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ANANKE - 2025

2025Activity‌ reportProject-TeamANANKE

RNSR:‌​‌ 202524721S
  • Research center Inria​​ Saclay Centre
  • In partnership​​​‌ with:Institut Polytechnique de‌ Paris
  • Team name: Analysis‌​‌ And Numerics of physical-Knowledge-based​​ Estimation
  • In collaboration with:​​​‌Centre de Mathématiques Appliquées‌ (CMAP)

Creation of the‌​‌ Project-Team: 2025 September 01​​

Each year, Inria research​​​‌ teams publish an Activity‌ Report presenting their work‌​‌ and results over the​​ reporting period. These reports​​​‌ follow a common structure,‌ with some optional sections‌​‌ depending on the specific​​​‌ team. They typically begin​ by outlining the overall​‌ objectives and research programme,​​ including the main research​​​‌ themes, goals, and methodological​ approaches. They also describe​‌ the application domains targeted​​ by the team, highlighting​​​‌ the scientific or societal​ contexts in which their​‌ work is situated.

The​​ reports then present the​​​‌ highlights of the year,​ covering major scientific achievements,​‌ software developments, or teaching​​ contributions. When relevant, they​​​‌ include sections on software,​ platforms, and open data,​‌ detailing the tools developed​​ and how they are​​​‌ shared. A substantial part​ is dedicated to new​‌ results, where scientific contributions​​ are described in detail,​​​‌ often with subsections specifying​ participants and associated keywords.​‌

Finally, the Activity Report​​ addresses funding, contracts, partnerships,​​​‌ and collaborations at various​ levels, from industrial agreements​‌ to international cooperations. It​​ also covers dissemination and​​​‌ teaching activities, such as​ participation in scientific events,​‌ outreach, and supervision. The​​ document concludes with a​​​‌ presentation of scientific production,​ including major publications and​‌ those produced during the​​ year.

Keywords

Computer Science​​​‌ and Digital Science

  • A6.1.1.​ Continuous Modeling (PDE, ODE)​‌
  • A6.1.2. Stochastic Modeling
  • A6.1.4.​​ Multiscale modeling
  • A6.1.5. Multiphysics​​​‌ modeling
  • A6.2.1. Numerical analysis​ of PDE and ODE​‌
  • A6.3.1. Inverse problems
  • A6.3.2.​​ Data assimilation
  • A6.3.4. Model​​​‌ reduction
  • A6.4.1. Deterministic control​
  • A6.4.2. Stochastic control
  • A6.4.3.​‌ Observability and Controlability
  • A6.4.4.​​ Stability and Stabilization
  • A6.4.6.​​​‌ Optimal control
  • A6.5.1. Solid​ mechanics
  • A6.5.2. Fluid mechanics​‌
  • A6.5.4. Waves
  • A9.2.5. Bayesian​​ methods
  • A9.2.6. Neural networks​​​‌

Other Research Topics and​ Application Domains

  • B1.1.9. Biomechanics​‌ and anatomy
  • B2.2.1. Cardiovascular​​ and respiratory diseases
  • B2.2.7.​​​‌ Virtual human twin
  • B2.6.2.​ Cardiac imaging
  • B2.6.3. Biological​‌ Imaging
  • B3.4.1. Natural risks​​

1 Team members, visitors,​​​‌ external collaborators

Research Scientists​

  • Dominique Chapelle [INRIA​‌, Senior Researcher,​​ from Sep 2025,​​​‌ HDR]
  • Sebastien Impériale​ [INRIA, Researcher​‌, from Sep 2025​​, HDR]

Faculty​​​‌ Member

  • Philippe Moireau [​Team leader, ECOLE​‌ POLY PALAISEAU, Professor​​, from Sep 2025​​​‌, HDR]

Post-Doctoral​ Fellow

  • Rodrigo Zelada Mancini​‌ [CEA, Post-Doctoral​​ Fellow, from Sep​​​‌ 2025]

PhD Students​

  • Julien Bonnafe [ESSILOR​‌, CIFRE, from​​ Sep 2025]
  • Martin​​​‌ Chassard [ENPC,​ from Oct 2025]​‌
  • Nagham Chibli [IP​​ PARIS, from Sep​​​‌ 2025]
  • Natacha Guegan–Fau​ [ECOLE POLY PALAISEAU​‌, from Nov 2025​​]
  • Martin Morange [​​​‌ECOLE POLY PALAISEAU,​ from Oct 2025]​‌
  • Zineb Ramiche [INRIA​​, from Sep 2025​​​‌]

Technical Staff

  • Jérôme​ Diaz [INRIA,​‌ Engineer]
  • Colin Drieu​​ [INRIA, Engineer​​​‌, from Sep 2025​]
  • Virgile Dubos [​‌INRIA, Engineer,​​ from Sep 2025]​​​‌
  • Sebastien Gilles [INRIA​, Engineer]
  • François​‌ Kimmig [INRIA,​​ Engineer, from Sep​​​‌ 2025 until Oct 2025​]
  • Matthieu Noel [​‌INRIA, Engineer,​​ from Sep 2025]​​​‌

Administrative Assistant

  • Bahar Carabetta​ [INRIA]

External​‌ Collaborators

  • Jean-Marc Allain [​​ECOLE POLY PALAISEAU,​​​‌ from Sep 2025,​ HDR]
  • Jeanne Brionnet​‌ [AP/HP, from​​ Sep 2025]
  • Matthieu​​ Caruel [UNIV PARIS​​​‌ XII, from Sep‌ 2025]
  • Radomir Chabiniok‌​‌ [UT SOUTHWESTERN,​​ from Sep 2025]​​​‌
  • Louis-Pierre Chaintron [EPFL‌ - Lausanne, from‌​‌ Sep 2025]
  • Martin​​ Genet [ECOLE POLY​​​‌ PALAISEAU, from Sep‌ 2025]
  • Alexandre Imperiale‌​‌ [CEA, from​​ Sep 2025]
  • Alexis​​​‌ Janin [AP/HP,‌ from Sep 2025]‌​‌
  • François Kimmig [François​​ Kimmig, from Nov​​​‌ 2025]
  • Arthur Le‌ Gall [AP/HP,‌​‌ from Sep 2025]​​
  • Adrian Padilla Segarra [​​​‌ONERA, from Sep‌ 2025]

2 Overall‌​‌ objectives

In recent years,​​ the concept of the​​​‌ digital twin has been‌ increasingly used in science‌​‌ and engineering to describe​​ the challenge of developing​​​‌ a numerical avatar of‌ an intended or actual‌​‌ real physical product, system​​ or process. While model-driven​​​‌ approaches based on equations‌ modeling the physics of‌​‌ interest were initially predominant,​​ very effective data-driven approaches​​​‌ are now becoming increasingly‌ popular. However, both approaches‌​‌ should not be played​​ off against each other,​​​‌ as they complement each‌ other. In fact, we‌​‌ believe that digital twin​​ must combine (1) modeling​​​‌ and simulation to create‌ a virtual representation of‌​‌ a physical counterpart mostly​​ based on physical principles​​​‌ and (2) a bidirectional‌ interaction between the virtual‌​‌ and the physical. This​​ bidirectional interaction forms a​​​‌ feedback loop that comprises‌ dynamic data-driven model updating‌​‌ (e.g., sensor fusion, inversion,​​ data assimilation) and optimal​​​‌ decision-making (e.g., control, sensor‌ steering).

