Publications

Below we provide a list of publications that use multiphenics or multiphenicsx.

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Year 2024

  1. J. Aguayo and R. Araya. A priori and a posteriori estimates for a linear elasticity equation with tangential jump condition. Submitted, 2024.

  2. M. Baldelli, G. Di Muccio, A. Sauciuc, B. M. della Rocca, F. Viola, S. Balme, A. Bonini, G. Maglia, and M. Chinappi. Controlling electroosmosis in nanopores without altering the nanopore sensing region. Advanced Materials, pages 2401761, 2024. doi:10.1002/adma.202401761.

  3. F. Ballarin, G. Bevilacqua, L. Lussardi, and A. Marzocchi. Elastic membranes spanning deformable curves. ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, pages e202300890, 2024. doi:10.1002/zamm.202300890.

  4. P. Benedusi, A. J. Ellingsrud, H. Herlyng, and M. E. Rognes. Scalable approximation and solvers for ionic electrodiffusion in cellular geometries. Submitted, 2024. arXiv:2403.04491.

  5. P. Benedusi, P. Ferrari, M. Causemann, and S. Serra-Capizzano. Dense cell-by-cell systems of pdes: approximation, spectral analysis, and preconditioning. Submitted, 2024. arXiv:2409.13432.

  6. E. Burman, R. Durst, M. A. Fernández, J. Guzmán, and S. Liu. A second-order correction method for loosely coupled discretizations applied to parabolic-parabolic interface problems. Submitted, 2024. arXiv:2404.01599.

  7. E. Burman, R. Durst, M. A. Fernández, J. Guzmán, and S. Liu. Estimates of discrete time derivatives for the parabolic-parabolic robin-robin coupling method. Submitted, 2024. arXiv:2404.01594.

  8. S. Cotin, M. Duprez, V. Lleras, A. Lozinski, and K. Vuillemot. Phi-fem: an efficient simulation tool using simple meshes for problems in structure mechanics and heat transfer. In S. P. A. Bordas, A. Menk, and S. Natarajan, editors, Partition of Unity Methods, pages 191–216. John Wiley & Sons, 2024.

  9. A. Gatti, P. Benedusi, and S. Pezzuto. Cell-by-cell modelling of electrical signaling in myelinated axons. Submitted, 2024.

  10. J. Kim, K. H. Kim, and N. Bouklas. Multiphysics modeling of surface diffusion coupled with large deformation in 3d solids. Submitted, 2024. arXiv:2403.06005.

  11. J. Kim, M. S. Sakar, and N. Bouklas. Modeling the mechanosensitive collective migration of cells on the surface and the interior of morphing soft tissues. Biomechanics and Modeling in Mechanobiology, 2024. doi:10.1007/s10237-024-01870-2.

  12. M. Magri and D. Riccobelli. Modelling of initially stressed solids: structure of the energy density in the incompressible limit. Submitted, 2024. arXiv:2403.08432.

  13. A. A. Siddiqui, E. Jessen, S. K. F. Stoter, D. Néron, and D. Schillinger. Reduced order modeling of blood perfusion in parametric multipatch liver lobules. Submitted, 2024. doi:10.21203/rs.3.rs-3906153/v1.

Year 2023

  1. S. Badia, M. Hornkjøl, A. Khan, K.-A. Mardal, A. F. Martín, and R. Ruiz-Baier. Efficient and reliable divergence-conforming methods for an elasticity-poroelasticity interface problem. Submitted, 2023. arXiv:2306.11213.

  2. P. Benedusi, P. Ferrari, M. Rognes, and S. Serra-Capizzano. Modeling excitable cells with the emi equations: spectral analysis and iterative solution strategy. Submitted, 2023. arXiv:2308.12145.

  3. J. Kim, I. Ang, F. Ballarin, C.-Y. Hui, and N. Bouklas. A finite element implementation of finite deformation surface and bulk poroelasticity. Submitted, 2023. arXiv:2305.08805.

  4. H. Mella, E. Sáez, and J. Mura. A hybrid pml formulation for the 2d three-field dynamic poroelastic equations. Submitted, 2023. arXiv:2308.09208.

  5. M. Nonino, F. Ballarin, G. Rozza, and Y. Maday. A reduced basis method by means of transport maps for a fluid–structure interaction problem with slowly decaying Kolmogorov n-width. Advances in Computational Science and Engineering, 1(1):36–58, 2023. doi:10.3934/acse.2023002.

  6. M. Nonino, F. Ballarin, G. Rozza, and Y. Maday. Projection based semi-implicit partitioned reduced basis method for fluid–structure interaction problems. Journal of Scientific Computing, 94(1):4, 2023. doi:10.1007/s10915-022-02049-6.

  7. I. Prusak. Application of optimisation-based domain–decomposition reduced order models to parameter-dependent fluid dynamics and multiphysics problems. PhD thesis, Mathematical Analysis, Modelling, and Applications, SISSA, Italy, Dec. 2023. URL: https://hdl.handle.net/20.500.11767/135830.

