Structural damage: robust, real-time, and data-driven adaptive modeling for online control

Información del proyecto

DREAM-ON

Identificador del acuerdo de subvención: 101002857

DOI

10.3030/101002857

Fecha de la firma de la CE 8 Abril 2021

Fecha de inicio 1 Junio 2021

Fecha de finalización 31 Mayo 2026

Financiado con arreglo a

• EXCELLENT SCIENCE - European Research Council (ERC)

Coste total

€ 1 937 500,00

Aportación de la UE

€ 1 937 500,00

Coordinado por

ECOLE NORMALE SUPERIEURE PARIS-SACLAY
France

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Publicaciones

Book chapters (4)

A novel DDDAS architecture combining advanced sensing and simulation technologies for effective real-time structural health monitoring

Autores: Chamoin, Ludovic; Baranger, Emmanuel; Benady, Antoine; Charbonnel, Pierre-Étienne; Diaz, Matthieu; Farahbakhsh, Sahar; Fribourg, Laurent; Xavier, Daniel Martin; Poncelet, Martin
Publicado en: Handbook of Dynamic Data Driven Application Systems, 2025, ISBN 978-3-031-88573-0
Editor: Springer Cham

Intégrer les connaissances physiques dans les réseaux de neurones: application à l'apprentissage des lois de comportement matériaux à partir de mesures de déformation par fibres optiques

Autores: A. BENADY, L. CHAMOIN, E. BARANGER
Publicado en: La Revue 3EI, Edición 109, 2022, ISSN 1252-770X
Editor: SEE

Model verification, updating, and selection from the constitutive relation error concept

Autores: L. CHAMOIN, P. LADEVEZE
Publicado en: Advances in Applied Mechanics, Error Control, Adaptive Discretizations, and Applications, Part 2, 2025, Página(s) 311-362
Editor: Elsevier
DOI: 10.1016/bs.aams.2024.08.005

DREAM-ON: merging advanced sensing techniques and simulation tools for future structural health monitoring technologies

Autores: L. CHAMOIN
Publicado en: The Project Repository Journal, Edición 10, 2021, Página(s) 124-127
Editor: EDMA
DOI: 10.54050/prj10124127

Conference proceedings (23)

A modified dual Kalman filter for damage detection using distributed optic fiber measurements

Autores: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Publicado en: 9th European Congress on Computational Methods in Applied Sciences and Engineering, 2024
Editor: ECCOMAS

Structural health monitoring and model updating with distributed optic fiber measurements

Autores: S. FARAHBAKHSH, M. PONCELET, L. CHAMOIN
Publicado en: 17th International Conference on Advances in Experimental Mechanics, 2023
Editor: Univ. Strathclyde

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

Autores: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Publicado en: 11th Conference on Adaptive Modeling and Simulation, 2023
Editor: ECCOMAS
DOI: 10.23967/admos.2023.021

Identification et suivi de l'endommagement structural à l'aide de mesures expérimentales et d'une approche par filtre de Kalman modifié

Autores: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Publicado en: 16e Colloque National en Calcul des Structures, 2024
Editor: CSMA

Physics-augmented neural networks for constitutive modeling: toward an application for structural health monitoring

Autores: A. BENADY, S. FARAHBAKHSH, E. BARANGER, L. CHAMOIN
Publicado en: 9th European Congress on Computational Methods in Applied Sciences and Engineering, 2024
Editor: ECCOMAS

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

Autores: A. BENADY, L. CHAMOIN, E. BARANGER
Publicado en: 2nd IACM Mechanistic Machine Learning and Digital Engineering for Computational Science Engineering and Technology, 2023
Editor: IACM

Training and generalization errors for Underparametrized Neural Networks

Autores: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Publicado en: American Control Conference, 2024
Editor: AACC

Physics-augmented neural networks for constitutive modeling: training with the modified constitutive relation error

Autores: A. BENADY, E. BARANGER, L. CHAMOIN
Publicado en: 6th International Workshop on Model Reduction Techniques, 2023
Editor: ECCOMAS

In situ structural damage tracking and monitoring from advanced sensing techniques and hybrid twins

Autores: L. CHAMOIN
Publicado en: 6th International Conference on Multi-scale Computational Methods for Solids and Fluids, 2023, ISBN 978-9958-638-73-2
Editor: ECCOMAS

Commande garantie pour le contrôle et la prévention de l'endommagement des structures

Autores: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Publicado en: 16e Colloque National en Calcul des Structures, 2024
Editor: CSMA

Physics-informed neural networks derived from a mCRE functional for constitutive modeling

Autores: A. BENADY, L. CHAMOIN, E. BARANGER
Publicado en: 2nd International Workshop on Artificial Intelligence and Augmented Engineering, 2022
Editor: INRIA

Real-time monitoring of evolutive structural damage from advanced sensing and simulation

Autores: L. CHAMOIN
Publicado en: Colloque IUF, 2023
Editor: IUF

Contrôle en ligne garantissant la sûreté de fonctionnement de structures en mode dégradé

Autores: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Publicado en: 1er Congrès Annuel de la Société Française d'Automatique, de Génie Industriel et de Productique, 2023
Editor: SAGIP

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

Autores: A. BENADY, E. BARANGER, L. CHAMOIN
Publicado en: 11th Conference on Adaptive Modeling and Simulation, 2023
Editor: ECCOMAS
DOI: 10.23967/admos.2023.020

Apprentissage non-supervisé de lois de comportement non-linéaires avec réseau de neurones thermodynamiquement consistent par minimisation de l'erreur en relation de comportement modifiée