In this context,‌​‌ the objective of the​​ Ananke team-project is to​​​‌ formulate and analyze methods‌ for integrating multimodal information‌​‌ sources into causal dynamic​​ physical models with the​​​‌ aim of prediction and‌ control. Our main focus‌​‌ will be dynamical systems​​ modeled by partial differential​​​‌ equations. This framework will‌ cover the mathematical and‌​‌ methodological foundations up to​​ the real applications in​​​‌ different contexts: life sciences,‌ environmental sciences or engineering.‌​‌

We follow a model-driven​​ vision, where we believe​​​‌ that the general concept‌ of digital twin corresponds‌​‌ to a mathematical multimodal​​ coupling between information sources​​​‌ in the same abstraction,‌ as the multiscale coupling‌​‌ is seen as the​​ coupling between physical scales​​​‌ or the multiphysical coupling‌ is understood as the‌​‌ coupling between different physics.​​ And the physical model​​​‌ description is central to‌ unify the different sources‌​‌ of information. In other​​ words, the model should​​​‌ be understood as a‌ common language for the‌​‌ integration of data.

3​​ Research program

  • Optimal control​​​‌ for data assimilation
  • Observer‌ formulation and analysis for‌​‌ PDEs
  • Observability and inverse​​ problems for PDE models​​​‌
  • Analysis and numerical analysis‌ of inverse problems and‌​‌ model-data interaction

4 Application​​ domains

  • Living systems and​​​‌ medical applications, in particular‌ the cardiovascular system
  • Structural‌​‌ health monitoring in engineering,​​ in particular using wave​​​‌ propagation
  • Environmental sciences

5‌ Social and environmental responsibility‌​‌

5.1 Impact of research​​ results

5.1.1 AnaestAssist project​​​‌ and impact for anaesthesia‌

Unstable hemodynamics during general‌​‌ anaesthesia increases the risk​​ of cardiac, renal and​​​‌ brain disfunctions during the‌ postoperative period, thus leading‌​‌ to a higher level​​​‌ of morbidity and mortality.​ To improve the patient's​‌ condition, learned societies therefore​​ recommend monitoring the hemodynamics​​​‌ of the patient and​ having treatment strategies with​‌ quantitative objectives based on​​ this monitoring. Currently, medical​​​‌ doctors have at their​ disposal some physiological signals​‌ (ECG, blood pressure) displayed​​ on their monitor, and​​​‌ must rely on established​ practices and their experience​‌ to act in case​​ of a dangerous drift.​​​‌

The AnaestAssist project proposes​ to develop an augmented​‌ monitoring tool for anaesthesia.​​ The proposed technology will​​​‌ introduce into the monitoring​ loop a predictive biophysical​‌ model, simulated in real​​ time, and fed by​​​‌ the measured physiological signals.​ The model will be​‌ personalised for the patient,​​ thus creating a digital​​​‌ twin of the patient's​ cardiovascular system. With this​‌ digital twin, physiological information​​ that can cannot be​​​‌ measured or that can​ only be obtained with​‌ highly invasive methods will​​ be computed in real​​​‌ time and treatment recommendations​ will be made. Our​‌ system will thus provide​​ a much more complete​​​‌ vision of the patient's​ cardiovascular state and allow​‌ more informed and faster​​ decisions. Eventually, the effects​​​‌ of drugs will be​ included in the model,​‌ which will make it​​ possible to determine (through​​​‌ predictive modeling) adapted action​ recommendations, or even a​‌ real-time automatic drug administration​​ loop. Our technology is​​​‌ expected to allow the​ medical staff to deliver​‌ a better treatment to​​ the patient, to improve​​​‌ the patient's condition through​ a reduction of the​‌ risk related to general​​ anaesthesia and a wiser​​​‌ exposition to drugs, and​ to reduce the costs​‌ for the health care​​ system due to a​​​‌ lower rate of complications​ and shorter hospital stays.​‌

The AnaestAssist project has​​ led to a startup​​​‌ creation in December 2025​ (company name Twynova).

6​‌ Highlights of the year​​

The startup Twynova (born​​​‌ out of Inria, the​ M3DISIM then ANANKE project​‌ team, the AP-HP, the​​ anesthesia and intensive care​​​‌ department at Lariboisière Hospital,​ and the École Polytechnique)​‌ was created on December​​ 29 last year. It​​​‌ is the culmination of​ the AnaestAssist project, which​‌ began to take shape​​ in December 2019 as​​​‌ part of the Inria​ Startup Studio program, then​‌ continued with financial support​​ from the Inria Saclay​​​‌ center and the M3DISIM​ project team, and with​‌ support from the Bernoulli​​ Lab. Twynova's mission is​​​‌ to offer digital twins​ of the cardiovascular system​‌ for various medical applications.​​ These digital twins aim​​​‌ to provide ongoing, even​ real-time, information on the​‌ condition of the person​​ concerned through various physiological​​​‌ and biophysical indicators that​ cannot be measured directly,​‌ in a context where​​ measurements are as non-invasive​​​‌ as possible. The co-founders​ of Twynova are François​‌ Kimmig, who led the​​ AnaestAssist project, Dominique Chapelle​​​‌ (Inria), Philippe Moireau (Ecole​ Polytechnique), and Fabrice Vallée​‌ (AP-HP), joined by Patricia​​ Poon as CEO, with​​​‌ 25 years of business​ development experience in world-class​‌ companies.

7 Latest software​​ developments, platforms, open data​​​‌

We are proud to​ announce the initial opensource​‌ release of the PhysioBlocks​​ Python library 25

PhysioBlocks​​ is designed to simulate​​​‌ the dynamics of physiological‌ systems (in particular cardiovascular‌​‌ systems) represented by block​​ diagrams, in order to​​​‌ provide built-in modularity. Accordingly,‌ a system is represented‌​‌ by a network of​​ modules (blocks) connected by​​​‌ nodes in which they‌ share physical quantities (degrees‌​‌ of freedom) and exchange​​ fluxes, see illustration below.​​​‌ The user can easily‌ create a new network‌​‌ by combining existing blocks.​​ At a more advanced​​​‌ level, new custom blocks‌ can be defined.

The‌​‌ library is distributed under​​ the LGPL licence, and​​​‌ the initial distribution focuses‌ on providing building blocks‌​‌ associated with lumped-parameter (a.k.a.​​ 0D) models of the​​​‌ cardiovascular system. In particular,‌ the 0D cardiac model‌​‌ that has been formulated​​ and elaborated in our​​​‌ team for over a‌ decade is already included‌​‌ in this distribution. In​​ this respect the library​​​‌ aims at replacing our‌ CardiacLab proprietary library.

7.1‌​‌ Latest software developments

7.1.1​​ MoReFEM

  • Name:
    Modeling Research​​​‌ with the Finite Element‌ Method
  • Keywords:
    HPC, Multiphysics‌​‌ modelling, Data assimilation
  • Functional​​ Description:
    MoReFEM is a​​​‌ HPC finite element library‌ for simulating multiphysics evolution‌​‌ problems like the ones​​ encounter in cardiac modeling​​​‌ (electrophysiology, structure and fluid‌ mechanics, transport-diffusion, wave equations)‌​‌
  • URL:
  • Contact:
    Sebastien​​ Gilles
  • Participants:
    Sebastien Gilles,​​​‌ Jerome Diaz, Philippe Moireau,‌ Dominique Chapelle

7.1.2 MoReFEM4Cardiac‌​‌

  • Keywords:
    HPC, Multiphysics modelling,​​ Data assimilation
  • Functional Description:​​​‌
    This is the implementation‌ of the cardiac models‌​‌ of Ananke team (formerly​​ M3DISIM) using the MoReFEM​​​‌ finite element library (https://bil.inria.fr/fr/software/view/3253/tab)‌
  • URL:
  • Contact:
    Jerome‌​‌ Diaz
  • Participants:
    Jerome Diaz,​​ Sebastien Gilles, Matthieu Noel,​​​‌ Philippe Moireau, Dominique Chapelle‌

