Medial axis transformation as a solid modeling representation method for computer aided design software

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Stabilized isogeometric discretizations on trimmed and union geometries, and weak imposition of the boundary conditions for the Darcy flow

Modern manufacturing engineering is based on a ``design-through-analysis'' workflow. According to this paradigm, a prototype is first designed with Computer-aided-design (CAD) software and then finalized by simulating its physical behavior, which usually i ...

EPFL2022

Meshing of Spiny Neuronal Morphologies using Union Operators

Felix Schürmann, Marwan Muhammad Ahmed Abdellah, Elvis Boci, Nadir Roman Guerrero, Juan José García Cantero, Alessandro Enrico Foni

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 ...

2022

Is There a Cap on Longevity? A Statistical Review

Anthony Christopher Davison, Léo Raymond-Belzile

There is sustained and widespread interest in understanding the limit, if there is any, to the human life span. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security sys ...

ANNUAL REVIEWS2022

Adaptive analysis-aware defeaturing

Ondine Gabrielle Chanon

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, ...

EPFL2022

Realizing doubles: a conjugation zoo

Jérôme Scherer

Conjugation spaces are topological spaces equipped with an involution such that their fixed points have the same mod 2 cohomology (as a graded vector space, a ring and even an unstable algebra) but with all degrees divided by two, generalizing the classica ...

CAMBRIDGE UNIV PRESS2021

Voss surfaces: A design space for geodesic gridshells

Corentin Jean Dominique Fivet, Nicolas Robin Montagne, Olivier Baverel

The design of envelopes with complex geometries often leads to construction challenges. To overcome these difficulties, resorting to discrete differential geometry proved successful by establishing close links between mesh properties and the existence of g ...

2021

Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks

Angelos Katharopoulos, Andreas Geiger, Despoina Paschalidou

Impressive progress in 3D shape extraction led to representations that can capture object geometries with high fidelity. In parallel, primitive-based methods seek to represent objects as semantically consistent part arrangements. However, due to the simpli ...

IEEE COMPUTER SOC2021

Global Frobenius liftability I

Maciej Emilian Zdanowicz

We formulate a conjecture characterizing smooth projective varieties in positive characteristic whose Frobenius morphism can be lifted modulo p(2)-we expect that such varieties, after a finite stale cover, admit a toric fibration over an ordinary abelian v ...

2021

Transformations silencieuses : étude sur l'architecture alpine

Patrick Giromini

This thesis addresses the question of abandonment in architecture, not in its negative sense of desertion, but as a possibility offered to buildings which have lost their original purpose, which is to say those buildings from social and economic contexts w ...

EPFL2021

On the asymptotic optimality of spectral coarse spaces

Tommaso Vanzan

This paper is concerned with the asymptotic optimality of spectral coarse spaces for two-level iterative methods. Spectral coarse spaces, namely coarse spaces obtained as the span of the slowest modes of the used one-level smoother, are known to be very ef ...

Springer-Verlag2023

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Stabilized isogeometric discretizations on trimmed and union geometries, and weak imposition of the boundary conditions for the Darcy flow

Riccardo Puppi

EPFL2022

Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks

Angelos Katharopoulos, Andreas Geiger, Despoina Paschalidou

IEEE COMPUTER SOC2021