Gianluigi Rozza | Mathematics Area - SISSA

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2024

Padula G, Romor F, Stabile G, Rozza G. Generative models for the deformation of industrial shapes with linear geometric constraints: Model order and parameter space reductions. . Computer Methods in Applied Mechanics and Engineering [Internet]. 2024 ;423. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0045782524000793

Ngan VEric Brice, Stabile G, Mola A, Rozza G. A hybrid reduced-order model for segregated fluid-structure interaction solvers in an ALE approach at high Reynolds number.; 2024.

Ali S, Ballarin F, Rozza G. An Online Stabilization Method for Parametrized Viscous Flows. In: Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators. Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators. Springer, Cham; 2024. Available from: https://link.springer.com/chapter/10.1007/978-3-031-55060-7_1

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

Zancanaro M, Ngan VEric Brice, Stabile G, Rozza G. A segregated reduced order model of a pressure-based solver for turbulent compressible flows.; 2024.

Prusak I, Torlo D, Nonino M, Rozza G. A time-adaptive algorithm for pressure dominated flows: a heuristic estimator. [Internet]. 2024 . Available from: https://arxiv.org/abs/2407.00428

2023

Salavatidezfouli S, Hajisharifi S, Girfoglio M, Stabile G, Rozza G. Applicable Methodologies for the Mass Transfer Phenomenon in Tumble Dryers: A Review. 2023 .

Donadini E, Strazzullo M, Tezzele M, Rozza G. A Data-Driven Partitioned Approach for the Resolution of Time-Dependent Optimal Control Problems with Dynamic Mode Decomposition. In: 13th International Conference on Spectral and High Order Methods, ICOSAHOM 2021. 13th International Conference on Spectral and High Order Methods, ICOSAHOM 2021. ; 2023.

Meneghetti L, Demo N, Rozza G. A dimensionality reduction approach for convolutional neural networks. Applied Intelligence [Internet]. 2023 ;58:2818-2833. Available from: https://link.springer.com/article/10.1007/s10489-023-04730-1

Romor F, Stabile G, Rozza G. Explicable hyper-reduced order models on nonlinearly approximated solution manifolds of compressible and incompressible Navier-Stokes equations.; 2023.

Romor F, Torlo D, Rozza G. Friedrichs' systems discretized with the Discontinuous Galerkin method: domain decomposable model order reduction and Graph Neural Networks approximating vanishing viscosity solutions.; 2023.

Romor F, Stabile G, Rozza G. Non-linear manifold reduced-order models with convolutional autoencoders and reduced over-collocation method. Journal of Scientific Computing [Internet]. 2023 ;94(3). Available from: https://link.springer.com/article/10.1007/s10915-023-02128-2

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

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

Shah N, Girfoglio M, Quintela P, Rozza G, Lengomin A, Ballarin F, Barral P. Finite element based Model Order Reduction for parametrized one-way coupled steady state linear thermo-mechanical problems. Finite Elements in Analysis and Design [Internet]. 2022 ;212. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0168874X2200110X

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 .

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