7.1.3 PhysioBlocks

  • Name:
    PhysioBlocks‌​‌
  • Keywords:
    Block diagram, Dynamical​​ system, Physiology, Cardiovascular and​​​‌ respiratory systems, Data assimilation,‌ Kalman filter
  • Functional Description:‌​‌
    The PhysioBlocks library is​​ designed to simulate the​​​‌ dynamics of physiological systems‌ (in particular cardiovascular systems)‌​‌ represented by block diagrams.​​ A system is thus​​​‌ represented by a network‌ of modules (blocks) connected‌​‌ by nodes in which​​ they share quantities (degrees​​​‌ of freedom) and exchange‌ flows. The user can‌​‌ easily create a new​​ network by combining existing​​​‌ modules. At a more‌ advanced level, new modules‌​‌ can be defined. In​​ addition, the library is​​​‌ designed from the outset‌ to enable data assimilation‌​‌ using Kalman filter-type methods,​​ in particular for parameter​​​‌ estimation.
  • Release Contributions:
    V1‌ for opensource distribution
  • URL:‌​‌
  • Contact:
    Dominique Chapelle​​
  • Participants:
    Colin Drieu, Dominique​​​‌ Chapelle, François Kimmig, Philippe‌ Moireau

7.1.4 HELEN

  • Name:‌​‌
    Heart Estimator For Live​​ Evaluation in aNesthesia
  • Keywords:​​​‌
    Low rank models, Dimensionality‌ reduction, Cardiovascular and respiratory‌​‌ systems, Kalman filter, Dynamical​​ system
  • Functional Description:
    Real-time​​​‌ fractional heartbeat simulation for‌ on-board monitoring devices. Certified‌​‌ models and implementation with​​ respect to numerical errors.​​​‌ Estimation of state and‌ parameters by sequential filtering‌​‌ for model inversion.
  • Release​​ Contributions:
    Launching simulations from​​​‌ option files in text‌ format Choice of modeling‌​‌ components from the option​​ file Simulation results exported​​​‌ in csv format and‌ visualization module available. Modules‌​‌ for the direct problem​​ and the inverse problem​​​‌ (Kalman filter type algorithm).‌ Unit tests implemented and‌​‌ workflow implementation on Inria's​​​‌ continuous integration platform. Non-regression​ tests implemented (integration test)​‌ and implementation of the​​ workflow on Inria's continuous​​​‌ integration platform
  • Contact:
    Philippe​ Moireau
  • Participants:
    Laurent Steff,​‌ Sebastien Gilles, François Kimmig,​​ Dominique Chapelle, Philippe Moireau​​​‌

7.1.5 PhysioDataVisualisation

  • Keyword:
    Data​ visualization
  • Functional Description:
    -​‌ data visualization in the​​ form of time series​​​‌ - dashboard for visualizing​ a digital twin
  • Release​‌ Contributions:
    initial version
  • Contact:​​
    François Kimmig
  • Participants:
    François​​​‌ Kimmig, Alexis Janin
  • Partner:​
    Assistance Publique - Hôpitaux​‌ de Paris

7.1.6 ToolboxDigitalTwin​​

  • Keywords:
    Data management, Post-processing,​​​‌ Data processing, Digital twin​
  • Functional Description:
    The ToolboxDigitalTwin​‌ library is designed to​​ provide tools for manipulating​​​‌ high-frequency time signals and​ linking them to digital​‌ models. The main features​​ provided by the library​​​‌ are: • data management​ • data visualization •​‌ data preprocessing • extraction​​ of data subsequences •​​​‌ preparation of simulation option​ files • collection and​‌ post-processing of simulation results​​ • production of output​​​‌ results (figures, tables, etc.).​
  • Release Contributions:
    initial version​‌
  • Contact:
    François Kimmig
  • Participants:​​
    François Kimmig, Alexis Janin​​​‌
  • Partner:
    Assistance Publique -​ Hôpitaux de Paris

7.1.7​‌ AnaestAssistDemo

  • Keywords:
    Digital twin,​​ Demonstration, Monitoring, Cardiovascular system​​​‌
  • Functional Description:
    - component​ for connecting to a​‌ Kafka data stream -​​ link with external library​​​‌ for the implementation of​ a method for building​‌ a cardiovascular digital twin​​ - real-time display of​​​‌ results
  • Release Contributions:
    initial​ version
  • Contact:
    François Kimmig​‌
  • Participants:
    François Kimmig, Alexis​​ Janin
  • Partner:
    Assistance Publique​​​‌ - Hôpitaux de Paris​

7.1.8 AKILLES

  • Name:
    Agnostic​‌ Kalman Inference parraLLEl Strategies.​​
  • Keywords:
    Kalman filter, Data​​​‌ assimilation
  • Functional Description:
    This​ library concerns sequential data​‌ assimilation algorithms and more​​ particularly of the Uscented​​​‌ Kalman Filter type (Normal,​ Reduced, Transformed etc.). The​‌ principle is to communicate​​ the sigma-points representing the​​​‌ model instances via a​ message exchange library (here​‌ ZeroMQ). Thus each particle​​ calculates in parallel with​​​‌ the others, and the​ core of the algorithm​‌ in C ++ can​​ cooperate with models written​​​‌ in any language.
  • Contact:​
    Philippe Moireau
  • Participants:
    Laurent​‌ Steff, Sebastien Gilles, Philippe​​ Moireau

8 New results​​​‌

8.1 Mathematical foundations of​ dynamical model-data interaction for​‌ digital twins formulation

8.1.1​​ Estimation problems for conservative​​​‌ collective models

Participants: Martin​ Morange, Philippe Moireau​‌.

Over the past​​ decades, population dynamics and​​​‌ related biological models have​ provided a rich source​‌ of interactions between analysis,​​ probability, and partial differential​​​‌ equations, with many models​ naturally expressed as conservative​‌ PDEs whose solutions are​​ probability measures. In this​​​‌ context, the Wasserstein distance,​ originating from optimal transport​‌ theory, has emerged as​​ a natural metric, and​​​‌ the development of gradient​ flow theory in Wasserstein​‌ spaces has revealed deep​​ connections between classical PDEs​​​‌ and variational structures on​ spaces of probability measures.​‌

This work, in collaboration​​ with Vincent Calvez, aims​​​‌ to extend the framework​ of deterministic data assimilation​‌ to Wasserstein spaces from​​ a control-theoretic perspective. Data​​​‌ assimilation seeks to combine​ prior information given by​‌ a dynamical model with​​ observational data, and in​​​‌ finite dimensions this problem​ is classically addressed by​‌ the Mortensen observer, a​​ nonlinear generalization of the​​ Kalman filter closely related​​​‌ to Hamilton-Jacobi-Bellman (HJB) equations.‌ Motivated by recent advances‌​‌ on HJB equations and​​ control problems in Wasserstein​​​‌ spaces, we investigate how‌ deterministic filtering and observer‌​‌ design can be formulated​​ in the infinite-dimensional setting​​​‌ of probability measures.

We‌ first study Luenberger-type observers‌​‌ for chemotaxis systems and​​ propose a first extension​​​‌ of the Mortensen observer‌ to a simple Wasserstein‌​‌ framework, together with a​​ corresponding discretization strategy. We​​​‌ also address parameter estimation‌ problems for PDEs posed‌​‌ in Wasserstein spaces, analyzing​​ both optimal filtering approaches​​​‌ for linear PDEs and‌ the dependence of solutions‌​‌ to equations on model​​ parameters. Overall, this work​​​‌ lays theoretical and numerical‌ foundations for data assimilation‌​‌ and parameter identification in​​ PDE models whose natural​​​‌ state space is the‌ Wasserstein space of probability‌​‌ measures, with applications to​​ models such as chemotaxis​​​‌ and polymerization.

8.1.2 Stability‌ analysis of a new‌​‌ curl-based full field reconstruction​​ method in 2D isotropic​​​‌ nearly-incompressible elasticity

Participants: Nagham‌ Chibli, Sébastien Imperiale‌​‌ [correspondant].

