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Filters: Author is Gianluigi Rozza
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
. 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
. . 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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A time-adaptive algorithm for pressure dominated flows: a heuristic estimator. [Internet]. 2024 . Available from: https://arxiv.org/abs/2407.00428
. 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.
. 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
. 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
. 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
. 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.
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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
. 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
. 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.
. 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
. . 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
. 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
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