This chapter presents an overview of Model Order Reduction–a new paradigm in the field of
simulationbased engineering sciences, and one that can tackle the challenges and leverage …

This chapter presents an overview of model order reduction–a new paradigm in the field of
simulation‐based engineering sciences, and one that can tackle the challenges and …

Research in diffusion phenomena was started by brilliant scientists in the nineteenth
century, and by the twentieth century, this phenomenon became widespread in many areas …

The computational cost of parametric studies currently represents the major limitation to the
application of simulation-based engineering techniques in a daily industrial environment …

In this paper, a deep learning based framework has been developed to predict
hydrodynamic forces on a mantle-undulated propulsion robot (MUPRo). A multiple proper …

The flow control constitutes a challenging research topic with numerous applications in
aeronautics, aerodynamics, fluid mechanics, civil engineering, and so on. Due to the use of …

In this paper, flow reconstruction accuracy and flow prediction capability of discontinuous
transonic flow field by means of proper orthogonal decomposition (POD) method is studied …

A reduced order model technique is presented to perform the parametric Noise, Vibration
and Harshness (NVH) study of a vehicle body-in-white (BIW) structure characterized by …

Abstract Design optimization and uncertainty quantification, among other applications of
industrial interest, require fast or multiple queries of some parametric model. The Proper …

The pressure term which appears in the ROM (reduced order model) associated to the
incompressible Navier–Stokes equations, in particular for the shear flows, plays an …