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Filters: Author is Marco Tezzele  [Clear All Filters]
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A
Salmoiraghi F, Ballarin F, Corsi G, Mola A, Tezzele M, Rozza G. Advances in geometrical parametrization and reduced order models and methods for computational fluid dynamics problems in applied sciences and engineering: overview and perspectives. In: Papadrakakis M, Papadopoulos V, Stefanou G, Plevris V Proceedings of the ECCOMAS Congress 2016, VII European Conference on Computational Methods in Applied Sciences and Engineering,. Proceedings of the ECCOMAS Congress 2016, VII European Conference on Computational Methods in Applied Sciences and Engineering,. Crete, Greece: ECCOMAS; 2016.
Rozza G, Malik MH, Demo N, Tezzele M, Girfoglio M, Stabile G, Mola A. Advances in reduced order methods for parametric industrial problems in computational fluid dynamics. In: Proceedings of the 6th European Conference on Computational Mechanics: Solids, Structures and Coupled Problems, ECCM 2018 and 7th European Conference on Computational Fluid Dynamics, ECFD 2018. Proceedings of the 6th European Conference on Computational Mechanics: Solids, Structures and Coupled Problems, ECCM 2018 and 7th European Conference on Computational Fluid Dynamics, ECFD 2018. ; 2020. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075395686&partnerID=40&md5=fb0b1a3cfdfd35a104db9921bc9be675
Romor F, Tezzele M, Rozza G. ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis. Software Impacts. 2021 ;10:100133.
B
Rozza G, Hess MW, Stabile G, Tezzele M, Ballarin F. Basic ideas and tools for projection-based model reduction of parametric partial differential equations. In: Model Order Reduction, Volume 2 Snapshot-Based Methods and Algorithms. Model Order Reduction, Volume 2 Snapshot-Based Methods and Algorithms. Berlin, Boston: De Gruyter; 2020. pp. 1 - 47. Available from: https://www.degruyter.com/view/book/9783110671490/10.1515/9783110671490-001.xml
Gadalla M, Tezzele M, Mola A, Rozza G. BladeX: Python Blade Morphing. The Journal of Open Source Software. 2019 ;4:1203.
C
Tezzele M, Ballarin F, Rozza G. Combined parameter and model reduction of cardiovascular problems by means of active subspaces and POD-Galerkin methods. In: Mathematical and Numerical Modeling of the Cardiovascular System and Applications. Mathematical and Numerical Modeling of the Cardiovascular System and Applications. Springer; 2018. pp. 185–207.
Gadalla M, Cianferra M, Tezzele M, Stabile G, Mola A, Rozza G. On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis. Computers & Fluids [Internet]. 2021 ;216:104819. Available from: https://www.sciencedirect.com/science/article/pii/S0045793020303893
Demo N, Tezzele M, Mola A, Rozza G. A complete data-driven framework for the efficient solution of parametric shape design and optimisation in naval engineering problems. In: VIII International Conference on Computational Methods in Marine Engineering. VIII International Conference on Computational Methods in Marine Engineering. ; 2019. Available from: https://arxiv.org/abs/1905.05982
Demo N, Tezzele M, Mola A, Rozza G. A complete data-driven framework for the efficient solution of parametric shape design and optimisation in naval engineering problems. 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-s2.0-85075342565&partnerID=40&md5=d76b8a1290053e7a84fb8801c0e6bb3d
D
Tezzele M. Data-driven parameter and model order reduction for industrial optimisation problems with applications in naval engineering. 2021 .
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. 2021 .
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.
Tezzele M, Salmoiraghi F, Mola A, Rozza G. Dimension reduction in heterogeneous parametric spaces with application to naval engineering shape design problems. Advanced Modeling and Simulation in Engineering Sciences. 2018 ;5:25.
E
Mola A, Tezzele M, Gadalla M, Valdenazzi F, Grassi D, Padovan R, Rozza G. 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
Demo N, Tezzele M, Mola A, Rozza G. 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
Tezzele M, Demo N, Stabile G, Mola A, Rozza G. Enhancing CFD predictions in shape design problems by model and parameter space reduction. Advanced Modeling and Simulation in Engineering Sciences [Internet]. 2020 ;7(40). Available from: https://arxiv.org/abs/2001.05237
Demo N, Tezzele M, Rozza G. 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
H
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
K
Romor F, Tezzele M, Lario A, Rozza G. Kernel-based Active Subspaces with application to CFD parametric problems using Discontinuous Galerkin method.; 2020.
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.
L
Romor F, Tezzele M, Rozza G. A local approach to parameter space reduction for regression and classification tasks. arXiv preprint arXiv:2107.10867. 2021 .
M
Tezzele M, Demo N, Gadalla M, Mola A, Rozza G. 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
Romor F, Tezzele M, Rozza G. Multi-fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces. In: Proceedings in Applied Mathematics & Mechanics. Vol. 20. Proceedings in Applied Mathematics & Mechanics. Wiley Online Library; 2021.
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 .
N
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

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