Model Order Reduction for Elastic Multibody Systems with Fast Rotating Flexible Bodies

The dynamical behavior of Elastic Multibody Systems (EMBS) is often analyzed using virtual prototypes described by high-dimensional systems of differential equations. Model Order Reduction (MOR) is a key step to permit efficient system evaluations by approximating the full system with a reduced order surrogate model. It is one challenge in MOR of EMBS, to describe the dynamics induced through the coupling of bodies in the reduced system. In this contribution, a workflow for the reduction of EMBS with fast rotating bodies is presented. The rotation causes a change of dynamical behavior due to inertia forces and, therefore, cannot be neglected. In the scope of this work a linear description of rotating bodies with constant angular velocity is given. Different projection-based MOR techniques are compared and applied to an industrial model of a helicopter with rotating rotor. For this purpose, a short introduction on modeling of EMBS and MOR is given. Substructured reduction is then contrasted to the reduction of the coupled system for modal reduction techniques, moment matching based on Krylov subspaces, and Proper Orthogonal Decomposition. The approximation errors of the reduced systems are compared in frequency domain. It is shown that rotation-dependent terms are essential to describe the dynamic behavior of the system correctly. Reduced models with low approximation errors and large speed-up are obtained with substructured Proper Orthogonal Decomposition and outperform the standard techniques modal truncation and Craig-Bampton reduction.