This book provides a basic introduction to reduced basis (RB) methods for problems
involving the repeated solution of partial differential equations (PDEs) arising from …

During the past decade, reduced order modeling has attracted growing interest in
computational science and engineering. It now plays an important role in delivering high …

Alfio Quarteroni Third Edition Page 1 MS&A – Modeling, Simulation and Applications 16
Numerical Models for Di erential Problems Alfio Quarteroni Third Edition Page 2 MS&A Volume …

This is a book on Optimal Control Problems (OCPs): how to formulate them, how to set up a
suitable mathematical framework for their analysis, how to approximate them numerically …

Parametric optimal control problems governed by partial differential equations (PDEs) are
widely found in scientific and engineering applications. Traditional grid-based numerical …

In this work we propose an application of physics informed supervised learning strategies to
parametric partial differential equations. Indeed, even if the latter are indisputably useful in …

In this work we review a reduced basis method for the solution of uncertainty quantification
problems. Based on the basic setting of an elliptic partial differential equation with random …

Galerkin reduced order models (ROMs), eg, based on proper orthogonal decomposition
(POD) or reduced basis methods, have achieved significant success in the numerical …

In this work we propose reduced order methods as a suitable approach to face parametrized
optimal control problems governed by partial differential equations, with applications in …

This work deals with optimal control problems as a strategy to drive bifurcating solution of
nonlinear parametrized partial differential equations towards a desired branch. Indeed, for …