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. A Reduced Order Approach for the Embedded Shifted Boundary FEM and a Heat Exchange System on Parametrized Geometries. In: IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018. IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018. Springer International Publishing; 2020. Available from: https://arxiv.org/abs/1807.07753
. A Reduced Order Cut Finite Element method for geometrically parametrized steady and unsteady Navier–Stokes problems. Computer & Mathematics With Applications [Internet]. 2021 . Available from: https://www.sciencedirect.com/science/article/pii/S0898122121002790
. Reduced order isogeometric analysis approach for pdes in parametrized domains. Lecture Notes in Computational Science and Engineering [Internet]. 2020 ;137:153-170. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089615035&doi=10.1007%2f978-3-030-48721-8_7&partnerID=40&md5=7b15836ae65fa28dcfe8733788d7730c
. Reduced Order Methods for Modeling and Computational Reduction. 1st ed. Milano: Springer; 2014 p. 334.
. Reduced order methods for parametric optimal flow control in coronary bypass grafts, toward patient-specific data assimilation. International Journal for Numerical Methods in Biomedical EngineeringInternational Journal for Numerical Methods in Biomedical EngineeringInt J Numer Meth Biomed Engng [Internet]. 2020 ;n/a(n/a):e3367. Available from: https://onlinelibrary.wiley.com/doi/10.1002/cnm.3367?af=R
. Reduced Order Methods for Parametrized Non-linear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences. In: Numerical Mathematics and Advanced Applications ENUMATH 2019. Vol. 139. Numerical Mathematics and Advanced Applications ENUMATH 2019. Springer; 2021. pp. 841–850. Available from: https://arxiv.org/abs/1912.07886
. Reduced Order Methods for Parametrized Non-linear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences. In: Numerical Mathematics and Advanced Applications ENUMATH 2019. Numerical Mathematics and Advanced Applications ENUMATH 2019. Cham: Springer International Publishing; 2021. Available from: https://www.springerprofessional.de/en/reduced-order-methods-for-parametrized-non-linear-and-time-depen/19122676
. A reduced order model for investigating the dynamics of the Gen-IV LFR coolant pool. Applied Mathematical Modelling [Internet]. 2017 ;46:263-284. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020006623&doi=10.1016%2fj.apm.2017.01.066&partnerID=40&md5=f6e5715037eb0ef2ecb9ae03f373294f
. A reduced order model for multi-group time-dependent parametrized reactor spatial kinetics. 22nd International Conference on Nuclear Engineering ICONE22 [Internet]. 2014 :V005T17A048-V005T17A048. Available from: http://urania.sissa.it/xmlui/handle/1963/35123
. A reduced order modeling technique to study bifurcating phenomena: Application to the gross-pitaevskii equation. SIAM Journal on Scientific Computing [Internet]. 2020 . Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096768803&doi=10.1137%2f20M1313106&partnerID=40&md5=47d6012d10854c2f9a04b9737f870592
. Reduced order models for the incompressible Navier-Stokes equations on collocated grids using a `discretize-then-project' approach. International Journal for Numerical Methods in Fluids [Internet]. 2021 ;93:2694–2722. Available from: https://doi.org/10.1002/fld.4994
. A Reduced Order technique to study bifurcating phenomena: application to the Gross-Pitaevskii equation. SIAM Journal on Scientific Computing [Internet]. 2020 . Available from: https://arxiv.org/abs/1907.07082
. A reduced order variational multiscale approach for turbulent flows. Advances in Computational Mathematics [Internet]. 2019 ;45:2349-2368. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068076665&doi=10.1007%2fs10444-019-09712-x&partnerID=40&md5=af0142e6d13bbc2e88c6f31750aef6ad
. Reduced-order semi-implicit schemes for fluid-structure interaction problems. In: Model Reduction of Parametrized Systems. Model Reduction of Parametrized Systems. Springer International Publishing; 2017. pp. 149–167.
. Reduced-order semi-implicit schemes for fluid-structure interaction problems. In: Model Reduction of Parametrized Systems. Model Reduction of Parametrized Systems. Springer International Publishing; 2017. pp. 149–167.
. A reduced-order shifted boundary method for parametrized incompressible Navier–Stokes equations. Computer Methods in Applied Mechanics and Engineering [Internet]. 2020 ;370. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087886522&doi=10.1016%2fj.cma.2020.113273&partnerID=40&md5=d864e4808190b682ecb1c8b27cda72d8
. A reduced-order strategy for solving inverse Bayesian identification problems in physiological flows. SISSA; 2013.
. Reduction strategies for PDE-constrained oprimization problems in Haemodynamics. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2012) J. Eberhardsteiner et.al. (eds.), Vienna, Austria, 10-14 sept. 2012 [Internet]. 2012 . Available from: http://hdl.handle.net/1963/6338
. Shape Optimization by Free-Form Deformation: Existence Results and Numerical Solution for Stokes Flows. [Internet]. 2014 . Available from: http://urania.sissa.it/xmlui/handle/1963/34698
. Shape Optimization by means of Proper Orthogonal Decomposition and Dynamic Mode Decomposition. In: Technology and Science for the Ships of the Future: Proceedings of NAV 2018: 19th International Conference on Ship & Maritime Research. Technology and Science for the Ships of the Future: Proceedings of NAV 2018: 19th International Conference on Ship & Maritime Research. Trieste, Italy: IOS Press; 2018. Available from: http://ebooks.iospress.nl/publication/49229
. Shape optimization through proper orthogonal decomposition with interpolation and dynamic mode decomposition enhanced by active subspaces. In: 8th International Conference on Computational Methods in Marine Engineering, MARINE 2019. 8th International Conference on Computational Methods in Marine Engineering, MARINE 2019. ; 2019. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075390244&partnerID=40&md5=3e1f2e9a2539d34594caff13766c94b8
. Simulation-based uncertainty quantification of human arterial network hemodynamics. International Journal Numerical Methods Biomedical Engineering. 2012 .
. Special Issue on Reduced Order Models in CFD. International Journal of Computational Fluid Dynamics [Internet]. 2020 ;34:91-92. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084258805&doi=10.1080%2f10618562.2020.1756497&partnerID=40&md5=d9316aad9ba95f244e07379318ebbcba
. A spectral element reduced basis method for navier–stokes equations with geometric variations. Lecture Notes in Computational Science and Engineering. 2020 ;134:561-571.