In this work, we present GAROM, a new approach for reduced order modelli...
In this paper, we propose a shape optimization pipeline for propeller bl...
In the present work, we introduce a novel approach to enhance the precis...
In this work, we propose a model order reduction framework to deal with
...
Convolutional Neural Network (CNN) is one of the most important architec...
As a major breakthrough in artificial intelligence and deep learning,
Co...
In this work we propose an extension of physics informed supervised lear...
The focus of this paper is the application of classical model order redu...
Dynamic mode decomposition (DMD) has recently become a popular tool for ...
Models with dominant advection always posed a difficult challenge for
pr...
In the field of parametric partial differential equations, shape optimiz...
This work describes the implementation of a data-driven approach for the...
In this work, we present an extension of the genetic algorithm (GA) whic...
This contribution describes the implementation of a data–driven shape
op...
In this work we present an advanced computational pipeline for the
appro...
Reduced order modeling (ROM) provides an efficient framework to compute
...