In time-harmonic​​ elastography, the shear modulus​​​‌ is typically inferred from‌ full-field displacement data by‌​‌ solving an inverse problem​​ based on the time-harmonic​​​‌ elastodynamic equation. In this‌ work, done in collaboration‌​‌ with Martin Genet (LMS,​​ École polytechnique) we focus​​​‌ on nearly incompressible media,‌ which pose robustness challenges,‌​‌ especially in the presence​​ of noisy data. Restricting​​​‌ ourselves to 2D and‌ considering an isotropic, linearly‌​‌ deforming medium, we reformulate​​ the problem as a​​​‌ non-autonomous hyperbolic system and,‌ through theoretical analysis, establish‌​‌ existence, uniqueness, and stability​​ of the inverse problem.​​​‌ To ensure robustness with‌ noisy data, we propose‌​‌ a least-squares approach with​​ regularization. The convergence properties​​​‌ of the method are‌ verified numerically using in‌​‌ silico data.

8.1.3 Optimal​​ virtual fields for inverse​​​‌ problems in elasticity

Participants:‌ Nagham Chibli, Sébastien‌​‌ Imperiale [correspondant].

This​​ work, done in collaboration​​​‌ with Martin Genet, addresses‌ the identification of nonhomogeneous‌​‌ constitutive parameters from full-field​​ measurements in both linear​​​‌ and nonlinear elasticity, considering‌ incompressible as well as‌​‌ compressible materials. The inverse​​ identification procedure relies on​​​‌ the Virtual Fields Method‌ (VFM), which is based‌​‌ on the principle of​​ virtual work with specifically​​​‌ chosen virtual fields. We‌ propose an optimal class‌​‌ of virtual fields, designed​​ to isolate each elastic​​​‌ coefficient within the virtual‌ work formulation, thereby optimizing‌​‌ the reconstruction stability with​​ respect to measurement noise.​​​‌ A series of numerical‌ experiments illustrate the effectiveness‌​‌ of the proposed approach.​​ The method exhibits moderate​​​‌ sensitivity to measurement noise‌ and remains robust even‌​‌ when the boundary conditions​​ are only partially known.​​​‌

8.1.4 Multiscale analysis of‌ wave propagation in complex‌​‌ media in the branched-flow​​ regime

Participants: Natacha Guegan-Feu​​​‌ [correspondant], Sébastien Imperiale‌, Josselin Garnier [Team‌​‌ ASCII].

The aim​​ of this work is​​​‌ to characterize the properties‌ of a wave field‌​‌ propagating in a complex​​ medium (in underwater acoustics​​​‌ or optics) in a‌ specific regime denoted the‌​‌ branched flow regime. More​​ precisely we are interested​​​‌ in studying solutions of‌ the wave equation in‌​‌ a smooth random media​​​‌ with random initial data​ in the paraxial regime.​‌ In a well chosen​​ regime where the correlation​​​‌ length of the initial​ field is larger than​‌ the wavelength but smaller​​ than the correlation length​​​‌ of the medium, numerical​ simulations (performed using the​‌ Split-Step Fourier Method) show​​ that the wave intensity​​​‌ forms branches of large​ intensity. A main aspect​‌ of the work is​​ to justify this phenomena​​​‌ by means of an​ asymptotic analysis of the​‌ random solutions of the​​ paraxial equations. In particular​​​‌ by carefully choosing the​ scales of the various​‌ parameters involved, we recover,​​ thank to the use​​​‌ of Wigner transforms, statistical​ informations (averaged intensities and​‌ moments of the field)​​ explaining the observed phenomena.​​​‌

8.1.5 Semi-discrete convergence analysis​ of a numerical method​‌ for waves in nearly-incompressible​​ media with spectral finite​​​‌ elements

Participants: Sébastien Imperiale​ [correspondant], Zineb Ramiche​‌.

In this work,​​ we present a convergence​​​‌ analysis of a fully​ explicit high-order space discretisation​‌ approach for the computation​​ of elastic field propagation​​​‌ in a nearly incompressible​ media. Our approach relies​‌ on the use of​​ high-order continuous spectral finite​​​‌ elements with mass-lumping. We​ present an approach that​‌ is valid for full​​ hexahedral and quadrilateral meshes,​​​‌ where the elastic field​ is sought in the​‌ space of k​​ continuous finite elements and​​​‌ the pressure in ℚ​k-2 discontinuous​‌ finite elements. Furthermore, we​​ provide proof of the​​​‌ stability of the finite​ element discretization. This allows​‌ us to carry out​​ error estimates for the​​​‌ semi-discrete problem in space,​ accounting in particular for​‌ quadrature errors.

8.1.6 Solving​​ inverse source wave problem​​​‌ from Carleman estimates to​ observer design

Participants: Tiphaine​‌ Delaunay [Team MONC],​​ Sébastien Imperiale, Philippe​​​‌ Moireau [correspondant].

In​ the work 13,​‌ done in collaboration with​​ Muriel Boulakia (LMV Versailles),​​​‌ Maya de Buhan (Safran),​ we are interested by​‌ the identification in a​​ wave equation of a​​​‌ space dependent source term​ multiplied by a known​‌ time and space dependent​​ function, from internal velocity​​​‌ or field measurements. The​ first part of the​‌ work consists in proving​​ stability inequalities associated with​​​‌ this inverse problem from​ adapted Carleman estimates. Then,​‌ we present a sequential​​ reconstruction strategy which is​​​‌ proved to be equivalent​ to the minimization of​‌ a cost functional with​​ Tikhonov regularization. Based on​​​‌ the obtained stability estimates,​ the reconstruction error is​‌ evaluated with respect to​​ the noise intensity. Finally,​​​‌ the proposed method is​ illustrated with numerical simulations,​‌ both in the case​​ of regular source terms​​​‌ and of piecewise constant​ source terms.

8.1.7 Mathematical​‌ analysis of an observer​​ for solving inverse source​​​‌ wave problem

Participants: Tiphaine​ Delaunay [Team MONC],​‌ Sébastien Imperiale [correspondant],​​ Philippe Moireau.

The​​​‌ objective of 15,​ done in collaboration with​‌ Tiphaine Delaunay (IMB, Inria​​ Monc, Bordeaux), is to​​​‌ propose a method using​ observers to estimate a​‌ source term of a​​ wave equation from internal​​​‌ measurements in a subdomain.​ The first part of​‌ the work consists in​​ proving an identifiability result​​ from classical observability conditions​​​‌ for wave equations. We‌ show that the source‌​‌ reconstruction is an ill-posed​​ inverse problem of degree​​​‌ 1 or 2 depending‌ on the measurements type.‌​‌ This inverse problem is​​ solved using observers –​​​‌ a sequential strategy –‌ that is proven to‌​‌ be equivalent to a​​ minimization of a cost​​​‌ functional with Tikhonov regularization.‌

8.1.8 Asymptotic analysis of‌​‌ a class of abstract​​ stiff wave propagation problems​​​‌

Participants: Sébastien Imperiale [correspondant]‌.

This work addresses‌​‌ the mathematical analysis, by​​ means of asymptotic analysis,​​​‌ of a class of‌ linear wave propagation problems‌​‌ with singular stiff terms​​ represented by a single​​​‌ small parameter. This abstract‌ setting is defined using‌​‌ linear operators in Hilbert​​ spaces. In this setting,​​​‌ we show, under some‌ assumptions on the structure‌​‌ of the wave propagation​​ problems, weak and strong​​​‌ convergence of solutions with‌ respect to the small‌​‌ parameter towards the solution​​ of a well-defined limit​​​‌ problem. Applications in nearly‌ incompressible elastodynamics, elastic waves‌​‌ in thin plates, piezoelectricity,​​ and homogenization are presented.​​​‌ This work has led‌ to the publication 18‌​‌

8.1.9 Fully explicit numerical​​ scheme for linearized wave​​​‌ propagation in nearly-incompressible soft‌ hyperelastic solids

Participants: Jean-Marc‌​‌ Allain [correspondant], Sébastien​​ Imperiale.

