Dissémination

Consulter le flux RSS

Publications

Toutes les publications du projet ERC.

Affichage des publications 1 à 10 sur 23 au total

Engineering Sciences

A modified Constitutive Relation Error framework to learn nonlinear constitutive laws using physics-augmented Neural Networks

A novel data-driven approach to learn constitutive law with observable data is proposed in the context of structural health monitoring (SHM). Constitutive laws are represented by a physics-augmented neural network taking strain in input and free…

Antoine Benady, Ludovic Chamoin, Emmanuel Baranger

IACM Mechanistic Machine Learning and Digital Engineering for Computational Science Engineering and Technology. -

Engineering Sciences

A modified Constitutive Relation Error (mCRE) framework to learn nonlinear constitutive models from strain measurements with thermodynamics-consistent Neural Networks

The damage of mechanical structures is a permanent concern in engineering, related to issues of durability and safety. The theme is currently the subject of various research activities; a typical example is the ERC project DREAM-ON (2021-2026), in…

Antoine Benady, Emmanuel Baranger, Ludovic Chamoin

XI Conference on Adaptive Modeling and Simulation -

Engineering Sciences

Model updating with a Modified Dual Kalman Filter acting on distributed strain measurements

Following the advances in measurement technology and its vast availability, mechanical systems and structures are increasingly equipped with sensors to obtain continuous information regarding the system state. Coupled with robust numerical models,…

Sahar Farahbakhsh, Ludovic Chamoin, Martin Poncelet

XI International Conference on Adaptive Modeling and Simulation (ADMOS 2023) -

Engineering Sciences

Data-based Model Updating, Selection, and Enrichment using the Modified Constitutive Relation Error Concept

In the context of computational engineering, physical systems are classically represented by a mathematical model which can be picked in a hierarchical list of possible models, with increasing complexity, and which is then numerically processed to…

Ludovic Chamoin, Antoine Benady, Sahar Farahbakhsh, Emmanuel Baranger, Martin Poncelet

15th World Congress on Computational Mechanics -

Engineering Sciences

Damage tracking using distributed optic fiber sensors in structures

Early detection of damage and monitoring helps improving the safety and durability of structures. The ability to model and simulate this phenomenon, along with measurements, facilitates system control. Various sensor types have been used in the…

S Farahbakhsh, L Chamoin, M Poncelet

25ème Congrès Français de Mécanique -

Structural mechanics

Réseaux de neurones informés par la physique pour l’apprentissage de lois de comportement.

L’endommagement des structures mécaniques est une préoccupation permanente en ingénierie, liée à des problématiques de durabilité et de sécurité. La thématique est actuellement l’objet de diverses activité de recherche ; un exemple caractéristique…

Antoine Benady, Ludovic Chamoin, Emmanuel Baranger

25ème Congrès Français de Mécanique 2022 -

Engineering Sciences

Data-based Model Updating, Selection, and Enrichment using the Modified Constitutive Relation Error Concept

In the context of computational engineering, physical systems are classically represented by a mathematical model which can be picked in a hierarchical list of possible models, with increasing complexity, and which is then numerically processed to…

Ludovic Chamoin, Antoine Benady, Sahar Farahbakhsh, Emmanuel Baranger, Martin Poncelet

15th World Congress on Computational Mechanics -

Engineering Sciences

An educational review on distributed optic fiber sensing based on Rayleigh backscattering for damage tracking and structural health monitoring

This paper is a review on distributed optic fiber sensing for structural health monitoring applications, with a focus on technologies relying on the Rayleigh backscattering phenomenon. It addresses the basic physical principles which are involved,…

Ludovic Chamoin, S Farahbakhsh, M Poncelet

Measurement Science and Technology -