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Filters: Author is Gianluigi Rozza  [Clear All Filters]
2021
Demo N, Tezzele M, Rozza G. A supervised learning approach involving active subspaces for an efficient genetic algorithm in high-dimensional optimization problems. SIAM Journal on Scientific Computing [Internet]. 2021 ;43(3). Available from: https://arxiv.org/abs/2006.07282
Carere G, Strazzullo M, Ballarin F, Rozza G, Stevenson R. A weighted POD-reduction approach for parametrized PDE-constrained optimal control problems with random inputs and applications to environmental sciences. Computers and Mathematics with Applications [Internet]. 2021 ;102:261-276. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117948561&doi=10.1016%2fj.camwa.2021.10.020&partnerID=40&md5=cb57d59a6975a35315b2cf5d0e3a6001
2022
Hess MW, Quaini A, Rozza G. 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.
Hess MW, Quaini A, Rozza G. Data-Driven Enhanced Model Reduction for Bifurcating Models in Computational Fluid Dynamics. 2022 .
Hess MW, Quaini A, Rozza G. A Data-Driven Surrogate Modeling Approach for Time-Dependent Incompressible Navier-Stokes Equations with Dynamic Mode Decomposition and Manifold Interpolation. 2022 .
Pichi F, Strazzullo M, Ballarin F, Rozza G. Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier–Stokes equations with model order reduction. ESAIM: M2AN [Internet]. 2022 ;56(4):1361 - 1400. Available from: https://doi.org/10.1051/m2an/2022044
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.
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, Rozza G. Model Reduction Using Sparse Polynomial Interpolation for the Incompressible Navier-Stokes Equations. 2022 .
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
Girfoglio M, Quaini A, Rozza G. A POD-Galerkin reduced order model for the Navier–Stokes equations in stream function-vorticity formulation. [Internet]. 2022 :105536. Available from: https://www.sciencedirect.com/science/article/pii/S0045793022001645
Nonino M, Ballarin F, Rozza G, Maday Y. Projection based semi–implicit partitioned Reduced Basis Method for non parametrized and parametrized Fluid–Structure Interaction problems. 2022 .
Meneghetti L, Demo N, Rozza G. A Proper Orthogonal Decomposition Approach for Parameters Reduction of Single Shot Detector Networks. In: 2022 IEEE International Conference on Image Processing (ICIP). 2022 IEEE International Conference on Image Processing (ICIP). ; 2022.
2023
Salavatidezfouli S, Hajisharifi S, Girfoglio M, Stabile G, Rozza G. Applicable Methodologies for the Mass Transfer Phenomenon in Tumble Dryers: A Review. 2023 .
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
2024
Prusak I, Torlo D, Nonino M, Rozza G. Optimisation–Based Coupling of Finite Element Model and Reduced Order Model for Computational Fluid Dynamics.; 2024.
Prusak I, Torlo D, Nonino M, Rozza G. An optimisation–based domain–decomposition reduced order model for parameter–dependent non–stationary fluid dynamics problems. Computers & Mathematics with Applications [Internet]. 2024 ;166:253-268. Available from: https://www.sciencedirect.com/science/article/pii/S0898122124002098

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