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DeepBND: A machine learning approach to enhance multiscale solid mechanics

Publications associées (149)

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The Advection Boundary Law in presence of mean-flow and spinning modes

In the attempt to reduce fuel consumption, a new generation of Ultra-High-By-Pass-Ratio (UHBR) turbofans have been introduced in the aeronautic industry which are structurally noisier especially at lower frequencies, because of their larger diameter, lower ...
SPIE2024

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Hitting with Probability One for Stochastic Heat Equations with Additive Noise

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Radiative transfer in luminescent solar concentrators

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A luminescent solar concentrator (LSC) offers a viable solution to spectrally convert and concentrate both direct and diffuse sunlight without the need for tracking. Its potential for commercialization is currently limited by the optical performance. A det ...
2024

Data-driven finite-thickness cohesive elements for frictional interfaces

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Model-free data-driven computational mechanics (DDCM) [Kirchdoerfer & Ortiz, 2016] is a new paradigm for simulations in solid mechanics. As in the classical method, the boundary value problem is formulated with physics-based PDEs such as the balance of mom ...
2023

Graph neural networks for dynamic modeling of roller bearings

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Machine learning has paved the way for the real-time monitoring of complex infrastructure and industrial systems. However, purely data-driven methods have not been able to learn the underlying dynamics and generalize them to operating conditions that have ...
PHM Society2023

Semiclassical Estimates for Eigenvalue Means of Laplacians on Spheres

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Thick points of the planar GFF are totally disconnected for all & gamma;=6 0*

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We prove that the set of-y-thick points of a planar Gaussian free field (GFF) with Dirichlet boundary conditions is a.s. totally disconnected for all-y =6 0. Our proof relies on the coupling between a GFF and the nested CLE4. In particular, we show that th ...
INST MATHEMATICAL STATISTICS-IMS2023

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