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

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

Autori: Chamoin, Ludovic; Baranger, Emmanuel; Benady, Antoine; Charbonnel, Pierre-Étienne; Diaz, Matthieu; Farahbakhsh, Sahar; Fribourg, Laurent; Xavier, Daniel Martin; Poncelet, Martin
Pubblicato in: Handbook of Dynamic Data Driven Application Systems, 2025, ISBN 978-3-031-88573-0
Editore: 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

Autori: A. BENADY, L. CHAMOIN, E. BARANGER
Pubblicato in: La Revue 3EI, Numero 109, 2022, ISSN 1252-770X
Editore: SEE

Data Assimilation and Integration Into Computational Mechanics Models

Autori: Ludovic Chamoin
Pubblicato in: SEMA SIMAI Springer Series, Mathematical and Computational Modelling Across the Scales, 2025, Pagina/e 39-76
Editore: Springer Nature Switzerland
DOI: 10.1007/978-3-031-84897-1_2

Contrôle en temps reel de l'évolution de l'endommagement dans les structures mécaniques à partir de techniques avancées de mesure et de simulation

Autori: L. CHAMOIN
Pubblicato in: Evolution(s): Science, art et littérature, 2025, ISBN 978-2-37361-492-3
Editore: Editions Matériologiques

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

Autori: L. CHAMOIN, P. LADEVEZE
Pubblicato in: Advances in Applied Mechanics, Error Control, Adaptive Discretizations, and Applications, Part 2, 2025, Pagina/e 311-362
Editore: Elsevier
DOI: 10.1016/bs.aams.2024.08.005

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

Autori: L. CHAMOIN
Pubblicato in: The Project Repository Journal, Numero 10, 2021, Pagina/e 124-127
Editore: EDMA
DOI: 10.54050/prj10124127

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

Autori: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Pubblicato in: 9th European Congress on Computational Methods in Applied Sciences and Engineering, 2024
Editore: ECCOMAS

Structural health monitoring and model updating with distributed optic fiber measurements

Autori: S. FARAHBAKHSH, M. PONCELET, L. CHAMOIN
Pubblicato in: 17th International Conference on Advances in Experimental Mechanics, 2023
Editore: Univ. Strathclyde

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

Autori: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Pubblicato in: 11th Conference on Adaptive Modeling and Simulation, 2023
Editore: 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

Autori: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Pubblicato in: 16e Colloque National en Calcul des Structures, 2024
Editore: CSMA

Integrated structural health monitoring with real-time data assimilation and hybrid twins

Autori: L. CHAMOIN
Pubblicato in: International Symposium Mathematical and applied aspects of complexity reduction methods (Collège de France), 2026
Editore: Collège de France

Integrated Structural Health Monitoring with real-time data assimilation and hybrid twins of dynamical systems

Autori: L. CHAMOIN
Pubblicato in: 10th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, 2025
Editore: ECCOMAS

Validation criteria for data-driven models of history-dependent materials

Autori: L. CHAMOIN, P. LADEVEZE
Pubblicato in: 17th World Congress on Computational Mechanics (WCCM 2026), 2026
Editore: IACM

Effective numerical strategies for in situ damage monitoring on engineering structures

Autori: L. CHAMOIN
Pubblicato in: Rencontres Franciliennes de Mécanique, 2024
Editore: Federation Francilienne de Mécanique

Data-driven modeling based on the Constitutive Relation Error for history-dependent materials

Autori: P. LADEVEZE, L. CHAMOIN
Pubblicato in: Digital Twins in Engineering (DTE) & Artificial Intelligence and Computational Methods in Applied Science (AICOMAS), 2025
Editore: ECCOMAS

Adaptive damage model identification in sequential data assimilation with distributed optic fiber sensing

Autori: L. CHAMOIN, S. FARAHBAKHSH, M. PONCELET
Pubblicato in: 12th International Conference on Adaptive Modeling and Simulation, 2025
Editore: ECCOMAS

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

Autori: A. BENADY, S. FARAHBAKHSH, E. BARANGER, L. CHAMOIN
Pubblicato in: 9th European Congress on Computational Methods in Applied Sciences and Engineering, 2024
Editore: ECCOMAS

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

Autori: A. BENADY, L. CHAMOIN, E. BARANGER
Pubblicato in: 2nd IACM Mechanistic Machine Learning and Digital Engineering for Computational Science Engineering and Technology, 2023
Editore: IACM

Training and generalization errors for Underparametrized Neural Networks

Autori: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Pubblicato in: American Control Conference, 2024
Editore: AACC

