Towards virtual forming and AI

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RS 2022 Implicit material modelling using AI techniques and big data generation Rúben Lourenço Supervisory team: A. Andrade-Campos, Pétia Georgieva Doctoral Programme in Mechanical Engineering TEMA – Centre for Mechanical Technology and Automation

Engineering

Towards virtual forming and AI
Implicit material modelling using AI techniques
and big data generation
Rúben Lourenço
Supervisory team: A. Andrade-Campos, Pétia Georgieva
Doctoral Programme in Mechanical Engineering
TEMA – Centre for Mechanical Technology and Automation

Constitutive models
• Parameters computed/calibrated via experimentation
• Complex models >> high number of parameters:
• Extensive experimental campaigns
• Expensive
• Time-consuming
• Accuracy constrains:
• phenomenological approach
• explicit formulation
• set of experiments used to calibrate
• Incompatibilities with DIC

Implicit constitutive modelling
Virtual Fields Method Artificial Neural Network

Scientific contribution
• Journal article:
a) R. Lourenço, A. Andrade-Campos, and P. Georgieva, “The Use of Machine-Learning Techniques in Material Constitutive
Modelling for Metal Forming Processes,” Metals, vol. 12, no. 3. MDPI AG, p. 427, Feb. 28, 2022 [Online]. Available:
http://dx.doi.org/10.3390/met12030427
• Conference articles:
a) Rúben Lourenço, António Andrade-Campos, Pétia Georgieva. "The Virtual Fields Method to indirectly train artificial neural
networks for implicit constitutive modelling". ESAFORM 2022 - 25th International Conference on Material Forming, Braga,
2022. (Accepted for publication)
b) A. Andrade-Campos, N. Bastos, M. Conde, M. Gonçalves, J. Henriques, R. M. B. Lourenço, J. M. P. Martins, M.G. Oliveira,
P.A. Prates, L. Rumor. IOP Conference Series: Materials Science and Engineering, vol. 1238, no. 1. IOP Publishing, p.
012059, May 01, 2022 [Online]. Available: http://dx.doi.org/10.1088/1757-899X/1238/1/012059
• Conference posters:
a) Rúben Lourenço, A. Andrade-Campos, Georgieva, Pétia. "Coupling the Virtual Fields Method with ANNs for Implicit
Constitutive Modelling". FCT - Encontro Ciência 2022, Lisbon, 2022.
• Oral communications:
a) “Towards virtual forming and design: implicit material modelling using AI techniques and big data generation”, Research
Summit 2021, 9th July 2021, University of Aveiro, Aveiro, Portugal
b) “The Virtual Fields Method to indirectly train artificial neural networks for implicit constitutive modelling”, ESAFORM 2022 -
25th International Conference on Material Forming, 27th-29th April 2022, Braga, Portugal

EUROPEAN UNION
European Social Fund
Rúben Lourenço acknowledges the Portuguese Foundation for Science and Technology (FCT) for the financial support provided through the grant 2020.05279.BD,
co-financed by the European Social Fund, through the Regional Operational Programme CENTRO 2020.
The authors also gratefully acknowledge the financial support of the Portuguese Foundation for Science and Technology (FCT) under the projects CENTRO-01-
0145-FEDER-029713, POCI-01-0145-FEDER-031243 and POCI-01-0145-FEDER-030592 by UE/FEDER through the programs CENTRO 2020 and COMPETE
2020, and UIDB/00481/2020 and UIDP/00481/2020-FCT under CENTRO-01-0145-FEDER-022083.
This project also supported by the Research Fund for Coal and Steel under grant agreement No 888153.
Thank you for your attention!

ESAFORM 2022 25th International Conference on Material Forming R. Lourenço1,a, A. Andrade-Campos1,b, P. Georgieva2,c 1Dept. of Mechanical Engineering Centre for Mechanical Technology and Automation, University of Aveiro, Portugal 2Dept. of Electronics Telecommunications and Informatics Institute of Electronics and Informatics Engineering, University of Aveiro, Portugal a rubenl@ua.pt, bgilac@ua.pt, cpetia@ua.pt 27-29 April, Braga, Portugal

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