Adaptive Isogeometric Methods With Hierarchical Splines: An Overview

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Low-Rank Tensor Methods for High-Dimensional Problems

In this thesis, we propose and analyze novel numerical algorithms for solving three different high-dimensional problems involving tensors. The commonality of these problems is that the tensors can potentially be well approximated in low-rank formats. Ident ...

EPFL2023

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Alfio Quarteroni, Francesco Regazzoni, Marco Fedele, Stefano Pagani

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

BMC2023

Numerical Study of the Optical Response of ITO-In2O3 Core-Shell Nanocrystals for Multispectral Electromagnetic Shielding

Nicolò Petrini, Michele Ghini

Nowadays materials to protect equipment from unwanted multispectral electromagnetic waves are needed in a broad range of applications including electronics, medical, military and aerospace. However, the shielding materials currently in use are bulky and wo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

A fully-coupled highly-parallelized geomechanical simulator for assessing induced seismicity

Jean-François Molinari, Guillaume Anciaux, Nicolas Richart, Brice Tanguy Alphonse Lecampion, Emil Gallyamov

Induced seismicity caused by anthropogenic modification of the subsurface effective stress state has been observed in a number of industrial applications -- from hydrocarbon extraction (e.g., Groningen [1]), drilling waste-water disposal (e.g., [2]) to the ...

2023

Learning ground states of gapped quantum Hamiltonians with Kernel Methods

Giuseppe Carleo, Filippo Vicentini, Riccardo Rossi, Clemens Giuliani

Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statistical learning approach that makes the optimization trivial by using kernel me ...

Verein Forderung Open Access Publizierens Quantenwissenschaf2023

Thermo-hydro-mechanical analysis of the complete lifetime of the bentonite barrier in the FEBEX in-situ test

Lyesse Laloui, Alessio Ferrari, Yafei Qiao, Jose Antonio Bosch Llufriu

The FEBEX test was a large-scale demonstration project for the deep geological disposal concept of nuclear waste involving bentonite seals that lasted 18 years. One of the objectives of the test was to evaluate the capabilities of numerical methods to prov ...

2023

An equilibrated flux a posteriori error estimator for defeaturing problems

Ondine Gabrielle Chanon, Annalisa Buffa, Rafael Vazquez Hernandez, Denise Grappein

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

2023

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Wiley2023

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