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

Autori: A. BENADY, E. BARANGER, L. CHAMOIN
Pubblicato in: 6th International Workshop on Model Reduction Techniques, 2023
Editore: ECCOMAS

Techniques d'intelligence artificielle au service de l'ingénierie: réduction de modèles complexes par Machine Learning

Autori: L. CHAMOIN
Pubblicato in: Journée Scientifique Dassault Aviation, 2024
Editore: Dassault Aviation

Nonlinear parametric identification using model reduction-based mCRE and MDKF

Autori: M. BHATTACHARYYA, L. CHAMOIN
Pubblicato in: 17e Colloque National en Calcul des Structure (CSMA), 2026
Editore: CSMA

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

Autori: L. CHAMOIN
Pubblicato in: 6th International Conference on Multi-scale Computational Methods for Solids and Fluids, 2023, ISBN 978-9958-638-73-2
Editore: ECCOMAS

Data-driven MPC for real-time control of an open-die forging problem

Autori: D. MARTIN XAVIER, L. CHAMOIN, L. FRIBOURG
Pubblicato in: European Control Conference (ECC 2025), 2025
Editore: European Control Association (EUCA)

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

Autori: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Pubblicato in: 16e Colloque National en Calcul des Structures, 2024
Editore: CSMA

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

Autori: A. BENADY, L. CHAMOIN, E. BARANGER
Pubblicato in: 2nd International Workshop on Artificial Intelligence and Augmented Engineering, 2022
Editore: INRIA

Approximation and definition of state variables for a comprehensive description of damage for ceramic matrix composites

Autori: E. BARANGER
Pubblicato in: 48th International Conference and Expo on Advanced Ceramics and Composites, 2024
Editore: American Ceramic Society

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

Autori: L. CHAMOIN
Pubblicato in: Colloque IUF, 2023
Editore: IUF

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

Autori: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Pubblicato in: 1er Congrès Annuel de la Société Française d'Automatique, de Génie Industriel et de Productique, 2023
Editore: SAGIP

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

Autori: A. BENADY, E. BARANGER, L. CHAMOIN
Pubblicato in: 11th Conference on Adaptive Modeling and Simulation, 2023
Editore: 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

Autori: A. BENADY, E. BARANGER, L. CHAMOIN
Pubblicato in: 16e Colloque National en Calcul des Structures, 2024
Editore: CSMA

Damage tracking using distributed optic fiber sensors in structures

Autori: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Pubblicato in: 25e Congrès Français de Mécanique, 2022
Editore: AFM

A PGD-based reduced order approximation for nonlinear parametric identification using the modified constitutive relation error method and modified Kalman filtering

Autori: M. BHATTACHARYYA, L. CHAMOIN
Pubblicato in: 12th International Conference on Adaptive Modeling and Simulation, 2025
Editore: ECCOMAS

Model parameter identification and damage detection using a modified dual Kalman filter with optical fiber sensor data

Autori: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Pubblicato in: Digital Twins in Engineering (DTE) & Artificial Intelligence and Computational Methods in Applied Science (AICOMAS), 2025
Editore: ECCOMAS

Unsupervised identification of constitutive laws using neural networks in a thermodynamically consistent framework guided by the CRE and mCRE methods

Autori: N. KLEBI, L. CHAMOIN
Pubblicato in: 18th Internation Conference on Computational Plasticity (COMPLAS 2025), 2025
Editore: ECCOMAS

Integrated structural health monitoring with real-time data assimilation and hybrid twins of dynamical systems

Autori: L. CHAMOIN
Pubblicato in: Seminar of IMB, 2026
Editore: IMB

An analysis of tube radius under approximate model prediction control

Autori: S. MAHALINGAM, L. CHAMOIN
Pubblicato in: 17th World Congress on Computational Mechanics (WCCM 2026), 2026
Editore: IACM

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

Autori: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Pubblicato in: 14e Colloque sur la Modélisation des Systèmes Réactifs, 2023
Editore: LAAS-CNRS

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

Autori: A. BENADY, L. CHAMOIN, E. BARANGER
Pubblicato in: 25e Congrès Français de Mécanique, 2022
Editore: AFM

Identification non supervisée de lois de comportement non-linéaire par réseaux de neurons dans un cadre thermodynamiquement coherent, guide par la méthode mCRE

Autori: N. KLEBI, L. CHAMOIN
Pubblicato in: 17e Colloque National en Calcul des Structure (CSMA), 2026
Editore: CSMA

Early stopping strategy using neural tangent kernel theory and Rademacher complexity