The numerical​​​‌ approximation of wave propagation‌ problems in nearly or‌​‌ pure incompressible solids faces​​ several challenges such as​​​‌ locking and stability constraints.‌ In this work, done‌​‌ incollaboration with Giulia Merlini​​ (ENPC, Marne-la-Vallée), we propose​​​‌ a stabilized Leapfrog scheme‌ based on the use‌​‌ of Chebyshev polynomials to​​ relax the stability condition,​​​‌ which is strongly limited‌ by the enforcement of‌​‌ incompressibility. The scheme is​​ fully explicit, second order​​​‌ accurate and energy-preserving. For‌ the space discretization we‌​‌ use a mixed formulation​​ with high-order spectral elements​​​‌ and mass-lumping. A strategy‌ is proposed for an‌​‌ efficient and accurate computation​​ of the pressure contribution​​​‌ with a new definition‌ of the discrete Grad-div‌​‌ operator. Finally, we consider​​ linear wave propagation problems​​​‌ in nearly-incompressible hyperelastic solids‌ subject to static preload.‌​‌ This work has led​​ to the publication 19​​​‌

8.1.10 Asymptotic approaches in‌ inverse problems for depolymerization‌​‌ estimation

Participants: Marie Doumic​​ [Team MERGE], Philippe​​​‌ Moireau [correspondant].

Depolymerization‌ reactions constitute frequent experiments,‌​‌ for instance in biochemistry​​ for the study of​​​‌ amyloid fibrils. The quantities‌ experimentally observed are related‌​‌ to the time dynamics​​ of a quantity averaged​​​‌ over all polymer sizes,‌ such as the total‌​‌ polymerised mass or the​​ mean size of particles.​​​‌ The question analysed in‌ 16 is to link‌​‌ this measurement to the​​ initial size distribution. To​​​‌ do so, we first‌ derive, from the initial‌​‌ reaction system two asymptotic​​ models: at first order,​​​‌ a backward transport equation,‌ and at second order,‌​‌ an advection-diffusion/Fokker-Planck equation complemented​​ with a mixed boundary​​​‌ condition at x=‌0. We estimate‌​‌ their distance to the​​ original system solution. We​​​‌ then turn to the‌ inverse problem, i.e., how‌​‌ to estimate the initial​​ size distribution from the​​​‌ time measurement of an‌ average quantity, given by‌​‌ a moment of the​​​‌ solution. This question has​ been already studied for​‌ the first order asymptotic​​ model, and we analyse​​​‌ here the second order​ asymptotic. Thanks to Carleman​‌ inequalities and to log-convexity​​ estimates, we prove observability​​​‌ results and error estimates​ for a Tikhonov regularization.​‌

We then develop a​​ Kalman-based observer approach, and​​​‌ implement it on simulated​ observations. Despite its severely​‌ ill-posed character, the secondorder​​ approach appears numerically more​​​‌ accurate than the first-order​ one.

8.2 Digital twin​‌ applications

8.2.1 Finite element​​ modelling for the reproduction​​​‌ of dynamic OCE measurements​ in the cornea

Participants:​‌ Jean-Marc Allain [correspondant],​​ Sébastien Imperiale.

Recent​​​‌ advances in dynamic elastography,​ particularly through optical coherence​‌ tomography combined with transient​​ excitations have enabled rapid,​​​‌ localized, and non-invasive mechanical​ data acquisition of the​‌ cornea. This data opens​​ the path to early-detection​​​‌ of pathologies and more​ accurate treatment. However, the​‌ analysis of the wave​​ propagation is a complex​​​‌ mechanical problem: the cornea​ is a structure under​‌ pressure, with non-linear material​​ behavior. Thus, computational analysis​​​‌ are needed to extract​ mechanical parameters from the​‌ data. In this study,​​ done in collaboration with​​​‌ Giulia Merlini (ENPC, Marne-la-Vallée),​ we present a time-dependent​‌ finite element model for​​ the reproduction of transient​​​‌ shear wave elastographic measurements​ in the cornea. The​‌ mechanical problem consists in​​ a smallamplitude wave propagating​​​‌ in the cornea, largely​ deformed by intraocular pressure​‌ in physiological conditions. The​​ model accounts for anisotropic,​​​‌ hyperelastic, and incompressible behavior​ of the cornea, as​‌ well as its accurate​​ geometry, and the preloaded​​​‌ condition. We have implemented​ two different numerical approaches​‌ to solve first the​​ static non-linear inflation of​​​‌ the cornea and then​ the linear wave propagation​‌ problem to reproduce the​​ measurements. We investigate the​​​‌ impact of material anisotropy​ and prestress on wave​‌ propagation and demonstrate that​​ intraocular pressure critically influences​​​‌ shear wave velocity. Additionally,​ by introducing a localized​‌ mechanical defect to simulate​​ a pathological defect, we​​​‌ show that simulated shear​ wave can detect and​‌ quantify mechanical weaknesses, suggesting​​ potential as a diagnostic​​​‌ tool to assess corneal​ health. This work has​‌ led to the publication​​ 20.

8.2.2 Venous​​​‌ return 0D model

Participants:​ Alexis Janin, François​‌ Kimmig, Dominique Chapelle​​.

Starting from a​​​‌ venous model designed by​ D. Chapelle and F.​‌ Kimmig, we investigated the​​ calibration of the model​​​‌ using respiratory trials. This​ led us to revise​‌ some of the Frank-Starling/Guyton​​ paradigm, and dig out​​​‌ the impact of the​ various parameters involved, as​‌ well as their sensitivity.​​ We also investigated which​​​‌ components of the model​ were missing to align​‌ on the physiology for​​ the various cases we​​​‌ aimed to reproduce. Lastly,​ we derived a new​‌ way of presenting the​​ Frank-Starling/Guyton curves, combining the​​​‌ relevant informations in a​ single curve, more aligned​‌ with the physiological concerns.​​ This work is part​​​‌ of the Diip_Heart project​ (PEPR Santé Numérique).

8.2.3​‌ Automatically generated cardiovascular digital​​ twin in critical care:​​​‌ a proof of concept​ study

Participants: François Kimmig​‌ [correspondant], Fabrice Vallée​​ [AP-HP Hôpital Lariboisière, Inserm​​ U942 MASCOT], Dominique​​​‌ Chapelle, Philippe Moireau‌.

This proof of‌​‌ concept study demonstrates the​​ capabilities of a virtually​​​‌ automatically generated digital twin‌ framework for enhancing hemodynamic‌​‌ monitoring in critical care.​​ By combining a deterministic​​​‌ cardiovascular model with patient-specific‌ data through data assimilation‌​‌ techniques, the digital twin​​ can act as a​​​‌ data denoiser, reconstruct physiological‌ waveforms that are typically‌​‌ unavailable in critical care​​ settings and generate clinically​​​‌ relevant biomarkers. Validation was‌ performed using real data‌​‌ from patients under general​​ anesthesia. The proposed framework​​​‌ efficient calibration and ability‌ to follow the patient's‌​‌ state over time supports​​ the possibility of real-time​​​‌ bedside applications. This has‌ led to the conference‌​‌ paper 22, with​​ a longer version in​​​‌ preparation for journal submission.‌

8.2.4 Left heart hemodynamics‌​‌ simulations with fluid-structure interaction​​ and reduced valve modeling​​​‌

Participants: Oscar Ruz [COMMEDIA]‌, Jerôme Diaz [correspondant]‌​‌, Marina Vidrascu [COMMEDIA]​​, Philippe Moireau,​​​‌ Dominique Chapelle, Miguel‌ Fernandez [Team COMMEDIA].‌​‌

