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. Advances in geometrical parametrization and reduced order models and methods for computational fluid dynamics problems in applied sciences and engineering: overview and perspectives. In: Proceedings of the ECCOMAS Congress 2016, VII European Conference on Computational Methods in Applied Sciences and Engineering,. Proceedings of the ECCOMAS Congress 2016, VII European Conference on Computational Methods in Applied Sciences and Engineering,. Crete, Greece: ECCOMAS; 2016.
. Advances in reduced order methods for parametric industrial problems in computational fluid dynamics. In: Proceedings of the 6th European Conference on Computational Mechanics: Solids, Structures and Coupled Problems, ECCM 2018 and 7th European Conference on Computational Fluid Dynamics, ECFD 2018. Proceedings of the 6th European Conference on Computational Mechanics: Solids, Structures and Coupled Problems, ECCM 2018 and 7th European Conference on Computational Fluid Dynamics, ECFD 2018. ; 2020. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075395686&partnerID=40&md5=fb0b1a3cfdfd35a104db9921bc9be675
. On the Application of Reduced Basis Methods to Bifurcation Problems in Incompressible Fluid Dynamics. Journal of Scientific Computing. 2017 .
. An artificial neural network approach to bifurcating phenomena in computational fluid dynamics. 2021 .
. ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis. Software Impacts. 2021 ;10:100133.
. Basic ideas and tools for projection-based model reduction of parametric partial differential equations. In: Model Order Reduction, Volume 2 Snapshot-Based Methods and Algorithms. Model Order Reduction, Volume 2 Snapshot-Based Methods and Algorithms. Berlin, Boston: De Gruyter; 2020. pp. 1 - 47. Available from: https://www.degruyter.com/view/book/9783110671490/10.1515/9783110671490-001.xml
. BladeX: Python Blade Morphing. The Journal of Open Source Software. 2019 ;4:1203.
. Boundary control and shape optimization for the robust design of bypass anastomoses under uncertainty. Mathematical Modelling and Numerical Analysis, in press, 2012-13 [Internet]. 2012 . Available from: http://hdl.handle.net/1963/6337
. Certi fied Reduced Basis Method for Affinely Parametric Isogeometric Analysis NURBS Approximation. In: Spectral and High Order Methods for Partial Differential Equations . Vol. 119. Bittencourt, Dumont, Hesthaven. (Eds). Spectral and High Order Methods for Partial Differential Equations . Heildeberg: Springer; 2017.
. Certified Reduced Basis Approximation for the Coupling of Viscous and Inviscid Parametrized Flow Models. Journal of Scientific Computing [Internet]. 2018 ;74:197-219. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017156114&doi=10.1007%2fs10915-017-0430-y&partnerID=40&md5=023ef0bb95713f4442d1fa374c92a964
. Certified Reduced Basis Methods for Parametrized Partial Differential Equations. 1st ed. Switzerland: Springer; 2015 p. 135.
. Certified Reduced Basis VMS-Smagorinsky model for natural convection flow in a cavity with variable height. Computers and Mathematics with Applications [Internet]. 2020 ;80:973-989. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085843368&doi=10.1016%2fj.camwa.2020.05.013&partnerID=40&md5=7c6596865ec89651319c7dd97159dd77
. On a certified smagorinsky reduced basis turbulence model. SIAM Journal on Numerical Analysis [Internet]. 2017 ;55:3047-3067. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039928218&doi=10.1137%2f17M1118233&partnerID=40&md5=221d9cd2bcc74121fcef93efd9d3d76c
. A combination between the reduced basis method and the ANOVA expansion: On the computation of sensitivity indices. Comptes Rendus Mathematique. Volume 351, Issue 15-16, August 2013, Pages 593-598 [Internet]. 2013 . Available from: http://hdl.handle.net/1963/7389
. Combined parameter and model reduction of cardiovascular problems by means of active subspaces and POD-Galerkin methods. In: Mathematical and Numerical Modeling of the Cardiovascular System and Applications. Mathematical and Numerical Modeling of the Cardiovascular System and Applications. Springer; 2018. pp. 185–207.
. Comparison between reduced basis and stochastic collocation methods for elliptic problems. [Internet]. 2014 . Available from: http://urania.sissa.it/xmlui/handle/1963/34727
. Comparison of a Modal Method and a Proper Orthogonal Decomposition approach for multi-group time-dependent reactor spatial kinetics. Annals of Nuclear Energy [Internet]. 2014 ;71:229. Available from: http://urania.sissa.it/xmlui/handle/1963/35039
. On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis. Computers & Fluids [Internet]. 2021 ;216:104819. Available from: https://www.sciencedirect.com/science/article/pii/S0045793020303893
. A comparison of reduced-order modeling approaches using artificial neural networks for PDEs with bifurcating solutions. ETNA - Electronic Transactions on Numerical Analysis. 2022 ;56:52–65.
. A complete data-driven framework for the efficient solution of parametric shape design and optimisation in naval engineering problems. In: VIII International Conference on Computational Methods in Marine Engineering. VIII International Conference on Computational Methods in Marine Engineering. ; 2019. Available from: https://arxiv.org/abs/1905.05982
. A complete data-driven framework for the efficient solution of parametric shape design and optimisation in naval engineering problems. 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-s2.0-85075342565&partnerID=40&md5=d76b8a1290053e7a84fb8801c0e6bb3d
. Computational methods in cardiovascular mechanics. In: Cardiovascular Mechanics. Cardiovascular Mechanics. CRC Press; 2018. p. 54. Available from: https://www.taylorfrancis.com/books/e/9781315280288/chapters/10.1201%2Fb21917-5
. Computational reduction strategies for the detection of steady bifurcations in incompressible fluid-dynamics: Applications to Coanda effect in cardiology. Journal of Computational Physics. 2017 ;344:557.