Autori: D. MARTIN XAVIER, L. CHAMOIN, L. FRIBOURG
Pubblicato in: American Control Conference (ACC 2025), 2025
Editore: American Automatic Control Council (AACC)

Some recent advances in structural damage tracking and monitoring

Autori: L. CHAMOIN, S. FARAHBAKHSH, M. DIAZ, M. PONCELET, PE. CHARBONNEL
Pubblicato in: 16th World Congress on Computational Mechanics, 2024
Editore: IACM

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

Autori: L. CHAMOIN, A. BENADY, S. FARAHBAKHSH, E. BARANGER, M. PONCELET
Pubblicato in: 15th World Congress on Computational Mechanics, 2022
Editore: IACM

Data assimilation from hybrid twins for the practical real-time monitoring of complex engineering systems

Autori: L. CHAMOIN
Pubblicato in: Digital Twins in Engineering (DTE) & Artificial Intelligence and Computational Methods in Applied Science (AICOMAS), 2025
Editore: ECCOMAS

An analysis of tube radius under approximate model prediction control

Autori: S. MAHALINGAM, L. CHAMOIN
Pubblicato in: 17e Colloque National en Calcul des Structure (CSMA), 2026
Editore: CSMA

Contrôle santé intégré des structures basée sur l’assimilation de données en temps réel et les jumeaux numériques

Autori: L. CHAMOIN
Pubblicato in: Seminar of EDF, 2026
Editore: EDF

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

Autori: A. BENADY, L. CHAMOIN, E. BARANGER
Pubblicato in: Workshop CNRS, l’IA pour les sciences et l’ingénierie, 2022
Editore: CNRS

Use of the modified constitutive relation error to learn constitutive relations

Autori: E. BARANGER, A. BENADY, L. CHAMOIN
Pubblicato in: 21st European Conference on Composite Materials, 2024
Editore: AMAC
DOI: 10.60691/yj56-np80

Unsupervised learning of constitutive model with neural networks and sparse identification of internal variables

Autori: A. BENADY, E. BARANGER, C. JAILIN, L. CHAMOIN
Pubblicato in: Digital Twins in Engineering (DTE) & Artificial Intelligence and Computational Methods in Applied Science (AICOMAS), 2025
Editore: ECCOMAS

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

Autori: A. BENADY, L. CHAMOIN, E. BARANGER
Pubblicato in: IUTAM Symposium on Data-driven mechanics, 2022
Editore: IUTAM

Adaptive modeling and learning of material laws for effective data assimilation

Autori: L. CHAMOIN, A. BENADY, S. FARAHBAKHSH, E. BARANGER, M. PONCELET
Pubblicato in: 16th World Congress on Computational Mechanics, 2024
Editore: IACM

Parsimonious identification of a viscoelastic model using the mCRE framework and Lasso regularization

Autori: N. KLEBI, L. CHAMOIN
Pubblicato in: 11th International Conference on Inverse Problems, Control and Shape Optimization (PICOF 2025), 2025
Editore: LAMSIN

Unsupervised identification of constitutive laws using neural networks in a thermodynamically consistent framework guided by the CRE and mCRE methods

Autori: N. KLEBI, L. CHAMOIN
Pubblicato in: 11th GACM Colloquium on Computational Mechanics, 2025
Editore: GACM

Data-driven MPC for real-time control of nonlinear systems

Autori: D. MARTIN XAVIER, L. CHAMOIN, L. FRIBOURG
Pubblicato in: Digital Twins in Engineering (DTE) & Artificial Intelligence and Computational Methods in Applied Science (AICOMAS), 2025
Editore: ECCOMAS

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

Autori: L. CHAMOIN
Pubblicato in: MORPHO Final Conference, 2025
Editore: ENSAM

Effective reduced-order approximation for fast and robust MCRE-based parametric identification of nonlinear history-dependent material laws

Autori: Mainak Bhattacharyya, Ludovic Chamoin
Pubblicato in: Computational Mechanics, Numero 78, 2026, Pagina/e 213-238, ISSN 0178-7675
Editore: Springer Verlag
DOI: 10.1007/s00466-026-02754-1

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

Autori: C. Jailin, A. Benady, R. Legroux, E. Baranger
Pubblicato in: Experimental Mechanics, Numero 64, 2024, Pagina/e 1465-1481, ISSN 0014-4851
Editore: 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

Autori: L. CHAMOIN, S. FARAHBAKHSH, M. PONCELET
Pubblicato in: Measurement Science and Technology, Numero 33:124008, 2022, ISSN 0957-0233
Editore: Institute of Physics and the Physical Society
DOI: 10.1088/1361-6501/ac9152

