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Journal Article
Georgaka S, Stabile G, Rozza G, Bluck MJ. Parametric POD-Galerkin Model Order Reduction for Unsteady-State Heat Transfer Problems. Communications in Computational Physics [Internet]. 2019 ;27:1–32. Available from: https://arxiv.org/abs/1808.05175
Prusak I, Nonino M, Torlo D, Ballarin F, Rozza G. An optimisation–based domain–decomposition reduced order model for the incompressible Navier-Stokes equations. [Internet]. 2023 ;151:172 - 189. Available from: https://www.sciencedirect.com/science/article/pii/S0898122123004248
Ballarin F, Faggiano E, Manzoni A, Quarteroni A, Rozza G, Ippolito S, Scrofani R. Numerical modeling of hemodynamics scenarios of patient-specific coronary artery bypass grafts. Biomechanics and Modeling in Mechanobiology [Internet]. 2017 ;16:1373-1399. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015065851&doi=10.1007%2fs10237-017-0893-7&partnerID=40&md5=c388f20bd5de14187bad9ed7d9affbd0
Morelli UEmil, Barral P, Quintela P, Rozza G, Stabile G. A numerical approach for heat flux estimation in thin slabs continuous casting molds using data assimilation. International Journal for Numerical Methods in Engineering [Internet]. 2021 ;122:4541–4574. Available from: https://doi.org/10.1002/nme.6713
Star K, Stabile G, Belloni F, Rozza G, Degroote J. A novel iterative penalty method to enforce boundary conditions in Finite Volume POD-Galerkin reduced order models for fluid dynamics problems. Communications in Computational Physics. 2021 ;30:34–66.
Girfoglio M, Scandurra L, Ballarin F, Infantino G, Nicolò F, Montalto A, Rozza G, Scrofani R, Comisso M, Musumeci F. Non-intrusive data-driven ROM framework for hemodynamics problems. Acta Mechanica Sinica. 2021 ;37:1183–1191.
Demo N, Tezzele M, Rozza G. A non-intrusive approach for the reconstruction of POD modal coefficients through active subspaces. Comptes Rendus - Mecanique [Internet]. 2019 ;347:873-881. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075379471&doi=10.1016%2fj.crme.2019.11.012&partnerID=40&md5=dcb27af39dc14dc8c3a4a5f681f7d84b
Papapicco D, Demo N, Girfoglio M, Stabile G, Rozza G. The Neural Network shifted-proper orthogonal decomposition: A machine learning approach for non-linear reduction of hyperbolic equations. Computer Methods in Applied Mechanics and Engineering [Internet]. 2022 ;392. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124488633&doi=10.1016%2fj.cma.2022.114687&partnerID=40&md5=12f82dcaba04c4a7c44f8e5b20101997
Sartori A, Cammi A, Luzzi L, Rozza G. A multi-physics reduced order model for the analysis of Lead Fast Reactor single channel. Annals of Nuclear Energy, 87, 2 (2016): pp. 198-208 [Internet]. 2016 ;87:208. Available from: http://urania.sissa.it/xmlui/handle/1963/35191
Rozza G, Chen P, Quarteroni A. Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations. Numerische Mathematik, (2015), 36 p. Article in Press [Internet]. 2015 . Available from: http://urania.sissa.it/xmlui/handle/1963/34491
Romor F, Tezzele M, Mrosek M, Othmer C, Rozza G. Multi-fidelity data fusion through parameter space reduction with applications to automotive engineering. arXiv preprint arXiv:2110.14396. 2021 .
Nonino M, Ballarin F, Rozza G. A Monolithic and a Partitioned, Reduced Basis Method for Fluid–Structure Interaction Problems. Fluids [Internet]. 2021 ;6:229. Available from: https://www.mdpi.com/2311-5521/6/6/229
Strazzullo M, Ballarin F, Mosetti R, Rozza G. 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
Benner P, Ohlberger M, Patera A, Rozza G, Sorensen DC, Urban K. 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.
Lassila T, Manzoni A, Quarteroni A, Rozza G. Model Order Reduction in Fluid Dynamics: Challenges and Perspectives. 2014 .
Khamlich M, Pichi F, Rozza G. Model order reduction for bifurcating phenomena in fluid-structure interaction problems. International Journal for Numerical Methods in FluidsInternational Journal for Numerical Methods in FluidsInt J Numer Meth Fluids [Internet]. 2022 ;n/a(n/a). Available from: https://doi.org/10.1002/fld.5118
Hess MW, Alla A, Quaini A, Rozza G, Gunzburger M. 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://arxiv.org/abs/1807.08851
Hess MW, Alla A, Quaini A, Rozza G, Gunzburger M. 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
Romor F, Tezzele M, Lario A, Rozza G. Kernel-based active subspaces with application to computational fluid dynamics parametric problems using discontinuous Galerkin method. International Journal for Numerical Methods in Engineering. 2022 ;123:6000-6027.
Jäggli C, Iapichino L, Rozza G. An improvement on geometrical parameterizations by transfinite maps. Comptes Rendus Mathematique. 2014 ;352:263–268.
Georgaka S, Stabile G, Star K, Rozza G, Bluck MJ. 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
Zancanaro M, Mrosek M, Stabile G, Othmer C, Rozza G. 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
Demo N, Tezzele M, Mola A, Rozza G. 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
Zancanaro M, Ballarin F, Perotto S, Rozza G. Hierarchical model reduction techniques for flow modeling in a parametrized setting. Multiscale Modeling and Simulation. 2021 ;19:267-293.
Salmoiraghi F, Scardigli A, Telib H, Rozza G. 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.

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