Computational fluid dynamics (CFD) models have been used for the simulation of urban
airflow and pollutant dispersion, due to their capability to capture different length scales and …

This work presents a nonintrusive projection-based model reduction approach for full
models based on time-dependent partial differential equations. Projection-based model …

We present a reduced basis technique for long-time integration of parametrized
incompressible turbulent flows. The new contributions are threefold. First, we propose a …

This paper, written as a tribute to Enrico Magenes, a giant that has kindly and warmly
supported generations of young researchers, introduces a generalization of the empirical …

The reduced basis approximation is a discretization method that can be implemented for
solving parameter-dependent problems in cases of many queries. In this work it is applied to …

Accurate error estimation is crucial in model order reduction, to obtain small reduced-order
models as well as to certify their accuracy when deployed in downstream applications such …

Abstract Computation Fluid Dynamics (CFD) simulation has become a routine design tool for
i) predicting accurately the thermal performances of electronics set ups and devices such as …

Reduced-order modeling (ROM) techniques involving physics are gaining importance due
to their ability to generate physically meaningful results swiftly and accurately. They are …

A novel reduced order model (ROM) for incompressible flows is developed by performing a
Galerkin projection based on a fully (space and time) discrete full order model (FOM) …

This work aims at investigating the use of reduced basis (RB) methods to diminish the cost of
numerical simulation of elastoplasticity problems arising from geotechnics modeling, and …