Plasma Spray Process, in Proceedings of the 6th International Conference on Electrical and Computer Engineering 2010. Dhaka, Bangladesh (2010) [Google Scholar]
- A. Safonova, G. Ghazaryan, S. Stiller, M. Main-Knorn, C. Nendel, M. Ryo, Ten deep learning techniques to address small data problems with remote sensing. Int. j. Appl. Earth Obs. Geoinf. 125, 1-17 (2023) https://doi.org/10.1016/j.jag.2023.103569 [Google Scholar]
- Z. Karoly, J. Szepvolgyi, Plasma spheroidization of ceramic particles. Chem. Eng. Process. 44, 221-224 (2004) 10.1016/j.cep.2004.02.015 [Google Scholar]
- Tekna, Teksphero-15: Plasma Powder Spheroidization. (2024) 2025; Available from: https://www.tekna.com/spheroidization-systems-teksphero-15. [Google Scholar]
- J.-H. Oh, S.H. Gwon, T.-H. Kim, J.-Y. Sun, S. Choi, Synthesis of titanium boride nanoparticles and fabrication of flexible material for radiation shielding. Curr. Appl. Phys. 31, 151-157 (2021) https://doi.org/10.1016/j.cap.2021.08.009 [Google Scholar]
- H.A. Gabbar, M. Aboughaly, V. Damideh, I. Hassen, RF-ICP Thermal Plasma for Thermoplastic Waste Pyrolysis Process with High Conversion Yield and Tar Elimination. Processes. 8, 1-15 (2020) https://doi.org/10.3390/pr8030281 [Google Scholar]
- N.Y.M. Gonzalez, M.E. Morsli, P. Proulx, Production of Nanoparticles in Thermal Plasmas: A Model Including Evaporation, Nucleation, Condensation, and Fractal Aggregation. J. Therm. Spray Technol. 17, 533-550 (2008) https://doi.org/10.1007/s11666-008-9209-x [Google Scholar]
- H. Bahouh, S. Rebiai, D. Rochette, D. Vacher, M. Dudeck, Modelling of an inductively coupled plasma torch with argon at atmospheric pressure. Phys. Scr. 014008, 1-4 (2014) https://doi.org/10.1088/0031-8949/2014/T161/014008 [Google Scholar]
- V. Frolov, D. Ivanov, V. Sosnin, Numerical simulation of high power RF-RF hybrid plasma torch, in Proceedings of the International Scientific Electric Power Conference. 2019. St. Petersburg, Russia: IOP Conf. Ser.: Mater. Sci. Eng. (2019) [Google Scholar]
- D.V. Ivanov, S.G. Zverev, Mathematical Simulation of Processes in ICP/RF Plasma Torch for Plasma Chemical Reactions. IEEE Trans. Plasma Sci. 45, 3125-3129 (2017) https://doi.org/10.1109/TPS.2017.2773140 [Google Scholar]
- K.J. Mbwebwe, A. Kolesnikov, I.J. Van der Walt, H. Bissett, Computational fluid dynamics evaluation of conditions before impact of particles in plasma spraying process. Suid-Afrik. tydskr. nat.wet. tegnol. 40, 16-21 (2021) https://doi.org/10.36303/SATNT.2021cosaami.04 [Google Scholar]
- P. Lyu, M. Lai, Y. Song, Z. Xue, F. Fang, Sub-nanometer finishing of polycrystalline tin by inductively coupled plasma-assisted cutting. Front. Mech. Eng. 2023. 18, 1-17 (2023) https://doi.org.10.1007/s11465-023-0751-5 [Google Scholar]
- W.A. Seya, A. Kolesnikov, I.J. Van der Walt, H. Bissett, Impact of heat transfer on spheroidization of titanium alloys, in Proceedings of the Conference of the South African Advanced Materials Initiative. 2021. Virtual (2021) [Google Scholar]
- Z. Hao, et al., Preparation of spherical Ti-6Al-4V powder by RF induction plasma spheroidization combined with spray granulation. Powder Technol. 387, 88-94 (2021) https://doi.org/10.1016/j.powtec.2021.04.021 [Google Scholar]
- N.M. Dignard, M.I. Boulos, Powder Spheroidization Using Induction Plasma Technology, in Proceedings of the International Thermal Spray Conference. 2000. Montreal, Quebec, Canada: ASM Thermal Spray Society (2000) [Google Scholar]
