28 research outputs found
geometrically-reduced-PVS-flow-v1.0
No full textSimulation code, meshes and associated data to reproduce numerical examples presented in "Geometrically reduced modelling of pulsatile flow in perivascular networks", C. Daversin-Catty, I. G. Gjerde and M.E. Rognes (2021)
This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 714892
mechanisms-behind-pvs-flow-v1.0
No full textSimulation code, meshes and associated data to reproduce numerical examples presented in "Mechanisms behind perivascular fluid flow", C. Daversin-Catty, V. Vinje, K-A. Mardal, and M.E. Rognes (2020)
This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 714892
Reduced basis methods and high performance computing. Applications to non-linear multi-physics problems
No full textInternational audienceWe present an open-source framework for the reduced basis methods implemented in the library Feel++ [3,4] and we consider in particular multi-physics, possibly non-linear, applications [1,2] which require high performance computing. We present how the mathematical methodology and technology scale with respect to complexity and the gain obtained in industrial context [1]. We present also briefly our first developments on low-rank methods within our framework with our colleagues from ECN. One of the main application presented is developed with the Laboratoire National des Champs Magnétiques Intenses (LNCMI), a large french equipment, allowing researchers to do experiments with magnetic fields up to 35T provided by water cooled resistive electro-magnet. Existing technologies (material properties,...) are pushed to the limits and users require now specific magnetic field profiles or homogeneous fields. These constraints and the international race for higher magnetic fields demand conception tools which are reliable and robust. The reduced basis methodology is now part of this tool chain. Another domain of application we will consider in the talk is fluid flows, both Stokes and Navier-Stokes.[1] Cécile Daversin, Stéphane Veys, Christophe Trophime, Christophe Prud'Homme. A Reduced Basis Framework: Application to large scale non-linear multi-physics problems http://hal.archives-ouvertes.fr/hal-00786557 [2] Elisa Schenone, Stéphane Veys, Christophe Prud'Homme. High Performance Computing for the Reduced Basis Method. Application to Natural Convection http://hal.archives-ouvertes.fr/hal-00786560[3] http://www.feelpp.org [4] C. Prudhomme, V. Chabannes, V. Doyeux, M. Ismail, A. Samake, G. Pena. Feel++ :A Computational Framework for Galerkin Methods and Advanced NumericalMethods, ESAIM Proc., Multiscale Coupling of Complex Models in Scientific Computing, 38 (2012), 429–455
Reduced basis methods and high performance computing. Applications to non-linear multi-physics problems
No full textInternational audienceWe present an open-source framework for the reduced basis methods implemented in the library Feel++ [3,4] and we consider in particular multi-physics, possibly non-linear, applications [1,2] which require high performance computing. We present how the mathematical methodology and technology scale with respect to complexity and the gain obtained in industrial context [1]. We present also briefly our first developments on low-rank methods within our framework with our colleagues from ECN. One of the main application presented is developed with the Laboratoire National des Champs Magnétiques Intenses (LNCMI), a large french equipment, allowing researchers to do experiments with magnetic fields up to 35T provided by water cooled resistive electro-magnet. Existing technologies (material properties,...) are pushed to the limits and users require now specific magnetic field profiles or homogeneous fields. These constraints and the international race for higher magnetic fields demand conception tools which are reliable and robust. The reduced basis methodology is now part of this tool chain. Another domain of application we will consider in the talk is fluid flows, both Stokes and Navier-Stokes.[1] Cécile Daversin, Stéphane Veys, Christophe Trophime, Christophe Prud'Homme. A Reduced Basis Framework: Application to large scale non-linear multi-physics problems http://hal.archives-ouvertes.fr/hal-00786557 [2] Elisa Schenone, Stéphane Veys, Christophe Prud'Homme. High Performance Computing for the Reduced Basis Method. Application to Natural Convection http://hal.archives-ouvertes.fr/hal-00786560[3] http://www.feelpp.org [4] C. Prudhomme, V. Chabannes, V. Doyeux, M. Ismail, A. Samake, G. Pena. Feel++ :A Computational Framework for Galerkin Methods and Advanced NumericalMethods, ESAIM Proc., Multiscale Coupling of Complex Models in Scientific Computing, 38 (2012), 429–455
Supplementary material (code) for Chapter 2 in 'EMI: Cell based mathematical model of excitable cells'
No full textThis file or directory contains supplementary material (code) for Chapter 2 in 'EMI: Cell based mathematical model of excitable cells' by A. J. Ellingsrud, C. Daversin-Catty M. E. Rognes.
This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 714892
Supplementary material (code) for Chapter 2 in 'Modeling excitable tissue - the EMI framework'
No full textThis file or directory contains supplementary material (code) for Chapter 2 in 'Modeling excitable tissue - the EMI framework' by A. J. Ellingsrud, C. Daversin-Catty M. E. Rognes.