Noise-bias compensation for the unsupervised learning of constitutive laws

Autori: Clément Jailin, Stéphane Roux, Antoine Benady, Emmanuel Baranger
Pubblicato in: Comptes Rendus. Mécanique, Numero 354, 2026, Pagina/e 1-24, ISSN 1631-0721
Editore: Elsevier Masson
DOI: 10.5802/crmeca.342

MPC surrogates based on supervised or unsupervised learning for the real-time control of nonlinear systems

Autori: Daniel Martin Xavier, Ludovic Chamoin, Laurent Fribourg
Pubblicato in: IFAC Journal of Systems and Control, Numero 36, 2026, Pagina/e 100409, ISSN 2468-6018
Editore: Elsevier BV
DOI: 10.1016/j.ifacsc.2026.100409

Optimal placement of distributed optic fiber sensors with the modified Constitutive Relation Error

Autori: José Andrés Pérez Orozco, Ludovic Chamoin, Julien Cortial, Maya de Buhan, Bruno Soulier
Pubblicato in: Mechanical Systems and Signal Processing, Numero 238, 2025, Pagina/e 113206, ISSN 0888-3270
Editore: Academic Press
DOI: 10.1016/j.ymssp.2025.113206

Training and generalization errors for Underparametrized Neural Networks

Autori: D. MARTIN-XAVIER, L. CHAMOIN, L. FRIBOURG
Pubblicato in: IEEE Control Systems Letters, Numero 7, 2023, Pagina/e 3926-3931, ISSN 2475-1456
Editore: IEEE
DOI: 10.1109/lcsys.2023.3344139

Data-driven material modeling based on the Constitutive Relation Error

Autori: Pierre Ladevèze, Ludovic Chamoin
Pubblicato in: Advanced Modeling and Simulation in Engineering Sciences, Numero 11, 2024, ISSN 2213-7467
Editore: 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

Autori: Hai Nam Nguyen, Ludovic Chamoin
Pubblicato in: Computational Mechanics, Numero 76, 2025, Pagina/e 251-277, ISSN 0178-7675
Editore: Springer Verlag
DOI: 10.1007/s00466-025-02598-1

Investigation of Distributed Optic Fiber Sensors Data Loss Due to Strain Gradient

Autori: S. Farahbakhsh, M. Poncelet, L. Chamoin
Pubblicato in: Experimental Techniques, 2025, ISSN 0732-8818
Editore: Society for Experimental Mechanics
DOI: 10.1007/s40799-025-00847-9

Continuous structural health monitoring with a modified dual Kalman filter applied with optical fiber sensing data

Autori: S. Farahbakhsh, L. Chamoin, M. Poncelet
Pubblicato in: Computers & Structures, Numero 329, 2026, Pagina/e 108284, ISSN 0045-7949
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.compstruc.2026.108284

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

Autori: Antoine Benady, Emmanuel Baranger, Ludovic Chamoin
Pubblicato in: Computer Methods in Applied Mechanics and Engineering, Numero 425, 2024, Pagina/e 116967, ISSN 0045-7825
Editore: 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

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

From data to reality: Criteria for the validation of data-driven models for history-dependent materials

Autori: Pierre Ladevèze, Ludovic Chamoin
Pubblicato in: European Journal of Mechanics - A/Solids, Numero 118, 2026, Pagina/e 106095, ISSN 0997-7538
Editore: Elsevier BV
DOI: 10.1016/j.euromechsol.2026.106095

Optimization of optic fiber sensor placement for structural health monitoring

Autori: Z. ZHOU, B. SOULIER, L. CHAMOIN
Pubblicato in: 2022
Editore: 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

Autori: E. ZEMBRA, A. BENADY, E. BARANGER, L. CHAMOIN
Pubblicato in: 2023
Editore: ENS Paris-Saclay

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

Autori: A. BENADY, F. LEHMANN, A. PULIKKATHODI, E. BARANGER, L. CHAMOIN, F. GATTI, D. CLOUTEAU
Pubblicato in: Journée du GDR I-GAIA, 2023
Editore: CNRS

OFDR optic fiber measurements: performance limitations

Autori: S. FARAHBAKHSH, M. PONCELET, L. CHAMOIN
Pubblicato in: Colloque National Mecamat, 2024
Editore: Mecamat

High resolution strain measurement using optic fiber sensors

Autori: S. FARAHBAKHSH, L. CHAMOIN, M. PONCELET
Pubblicato in: Journées des doctorants du LMPS, 2022
Editore: LMPS, ENS Paris-Saclay

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

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