Join us on 31st March at 16:00 (CET)
In the research of lightweighting solutions, the use of CFRP has dramatically increased during the last two decades in aeronautics and aerospace industries. However, designers are still facing the challenge to accelerate the insertion of new materials into the design. One of the main challenge concerns the reduction of the material screening and selection time which relies only on experimental procedure. Globally speaking, there is a need for material properties definition in a numerical form to meet design requirement and that allows to reduce cost and development time of new material by replacing manual tests with advanced simulation.
A comprehensive simulation process is then proposed and will be described. This process allows to define a complete test matrix in order to generate coupon strength for a given material system in standard testing conditions. Several aspects have to be considered:
- The first concerns the material modeling. This modeling combines micromechanics that derives through mean-field homogenization the composite properties from constituent properties and microstructure description. The post-failure behavior of the composite is also taken into account using a progressive failure method. In this context, the key ingredients of the modeling are the LARC03 damage initiation criteria, adapted damage propagation laws relying on physical measurements, a crack band method to mitigate the mesh sensitivity, the effect of residual stresses coming from the manufacturing and specific laws to add delamination prediction and propagation. Using this material modeling, coupon geometries and meshes for any layups are automatically generated for standard test configurations, then coupons strength is computed.
- A second aspect considers the possibility to insert some defects in a pristine coupon configuration to generate realistic coupon taking into account out-of-ply waviness or presence of porosity.
- Finally, the last aspect considers the material sensitivity to parameters variability with full Uncertainty Quantification Method to generate statistical results such a b-basis value.
Another aspect will describe also how such tools are integrated in the DIGIMAT Software package.