Publications

2025

• Inverse Uncertainty Quantification for Personalized Biomechanical Modeling: Application to Pulmonary Poromechanical Digital Twins
  
  • Peyraut A.
  • Genet M.
  Journal of Biomechanical Engineering, American Society of Mechanical Engineers, 2025, 147 (8), pp.081003. The development of personalized models is a key step for addressing various problems, especially in biomechanics. These models typically include many constants, introduced in the model material law or loading definition, and their estimation is crucial for the model personalization. However, performing solely the estimation does not yield any information on the estimation accuracy. Additionally, all parameters can typically not be estimated based only on clinical data: some parameters are identified, while others are fixed at generic values. The question of the identifiability of the parameters, along with the robustness of the estimation, notably to measurement errors and to model errors, is therefore crucial and should be quantitatively addressed in parallel to the model development. In this paper, we propose a general inverse uncertainty quantification pipeline based on the creation of synthetic data—for which the parameters ground-truth values are known—generated for different noise and model error levels. Estimation is then performed for many realizations of the noise or model errors, as well as parameter initializations, until convergence of the estimated parameters error distributions. This pipeline was applied to a poromechanical lung model for illustration and validation purposes. It provides quantitative information on the actual identifiability of the parameters, and any derived quantity of interest, in the clinical setting. In particular, it allows us to retrieve a confidence interval for each estimated parameter, which represents valuable information for diagnosis or prognosis use of the estimated values. This work is therefore a step toward improving the reliability of digital twins pipelines. (10.1115/1.4068578)
  DOI : 10.1115/1.4068578
• Deformation of synthetic rock salt investigated by X-Ray micro-computed tomography: Effect of brine, confining pressure and loading rate
  
  • Du Nina
  • Bornert Michel
  • Dimanov Alexandre
  • Aimedieu Patrick
  • King Andrew
  , 2025, pp.438-447. The development of micro-cracks in rock salt has been studied in 3D. In order to investigate the influence of brine, dry and humid materials have been synthetized by powder compaction. We present results of in situ X-Ray micro-tomography triaxial tests performed on the PSICHE beamline of Synchrotron SOLEIL. We have explored different loading rates and confining pressures for both types of synthetic rock salt.
• Finite Element Neural Network Interpolation. Part I: Interpretable and Adaptive Discretization for Solving PDEs
  
  • Škardová Kateřina
  • Daby-Seesaram Alexandre
  • Genet Martin
  Computational Mechanics, Springer Verlag, 2025. We present the Finite Element Neural Network Interpolation (FENNI) framework, a sparse neural network architecture extending previous work on Embedded Finite Element Neural Networks (EFENN) introduced with the Hierarchical Deep-learning Neural Networks (HiDeNN). Due to their mesh-based structure, EFENN requires significantly fewer trainable parameters than fully connected neural networks, with individual weights and biases having a clear interpretation. Our FENNI framework, within the EFENN framework, brings improvements to the HiDeNN approach. First, we propose a reference element-based architecture where shape functions are defined on a reference element, enabling variability in interpolation functions and straightforward use of Gaussian quadrature rules for evaluating the loss function. Second, we propose a pragmatic multigrid training strategy based on the framework's interpretability. Third, HiDeNN's combined rh-adaptivity is extended from 1D to 2D, with a new Jacobian-based criterion for adding nodes combining h- and r-adaptivity. From a deep learning perspective, adaptive mesh behavior through rh-adaptivity and the multigrid approach correspond to transfer learning, enabling FENNI to optimize the network's architecture dynamically during training. The framework's capabilities are demonstrated on 1D and 2D test cases, where its accuracy and computational cost are compared against an analytical solution and a classical FEM solver. On these cases, the multigrid training strategy drastically improves the training stage's efficiency and robustness. Finally, we introduce a variational loss within the EFENN framework, showing that it performs as well as energy-based losses and outperforms residual-based losses. This framework is extended to surrogate modeling over the parametric space in Part II. (10.1007/s00466-025-02677-3)
  DOI : 10.1007/s00466-025-02677-3
• The Rapid Mechanically Activated (RMA) channel transduces increases in plasma membrane tension into transient calcium influx
  
