[en] The response of polymeric materials can be represented using complex finite-strain visco-elastic visco-plastic material models. Such a model requires the identification of tens of parameters in order to remain accurate for a wide range of strain rates and stress states, the response in compression being different than in tension. A complex experimental campaign involving dynamic mechanical analysis (DMA), and compressive and tensile cyclic loading at different strain rates is thus required.
Besides, when considering lattice structures obtained by additive manufacturing, the struts response is not similar to the macro-bulk material response. Because a complex experimental campaign cannot be conducted at the level of the struts, the parameters identification also needs to be conducted at the level of the lattice response.
However, when performing the parameters identification using these different loading cases, a unique set of parameters cannot usually reproduce all the experimental tests because of the model limitations and errors, in particular when considering nonlinear responses. Besides, the data are inevitably entailed by experimental errors. These difficulties can be circumvented by considering a Bayesian Inference (BI) process. In this presentation we consider experimental tests conducted at different scales on polyamide lattices in order to infer the model parameters of a complex finite-strain visco-elastic visco-plastic material model.
Research center :
A&M - Aérospatiale et Mécanique - ULiège
Mechanical engineering Mechanical engineering
Author, co-author :
Wu, Ling ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > Computational & Multiscale Mechanics of Materials (CM3)
Cobian, Lucia; IMDEA Materials Institute
Monclus, Miguel A.; IMDEA Materials Institute
Segurado, Javier; IMDEA Materials Institute ; UPM
Hössinger-Kalteis, Anna; Johannes Kepler University Linz
Major, Zoltan; Johannes Kepler University Linz
Karayagiz, Fatma; cirp GmbH
Lück; Thomas; cirp GmbH
Noels, Ludovic ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > Computational & Multiscale Mechanics of Materials (CM3)
Bayesian Inference of Visco-Elastic Visco-Plastic Material Model Parameters for SLS-printed polyamide lattices
Publication date :
13 June 2023
Event name :
5th International Conference on Uncertainty Quantification in Computational Science and Engineering (UNCECOMP2023)
Event organizer :
Event place :
Event date :
12-14 June 2023
European Projects :
H2020 - 862015 - MOAMMM - Multi-scale Optimisation for Additive Manufacturing of fatigue resistant shock-absorbing MetaMaterials
Name of the research project :
Multiscale Optimisation for Additive Manufacturing of fatigue resistant shock-absorbing MetaMaterials (MOAMMM)
EC - European Commission [BE] Union Européenne [BE]
Funding number :
Funding text :
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 862015.