A virtual lab for Ni/PU hybrid foams: stochastic micromechanical identification and efficient numerical simulations

• Applicant: Professorin Dr.-Ing. Anne Jung
• Subject Area: Mechanics ; Mechanical Properties of Metallic Materials and their Microstructural Origins
• Term: from 2017 to 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 338131106

The main goal of the project is a virtual lab for open-cell metal foams that can predict macroscopic mechanical responses and their variations, based on the mesoscopic and microscopic distributions of the geometrical and mechanical parameters. A discrete mesostructural model will act as the virtual lab. It will account for variations of the strut connectivity, variations of the strut dimensions and variations of the strut material parameters. The model developments and the experimental identification of the stochastic geometrical and material parameters will be performed for a recently developed Ni/PU hybrid foams, which are substantially cheaper than alternative open-cell hybrid metal foams.The innovations in the project largely focus on experimental techniques and stochastic parameter identification. The main innovations can clearly be distinguished in four sub-aims. First, an experimental procedure to measure forces as functions of local strain fields for individual struts, as well as for several pores. Second, a 3D beam model to represent the discrete mesostructure of metal foams will be developed. The beam model will serve as the virtual lab and will account for variations by employing a Monte Carlo based approach, in which numerous realisations of the stochastic parameters are made. Single struts will be represented by series of 1D beams. The 1D beam formulation will be geometrically nonlinear and able to predict the elastoplastic response of single struts. The full 3D beam model will furthermore be able to predict failure of individual struts and deal with strut-to-strut contact (beam-to-beam contact). Furthermore, an inverse modelling procedure using Bayesian Inference will be used to identify the distributions of the material parameters of single struts, when they are modelled by a series of beams. Bayesian Inference ensures a consistent approach to treat the material parameters as stochastic, and not deterministic, variables. Finally, the 3D beam model (i.e. the virtual lab) will be validated based on experimental results at the mesoscale (several pores). The strut connectivity and strut dimensions of the samples must be known in detail for this. Therefore, both factors must be expliciteöy determined.A successful project will result in a full 3D beam model able to account for stochastic effects in the foams structure to improve the prediction of the macroscopic foams behaviour by numerical simulations.

• DFG Programme: Research Grants
• International Connection: Luxembourg
• Partner Organisation: Fonds National de la Recherche
• Co-Investigator: Dr. Lars A.A. Beex