  • Guerringue Yannick
  • Thomine Sebastien
  • Allain Jean-Marc
  • Frachisse Jean-Marie
  New Phytologist, Wiley, 2025, 251 (1), pp.276-287. Plants respond to mechanical stimuli by a rapid increase in cytosolic calcium. The intensity and kinetics of the calcium changes define calcium signatures important for biological responses . In this study, we determine the properties of a calcium permeable force-gated channel localized at the plasma membrane called Rapid Mechanically Activated (RMA). Using patch-clamp and pressure-clamp, we characterized the kinetics of activation and inactivation of RMA channel upon stimulation by pulses of pressure applied onto the plasma membrane. Combining repetitive pressure pulse protocols at different frequencies with modeling, we investigated the channel's capacity to transduce high frequency mechanical stimuli. RMA channel rapidly activates in response to membrane tension, then it inactivates during prolonged stimulation. Upon repeated stimulations, RMA current amplitude decreases irreversibly indicating that undergoes adaptation. The channel kinetics may be modeled with four chemical states and the model predicts that it behaves as a pass band filter in the 10 Hz -1 kHz range. In conclusion, due to its activation/inactivation characteristics, RMA channel is a candidate to mediate cytosolic calcium signaling in response to mechano-stimulation. Its adaptation and filtering properties suggest its involvement in the transduction of high frequency mechanical stimulation such as those produced by insects' vibrations. (10.1111/nph.71241)
  DOI : 10.1111/nph.71241
• Avoiding cracks in multi-material printing by combining laser powder bed fusion with metallic foils: Application to Ti6Al4V-AlSi12 structures
  
  • Jamili A.M.
  • Jhabvala J.
  • van Petegem S.
  • Weisz-Patrault Daniel
  • Boillat E.
  • Nohava J.
  • Özsoy A.
  • Banait S.
  • Casati N.
  • Logé Roland
  Additive Manufacturing, Elsevier, 2025, 97, pp.104615. Laser powder bed fusion (LPBF) as an additive manufacturing (AM) technology has emerged as a powerful platform for producing multi-material metallic structures. The main drawbacks of using metallic powders for multi-material printing are related to technical issues (i.e. powder contamination reducing the reusability of the powder) and interfacial defects. This paper attempts to demonstrate the advantages of using a combination of metallic powders and thin foils for printing light titanium-aluminum multi-material structures. An AlSi12 powder was printed using the conventional LPBF process and the behavior of the second material feedstock was investigated using both Ti6Al4V powders and foils. The printing process was simulated numerically using a finite element model (FEM), and characterized experimentally through operando X-Ray diffraction (XRD). For the powder-powder combination, cracking near the interface between the two alloys was considered as a combined effect of residual stresses and the presence of brittle intermetallic compounds (IMCs); both were investigated using nanoindentation. Replacing the Ti6Al4V powder by a foil resulted in a thinner layer of Ti-Al IMCs near the interface, and eliminated the large interfacial cracks. The results from FEM and CALPHAD thermodynamic simulations, supported by operando XRD, indicated that the increased thermal conductivity of the foil, compared to powders, led to heat transfer within the foil and to the underlying LPBF structure, prior to local melting. The new thermal regime produced a flawless interface between Ti6Al4V and AlSi12, due to reduced residual stresses in the plane normal to the building direction, and lower volumes of brittle IMCs. It is concluded that using foils instead of powders mitigates cracking and enhances microstructures near the interface, due to changes in thermal regime and alloys mixing patterns. (10.1016/j.addma.2024.104615)
  DOI : 10.1016/j.addma.2024.104615
• Objective assessment of cardiac function using patient-specific biophysical modeling based on cardiovascular MRI combined with catheterization
  
  • Gusseva Maria
  • Castellanos Daniel Alexander
  • Veeram Reddy Surendranath
  • Hussain Tarique
  • Chapelle Dominique
  • Chabiniok Radomír
  AJP - Heart and Circulatory Physiology, American Physiological Society, 2025, 329 (5), pp.H118-H1191. 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. (10.1152/ajpheart.00232.2025)
  DOI : 10.1152/ajpheart.00232.2025
• Experiments and modeling of mechanically-soft, hard magnetorheological foams with potential applications in haptic sensing
  
  • Lin Zehui
  • Hooshmand-Ahoor Zahra
  • Bodelot Laurence
  • Danas Kostas
  Journal of the Mechanics and Physics of Solids, Elsevier, 2025, 203, pp.106218. This study proposes a family of novel mechanically-soft and magnetically-hard magnetorheological foams that, upon deformation, lead to robust and measurable magnetic flux changes in their surroundings. This allows to infer qualitatively and even quantitatively the imposed deformation and, eventually from that, an estimation of the stiffness and average stress on the sample even in complex loading scenarios involving combinations of uniform or nonuniform compression/tension with superposed shearing in different directions. The work provides a complete experimental, theoretical and numerical framework on finite strain, compressible magneto-elasticity, thereby allowing to measure and predict coupled magneto-mechanical properties of such materials with different particle volume fractions and then use it to estimate and design potential haptic sensing devices. (10.1016/j.jmps.2025.106218)
  DOI : 10.1016/j.jmps.2025.106218
• Model-order reduction framework for non-linear dynamics problems involving multiple non-parameterised loading configurations for damage assessment
  
  • Daby-Seesaram Alexandre
  • Néron David
  • Charbonnel Pierre-Étienne
  • Fau Amélie
  Computational Mechanics, Springer Verlag, 2025. (10.1007/s00466-024-02586-x)
  DOI : 10.1007/s00466-024-02586-x