A short review on model order reduction based on proper generalized decomposition
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 …
representations, the so called Proper Generalized Decomposition—PGD. Space and time …
Virtual, digital and hybrid twins: a new paradigm in data-based engineering and engineered data
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 …
a prominence never imagined. In the past, in the domain of materials, processes and …
Self-consistent clustering analysis: an efficient multi-scale scheme for inelastic heterogeneous materials
The discovery of efficient and accurate descriptions for the macroscopic behavior of
materials with complex microstructure is an outstanding challenge in mechanics of …
materials with complex microstructure is an outstanding challenge in mechanics of …
PGD-Based Computational Vademecum for Efficient Design, Optimization and Control
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 …
sciences (SBES) to face the challenges posed by current ICT technologies. Despite the …
Digital twins that learn and correct themselves
Digital twins can be defined as digital representations of physical entities that employ real‐
time data to enable understanding of the operating conditions of these entities. Here we …
time data to enable understanding of the operating conditions of these entities. Here we …
[PDF][PDF] Model order reduction
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 …
simulationbased engineering sciences, and one that can tackle the challenges and leverage …
An intelligent nonlinear meta element for elastoplastic continua: deep learning using a new Time-distributed Residual U-Net architecture
Substructuring is a model order reduction technique that accelerates the finite element
method in solid mechanics. In this improved hybrid substructuring approach, methods from …
method in solid mechanics. In this improved hybrid substructuring approach, methods from …
First steps towards an advanced simulation of composites manufacturing by automated tape placement
Composite materials and their related manufacturing processes involve many modeling and
simulation issues, mainly related to their multi-physics and multi-scale nature, to the strong …
simulation issues, mainly related to their multi-physics and multi-scale nature, to the strong …
Model reduction methods
This chapter presents an overview of model order reduction–a new paradigm in the field of
simulation‐based engineering sciences, and one that can tackle the challenges and …
simulation‐based engineering sciences, and one that can tackle the challenges and …
Non-intrusive Sparse Subspace Learning for Parametrized Problems
We discuss the use of hierarchical collocation to approximate the numerical solution of
parametric models. With respect to traditional projection-based reduced order modeling, the …
parametric models. With respect to traditional projection-based reduced order modeling, the …