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. 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
. 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
. Enhancing CFD predictions in shape design problems by model and parameter space reduction. [Internet]. 2020 . Available from: https://arxiv.org/abs/2001.05237
. 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
. Fast simulations of patient-specific haemodynamics of coronary artery bypass grafts based on a POD-Galerkin method and a vascular shape parametrization.; 2015. Available from: http://urania.sissa.it/xmlui/handle/1963/34623
. A fast virtual surgery platform for many scenarios haemodynamics of patient-specific coronary artery bypass grafts. Submitted; 2016. Available from: http://urania.sissa.it/xmlui/handle/1963/35240
. 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
. Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier-Stokes equations. Computers & Fluids [Internet]. 2018 . Available from: https://doi.org/10.1016/j.compfluid.2018.01.035
. Free Form Deformation Techniques Applied to 3D Shape Optimization Problems. Communications in Applied and Industrial Mathematics. 2013 .
. 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.
. 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.
. 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
. Hierarchical model reduction techniques for flow modeling in a parametrized setting. Multiscale Modeling and Simulation. 2021 ;19:267-293.
. 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
. 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
. An improvement on geometrical parameterizations by transfinite maps. Comptes Rendus Mathematique. 2014 ;352:263–268.
. Isogeometric analysis-based reduced order modelling for incompressible linear viscous flows in parametrized shapes. Springer, AMOS Advanced Modelling and Simulation in Engineering Sciences; 2016. Available from: http://urania.sissa.it/xmlui/handle/1963/35199
. A localized reduced-order modeling approach for PDEs with bifurcating solutions. Computer Methods in Applied Mechanics and Engineering [Internet]. 2019 ;351:379-403. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064313505&doi=10.1016%2fj.cma.2019.03.050&partnerID=40&md5=8b095034b9e539995facc7ce7bafa9e9
. Model Order Reduction: a survey. In: Wiley Encyclopedia of Computational Mechanics, 2016. Wiley Encyclopedia of Computational Mechanics, 2016. Wiley; 2016. Available from: http://urania.sissa.it/xmlui/handle/1963/35194
. Model Order Reduction by means of Active Subspaces and Dynamic Mode Decomposition for Parametric Hull Shape Design Hydrodynamics. 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/49270
. Model order reduction of parameterized systems (MoRePaS): Preface to the special issue of advances in computational mathematics. Advances in Computational Mathematics. 2015 ;41:955–960.
. Model Reduction for Parametrized Optimal Control Problems in Environmental Marine Sciences and Engineering. SIAM Journal on Scientific Computing [Internet]. 2018 ;40:B1055-B1079. Available from: https://doi.org/10.1137/17M1150591
. Model Reduction Methods. In: Encyclopedia of Computational Mechanics Second Edition. Encyclopedia of Computational Mechanics Second Edition. John Wiley & Sons; 2017. pp. 1-36.