  8. F. Rocha, S. Deparis, P. Antolin, and A. Buffa. Deepbnd: a machine learning approach to enhance multiscale solid mechanics. Journal of Computational Physics, 479:111996, 2023. doi:10.1016/j.jcp.2023.111996.

  9. F. Zoccolan, M. Strazzullo, and G. Rozza. A streamline upwind petrov-galerkin reduced order method for advection-dominated partial differential equations under optimal control. Submitted, 2023. arXiv:2301.01973.

  10. F. Zoccolan, M. Strazzullo, and G. Rozza. Stabilized weighted reduced order methods for parametrized advection-dominated optimal control problems governed by partial differential equations with random inputs. Submitted, 2023. arXiv:2301.01975.

Year 2022

  1. V. Anaya, A. Khan, D. Mora, and R. Ruiz-Baier. Robust a posteriori error analysis for rotation-based formulations of the elasticity/poroelasticity coupling. SIAM Journal on Scientific Computing, 44(4):B964–B995, 2022. doi:10.1137/21M1427516.

  2. R. Ciria Aylagas, C. Ganuza, R. Parra, M. Yañez, and E. Ayerbe. Cidemod: an open source tool for battery cell inhomogeneous performance understanding. Journal of The Electrochemical Society, 169(9):090528, 2022. doi:10.1149/1945-7111/ac91fb.

  3. C. Balzotti, P. Siena, M. Girfoglio, A. Quaini, and G. Rozza. A data-driven reduced order method for parametric optimal blood flow control: application to coronary bypass graft. Submitted, 2022. arXiv:2206.15384.

  4. M. Causemann, V. Vinje, and M. E. Rognes. Human intracranial pulsatility during the cardiac cycle: a computational modelling framework. Fluids and Barriers of the CNS, 19(1):84, 2022. doi:10.1186/s12987-022-00376-2.

  5. G. Haine, D. Matignon, and F. Monteghetti. Long-time behavior of a coupled heat-wave system using a structure-preserving finite element method. Mathematical Reports, 22(1-2):187–215, 2022. URL: http://imar.ro/journals/Mathematical_Reports/Pdfs/2022/1-2/11.pdf.

  6. G. Haine, D. Matignon, and F. Monteghetti. Structure-preserving discretization of Maxwell's equations as a port-Hamiltonian system. IFAC-PapersOnLine, 55(30):424–429, 2022. doi:10.1016/j.ifacol.2022.11.090.

  7. M. G. Hennessy, R. V. Craster, and O. K. Matar. Time-dependent modelling of thin poroelastic films drying on deformable plates. Submitted, 2022. arXiv:2210.17229.

  8. T. Kadeethum, F. Ballarin, Y. Choi, D. O'Malley, H. Yoon, and N. Bouklas. Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques. Advances in Water Resources, 160:104098, 2022. doi:10.1016/j.advwatres.2021.104098.

  9. T. Kadeethum, D. O'Malley, Y. Choi, H.S. Viswanathan, N. Bouklas, and H. Yoon. Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties. Computers & Geosciences, 167:105212, 2022. doi:10.1016/j.cageo.2022.105212.

  10. M. Khamlich, F. Pichi, and G. Rozza. Model order reduction for bifurcating phenomena in fluid-structure interaction problems. International Journal for Numerical Methods in Fluids, 94(10):1611–1640, 2022. doi:10.1002/fld.5118.

  11. I. Prusak, M. Nonino, D. Torlo, F. Ballarin, and G. Rozza. An optimisation-based domain-decomposition reduced order model for the incompressible Navier-Stokes equations. Submitted, 2022. arXiv:2211.14528.

  12. Z. Pérez and B. Steven. Implementación del método de elements finitos en FEniCS para problems de fluidos en dominios axisimétricos. Master's thesis, Faculty of Basic Sciences, Pregrado en Matematica, Universidad de Córdoba, Colombia, Mar. 2022. URL: https://repositorio.unicordoba.edu.co/handle/ucordoba/5046.

  13. G. Rozza, G. Stabile, and F. Ballarin. Advanced Reduced Order Methods and Applications in Computational Fluid Dynamics. Computational science and engineering. Society for Industrial and Applied Mathematics, Philadelphia, PA, 2022. ISBN 978-1-611977-24-0. doi:10.1137/1.9781611977257.

  14. L. Shang, C. Hoareau, and A. Zilian. Modeling and simulation of thin-walled piezoelectric energy harvesters immersed in flow using monolithic fluid–structure interaction. Finite Elements in Analysis and Design, 206:103761, 2022. doi:10.1016/j.finel.2022.103761.

Year 2021

  1. E. Donadini, M. Strazzullo, M. Tezzele, and G. Rozza. A data-driven partitioned approach for the resolution of time-dependent optimal control problems with dynamic mode decomposition. Submitted, 2021. arXiv:2111.13906.