The combination of reduced​​ models of cardiac valve​​​‌ dynamics with a one-way‌ kinematic uncoupling of blood‌​‌ flow and electromechanics is​​ a widespread approach for​​​‌ reducing the complexity of‌ cardiac hemodynamics simulations. This‌​‌ comes however with a​​ number of shortcomings: artificial​​​‌ pressure oscillations, missing isovolumetric‌ phases and valve laws‌​‌ without precise continuous formulation.​​ This paper is aimed​​​‌ at overcoming these three‌ difficulties while still mitigating‌​‌ computational cost. A novel​​ reduced model of valve​​​‌ dynamics is proposed in‌ which unidirectional flow is‌​‌ enforced in a mathematically​​ sound fashion. Artificial pressure​​​‌ oscillations are overcome by‌ considering a fluid-structure interaction‌​‌ model, which couples bi-ventricular​​ electromechanics and blood flow​​​‌ in the left cavities.‌ The interface coupling is‌​‌ solved in a partitioned​​ fashion via an unconditionally​​​‌ stable loosely coupled scheme.‌ A priori energy estimates‌​‌ are derived for both​​ the continuous coupled problem​​​‌ and its numerical approximation.‌ The benefits and limitations‌​‌ of the proposed approaches​​ are illustrated in a​​​‌ comprehensive numerical study. This‌ work has been published‌​‌ in 21.

8.2.5​​ Objective assessment of cardiac​​​‌ function using patient-specific biophysical‌ modeling based on cardiovascular‌​‌ MRI combined with catheterization​​

Participants: Dominique Chapelle [correspondant]​​​‌, Radomir Chabiniok [UTSW‌ Dallas], Maria Gusseva‌​‌ [UTSW Dallas].

This​​ is a collaborative work​​​‌ with UTSW Dallas Medical‌ Center and Boston Children's‌​‌ Hospital. Synthesizing multi-modality data,​​ such as cardiovascular magnetic​​​‌ resonance imaging (MRI) combined‌ with catheterization, into a‌​‌ single framework is challenging.​​ Different acquisition systems are​​​‌ subjected to different measurement‌ errors. Coupling clinical data‌​‌ with biomechanical models can​​ assist in clinical data​​​‌ processing (e.g., model-based filtering‌ of measurement noise) and‌​‌ quantify myocardial mechanics via​​ metrics not readily available​​​‌ in the data, such‌ as myocardial contractility. In‌​‌ this work we use​​ a biomechanical modeling with​​​‌ the aim 1) to‌ quantitatively compare model- and‌​‌ data-derived signals, and 2)​​ to explore the potential​​​‌ of model-derived myocardial contractility‌ and distal resistance of‌​‌ the circulation (Rd) to​​ robustly quantify cardiovascular physiology.​​​‌ We used 51 ventricular‌ catheterization pressure and cine‌​‌ MRI volume datasets from​​​‌ patients with single-ventricle physiology​ and left and right​‌ ventricles of patients with​​ repaired tetralogy of Fallot.​​​‌ Ventricular time-varying elastance (TVE)​ metrics and linear regression​‌ were used to quantify​​ the relationship between the​​​‌ maximum value of TVE​ (Emax) and maximum time​‌ derivative of ventricular pressure​​ (max(dP/dt)) in data- and​​​‌ model-derived pressure and volume​ signals at p<0.05. Pearson’s​‌ correlations were used to​​ compare model-derived contractility and​​​‌ data-derived Emax and max(dP/dt),​ and model-derived Rd and​‌ data-derived vascular resistance. All​​ data and model-derived linear​​​‌ regressions were significant (p<0.05).​ Model-derived max(dP/dt) vs. data-derived​‌ Emax produced higher R2​​ than data-derived max(dP/dt) vs.​​​‌ data-derived Emax. Correlations demonstrated​ significant relationships between most​‌ data- and model-derived metrics.​​ This work revealed the​​​‌ clinical value of biomechanical​ modeling to assist in​‌ clinical data processing by​​ providing high-quality pressure and​​​‌ volume signals, and to​ quantify cardiovascular pathophysiology. This​‌ work has been published​​ as 17.

8.2.6​​​‌ Modeling and simulation of​ hydro-acoustic waves for geophysics​‌

Participants: Natacha Guegan-Feu [correspondant]​​, Sébastien Imperiale,​​​‌ Jacques Sainte-Marie [Team ANGE​ - Sorbonne Université].​‌

This work has been​​ done in collaboration with​​​‌ Juliette Dubois (TU Berlin)​ and Anne Mangeney (IPG).​‌ We aimed at investigating​​ the generation and propagation​​​‌ of hydro-acoustic and seismic​ waves due to landslides.​‌ The governing equations are​​ formulated in both Eulerian​​​‌ and Lagrangian coordinates and​ subsequently linearized. Corresponding linearized​‌ transmission conditions at the​​ ocean–seabed interface are derived.​​​‌ Focusing on the case​ where the deviatoric component​‌ of the prestress vanishes,​​ a variational framework is​​​‌ developed to establish the​ well-posedness and stability of​‌ the model.

The problem​​ is implemented using the​​​‌ library C++ OndomathX employing​ the spectral finite element​‌ method. To simulate an​​ unbounded domain, two approaches​​​‌ are employed: introducing dissipation​ terms and constructing a​‌ Perfectly Matched Layer (PML).​​ The ocean is represented​​​‌ as a barotropic fluid,​ while two models are​‌ considered for the Earth:​​ a rigid solid and​​​‌ an elastic solid. The​ elastic solid is described​‌ by the full elastic​​ equations, providing a physically​​​‌ realistic representation, whereas the​ rigid model imposes a​‌ Dirichlet boundary condition, offering​​ reduced computational cost.

Numerical​​​‌ simulations reveal substantial differences​ between the two Earth​‌ models. In particular, head​​ waves in the fluid​​​‌ are absent in the​ rigid case. Those waves​‌ are important for the​​ early detection of landslides​​​‌ since they propagates faster​ than acoustic waves in​‌ the fluid.

9 Partnerships​​ and cooperations

9.1 National​​​‌ initiatives

9.1.1 MEDITWIN

Participants:​ Dominique Chapelle, Philippe​‌ Moireau, Colin Drieu​​, Matthieu Noel,​​​‌ Virgile Dubos.

MediTwin​ is an i-Démo project​‌ funded by France 2030.​​ It ambitions to offer​​​‌ digital twins for medical​ applications, for better diagnosis​‌ and treatment, in neurology,​​ cardiology and oncology. Coordinated​​​‌ by Dassault-Systèmes, it involves​ Inria as sole academic​‌ partner, together with seven​​ French University Hospital Institutes​​​‌ (IHUs) and a few​ other private and public​‌ actors.

In this project,​​ the team operates within​​​‌ the infrastructure-oriented workpackage (WP5)​ and will develop software​‌ tools that are essential​​ ingredients in the construction​​ of digital twins, namely,​​​‌ for simulation and estimation‌ purposes. All these tools‌​‌ will be shared within​​ the consortium during the​​​‌ project, and a major‌ part of them will‌​‌ also be distributed as​​ opensource software.

The project​​​‌ is funded for 5‌ years (2024-2029), funding for‌​‌ the team 1,160,000 euros.​​

9.1.2 PREMYOM

Participants: Jean-Marc​​​‌ Allain, Julien Bonafe‌.

