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Filters: Author is Marco Tezzele  [Clear All Filters]
2021
Romor F, Tezzele M, Rozza G. ATHENA: Advanced Techniques for High dimensional parameter spaces to Enhance Numerical Analysis. Software Impacts. 2021 ;10:100133.
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
Tezzele M. Data-driven parameter and model order reduction for industrial optimisation problems with applications in naval engineering. 2021 .
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
Romor F, Tezzele M, Rozza G. A local approach to parameter space reduction for regression and classification tasks. arXiv preprint arXiv:2107.10867. 2021 .
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.
Tezzele M, Demo N, Mola A, Rozza G. PyGeM: Python Geometrical Morphing. Software Impacts. 2021 ;7:100047.
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
2020
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
Rozza G, Hess M, 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
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
Romor F, Tezzele M, Lario A, Rozza G. Kernel-based Active Subspaces with application to CFD parametric problems using Discontinuous Galerkin method. arXiv preprint arXiv:2008.12083. 2020 .
Garotta F, Demo N, Tezzele M, Carraturo M, Reali A, Rozza G. Reduced order isogeometric analysis approach for pdes in parametrized domains. Lecture Notes in Computational Science and Engineering [Internet]. 2020 ;137:153-170. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089615035&doi=10.1007%2f978-3-030-48721-8_7&partnerID=40&md5=7b15836ae65fa28dcfe8733788d7730c
2019
Gadalla M, Tezzele M, Mola A, Rozza G. BladeX: Python Blade Morphing. The Journal of Open Source Software. 2019 ;4:1203.
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
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
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, 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
Tezzele M, Demo N, Rozza G. Shape optimization through proper orthogonal decomposition with interpolation and dynamic mode decomposition enhanced by active subspaces. 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-s2.0-85075390244&partnerID=40&md5=3e1f2e9a2539d34594caff13766c94b8
2018
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.
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.
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
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
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
Demo N, Tezzele M, Rozza G. PyDMD: Python Dynamic Mode Decomposition. The Journal of Open Source Software [Internet]. 2018 ;3:530. Available from: https://joss.theoj.org/papers/734e4326edd5062c6e8ee98d03df9e1d

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