- L.A.C.D. Filippis, L.M. Serio, F. Facchini, G. Mummolo, ANN Modelling to Optimize Manufacturing Process, in Advanced Applications for Artificial Neural Networks, A.E. Shahat, Editor. p. 201-225. (2018) [Google Scholar]
- M. Leparoux, M. Loher, C. Schreuders, S. Siegmann, Neural network modelling of the inductively coupled RF plasma synthesis of silicon nanoparticles. Powder Technol. 185, 109-115 (2008) https://doi.org/10.1016/j.powtec.2007.10.004 [Google Scholar]
- K. Premlall, L. Koech, D. Faurie, Sorption capacity evaluation of industrial flue gas mixture using South African coal seams: Conventional and ANN modelling. Unconv. Resour. 6, 1-13 (2025) https://doi.org/10.1016/j.uncres.2025.100168 [Google Scholar]
- I. Sadrehaghighi, Artificial Neural Networks (ANNs) Applied as CFD Optimization Techniques, in CFD Open Series. p. 1-89. (2021) [Google Scholar]
- V.V. Pozevalkin, I.V. Parfenov, A.N. Polyakov, Approximation of machine tool experimental thermal characteristics by neural network. J. Phys. Conf. Ser. 1399, 1-7 (2019) https://doi.org/10.1088/1742-6596/1399/4/04418 [Google Scholar]
- S. Keaveney, A. Shmeliov, V. Nicolosi, D.P. Dowling, Investigation of process by-products during the Selective Laser Melting of Ti6Al4V. Addit. Manuf. 36, (2020) https://doi.org/10.1016/j.addma.2020.101514 [Google Scholar]
- H. Zhu, X. Li, Q. Chen, Three-Dimensional Simulation and Experimental Investigation on Spheroidization of Stainless Steel Powders Using Radio Frequency Thermal Plasma. J. Mater. Eng. Perform. 31, 6606-6616 (2022) https://doi.org/10.1007/s11665-022-06714-7 [Google Scholar]
- L.-S. Lin, Y.-S. Lin, D.-C. Li, Y.-H. Liu, Improved learning performance for small datasets in high dimensions by new dual-net model for non-linear interpolation virtual sample generation. Decis. Support Syst. 172, 113996 (2023) https://doi.org/10.1016/j.dss.2023.113996 [Google Scholar]
- T. Linjordet, K. Balog, Impact of Training Dataset Size on Neural Answer Selection Models, in Advances in Information Retrieval. p. 828-835. (2019) [Google Scholar]
- Himmelblau, D.M., Accounts of Experiences in the Application of Artificial Neural Networks in Chemical Engineering. Ind. Eng. Chem. Res. 47, 5782-5796 (2008) [Google Scholar]
- S. Chikosha, et al., Spheroidization of Stainless Steel Powder for Additive Manufacturing. Metals. 11, 1-15 (2021) https://doi.org/10.3390/met11071081 [Google Scholar]
- H. Bissett, I.J.v.d. Walt, Metal and alloy spheroidization for the Advanced Metals Initiative of South Africa, using high-temperature radio frequency plasmas. J. South. Afr. Inst. Min. Metall. 117, 975-980 (2017) https://doi.org/10.17159/2411-9717/2017/v117n10a8 [Google Scholar]
- J.-S. Nam, E. Park, J.-H. Seo, Numerical Analysis of Radio-Frequency Inductively Coupled Plasma Spheroidization of Titanium Metal Powder Under Single Particle and Dense Loading Conditions. Met. Mater. Int., 1-10 (2019) https://doi.org/10.1007/s12540-019-00348-6 [Google Scholar]
- X.-P. Liu, K.-S. Wang, P. Hu, Q. Chen, A.A. Volinsky, Spheroidization of molybdenum powder by radio frequency thermal plasma. Int. J. Miner. Metall. Mater. 22, 1212-1218 (2015) https://doi.org/10.1007/s12613-015-1187-7 [Google Scholar]
- S. Kumar, V. Selvarajan, P.V.A Padmanabhan, S.P. Sreekumar, Spheroidization of metal and ceramic powders in thermal plasma jet: Comparison between experimental results and theoretical estimation. J. Mater. Process. Technol. 176, 87-94 (2006) https://doi.org/10.1016/j.jmatprotec.2006.02.023 [Google Scholar]
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