The project addresses the optimization of jointed components. Optimizing a component individually causes the risk that the jointed component and the connection itself are exposed to higher loading. This is especially critical if the joint component is a composite structure. In difference to metallic structures, composite structures fail at stress peak, which can be caused by a stiffness increase of the joint optimized component.

Within the project, methods will be developed which allow the simultaneous optimization of isotropic components, composite structures and their connection. Therein, the failure of the composite laminate as well as the failure of the connecting elements will be considered in the optimization. Connection types that will be considered are pointwise connections like rivet and bolts, as well as surface connections like bonding. Both types of connections will be considered as anisotropic.
For the optimization of isotropic components, topology optimization methods will be used, which provide structures with material only in areas where it contributes to the load bearing. For the optimization of the fiber composite laminate, two different approaches will be considered. In one approach, the thicknesses of the composite layer are varied, whereas the second approach is similar to topology optimization.

Both, the pointwise connections as well as the surface connections, will be modelled by spring elements which couple the connected components. This coupling is mesh independent, which allows to consider the position of the connection or its shape, respectively, as continuous design variables.
Finally, the developed methods will be embedded into an optimization with respect to fail-safety. Therein, a partial failure of the connection is considered and the remaining structure must be able to bear the applied load.
All gradients that are required for the simultaneous optimization are derived in the project and the potential of the method is demonstrated through examples.
 

• Contact: Olaf Ambrozkiewicz
• Duration: 01/2022-12/2023
• Funded by: DFG
• Individual funding