This paper revisits a new model reduction methodology based on the use of separated
representations, the so called Proper Generalized Decomposition—PGD. Space and time …

This chapter reviews techniques of model reduction of fluid dynamics systems. Fluid systems
are known to be difficult to reduce efficiently due to several reasons. First of all, they exhibit …

Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …

In the past, data in which science and engineering is based, was scarce and frequently
obtained by experiments proposed to verify a given hypothesis. Each experiment was able …

In this paper we are addressing a new paradigm in the field of simulation-based engineering
sciences (SBES) to face the challenges posed by current ICT technologies. Despite the …

The objective of this contribution is to present a unifying review on strain-driven
computational homogenization at finite strains, thereby elaborating on computational …

A digital twin can be defined as an adaptive model of a complex physical system. Recent
advances in computational pipelines, multiphysics solvers, artificial intelligence, big data …

This paper reviews the recent developments in the field of multiscale modelling of
heterogeneous materials with emphasis on homogenization methods and strain localization …

In this work, we introduce a consistent error estimator for numerical simulations performed
by means of the proper generalized decomposition (PGD) approximation. This estimator …

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 …