Data-driven modal decomposition methods as feature detection techniques for flow problems: A critical assessment
Modal decomposition techniques are showing a fast growth in popularity for their wide range
of applications and their various properties, especially as data-driven tools. There are many …
of applications and their various properties, especially as data-driven tools. There are many …
Delay differential equations for the spatially resolved simulation of epidemics with specific application to COVID‐19
N Guglielmi, E Iacomini… - Mathematical Methods in …, 2022 - Wiley Online Library
In the wake of the 2020 COVID‐19 epidemic, much work has been performed on the
development of mathematical models for the simulation of the epidemic and of disease …
development of mathematical models for the simulation of the epidemic and of disease …
Coupled and uncoupled dynamic mode decomposition in multi-compartmental systems with applications to epidemiological and additive manufacturing problems
Abstract Dynamic Mode Decomposition (DMD) is an unsupervised machine learning
method that has attracted considerable attention in recent years owing to its equation-free …
method that has attracted considerable attention in recent years owing to its equation-free …
Implementation of the adaptive phase-field method with variable-node elements for cohesive fracture
In this paper, an adaptive phase-field model based on variable-node elements and error-
indicator is presented to predict cohesive fracture evolution. The phase-field cohesive-zone …
indicator is presented to predict cohesive fracture evolution. The phase-field cohesive-zone …
[HTML][HTML] pyLOM: A HPC open source reduced order model suite for fluid dynamics applications
This paper describes the numerical implementation in a high-performance computing
environment of an open-source library for model order reduction in fluid dynamics. This …
environment of an open-source library for model order reduction in fluid dynamics. This …
Efficient Simulation of Volumetric Deformable Objects in Unity3D: GPU-Accelerated Position-Based Dynamics
This paper proposes an efficient approach for simulating volumetric deformable objects
using the Position-Based Dynamics (PBD) method. Volumetric bodies generated by TetGen …
using the Position-Based Dynamics (PBD) method. Volumetric bodies generated by TetGen …
Locally refined quad meshing for linear elasticity problems based on convolutional neural networks
In this paper we propose a method to generate suitably refined finite element meshes using
neural networks. As a model problem we consider a linear elasticity problem on a planar …
neural networks. As a model problem we consider a linear elasticity problem on a planar …
Identification of time delays in COVID-19 data
Objective COVID-19 data released by public health authorities is subject to inherent time
delays. Such delays have many causes, including delays in data reporting and the natural …
delays. Such delays have many causes, including delays in data reporting and the natural …
Data-driven simulation of Fisher–Kolmogorov tumor growth models using dynamic mode decomposition
The computer simulation of organ-scale biomechanistic models of cancer personalized via
routinely collected clinical and imaging data enables to obtain patient-specific predictions of …
routinely collected clinical and imaging data enables to obtain patient-specific predictions of …
Enhancing dynamic mode decomposition workflow with in situ visualization and data compression
Modern computational science and engineering applications are being improved by
advances in scientific machine learning. Data-driven methods such as dynamic mode …
advances in scientific machine learning. Data-driven methods such as dynamic mode …