Publications related to Localized model order reduction and domain decomposition methods for coupled heterogeneous systems

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Alfio Quarteroni, Francesco Regazzoni, Stefano Pagani

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

Nature Portfolio2024

Model reduction of coupled systems based on non-intrusive approximations of the boundary response maps

Jan Sickmann Hesthaven, Niccolo' Discacciati

We propose a local, non -intrusive model order reduction technique to accurately approximate the solution of coupled multi -component parametrized systems governed by partial differential equations. Our approach is based on the approximation of the boundar ...

Elsevier Science Sa2024

Reduced order models for coupled systems

Niccolo' Discacciati

Efficient numerical simulations of coupled multi-component systems can be particularly challenging. This is mostly due to the complexity of their solutions, as mutual interactions may cause emergent behaviors, including synchronization and instabilities. V ...

EPFL2023

Spatial symmetries in nonlocal multipolar metasurfaces

Olivier Martin, Karim Achouri, Ville Tuovi Tiukuvaara

We propose a framework that connects the spatial symmetries of a metasurface to its material parameter tensors and its scattering matrix. This provides a simple and universal way to effortlessly determine the properties of a metasurface scattering response ...

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS2023

Avalanche risks management as intangible cultural heritage

Florence Graezer Bideau, Chiara Maria Bortolotto

This paper tackles Avalanche Risks Management (ARM), nominated by Switzerland and Austria and inscribed on the UNESCO Representative List of Intangible Cultural Heritage in 2018. On the one hand, this nomination conventionally highlights how traditional em ...

2023

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-Driven Cultural Contact Detection Approach

Yumeng Hou

Investigating the intangible nature of a cultural domain can take multiple forms, addressing for example the aesthetic, epistemic and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance as it c ...

2023

Adaptive Symplectic Model Order Reduction Of Parametric Particle-Based Vlasov-Poisson Equation

Cecilia Pagliantini, Jan Sickmann Hesthaven, Nicolò Ripamonti

. High-resolution simulations of particle-based kinetic plasma models typically require a high number of particles and thus often become computationally intractable. This is exacerbated in multi-query simulations, where the problem depends on a set of para ...

AMER MATHEMATICAL SOC2023

A Compressive Sensing Framework for EMI Source Localization Using a Metalens Structure: Localization Beyond the Diffraction Limit

Farhad Rachidi-Haeri, Marcos Rubinstein, Mohammad Azadifar, Hamidreza Karami

In this article, we propose a novel approach for the localization of electromagnetic interference (EMI) sources based on the concept of compressive sensing and metalenses. We show that using the spatial and frequency dispersion offered by the metalens, we ...

2022

Experimental quantification of unsteady leading-edge flow separation

Karen Ann J Mulleners, Julien Dominique Claude Deparday

We propose here a method to experimentally quantify unsteady leading-edge flow separation on aerofoils with finite thickness. The methodology relies on the computation of a leading-edge suction parameter based on measured values of the partial circulation ...

Cambridge University Press2022

A Coarse-mesh Methodology for the Analysis of One and Two-phase Nuclear Reactor Thermal-hydraulics in a Multi-physics Context

Stefan Radman

The analysis of nuclear reactors for performance and safety assessment benefits from the use of computational tools. In this context, this work aims at the development and application of a thermal-hydraulics methodology and related software that respond to ...

EPFL2021

Real-time camera pose estimation for sports fields

Pascal Fua, Charles Dubout, Horesh Beny Ben Shitrit, Pablo Marquez Neila, Stefano Savarè, Leonardo Citraro

Given an image sequence featuring a portion of a sports field filmed by a moving and uncalibrated camera, such as the one of the smartphones, our goal is to compute automatically in real time the focal length and extrinsic camera parameters for each image ...

2020

Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics

Alfio Quarteroni, Francesco Regazzoni

High fidelity (HF) mathematical models describing the generation of active force in the cardiac muscle tissue typically feature a large number of state variables to capture the intrinsically complex underlying subcellular mechanisms. With the aim of drasti ...

2020

Algorithms and flowchart for the design of synthetic biochemical networks

Homa Mohammadi Peyhani

New drugs are needed to assure effective therapies for previously untreated diseases, emerging diseases, and personalized medicine, but the process of drug development is complex, costly, and time-consuming. This is especially problematic considering that ...

EPFL2020

Model-informed machine learning for multi-component T2 relaxometry

Jean-Philippe Thiran, Meritxell Bach Cuadra, Tobias Kober, Elda Fischi Gomez, Cristina Granziera, Tom Hilbert, Muhamed Barakovic, Gian Franco Piredda, Erick Jorge Canales Rodriguez, Marco Pizzolato, Thomas Yu

Recovering the distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to comb ...

2020

Model order reduction for large-scale structures with local nonlinearities

Jan Sickmann Hesthaven, Mengwu Guo, Zhenying Zhang

In solid mechanics, linear structures often exhibit (local) nonlinear behavior when close to failure. For instance, the elastic deformation of a structure becomes plastic after being deformed beyond recovery. To properly assess such problems in a real-life ...

ELSEVIER SCIENCE SA2019

Explicit versus implicit front advancing schemes for the simulation of hydraulic fracture growth

Brice Tanguy Alphonse Lecampion, Haseeb Zia

The proper computation of the time evolution of the fracture front is the main challenge of three-dimensional (3D) hydraulic fracture growth simulation. We discuss explicit and implicit variants of a hydraulic fracture propagation scheme based on a level s ...

2019

Using A Priori Knowledge to Improve Scene Understanding

Alexandre Massoud Alahi

Semantic segmentation algorithms that can robustly segment objects across multiple camera viewpoints are crucial for assuring navigation and safety in emerging applications such as autonomous driving. Existing algorithms treat each image in isolation, but ...

IEEE2019

Using Regularized Linear-Regression Surrogate Models for Accurate Probabilistic Structural Identification

Ian Smith, Sai Ganesh Sarvotham Pai

Model-based data interpretation has the potential to increase knowledge of structural behavior and support asset management. Models are usually conservative and contain many parameters and sources of systematic uncertainty, which need to be taken into acco ...

AMER SOC CIVIL ENGINEERS2019

The Fluctuation Dissipation Theorem as a Diagnosis and Cure for Zero-Point Energy Leakage in Quantum Thermal Bath Simulations

Sara Bonella

Quantum thermal bath (QTB) simulations reproduce statistical nuclear quantum effects via a Langevin equation with a colored random force. Although this approach has proven efficient for a variety of chemical and condensed-matter problems, the QTB, as many ...

2019

Autonomous illumination control for localization microscopy

Suliana Manley, Baptiste Romain Samuel Ottino, Kyle Michael Douglass, Marcel Stefko

Super-resolution fluorescence microscopy improves spatial resolution, but this comes at a loss of image throughput and presents unique challenges in identifying optimal acquisition parameters. Microscope automation routines can offset these drawbacks, but ...

OPTICAL SOC AMER2018