The estimation of modal parameters from a set of noisy measured data is a highly
judgmental task, with user expertise playing a significant role in distinguishing between …

Simulations and parametric studies of large-scale models can be facilitated by high-fidelity
reduced order models (ROMs). One of the methods to obtain these ROMs, which is of …

Uncertainty induced by our incomplete state of knowledge about engineering systems and
their surrounding environment give rise to challenging problems in the process of building …

This paper presents an approach to obtain reduced-order models for power networks
involving power electronic converters (PEC) via the frequency-domain balanced realizations …

Integration of complex models of wind turbine blades in aeroelastic simulations places an
untenable demand on computational resources and, hence, means of speed-up become …

In this chapter, we give an overview of some of the most common reduction techniques
based on substructuring. Although all techniques follow a similar approach, the main …

The estimation of modal parameters from a set of measured data is a highly judgmental task,
with user expertise playing a significant role for distinguishing between physical and …

One of the most important limiting factors in the study of the dynamic response of a structure
is represented by the computational effort. A comprehensive dynamic analysis requires …

Abstract The ESA Micro Vibrations Measurement System (MVMS) is a facility conceived to
perform measurements of the micro-vibrations generated by spacecraft components as well …

Bayesian model updating provides a rigorous framework to account for uncertainty induced
by lack of knowledge about engineering systems in their respective mathematical models …