This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 714892
Advances in Feel++: a domain specific embedded language in C++ for partial differential equations
No full textMS404-1 Automation of computational modeling by advanced software tools and techniquesInternational audienceWe present our advances in developing a language specific to partial differential equations embedded in C++. We have been developing the Feel++ framework (Finite Element method Embedded Language in C++) to the point where it allows to use a very wide range of Galerkin methods and advanced numerical methods such as domain decomposition methods including mortar and three fields methods, fictitious domain methods or certified reduced basis. We shall present an overview of the various ingredients as well as some illustrations. The ingredients include a very expressive embedded language, seamless interpolation, mesh adaption, seamless parallelisation and automatic differentiation using Frechet derivative. As to the illustrations, they exercise the versatility of the framework either by allowing the developement and/or numerical verification of (new) mathematical methods or the development of large multi-physics applications -- e.g. fluid-structure interaction using either an Arbitrary Lagrangian Eulerian formulation or a levelset based one; high field magnets modeling which involves electro-thermal, magnetostatics, mechanical and thermo-hydraulics model
A Reduced Basis Framework: Application to large scale non-linear multi-physics problems
No full textIn this paper we present applications of the reduced basis method (RBM) to large-scale
non-linear multi-physics problems. We first describe the mathematical framework in place
and in particular the Empirical Interpolation Method (EIM) to recover an affine
decomposition and then we propose an implementation using the open-source library
Feel++ which provides both the reduced basis and finite element layers. Large
scale numerical examples are shown and are connected to real industrial applications
arising from the High Field Resistive Magnets development at the Laboratoire National des
Champs Magnétiques Intenses
Insights from electromechanical simulations to assess omecamtiv mecarbil efficacy in heart failure
No full text[EN] Heart failure is a cardiac pathology characterized by causing myocardial dysfunction. The need to improve current pharmacotherapy for patients with heart failure has encouraged the development of more promising compounds. Currently, the amount of experimentation required during the early phases of drug development to assess safety and efficacy is costly, but computer simulations can help accelerate the process. In the present study, we performed computer simulations to investigate the electromechanical effects of the sarcomeric drug omecamtiv mecarbil on cardiac tissue. We used a cellular human electromechanical model to develop a concentration-dependent numerical model for the pharmacological compound based on previous experimental evidence. It was then implemented on a ventricular slab to extrapolate cellular activity to myocardial tissue scale, and heart failure with reduced ejection fraction conditions was reproduced. In silico results reveal that omecamtiv mecarbil can correct the depressed active force developed by failing myocytes and make the slab contract to the same extent as in healthy conditions. However, additional changes involving contraction times and diastolic function, measured as the time to active tension peak and baseline slab stretch, respectively, can compromise the pumping capacity of the heart. After exploring drug effects at different heart rates, results show that elevated stimulation frequencies (2 Hz), together with overdoses (omecamtiv mecarbil > 0.8 mu m), are the main factors reducing fractional shortening and leading to loss of function. We demonstrate that electromechanical simulation results can provide a better understanding of the mechanism of action of a drug and facilitate the redirection of future investigations.Key points A new pipeline to assess the efficacy of inotropic drugs based on computational electromechanical models is described. Omecamtiv mecarbil increases developed force in failing cardiac tissue. Undesirable effects on diastolic function and contraction duration override the positive effects. Fast heart rates and elevated omecamtiv mecarbil doses aggravate cardiac dysfunction.This work was partially funded by European Union's Horizon 2020 Framework Programme (SimCardioTest project, grant agreement 101 016 496), and by grant PID2022-140553OB-C41 funded by MICIU/AEI/10.13039/501 100 011 033 and by ERDF/EU. Funding for open access charge: CRUE-Universitat Politecnica de Valencia.Mora-Fenoll, María Teresa;Van Herck, I.;Daversin-Catty, C.;Finsberg, H.;Llopis-Lorente, J.;Saiz Rodríguez, Francisco Javier;Arevalo, H.... (2025). Insights from electromechanical simulations to assess omecamtiv mecarbil efficacy in heart failure. The Journal of Physiology. https://doi.org/10.1113/JP288233
Advances in Feel++: a domain specific embedded language in C++ for partial differential equations
No full textMS404-1 Automation of computational modeling by advanced software tools and techniquesInternational audienceWe present our advances in developing a language specific to partial differential equations embedded in C++. We have been developing the Feel++ framework (Finite Element method Embedded Language in C++) to the point where it allows to use a very wide range of Galerkin methods and advanced numerical methods such as domain decomposition methods including mortar and three fields methods, fictitious domain methods or certified reduced basis. We shall present an overview of the various ingredients as well as some illustrations. The ingredients include a very expressive embedded language, seamless interpolation, mesh adaption, seamless parallelisation and automatic differentiation using Frechet derivative. As to the illustrations, they exercise the versatility of the framework either by allowing the developement and/or numerical verification of (new) mathematical methods or the development of large multi-physics applications -- e.g. fluid-structure interaction using either an Arbitrary Lagrangian Eulerian formulation or a levelset based one; high field magnets modeling which involves electro-thermal, magnetostatics, mechanical and thermo-hydraulics model
