This paper proposed a new methodology to address the key problem in model order
reduction methods of setting random values of lower and upper bounds and initial values of …

This contribution combines a low-rank matrix approximation through Singular Value
Decomposition (SVD) with second-order Krylov subspace-based Model Order Reduction …

For the purpose of high-fidelity aircraft cabin noise simulations during early design phases,
we study three efficient solving approaches for the fully coupled finite element model of an …

Parametric model order reduction techniques have seen significant applications in the field
of multi-query problems like uncertainty quantification, optimization and sensitivity analysis …

The steady advancements in computer technology as well as modeling techniques allow
simulation models often used in engineering applications, such as design and optimization …

This contribution presents a combined framework to perform parametric surrogate modeling
of vibroacoustic problems that enables efficient training of large-scale problems. The …