Nonlinear Mechanics for Composite Heterogeneous Structures

 Nonlinear Mechanics for Composite  Heterogeneous Structures

Nonlinear Mechanics for Composite  Heterogeneous Structures

Composites are found in every modern structure. The advent of additive manufacturing or 3D printing with various materials and the possibility to create graded composites and microstructures have pushed the limit of applications and require new analysis and design tools. Prediction of the mechanical behaviour, especially beyond linearity, becomes a challenging task. Established theories, like large displacements, plasticity, damage and contact mechanics,can still be used.

In several cases, plenty of experimental measurements are available while a clear application of a classical theoretical framework is questionable. A kind of interpolation from the available experimental data seems to be in right place. In other cases, the need for quick development of new materials and applications with reduced cost does now allow the execution of many experiments.

Therefore, fusion of classical computational mechanics and machine learning tools, the artificial neural networks being the most known of these, constitutes a modern tool of choice. Alternatively, new approaches utilize directly the available experimental data, mainly for the missing material constitutive law, within the non-linear incremental-iterative solution scheme.

From another point of view, classical micromechanical models and the prediction of the overall behaviour have been exploited mainly within the framework of linear homogenization. For more complex, non-linear behaviour, and under the presence of non-linear interfaces, new approaches are required.

The multi-scale or concurrent, FE2 computational homogenization tool has been proposed and proven to be an efficient technique for the study of composites. Unfortunately, it requires significant computational effort and is not directly available within commercial finite element codes.

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