  In this work, a modular approach is introduced to select the most important
eigenmodes for each component of a composed structural dynamics system to
obtain the required accuracy of the reduced-order assembly model. To enable the
use of models of complex (structural) dynamical systems in engineering
practice, e.g., in a design, optimization and/or control context, the
complexity of the models needs to be reduced. When the model consist of an
assembly of multiple interconnected structural components, component mode
synthesis is often the preferred model reduction method. The standard approach
to component mode synthesis for such system is to select the eigenmodes of a
component that are most important to accurately model the dynamic behavior of
this component in a certain frequency range of interest. However, often, a more
relevant goal is to obtain, in this frequency range, an accurate model of the
assembly. In the proposed approach, accuracy requirements on the level of the
assembly are translated to accuracy requirements on component level, by
employing techniques from the field of systems and control. With these
component-level requirements, the eigenmodes that are most important to
accurately model the dynamic behavior of the assembly can be selected in a
modular fashion. We demonstrate with two structural dynamics benchmark systems
that this method based on assembly accuracy allows for a computationally
efficient selection of eigenmodes that 1) guarantees satisfaction of the
assembly accuracy requirements and 2) results in most cases in reduced-order
models of significantly lower order with respect to the industrial standard
approach in which component eigenmodes are selected using a frequency
criterion.
