For many applications, the projected quantities arising from projectionbased model order
reduction (PMOR) must be repeatedly recomputed due to, for example, nonlinearities or …

Numerical simulation of parametrized differential equations is of crucial importance in the
study of real-world phenomena in applied science and engineering. Computational methods …

This book results from a course developed by the author and reflects both his own and
collaborative research regarding the development and implementation of uncertainty …

A quadratic approximation manifold is presented for performing nonlinear, projection-based,
model order reduction (PMOR). It constitutes a departure from the traditional affine subspace …

This paper presents a novel non-intrusive surrogate modeling scheme based on deep
learning for predictive modeling of complex systems, described by parametrized time …

Inspired by our previous work on a quadratic approximation manifold [1], we propose in this
paper a computationally tractable approach for combining a projection-based reduced-order …

We present a general framework for the dimensional reduction, in terms of number of
degrees of freedom as well as number of integration points (“hyper-reduction”), of nonlinear …

In the literature on nonlinear projection-based model order reduction for computational fluid
dynamics problems, it is often claimed that due to modal truncation, a projection-based …

Turbine bladed disks or blisks, which constitute critical components of most modern
turbomachinery, are known for their complex vibratory behavior. The nonlinear dynamics …

This paper describes the use of a quadratic manifold for the model order reduction of
structural dynamics problems featuring geometric nonlinearities. The manifold is tangent to a …