Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-26T16:54:24.714Z Has data issue: false hasContentIssue false

B-SPLINE BASED METAMODEL OF THE THERMAL ANALYSIS OF THE WIRE ARC ADDITIVE MANUFACTURING PROCESS

Published online by Cambridge University Press:  19 June 2023

Mathilde Zani*
Affiliation:
Arts et Métiers Institute of Technology, Université de Bordeaux, CNRS, INRA, Bordeaux INP, HESAM Université, I2M UMR, F-33405 Talence, France;
Marco Montemurro
Affiliation:
Arts et Métiers Institute of Technology, Université de Bordeaux, CNRS, INRA, Bordeaux INP, HESAM Université, I2M UMR, F-33405 Talence, France;
Enrico Panettieri
Affiliation:
Arts et Métiers Institute of Technology, Université de Bordeaux, CNRS, INRA, Bordeaux INP, HESAM Université, I2M UMR, F-33405 Talence, France;
Philippe Marin
Affiliation:
Grenoble Alpes - Laboratoire G-SCOP UMR 5272, F-38000 Grenoble, France
*
Zani, Mathilde, I2M laboratory, France, mathilde.zani@ensam.eu

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Among additive manufacturing processes, wire arc additive manufacturing (WAAM) is one of the most promising methods for manufacturing complex near-net-shape parts, as it allows the layer-by-layer deposition of welded material at a high deposition rate. However, this technology is highly dependent on deposition conditions and thermomechanical phenomena during the process. Therefore, process simulation could be used to analyse the effects of different deposition parameters on the thermomechanical results to optimise the process. However, as the computing time required for this study may become prohibitive, a dedicated strategy is needed to reduce it while maintaining a good level of accuracy. In this study, only the thermal analysis of the process is investigated. An efficient metamodel based on B-spline entities is developed to emulate the thermal response of the WAAM process when building a mild steel four-layer wall structure. Thanks to B-spline entities, the temperature profile at different locations is approximated as a function of a subset of deposition parameters of WAAM process, and the results are compared with the simulated temperature profile resulting from a validation dataset.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Audoux, Y., Montemurro, M. and Pailhes, J. (2020a), “A metamodel based on non-uniform rational basis spline hyper-surfaces for optimisation of composite structures”, Composite Structures, Vol. 247, p. 112439, https://doi.org/10.1016/j.compstruct.2020.112439.CrossRefGoogle Scholar
Audoux, Y., Montemurro, M. and Pailhes, J. (2020b), “Non-uniform rational basis spline hyper-surfaces for metamodelling”, Computer Methods in Applied Mechanics and Engineering, Vol. 364, p. 112918, https://doi.org/10.1016/j.cma.2020.112918.CrossRefGoogle Scholar
Baillargeon, S. (2005), “Le krigeage: revue de la theorie et application a l'interpolation spatiale de donnees de precipitations, memoire presente pour l'obtention du grade de maitre es sciences (m. sc.)”, Universite de Laval, Faculte des Sciences et de Genie, Quebec.Google Scholar
Cambon, C. (2021), Etude thermomecanique du procede de fabrication metallique arc-fil: approche numerique et experimentale, Theses, Universite Montpellier.Google Scholar
Chergui, M.A. (2021), Simulation Based deposition Strategies Evaluation and Optimization in Wire Arc Additive Manufacturing, Theses, Universite Grenoble Alpes.Google Scholar
Costa, G., Montemurro, M. and Pailhes, J. (2021), “Nurbs hyper-surfaces for 3d topology optimization problems”, Mechanics of Advanced Materials and Structures, Vol. 28 No. 7, pp. 665684, https://doi.org/10.1080/15376494.2019.1582826.CrossRefGoogle Scholar
