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. An improvement on geometrical parameterizations by transfinite maps. Comptes Rendus Mathematique. 2014 ;352:263–268.
. A hybrid reduced order method for modelling turbulent heat transfer problems. Computers & Fluids [Internet]. 2020 ;208:104615. Available from: https://arxiv.org/abs/1906.08725
. Hybrid Neural Network Reduced Order Modelling for Turbulent Flows with Geometric Parameters. Fluids [Internet]. 2021 ;6:296. Available from: https://doi.org/10.3390/fluids6080296
. Hull Shape Design Optimization with Parameter Space and Model Reductions, and Self-Learning Mesh Morphing. Journal of Marine Science and Engineering [Internet]. 2021 ;9:185. Available from: https://www.mdpi.com/2077-1312/9/2/185
. Hierarchical model reduction techniques for flow modeling in a parametrized setting. Multiscale Modeling and Simulation. 2021 ;19:267-293.
. Generalized reduced basis methods and n-width estimates for the approximation of the solution manifold of parametric PDEs. In: Springer, Indam Series, Vol. 4, 2012. Springer, Indam Series, Vol. 4, 2012. Springer; 2012. Available from: http://hdl.handle.net/1963/6340
. Fundamentals of Reduced Basis Method for problems governed by parametrized PDEs and applications. In: Separated representations and PGD-based model reduction : fundamentals and applications. Vol. 554. Separated representations and PGD-based model reduction : fundamentals and applications. Wien: Springer; 2014.
. Free-form deformation, mesh morphing and reduced-order methods: enablers for efficient aerodynamic shape optimisation. International Journal of Computational Fluid Dynamics. 2018 ;32:233-247.
. Free Form Deformation Techniques Applied to 3D Shape Optimization Problems. Communications in Applied and Industrial Mathematics. 2013 .
. Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier–Stokes equations. Computers and Fluids [Internet]. 2018 ;173:273-284. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85043366603&doi=10.1016%2fj.compfluid.2018.01.035&partnerID=40&md5=c15435ea3b632e55450da19ba2bb6125
. A Finite Volume approximation of the Navier-Stokes equations with nonlinear filtering stabilization. Computers and Fluids [Internet]. 2019 ;187:27-45. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065471890&doi=10.1016%2fj.compfluid.2019.05.001&partnerID=40&md5=c982371b5b5d4b5664a676902aaa60f4
. A Finite Volume approximation of the Navier-Stokes equations with nonlinear filtering stabilization. Computers & Fluids [Internet]. 2019 ;187:27-45. Available from: https://arxiv.org/abs/1901.05251
. EZyRB: Easy Reduced Basis method. The Journal of Open Source Software [Internet]. 2018 ;3:661. Available from: https://joss.theoj.org/papers/10.21105/joss.00661
. Enhancing CFD predictions in shape design problems by model and parameter space reduction. Advanced Modeling and Simulation in Engineering Sciences [Internet]. 2020 ;7(40). Available from: https://arxiv.org/abs/2001.05237
. The Effort of Increasing Reynolds Number in Projection-Based Reduced Order Methods: from Laminar to Turbulent Flows. In: Lecture Notes in Computational Science and Engineering. Lecture Notes in Computational Science and Engineering. Cham: Springer International Publishing; 2020. pp. 245–264.
. An efficient shape parametrisation by free-form deformation enhanced by active subspace for hull hydrodynamic ship design problems in open source environment. The 28th International Ocean and Polar Engineering Conference [Internet]. 2018 . Available from: https://www.onepetro.org/conference-paper/ISOPE-I-18-481
. Efficient reduction in shape parameter space dimension for ship propeller blade design. 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-s2.0-85075395143&partnerID=40&md5=b6aa0fcedc2f88e78c295d0f437824d0
. Efficient Geometrical parametrization for finite-volume based reduced order methods. International Journal for Numerical Methods in Engineering [Internet]. 2020 ;121:2655-2682. Available from: https://arxiv.org/abs/1901.06373
. Efficient geometrical parametrisation techniques of interfaces for reduced-order modelling: application to fluid–structure interaction coupling problems. International Journal of Computational Fluid Dynamics. 2014 ;28:158–169.
. An efficient computational framework for naval shape design and optimization problems by means of data-driven reduced order modeling techniques. Bolletino dell Unione Matematica Italiana. 2021 ;14:211-230.
. Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method. Advances in Computational Mathematics. 2021 ;47.
. Efficient computation of bifurcation diagrams with a deflated approach to reduced basis spectral element method. Advances in Computational Mathematics [Internet]. 2020 . Available from: https://arxiv.org/abs/1912.06089