The PREMYOM project‌​‌ (Prise en charge et​​ Ralentissement de l'Epidémie de​​​‌ MYopie par l'Optique Médicale),‌ focused on medical optics-based‌​‌ solutions to slow down​​ the global myopia epidemic,​​​‌ aims to establish the‌ Gold Standard for personalized‌​‌ myopia treatment through rigorous​​ investigation, development, and delivery.​​​‌

PREMYOM is a multidisciplinary‌ consortium of well-known partners‌​‌ from industry, healthcare and​​ research, coordinated by EssilorLuxottica,​​​‌ bringing an unprecedented blend‌ of technical, clinical, and‌​‌ digital expertise: Hôpital Fondation​​ Adolphe de Rothschild, Institut​​​‌ Français de Myopie, Inria,‌ InSimo, Institut Mines-Télécom, and‌​‌ Institut de la Vision.​​

The project is part​​​‌ of the France 2030‌ plan and i-Demo-2 State‌​‌ funding, highlighting the critical​​ importance of addressing children's​​​‌ visual health as a‌ major public health issue‌​‌ and tackling European myopia​​ epidemic

The project is​​​‌ funded for 5 years‌ (2024-2029) with 500,000 euros‌​‌ for the team for​​ a total budget of​​​‌ 3 million euros.

9.1.3‌ ANR Elastoheart

Participants: Philippe‌​‌ Moireau, Sébastien Imperiale​​, Dominique Chapelle,​​​‌ Zineb Ramiche.

The‌ objective of this project‌​‌ (212,000 euros for the​​ team) is to develop​​​‌ in collaboration with “Institut‌ Mondor de recherche biomédicale”'‌​‌ (Creteil) and “Physique pour​​ la Medecine”' Inserm group​​​‌ a comprehensive mathematical and‌ numerical modeling (direct and‌​‌ inverse) of 3D Shear-Wave​​ (SW) propagation in cardiac​​​‌ realistic physiological models, and‌ to demonstrate in vivo‌​‌ that shear velocity can​​ assess important cardiac function​​​‌ and characteristics in experimental‌ pathological models and in‌​‌ patients.

9.1.4 PEPR santé​​ numérique - DiipHeart project​​​‌

Participants: François Kimmig,‌ Dominique Chapelle, Philippe‌​‌ Moireau.

This project​​ is led by the​​​‌ Inserm team U942 MASCOT.‌ It aims to set‌​‌ up elements of augmented​​ monitoring in the perioperative​​​‌ period allowing to anticipate‌ all serious cardiovascular events‌​‌ (total grant: 1.8 million​​ euros, team grant: 253,000​​​‌ euros).

9.1.5 PEPR Math-Vives‌ - MesoCardio project

Participants:‌​‌ Sebastien Imperiale, Dominique​​ Chapelle, Philippe Moireau​​​‌.

This project establishes‌ an interdisciplinary consortium to‌​‌ develop models of cardiac​​ contraction at the mesoscopic​​​‌ scale, enabling the simulation‌ of the physiological mechanisms‌​‌ involved in its regulation.​​ The consortium brings together​​​‌ two mathematics laboratories (CERMICS,‌ ENPC and ANANKE, Inria,‌​‌ France), a biomechanics laboratory​​ (MSME, UPEC, France), and​​​‌ a physiology laboratory (PhysioLab,‌ University of Florence, Italy).‌​‌ The work program encompasses​​ statistical mechanics modeling, mathematical​​​‌ analysis of stochastic systems,‌ nonlinear continuum mechanics and‌​‌ homogenization, the development of​​ innovative numerical methods, and​​​‌ in situ experiments.

The‌ project is funded for‌​‌ 5 years (2025-2030), 150,000​​ euros for the team​​​‌ (overall budget 600,000 euros)‌

9.1.6 Other funding

  • AP-HP‌​‌ FHU-Carnot - MAJOR project​​ (72,000 euros)

    Participants: François​​​‌ Kimmig, Alexis Janin‌, Dominique Chapelle.‌​‌

    The MAJOR project is​​​‌ led by the anesthesia​ department of Lariboisière Hospital​‌ (AP-HP) and also involves​​ the Inria team COMMEDIA.​​​‌ The project MAJOR aims​ to extend to the​‌ augmented monitoring tools developed​​ in the AnaestAssist project​​​‌ to intensive care, which​ requires to incorporate the​‌ pulmonary system into the​​ models (total grant: 250,000​​​‌ euros).

  • Programme Audace! CEA​ - (100,000 euros)

    Participants:​‌ Rodrigo Zelada Mancini,​​ Philippe Moireau.

    The​​​‌ Audace! Program of CEA​ is the new Seed​‌ Grant program initiated and​​ hosted by CEA. In​​​‌ this program, our project,​ "Characterization of Nonlinear Ultrasonic​‌ Responses through Data Assimilation,"​​ aims to identify cracks​​​‌ or delamination defects in​ complex materials used in​‌ the energy sector (e.g.,​​ welded metallic materials or​​​‌ laminated composite materials) using​ ultrasonic testing. To achieve​‌ this objective, we propose​​ with Alexandre Imperiale from​​​‌ CEA to develop sequential​ methods for assimilating nonlinear​‌ response data from these​​ defects. These strategies aim​​​‌ to filter experimental data​ by incorporating it into​‌ a suitable dynamic system,​​ thereby enabling real-time updating​​​‌ of the characteristics of​ the defects being sought.​‌ Several obstacles must be​​ addressed in this context:​​​‌ the development of accurate​ and effective modeling tools,​‌ the consideration of nonlinearities​​ in the data assimilation​​​‌ method, and the use​ of noisy data.

10​‌ Dissemination

10.1 Promoting scientific​​ activities

10.1.1 Scientific events:​​​‌ organisation

General chair, scientific​ chair
  • Philippe Moireau –​‌ Organizer and Chair of​​ the mini-symposium “Digital twins​​​‌ of living systems: theoretical,​ implementation & application challenges”​‌ with Martin Genet. DTE​​ & AICOMAS 2025, Paris.​​​‌
Member of the organizing​ committees
  • Sébastien Imperiale –​‌ Member of the organizing​​ committee of PDEs and​​​‌ Numerical Analysis IPP day,​ July 2025

10.1.2 Scientific​‌ events: selection

Member of​​ the conference program committees​​​‌
  • Philippe Moireau – is​ the president of the​‌ scientific committee for the​​ conference “Data Assimilation and​​​‌ Inverse Problems for Biomedical​ Problems”, which will be​‌ held in Nantes in​​ 2026.

10.1.3 Journal

Member​​​‌ of the editorial boards​
  • Dominique Chapelle – Member​‌ of the editorial board​​ of journal ESAIM:M2AN
Reviewer​​​‌ - reviewing activities
  • Dominique​ Chapelle – Reviewer for​‌ “FIMH Conference”
  • François Kimmig​​ – Reviewer for “FIMH​​​‌ Conference”
  • Philippe Moireau –​ Reviewer for “IMA Journal​‌ of Numerical Analysis”, “ESAIM:​​ Control, Optimisation and Calculus​​​‌ of Variations”, “Journal of​ Uncertainty Quantification”, “MathInAction” and​‌ “FIMH Conference”
  • Sébastien Imperiale​​ – Reviewer for “IMA​​​‌ Journal of Numerical Analysis”,​ “Numerische Mathematik”, “Mathematics of​‌ computations”, “Journal of Mathematical​​ Analysis and Applications” and​​​‌ “SIAM Journal on Scientific​ Computing”

10.1.4 Invited talks​‌

  • Philippe Moireau – Symposium​​ in the honor of​​​‌ Patrick Le Tallec, Dec​ 2025

10.1.5 Leadership within​‌ the scientific community

  • Philippe​​ Moireau has been elected​​​‌ Director of the Mathematics​ Departement of Institut Polytechnique​‌ de Paris
  • Dominique Chapelle​​ is the scientific director​​​‌ of the Bernouilli Lab​

10.1.6 Research administration

  • Dominique​‌ Chapelle is the scientific​​ director of the joint​​​‌ AP-HP-Inria laboratory “Daniel Bernoulli”​
  • Dominique Chapelle is a​‌ member of the steering​​ committee of the interdisciplinary​​​‌ center “Engineering for Health”​ (E4H) of IPP
  • Philippe​‌ Moireau is Director of​​ the Mathematics Departement of​​ Institut Polytechnique de Paris​​​‌