Ding, D., Pan, Z., Cuiuri, D. and Li, H. (2015), “Wire-feed additive manufacturing of metal components: technologies, developments and future interests”, The International Journal of Advanced Manufacturing Technology, Vol. 81, pp. 465481, https://doi.org/10.1007/s00170-015-7077-3.CrossRefGoogle Scholar
Ding, J., Colegrove, P., Mehnen, J., Ganguly, S., Sequeira Almeida, P., Wang, F. and Williams, S. (2011), “Thermo- mechanical analysis of wire and arc additive layer manufacturing process on large multi-layer parts”, Computational Materials Science, Vol. 50 No. 12, pp. 33153322, https://doi.org/10.1016/jxommatsci.2011.06.023.CrossRefGoogle Scholar
Goldak, J., Chakravarti, A. and Bibby, M. (1984), “A new finite element model for welding heat sources”, Metallurgical transactions B, Vol. 15 No. 2, pp. 299305, https://doi.org/10.1007/BF02667333.CrossRefGoogle Scholar
Michaleris, P. (2014), “Modeling metal deposition in heat transfer analyses of additive manufacturing processes”, Finite Elements in Analysis and Design, Vol. 86, pp. 5160, https://doi.org/10.1016/jj.finel.2014.04.003.CrossRefGoogle Scholar
Michaleris, P., DeBiccari, A. et al. (1997), “Prediction of welding distortion”, Welding Journal-Including Welding Research Supplement, Vol. 76 No. 4, p. 172s.Google Scholar
Montemurro, M. and Catapano, A. (2019), “A general b-spline surfaces theoretical framework for optimisation of variable angle-tow laminates”, Composite Structures, Vol. 209, pp. 561578, https://doi.org/10.1016/j.compstruct.2018.10.094.CrossRefGoogle Scholar
Montevecchi, F., Venturini, G., Grossi, N., Scippa, A. and Campatelli, G. (2017), “Finite element mesh coarsening for effective distortion prediction in wire arc additive manufacturing”, Additive Manufacturing, Vol. 18, pp. 145155, https://doi.org/10.1016/jj.addma.2017.10.010.CrossRefGoogle Scholar
Montevecchi, F., Venturini, G., Scippa, A. and Campatelli, G. (2016), “Finite element modelling of wire-arc-additive-manufacturing process”, Procedia Cirp, Vol. 55, pp. 109114, https://doi.org/10.1016Zj.procir.2016.08.024.CrossRefGoogle Scholar
Piegl, L. and Tiller, W. (1996), The NURBS book, Springer Science & Business Media, https://doi.org/10.1007/978-3-642-97385-7.Google Scholar
Querard, V. (2019), Realisation de pieces aeronautiques de grandes dimensions par fabrication additive WAAM, Theses, Ecole centrale de Nantes.Google Scholar
Rodrigues, T.A., Duarte, V., Miranda, R.M., Santos, T.G. and Oliveira, J.P. (2019), “Current status and perspectives on wire and arc additive manufacturing (waam)”, Materials, Vol. 12 No. 7, https://doi.org/10.3390/ma12071121.CrossRefGoogle ScholarPubMed
Smith, M. (2020), “Abaqus/standard user's manual, version 6.20”,.Google Scholar
Song, X., Feih, S., Zhai, W., Sun, C.N., Li, F., Maiti, R., Wei, J., Yang, Y., Oancea, V., Brandt, L.R. et al. (2020), “Advances in additive manufacturing process simulation: Residual stresses and distortion predictions in complex metallic components”, Materials & Design, Vol. 193, p. 108779.CrossRefGoogle Scholar
Turner, C.J. (2005), HyPerModels: hyperdimensional performance models for engineering design, The University of Texas at Austin.Google Scholar
Wang, L., Chen, X., Kang, S., Deng, X. and Jin, R. (2020), “Meta-modeling of high-fidelity fea simulation for efficient product and process design in additive manufacturing”, Additive Manufacturing, Vol. 35, p. 101211, https://doi.org/10.1016/jj.addma.2020.101211.CrossRefGoogle Scholar
Wu, B., Pan, Z., Ding, D., Cuiuri, D., Li, H., Xu, J. and Norrish, J. (2018), “A review of the wire arc additive manufacturing of metals: properties, defects and quality improvement”, Journal of Manufacturing Processes, Vol. 35, pp. 127139, https://doi.org/10.1016/jjmapro.2018.08.001.CrossRefGoogle Scholar