Publications associées à Refinement Algorithms for Adaptive Isogeometric Methods with Hierarchical Splines

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

EPFL2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

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In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

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Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

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Region extraction is a very common task in both Computer Science and Engineering with several applications in object recognition and motion analysis, among others. Most of the literature focuses on regions delimited by straight lines, often in the special ...

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Adaptive isogeometric methods with C-1 (truncated) hierarchical splines on planar multi-patch domains

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Isogeometric analysis is a powerful paradigm which exploits the high smoothness of splines for the numerical solution of high order partial differential equations. However, the tensor-product structure of standard multivariate B-spline models is not well s ...

WORLD SCIENTIFIC PUBL CO PTE LTD2023

A method and system for enforcing smoothness constraints on surface meshes from a graph convolutional neural network

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Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-Constrained Cycles

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Finding cycles in directed graphs enables important applications in various domains such as finance, biology, chemistry, and network science. However, as the size of graph datasets continues to grow, it becomes increasingly difficult to discover cycles wit ...

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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Fast Parallel Algorithms for Enumeration of Simple, Temporal, and Hop-constrained Cycles

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Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

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In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Learning revolution, similarly to the way that Deep Learning revolutionized Computer Vision. To do so, we consider a variety of Computer-Aided Engineering pr ...

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Differentiable Signed Distance Function Rendering

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Physically-based differentiable rendering has recently emerged as an attractive new technique for solving inverse problems that recover complete 3D scene representations from images. The inversion of shape parameters is of particular interest but also pose ...

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Application of optimal spline subspaces for the removal of spurious outliers in isogeometric discretizations

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We show that isogeometric Galerkin discretizations of eigenvalue problems related to the Laplace operator subject to any standard type of homogeneous boundary conditions have no outliers in certain optimal spline subspaces. Roughly speaking, these optimal ...

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Multi-Level Monte Carlo Methods for Uncertainty Quantification and Risk-Averse Optimisation

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This work aims to study the effects of wind uncertainties in civil engineering structural design. Optimising the design of a structure for safety or operability without factoring in these uncertainties can result in a design that is not robust to these per ...

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A virtual microstructure generator for 3D stone masonry walls

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Detailed micromodel simulations of stone masonry walls require as input a 3D mesh that represents a realistic arrangement of stones in the masonry wall. In this paper, we constructed the first 3D masonry microstructures to derive 2D and 3D finite or discre ...

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Geometrical Treatise on the Modelling of 3D Particulate Inclusion-Matrix Microstructures with an Application to Historical Stone Masonry Walls

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Adaptive analysis-aware defeaturing

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Removing geometrical details from a complex domain is a classical operation in computer aided design for simulation and manufacturing. This procedure simplifies the meshing process, and it enables faster simulations with less memory requirements. However, ...

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Investigation and Validation of Unstructured Mesh Methodologies for Modeling Experimental Reactors

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This paper summarizes a methodology developed at Ecole Polytechnique Federale de Lausanne for the neutronic modeling of the CROCUS experimental reactor and proposes solutions to the challenges one may face while modeling a research reactor with a complex g ...

MDPI2022

Meshing of Spiny Neuronal Morphologies using Union Operators

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Neurons are characterized by thin and long interleaving arborizations in which creating accurate mesh models of their cellular membranes is challenging. While union operators are central for CAD/CAM modeling and computer graphics applications, their applic ...

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