Autores: A. BENADY, E. BARANGER, L. CHAMOIN
Publicado en: 16e Colloque National en Calcul des Structures, 2024
Editor: CSMA

Damage tracking using distributed optic fiber sensors in structures

Autores: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Publicado en: 25e Congrès Français de Mécanique, 2022
Editor: AFM

Data-driven MPC applied to nonlinear systems for real-time applications

Autores: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Publicado en: 14e Colloque sur la Modélisation des Systèmes Réactifs, 2023
Editor: LAAS-CNRS

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

Autores: A. BENADY, L. CHAMOIN, E. BARANGER
Publicado en: 25e Congrès Français de Mécanique, 2022
Editor: AFM

Some recent advances in structural damage tracking and monitoring

Autores: L. CHAMOIN, S. FARAHBAKHSH, M. DIAZ, M. PONCELET, PE. CHARBONNEL
Publicado en: 16th World Congress on Computational Mechanics, 2024
Editor: IACM

Data-based model updating, selection, and enrichment using the modified constitutive relation error concept

Autores: L. CHAMOIN, A. BENADY, S. FARAHBAKHSH, E. BARANGER, M. PONCELET
Publicado en: 15th World Congress on Computational Mechanics, 2022
Editor: IACM

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

Autores: A. BENADY, L. CHAMOIN, E. BARANGER
Publicado en: Workshop CNRS, l’IA pour les sciences et l’ingénierie, 2022
Editor: CNRS

Physics-informed neural networks derived from a mCRE functional for constitutive modelling

Autores: A. BENADY, L. CHAMOIN, E. BARANGER
Publicado en: IUTAM Symposium on Data-driven mechanics, 2022
Editor: IUTAM

Adaptive modeling and learning of material laws for effective data assimilation

Autores: L. CHAMOIN, A. BENADY, S. FARAHBAKHSH, E. BARANGER, M. PONCELET
Publicado en: 16th World Congress on Computational Mechanics, 2024
Editor: IACM

Other (5)

Optimization of optic fiber sensor placement for structural health monitoring

Autores: Z. ZHOU, B. SOULIER, L. CHAMOIN
Publicado en: 2022
Editor: ENS Paris-Saclay

Use of physics-augmented neural networks for unsupervised learning of material constitutive relations - Comparison of the NN-Euclid and NN-mCRE methods

Autores: E. ZEMBRA, A. BENADY, E. BARANGER, L. CHAMOIN
Publicado en: 2023
Editor: ENS Paris-Saclay

Scientific machine learning and physics-augmented neural networks for hybrid digital twins

Autores: A. BENADY, F. LEHMANN, A. PULIKKATHODI, E. BARANGER, L. CHAMOIN, F. GATTI, D. CLOUTEAU
Publicado en: Journée du GDR I-GAIA, 2023
Editor: CNRS

OFDR optic fiber measurements: performance limitations

Autores: S. FARAHBAKHSH, M. PONCELET, L. CHAMOIN
Publicado en: Colloque National Mecamat, 2024
Editor: Mecamat

High resolution strain measurement using optic fiber sensors

Autores: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Publicado en: Journées des doctorants du LMPS, 2022
Editor: LMPS, ENS Paris-Saclay

Peer reviewed articles (7)

Experimental Learning of a Hyperelastic Behavior with a Physics-Augmented Neural Network

Autores: C. Jailin, A. Benady, R. Legroux, E. Baranger
Publicado en: Experimental Mechanics, Edición 64, 2024, Página(s) 1465-1481, ISSN 0014-4851
Editor: Sage Science Press
DOI: 10.1007/s11340-024-01106-5

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

Autores: L. CHAMOIN, S. FARAHBAKHSH, M. PONCELET
Publicado en: Measurement Science and Technology, Edición 33:124008, 2022, ISSN 0957-0233
Editor: Institute of Physics and the Physical Society
DOI: 10.1088/1361-6501/ac9152

Training and generalization errors for Underparametrized Neural Networks

Autores: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Publicado en: IEEE Control Systems Letters, Edición 7, 2023, Página(s) 3926-3931, ISSN 2475-1456
Editor: IEEE
DOI: 10.1109/lcsys.2023.3344139

Data-driven material modeling based on the Constitutive Relation Error

Autores: Pierre Ladevèze, Ludovic Chamoin
Publicado en: Advanced Modeling and Simulation in Engineering Sciences, Edición 11, 2024, ISSN 2213-7467
Editor: Springer Science and Business Media LLC
DOI: 10.1186/s40323-024-00279-x

Model and mesh selection from a mCRE functional in the context of parameter identification with full-field measurements

Autores: Hai Nam Nguyen, Ludovic Chamoin
Publicado en: Computational Mechanics, Edición 76, 2025, Página(s) 251-277, ISSN 0178-7675
Editor: Springer Verlag
DOI: 10.1007/s00466-025-02598-1

Unsupervised learning of history-dependent constitutive material laws with thermodynamically-consistent neural networks in the modified Constitutive Relation Error framework

Autores: Antoine Benady, Emmanuel Baranger, Ludovic Chamoin
Publicado en: Computer Methods in Applied Mechanics and Engineering, Edición 425, 2024, Página(s) 116967, ISSN 0045-7825
Editor: Elsevier BV
DOI: 10.1016/j.cma.2024.116967

NN-mCRE: a modified Constitutive Relation Error framework for unsupervised learning of nonlinear state laws with physics-augmented Neural Networks

Autores: A. BENADY, E. BARANGER, L. CHAMOIN
Publicado en: International Journal for Numerical Methods in Engineering, 2024, ISSN 0029-5981
Editor: John Wiley & Sons Inc.
DOI: 10.1002/nme.7439