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Optimization in Composite Materials modelling and simulation

Author: 
Gherard Goldbeck | Goldbeck Consulting, Danilo Di Stefano | ESTECO
Year: 
2012

 

Polymer and two fillers of different particle size

Composite materials are gaining importance in a huge range of applications. Among others, reinforced plastics replace metal designs and are used in many industries including automotive and aerospace, targeting the request to build lightweight structures, a common driver for these industries. However, they exhibit highly complex material behaviours imposing the assessment of various part performances for the composite design. Covering performances means to describe properly the stiffness and failure of composites under static and dynamic load. Also fatigue properties simulation meets increasing interest in order to predict the life of the final design. The complexity of the performance assessment of composite parts is due to the influence of the underlying microstructure of the composite material. The microstructure causes anisotropic and locally different material behaviour. A strong dependency on the processing conditions is observed. Commonly, the material response is non-linear as well as temperature and strain rate-dependent. Hence each composite exhibits its own challenging behaviour and needs individual treatment for its description in a computational approach.

 

For advanced studies, such as those dealing with material anisotropy, temperature and strain rate dependency or creep, the setup of coupled analyses can become challenging. These are efficiently designed with modeFRONTIER, the integration platform for multi-objective optimization, multidisciplinary design process automation, and analytic decision making. Indeed, modeFRONTIER together with DIGIMAT, a non-linear multi-scale material and structure modelling platform, offers parametric optimization at different levels. First it drives the modulation of the required material models towards a desired optimum macroscopic response, as illustrated in the present article for the composition of a multiphase polymer composite. Secondly, it enables the fitting of material models to experimental data. Furthermore, it could tackle the parameterization of the coupled analyzes such as structural models. Finally, it could bring the processing step into the loop so that the processing parameters themselves become design variables influencing the performance of the final part. The link between DIGIMAT and modeFRONTIER thus supports collaboration and faster development times, fostering the integration of computational material engineering and design.

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