Publications

Risques

Kriging metamodels for 2D finite element simulations of the settlements induced by TBM excavation in urban areas

The finite element method (FEM) is a classical approach to simulate the surface settlements induced by a tunnel boring machine (TBM). Unfortunately, for this application, the FEM is also computationally demanding. In this case, it is often useful to…

Boris Kratz, Pierre Jehel, Maxime Tatin, Emmanuel Vazquez

Congrès Français du Génie Civil 2023 - 2023

General Relativity and Quantum Cosmology

Souriau's Relativistic general covariant formulation of hyperelasticity revisited

We present and modernize Souriau’s 1958 geometric framework for Relativistic continuous media, and enlighten the necessary and the ad hoc modeling choices made since. We focus as much as possible on the Continuum Mechanics point of view and describe…

Boris Kolev, Rodrigue Desmorat

Journal of the Mechanics and Physics of Solids - 2023

Numerical Analysis

Asynchronous global-local non-invasive coupling for linear elliptic problems

This paper presents the first asynchronous version of the Global/Local non-invasive coupling, capable of dealing efficiently with multiple, possibly adjacent, patches. We give a new interpretation of the coupling in terms of primal domain…

Ahmed El Kerim, Pierre Gosselet, Frederic Magoules

Computer Methods in Applied Mechanics and Engineering - 2023

Structural mechanics

Real-time inverse crack tracking in uncertain microstructures using PGD-based model reduction and extended Kalman filtering

Despite recent advances in sensing techniques and rapid growth of computational mechanics, it remains a challenge to monitor mechanical structures in real-time and evaluate their sustainability. In the present work, crack propagation is investigated…

Afsal Pulikkathodi, Elisabeth Longatte-Lacazedieu, Ludovic Chamoin

Computational Mechanics - 2023

Neural and Evolutionary Computing

Design of Artificial Neural Networks for damage estimation of composite laminates: Application to delamination failures in ply drops

This work proposes a data driven approach which utilizes Artificial Neural Networks (ANN) in conjunction with parametric non-linear finite element analysis. The aim is to provide a low cost numerical counterpart to the expensive experimental testing…

Arturo Mendoza, Orestis Friderikos, Roger Trullo, Emmanuel Baranger

Composite Structures - 2023

Mechanics of materials

Calibration of cohesive parameters for a castable refractory using 4D tomographic data and realistic crack path from in-situ wedge splitting test

Rafael Vargas, Rodrigo Bresciani Canto, François Hild, Benjamin Smaniotto

Journal of the European Ceramic Society - 2023

Solid mechanics

Reduced polynomial invariant integrity basis for in-plane magneto-mechanical loading

The description of the behavior of a material subjected to multi-physics loadings requires the formulation of constitutive laws that usually derive from Gibbs free energies, using invariant quantities depending on the considered physics and material…

Julien Taurines, Boris Kolev, Rodrigue Desmorat, Olivier Hubert

Journal of Magnetism and Magnetic Materials - 2023

Risques

Blind broad-band (0-10 Hz) numerical prediction of the 3-D near field seismic response of a Mw6.0 extended fault scenario: application to the nuclear site of Cadarache (France)

In this paper, physics-based numerical simulation (PBS) is employed to render a broad-band (0–10 Hz) realization of the near-field seismic response of the experimental nuclear site of Cadarache, located nearby the active Middle Durance Fault …

David Alejandro Castro Cruz, Filippo Gatti, Fernando Lopez‐caballero, Fabrice Hollender, Elias El Haber, Mathieu Causse

Geophysical Journal International - 2023

Mechanics

Validation of a new viscoelastic model for unidirectional polymer matrix composites by analytical and numerical homogenisation

The long-term response of unidirectional, fibres-reinforced, polymer matrix composites is affected by the viscoelastic behaviour of the matrix. Most composite models introduce a different relaxation function for each of the five elastic parameters…

Federica Daghia, Alexandre Lagache, L Di Gennaro

European Journal of Mechanics - A/Solids - 2023

Civil Engineering

Machine learning and micromechanics as allies to establish composition-property correlations in cement pastes

Composition-property correlations are fundamental to understand cement-based materials behavior and optimize their formulation. Modelling based on fundamental material component constitutes a reliable tool to establish these correlations with the…

Tulio Honorio, Sofiane Ait Hamadouche, Amélie Fau

Journal of Theoretical, Computational and Applied Mechanics - 2023