10.2 Teaching - Supervision‌ - Juries - Educational‌​‌ and pedagogical outreach

10.2.1​​ Teaching

  • Bachelor: Nagham Chibli​​​‌ , “Linear Algebra”, 56h,‌ École Polytechnique.
  • Master: Martin‌​‌ Morange and Natacha Guegan-Feu​​ , Teaching assistant, “Introduction​​​‌ to numerical analysis: from‌ mathematics fundamentals to numerical‌​‌ experiments with Jupyter”, 14h,​​ (M1), École polytechnique, France​​​‌
  • Master: Sébastien Imperiale –‌ “APM42031 – Analyse variationnelle',‌​‌ 40h, M1, École polytechnique​​
  • Master: Philippe Moireau –​​​‌ “APM42031 – Analyse variationnelle',‌ 40h, M1, École polytechnique‌​‌
  • Master: Dominique Chapelle –​​ “5MSE3 – Modélisation mathématique​​​‌ et estimation en biomécanique‌ cardiaque – De la‌​‌ théorie aux applications médicales”,​​ 9h, M2, IP-Paris and​​​‌ Université Paris-Saclay
  • Master: Sébastien‌ Imperiale – “AMS306 –‌​‌ Techniques de discrétisation avancées​​ pour les problèmes d'évolutions”,​​​‌ 18h, M2, IP-Paris and‌ Université Paris-Saclay
  • Master: Philippe‌​‌ Moireau – “5MS05 –​​ Complétion de données et​​​‌ identification dans les problèmes‌ gouvernés par des équations‌​‌ aux dérivées partielles”, 16h,​​ M2, IP-Paris and Université​​​‌ Paris-Saclay
  • Master: Philippe Moireau‌ – “5MSE3 – Modélisation‌​‌ mathématique et estimation en​​ biomécanique cardiaque – De​​​‌ la théorie aux applications‌ médicales”, 16h, M2, IP-Paris‌​‌ and Université Paris-Saclay
  • Sebastien​​ Gilles and Jerôme Diaz​​​‌ , Introduction to Modern‌ C++, in collaboration with‌​‌ V. Rouvreau and L.​​ Steff, 5 days of​​​‌ teaching for engineers, PhD‌ students and researchers, Inria‌​‌ Saclay, France

10.2.2 Supervision​​

  • M2: Jeanne Brionnet, “Monitorage​​​‌ hémodynamique par jumeau numérique‌ chez les patients en‌​‌ défaillance circulatoire”, supervisors: Fabrice​​ Vallée and François Kimmig,​​​‌ Université Paris-Saclay, defended June‌ 2025
  • Medical thesis: Jeanne‌​‌ Brionnet, “Du monitorage du​​ débit cardiaque au monitorage​​​‌ augmenté par la modélisation‌ cardio-vasculaire : résultats préliminaires‌​‌ de l'étude CardioTwin”, supervisors:​​ Fabrice Vallée and François​​​‌ Kimmig, Université Paris-Saclay, defended‌ October 2025
  • PhD in‌​‌ progress: Martin Chassard ,​​ “When optimal control of​​​‌ PDEs meets Neural Networks”',‌ started 10/2025, supervisors: V.‌​‌ Ehrlacher, D. Lombardi, P.​​ Moireau
  • PhD in progress:​​​‌ Nagham Chibli , “Mathematical‌ and numerical analysis of‌​‌ inverse problems methods for​​ soft tissue quasi-static elastography”,​​​‌ started 11/2023, supervisors: S.‌ Imperiale and M. Genet‌​‌
  • PhD in progress: Natacha​​ Guegan-Feu , “Multiscale analysis​​​‌ of wave propagation in‌ complex media in the‌​‌ branched-flow regim”, started 11/2025,​​ supervisors: J. Garnier and​​​‌ S. Imperiale
  • PhD defended:‌ Gaël Le Ruz ,‌​‌ “Optimal estimation in manifolds”​​ defended 12/2025, supervisors: D.​​​‌ Lombardi, P. Moireau
  • PhD‌ in progress: Martin Morange‌​‌ , “When optimal estimation​​ meets population dynamics”, started​​​‌ 10/2025, supervisors: V. Calvez,‌ P. Moireau
  • PhD in‌​‌ progress: Raphaël Terrine [Team​​ POEMS], “Identification of seabed​​​‌ deformations using measurements on‌ the free surface. Mathematical‌​‌ and numerical approach”', started​​ 10/2023, supervisors: L. Bourgeois,​​​‌ P. Moireau
  • PhD in‌ progress: Zineb Ramiche ,‌​‌ “Mathematical and numerical modeling​​ of shear-wave propagation in​​​‌ the heart in the‌ context of elastography”, started‌​‌ 10/2022, supervisors: S. Imperiale​​
  • PhD in progress: Juilen​​​‌ Bonnafé , “Biomechanical modeling‌ of the eye movements”,‌​‌ started 09/2023; supervisor: J.M.​​ Allain

10.2.3 Juries

  • Dominique​​​‌ Chapelle – PhD Jury‌ (co-supervisor) of Oscar Ruz,‌​‌ LJLL Sorbone Université, 01/2025​​
  • Sébastien Imperiale – PhD​​​‌ Jury (examinateur) of Romain‌ Mottier, Ecole des ponts,‌​‌ 07/2025
  • Sébastien Imperiale –​​​‌ PhD Jury (rapporteur) of​ Arjeta HetA, Université de​‌ Pau et des pays​​ de l'Adour, 01/2025
  • Philippe​​​‌ Moireau – Master Program​ Jury for M1 J.​‌ Hadamard (Saclay) and M2​​ Analyse Modelisation Simulation (Saclay)​​​‌ and mathématiques de la​ modélisation (IP-Paris)
  • Philippe Moireau​‌ – PhD Jury (reviewer)​​ of Oscar Ruz, LJLL​​​‌ Sorbone Université, 01/2025
  • Philippe​ Moireau – PhD Jury​‌ (reviewer) of Jesper Schroder,​​ Institute of Mathematics, TU​​​‌ Berlin 03/2025
  • Philippe Moireau​ – PhD Jury (co-supervisor)​‌ of Gaël Le Ruz,​​ Sorbone Université, Dec 2025​​​‌
  • Philippe Moireau – SMAI​ Gamni PhD Thesis Prize,​‌ 04/2025
  • Philippe Moireau –​​ Associate Professor Jury Engineering4Health​​​‌ Ecole Polytechnique, 06/2025

10.3​ Popularization

10.3.1 Productions (articles,​‌ videos, podcasts, serious games,​​ ...)

  • Sébastien Imperiale –​​​‌ Popularization article: “Modeling refines​ observation of the heart​‌ and cornea” for inria.fr​​

10.3.2 Others science outreach​​​‌ relevant activities

  • Sebastien Gilles​ – Fête de la​‌ Science Université Paris Saclay​​ - 3 octobre (public​​​‌ scolaire niveau collège et​ lycée) et 4 octobre​‌ (grand public)
  • Sebastien Gilles​​ – Accueil des stagiaires​​​‌ de 3e - décembre​ 2025 - atelier de​‌ médiation scientifique (3 h)​​
  • SSebastien Gilles –​​​‌ Accueil de stagiaires de​ 2nde - juin 2025​‌ - atelier de médiation​​ scientifique (1h30)

11 Scientific​​​‌ production

11.1 Major publications​

11.2 Publications of the​​​‌ year

International journals

International​​​‌ peer-reviewed conferences

Doctoral dissertations and habilitation​​ theses

  • 23 thesisG.​​​‌Gaël Le Ruz.​ Optimal observer theory in​‌ manifolds – from formulations​​ to applications.Sorbonne​​​‌ universitéDecember 2025HAL​

Reports & preprints