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. 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
. 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
. 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 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
. Reduced order methods for parametrized non-linear and time dependent optimal flow control problems, towards applications in biomedical and environmental sciences. In: ENUMATH2019 proceedings. ENUMATH2019 proceedings. Springer; 2020. Available from: https://arxiv.org/abs/1912.07886
. Reduced order methods for parametric optimal flow control in coronary bypass grafts, toward patient-specific data assimilation. International Journal for Numerical Methods in Biomedical Engineering [Internet]. 2020 . Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087646515&doi=10.1002%2fcnm.3367&partnerID=40&md5=3713db6d2b8f9d079b5534445621decf
. Reduced Order Methods for Modeling and Computational Reduction. 1st ed. Milano: Springer; 2014 p. 334.
. 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
. 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 Computational and Geometrical Framework for Inverse Problems in Haemodynamics. SISSA; 2013.
. Reduced basis model order reduction for Navier–Stokes equations in domains with walls of varying curvature. International Journal of Computational Fluid Dynamics [Internet]. 2020 ;34:119-126. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085233294&doi=10.1080%2f10618562.2019.1645328&partnerID=40&md5=e2ed8f24c66376cdc8b5485aa400efb0
. Reduced Basis Methods for Uncertainty Quantification. SIAM/ASA Journal on Uncertainty Quantification. 2017 ;5(1):869.
. Reduced basis method for the Stokes equations in decomposable domains using greedy optimization. In: ECMI 2014 proceedings. ECMI 2014 proceedings. ; 2014. pp. 1–7.
. Reduced basis method for parametrized elliptic optimal control problems. SIAM Journal on Scientific Computing. 2013 ;35:A2316–A2340.
. Reduced basis method and domain decomposition for elliptic problems in networks and complex parametrized geometries. Computers and Mathematics with Applications . 2016 ;71(1):430.
. Reduced basis approximation of parametrized optimal flow control problems for the Stokes equations. Computers and Mathematics with Applications. 2015 ;69:319–336.
. Reduced basis approximation of parametrized advection-diffusion PDEs with high Péclet number. Lecture Notes in Computational Science and Engineering. 2015 ;103:419–426.
. Reduced Basis Approximation for the Structural-Acoustic Design based on Energy Finite Element Analysis (RB-EFEA). In: CEMRACS 2013 - Modelling and simulation of complex systems: stochastic and deterministic approaches. Vol. 48. CEMRACS 2013 - Modelling and simulation of complex systems: stochastic and deterministic approaches. ; 2013. pp. 98-115.
. Reduced basis approximation and a-posteriori error estimation for the coupled Stokes-Darcy system. Advances in Computational Mathematics. 2015 ;special issue for MoRePaS 2012(in press).
. Reduced basis approximation and a posteriori error estimation for Stokes flows in parametrized geometries: roles of the inf-sup stability constants. Numerische Mathematik, 2013 [Internet]. 2013 . Available from: http://hdl.handle.net/1963/6339
. Reduced Basis Approximation and A Posteriori Error Estimation: Applications to Elasticity Problems in Several Parametric Settings. SEMA SIMAI Springer Series [Internet]. 2018 ;15:203-247. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85055036627&doi=10.1007%2f978-3-319-94676-4_8&partnerID=40&md5=e9c07038e7bcc6668ec702c0653410dc
. Reduced basis approaches in time-dependent noncoercive settings for modelling the movement of nuclear reactor control rods. Communications in Computational Physics [Internet]. 2016 ;(in press). Available from: http://urania.sissa.it/xmlui/handle/1963/34963
. Reduced Basis Approaches for Parametrized Bifurcation Problems held by Non-linear Von Kármán Equations. Journal of Scientific Computing [Internet]. 2019 ;81:112-135. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068973907&doi=10.1007%2fs10915-019-01003-3&partnerID=40&md5=a09af83ce45183d6965cdb79d87a919b
. A reduced basis approach for PDEs on parametrized geometries based on the shifted boundary finite element method and application to a Stokes flow. Computer Methods in Applied Mechanics and Engineering [Internet]. 2019 ;347:568-587. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060107322&doi=10.1016%2fj.cma.2018.12.040&partnerID=40&md5=1a3234f0cb000c91494d946428f8ebef