Novel Aerospace Architectures Made Possible by Forming Simulation

In the aerospace industry lightweight design in combination with fast and reliable manufacturing processes are key components to defend the leading position in the worldwide competition. In this frame it is an overall goal to reduce the number of process steps in order to produce parts for an aircraft to its minimum. Integral design is one way to cope with this goal but on the other hand raises a lot of problems that may occur in manufacturing or final assembly. To be able to predict potential bottlenecks or drawbacks in certain designs, finite element simulation can be helpful. Especially if it’s an early design phase and new material concepts are taking into account, the virtual manufacturing, done by finite element simulations is the only way to predict real life behavior. In this paper we will focus on the use and benefit of finite element simulations in the early design phase of very huge integral parts of a next generation aircraft. The parts do belong to the nose fuselage structure and will be manufactured from a 100-150mm thick AlMgSc plate. Two different manufacturing routes will be covered by simulation. 1. Hot forming the plates at around 300°C and machining 2. Explosive forming of the plates and machining For both routes, a complete simulation chain from forming over springback to final machining is developed and presented in detail. Special care is taken on a fully automated workflow from one step to the other to allow an easy adaptation to other part geometries in the future. To ensure a high quality of the simulation results all process steps of the hot forming route are simulated with ABAQUS implicit and approved constitutive laws. The explosive forming manufacturing route is simulated using an Eulerian-Lagrange approach taken into account the various possibilities of detonation loading. To validate the simulation results to real measurements, a scaled down version of one of the parts is manufactured in reality and each process step is compared with the simulation result.