A hybrid two-stage Model Order Reduction framework for large-scale structural problems

This paper presents a hybrid two-stage Model Order Reduction framework tailored for largescale industrial finite element problems in structural dynamics. The proposed approach combines a preliminary reduction step using a Component Mode Synthesis (CMS) method with a second reduction stage employing a state-space based approach. By leveraging the complementary strengths of these families of techniques, the framework ensures accurate preservation of input/output behavior, making it particularly well-suited for applications like transfer path analysis and control system design. For the CMS stage, the study investigates the classical Craig-Bampton method and the Enhanced Craig-Bampton technique, introducing an alternative primal assembly strategy to enable the use of the latter method with separate finite element models of substructures. The state-space reduction stage explores both modal truncation and balanced truncation, with the latter demonstrating superior performance in representing critical input/output dynamics. This hybrid scheme is designed for industrial scenarios requiring reduced-order models of large-scale structures as a prodromal step for controller design or transfer path analysis. The hybrid framework is finally applied to a large-scale finite element model derived from the European Space Agency's Micro Vibration Measurement System facility, showcasing its effectiveness and practical applicability.