Friction stir welding and processing enabled the creation of stronger joints, novel ultrafine-
grained metals, new metal matrix composites, and multifunctional surfaces at user-defined …

This paper aims at reviewing nonlinear methods for model order reduction in structures with
geometric nonlinearity, with a special emphasis on the techniques based on invariant …

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 …

The curse-of-dimensionality taxes computational resources heavily with exponentially
increasing computational cost as the dimension increases. This poses great challenges in …

Aerodynamic modeling plays an important role in multiphysics and design problems, in
addition to experiment and numerical simulation, due to its low-dimensional representation …

In many situations across computational science and engineering, multiple computational
models are available that describe a system of interest. These different models have varying …

This paper considers the creation of parametric surrogate models for applications in science
and engineering where the goal is to predict high-dimensional output quantities of interest …

A reduced basis method based on a physics-informed machine learning framework is
developed for efficient reduced-order modeling of parametrized partial differential equations …

Featured Application This work was elaborated in the frame of a collaborative innovation
project named CyberFactory# 1 which aims at enhancing optimization and resilience of …

Engineering is evolving in the same way than society is doing. Nowadays, data is acquiring
a prominence never imagined. In the past, in the domain of materials, processes and …