Zobrazeno 1 - 10
of 7 537
pro vyhledávání: '"[ PHYS.MECA.MEMA ] Physics [physics]/Mechanics [physics]/Mechanics of materials [physics.class-ph]"'
Autor:
Xie, Kaili, Leonetti, Marc
Publikováno v:
Comptes Rendus. Mécanique
Comptes Rendus. Mécanique, 2023, 351 (S2), pp.1-20. ⟨10.5802/crmeca.148⟩
Comptes Rendus. Mécanique, 2023, 351 (S2), pp.1-20. ⟨10.5802/crmeca.148⟩
International audience; Core-shell configurations are ubiquitous in nature such as in the form of bacterial and cells. Inspired by this, microcapsules are designed with actives as the cores surrounded by thin shells. They not only play an increasing
Publikováno v:
Journal of Theoretical, Computational and Applied Mechanics (2021)
Dynamic crack propagation in elastomer membranes is investigated; the focus is laid on cracks reaching the speed of shear waves in the material. The specific experimental setup developed to measure crack speed is presented in details. The protocol co
Externí odkaz:
https://doaj.org/article/1fac32ae9cca41d883025d978faec8d1
Publikováno v:
Journal of Theoretical, Computational and Applied Mechanics (2021)
FFT-based solvers are increasingly used by many researcher groups interested in modelling the mechanical behavior associated to a heterogeneous microstructure. A development is reported here that concerns the viscoelastic behavior of composite struct
Externí odkaz:
https://doaj.org/article/928c326754c84552a0ded2078e45c901
Publikováno v:
Journal of Materials Research and Technology
Journal of Materials Research and Technology, 2022, ⟨10.1016/j.jmrt.2022.10.125⟩
Journal of Materials Research and Technology, 2022, ⟨10.1016/j.jmrt.2022.10.125⟩
International audience
Autor:
Luca Uzielli, Paolo Dionisi-Vici, Paola Mazzanti, Lorenzo Riparbelli, Giacomo Goli, Patrick Mandron, Marco Togni, Joseph Gril
Publikováno v:
Journal of Cultural Heritage
Journal of Cultural Heritage, 2022, 58, pp.146-155. ⟨10.1016/j.culher.2022.10.002⟩
Journal of Cultural Heritage, 2022, 58, pp.146-155. ⟨10.1016/j.culher.2022.10.002⟩
International audience; This paper describes an innovative method, and related equipment, developed by the authors to monitor non-invasively historic panel paintings under museum display conditions. This method permits in-depth knowledge about such a
Publikováno v:
Acta Mechanica
Acta Mechanica, 2022, ⟨10.1007/s00707-022-03355-8⟩
Acta Mechanica, 2022, ⟨10.1007/s00707-022-03355-8⟩
International audience; This study aims to analyze the influence of the fibrils oscillations and connections on the effective hygro-elastic behavior of the wood cell wall. For that, two different models of microstructure describing the cell wall are
Autor:
Héloïse Delpouve, Gérald Camus, Stéphane Jouannigot, Bruno Humez, Hervé Plaisantin, Claudie Josse, Sylvain Jacques
Publikováno v:
Journal of Materials Science
Journal of Materials Science, 2022, 2022, ⟨10.1007/s10853-022-07753-0⟩
Journal of Materials Science, 2022, 2022, ⟨10.1007/s10853-022-07753-0⟩
International audience; SiC/BN/SiC-Si single-ply composites with Hi-Nicalon STM fibres were synthesised by chemical vapour infiltration and the liquid route. These are model composites representing the behaviour of industrial composites intended to b
Mechanisms of elastic softening in highly anisotropic carbons under in-plane compression/indentation
Publikováno v:
Carbon
Carbon, 2022, 197, pp.425-434. ⟨10.1016/j.carbon.2022.06.063⟩
Carbon, 2022, 197, pp.425-434. ⟨10.1016/j.carbon.2022.06.063⟩
International audience; We present a combined experimental and computational study of the elastic behavior of a series of highly anisotropic pyrocarbons, with crystallite sizes La in the 2–10 nm range, under a-axis compressive load. The materials i
Publikováno v:
Advanced Materials
Advanced Materials, In press, ⟨10.1002/adma.202302237⟩
Advanced Materials, In press, ⟨10.1002/adma.202302237⟩
International audience; Using very large-scale classical molecular dynamics we examine the mechanics of nano-reinforcement of graphene-based nanocomposites. Our simulations show that significant quantities of large, defect-free and predominantly flat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2755::367c21b2388ffd1347cb168612775a95
https://hal.science/hal-04159456/file/Large_flake_paper___Adv_Mat_revision_zip_Latex_Template.pdf
https://hal.science/hal-04159456/file/Large_flake_paper___Adv_Mat_revision_zip_Latex_Template.pdf
In the last years, neural networks have been used to learn physical simulations in a wide range of contexts. The present work tackles the training of neural networks for large deformation plasticity. There are two sources of nonlinearity: geometric (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3515::9e26fc9c1fc21ca1452842b9c9dfba0a
https://hal.science/hal-04130741/file/neurips_2023.pdf
https://hal.science/hal-04130741/file/neurips_2023.pdf