  2. E. Fevola, F. Ballarin, L. Jiménez-Juan, S. Fremes, S. Grivet-Talocia, G. Rozza, and P. Triverio. An optimal control approach to determine resistance-type boundary conditions from in-vivo data for cardiovascular simulations. International Journal for Numerical Methods in Biomedical Engineering, 37(10):e3516, 2021. doi:10.1002/cnm.3516.

  3. T. Kadeethum, F. Ballarin, and N. Bouklas. Data-driven reduced order modeling of poroelasticity of heterogeneous media based on a discontinuous Galerkin approximation. GEM - International Journal on Geomathematics, 12:12, 2021. doi:10.1007/s13137-021-00180-4.

  4. T. Kadeethum, S. Lee, F. Ballarin, J. Choo, and H. M. Nick. A locally conservative mixed finite element framework for coupled hydro-mechanical-chemical processes in heterogeneous porous media. Computers & Geosciences, 152:104774, 2021. doi:10.1016/j.cageo.2021.104774.

  5. T. Kadeethum, H. M. Nick, S. Lee, and F. Ballarin. Enriched Galerkin discretization for modeling poroelasticity and permeability alteration in heterogeneous porous media. Journal of Computational Physics, 427:110030, 2021. doi:10.1016/j.jcp.2020.110030.

  6. T. Kadeethum, D. O'Malley, J. N. Fuhg, Y. Choi, J. Lee, H. S. Viswanathan, and N. Bouklas. A framework for data-driven solution and parameter estimation of pdes using conditional generative adversarial networks. Nature Computational Science, 1(12):819–829, 2021. doi:10.1038/s43588-021-00171-3.

  7. M. Nonino, F. Ballarin, and G. Rozza. A monolithic and a partitioned, reduced basis method for fluid-structure interaction problems. Fluids, 6(6):229, 2021. doi:10.3390/fluids6060229.

  8. M. Strazzullo. Model Order Reduction for Nonlinear and Time-Dependent Parametric Optimal Flow Control Problems. PhD thesis, Mathematical Analysis, Modelling, and Applications, SISSA, Italy, Sep. 2021. URL: http://hdl.handle.net/20.500.11767/124559.

  9. Z. Zainib, F. Ballarin, S. Fremes, P. Triverio, L. Jiménez-Juan, and G. Rozza. Reduced order methods for parametric optimal flow control in coronary bypass grafts, towards patient-specific data assimilation. International Journal for Numerical Methods in Biomedical Engineering, 37(12):e3367, 2021. doi:10.1002/cnm.3367.

Year 2020

  1. J. A. Almonacid, G. N. Gatica, R. Oyarzúa, and R. Ruiz-Baier. A new mixed finite element method for the n-dimensional boussinesq problem with temperature-dependent viscosity. Networks and Heterogeneous Media, 15(2):215–245, 2020. doi:10.3934/nhm.2020010.

  2. M. Huck and D.-U. Sauer. Modeling transient processes in lead-acid batteries in the time domain. Journal of Energy Storage, 29:101430, 2020. doi:https://doi.org/10.1016/j.est.2020.101430.

  3. T. Kadeethum, S. Lee, and H. M. Nick. Finite element solvers for Biot's poroelasticity equations in porous media. Mathematical Geosciences, 52(8):977–1015, 2020. doi:10.1007/s11004-020-09893-y.

  4. T. Kadeethum, H. M. Nick, S. Lee, and F. Ballarin. Flow in porous media with low dimensional fractures by employing enriched Galerkin method. Advances in Water Resources, 142:103620, 2020. doi:10.1016/j.advwatres.2020.103620.

  5. E. Korec. Evaluation of accuracy and efficiency of numerical methods for contact problems. Master's thesis, Faculty of Civil Engineering, Department of Mechanics, Czech Technical University in Prague, Czech Republic, May 2020. URL: https://dspace.cvut.cz/bitstream/handle/10467/88830/F1-DP-2020-Korec-Evzen-text.pdf?sequence=-1&isAllowed=y.

  6. S. Lee, T. Kadeethum, and H. M. Nick. Choice of interior penalty coefficient for interior penalty discontinuous Galerkin method for Biot's system by employing machine learning. Submitted, 2020. arXiv:2007.10119.

  7. H. Ramaswamy, S. Dey, and A. A. Oberai. Material parameter optimization for interior and exterior fluid-structure acoustic problems. International Journal for Numerical Methods in Engineering, 121(24):5568–5589, 2020. doi:10.1002/nme.6502.

Year 2019

  1. Z. Zainib. Reduced order parametrized viscous optimal flow control problems and applications in coronary artery bypass grafts with patient-specific geometrical reconstruction and data assimilation. PhD thesis, Mathematical Analysis, Modelling, and Applications, SISSA, Italy, Sep. 2019. URL: http://hdl.handle.net/20.500.11767/103036.