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Filters: Author is Giovanni Stabile  [Clear All Filters]
Book Chapter
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
Marino E, Stabile G, Borri C, Lugni C. A comparative study about the effects of linear, weakly and fully nonlinear wave models on the dynamic response of offshore wind turbines. In: Research and Applications in Structural Engineering, Mechanics and Computation. Research and Applications in Structural Engineering, Mechanics and Computation. CRC Press; 2013. pp. 389–390.
Hijazi S, Stabile G, Mola A, Rozza G. Non-intrusive Polynomial Chaos Method Applied to Full-Order and Reduced Problems in Computational Fluid Dynamics: A Comparison and Perspectives. In: Quantification of Uncertainty: Improving Efficiency and Technology: QUIET selected contributions. Quantification of Uncertainty: Improving Efficiency and Technology: QUIET selected contributions. Cham: Springer International Publishing; 2020. pp. 217–240. Available from: https://doi.org/10.1007/978-3-030-48721-8_10
Conference Paper
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
Marino E, Lugni C, Stabile G, Borri C, Manuel L. Coupled dynamic simulations of offshore wind turbines: influence of wave modelling on the fatigue load assesment. In: XIII Conference of the Italian Association for Wind Engineering (In-Vento 2014). XIII Conference of the Italian Association for Wind Engineering (In-Vento 2014). ; 2014.
Marino E, Lugni C, Stabile G, Borri C. Coupled dynamic simulations of offshore wind turbines using linear, weakly and fully nonlinear wave models: the limitations of the second-order wave theory. In: 9th International Conference on Structural Dynamics (EURODYN 2014). 9th International Conference on Structural Dynamics (EURODYN 2014). ; 2014.
Hijazi S, Ali S, Stabile G, Ballarin F, Rozza G. The Effort of Increasing Reynolds Number in Projection-Based Reduced Order Methods: from Laminar to Turbulent Flows. In: Lecture Notes in Computational Science and Engineering. Lecture Notes in Computational Science and Engineering. Cham: Springer International Publishing; 2020. pp. 245–264.
Star K, Stabile G, Georgaka S, Belloni F, Rozza G, Degroote J. POD-Galerkin Reduced Order Model of the Boussinesq Approximation for Buoyancy-Driven Enclosed Flows. In: International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019. International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering, M and C 2019. ; 2019.
Karatzas EN, Stabile G, Atallah N, Scovazzi G, Rozza G. A Reduced Order Approach for the Embedded Shifted Boundary FEM and a Heat Exchange System on Parametrized Geometries. In: Fehr J, Haasdonk B IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018. IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22–25, 2018. Springer International Publishing; 2020. Available from: https://arxiv.org/abs/1807.07753
Stabile G, Matthies HG, Borri C. A Reduced Order Model for the Simulation of Mooring Cable Dynamics. In: Computational Methods in Marine Engineering VI – MARINE2015. Computational Methods in Marine Engineering VI – MARINE2015. Salvatore, Francesco; Broglia, Riccardo; Muscari, Roberto; 2015. pp. 387–400.
Journal Article
Stabile G, Rosic B. Bayesian identification of a projection-based reduced order model for computational fluid dynamics. Computers & Fluids. 2020 ;201:104477.
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
Giusti A, Stabile G, Marino E, Borri C. Coupling effects on the dynamic response of moored floating platforms for offshore wind energy plants. Procedia engineering. 2017 ;199:3194–3199.
Hijazi S, Stabile G, Mola A, Rozza G. Data-driven POD-Galerkin reduced order model for turbulent flows. Journal of Computational Physics [Internet]. 2020 ;416:109513. Available from: https://arxiv.org/abs/1907.09909
Stabile G, Zancanaro M, Rozza G. Efficient Geometrical parametrization for finite-volume based reduced order methods. International Journal for Numerical Methods in Engineering [Internet]. 2020 ;121:2655-2682. Available from: https://arxiv.org/abs/1901.06373
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
Stabile G, Rozza G. Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier–Stokes equations. Computers and Fluids [Internet]. 2018 ;173:273-284. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85043366603&doi=10.1016%2fj.compfluid.2018.01.035&partnerID=40&md5=c15435ea3b632e55450da19ba2bb6125
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
Zancanaro M, Mrosek M, Stabile G, Othmer C, Rozza G. Hybrid Neural Network Reduced Order Modelling for Turbulent Flows with Geometric Parameters. Fluids [Internet]. 2021 ;6:296. Available from: https://doi.org/10.3390/fluids6080296
Georgaka S, Stabile G, Star K, Rozza G, Bluck MJ. A hybrid reduced order method for modelling turbulent heat transfer problems. Computers & Fluids [Internet]. 2020 ;208:104615. Available from: https://arxiv.org/abs/1906.08725
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
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
Star K, Stabile G, Belloni F, Rozza G, Degroote J. A novel iterative penalty method to enforce boundary conditions in Finite Volume POD-Galerkin reduced order models for fluid dynamics problems. Communications in Computational Physics. 2021 ;30:34–66.
Stabile G, Matthies HG, Borri C. A novel reduced order model for vortex induced vibrations of long flexible cylinders. [Internet]. 2018 ;156:191–207. Available from: https://doi.org/10.1016/j.oceaneng.2018.02.064
Morelli UEmil, Barral P, Quintela P, Rozza G, Stabile G. A numerical approach for heat flux estimation in thin slabs continuous casting molds using data assimilation. International Journal for Numerical Methods in Engineering [Internet]. 2021 ;122:4541–4574. Available from: https://doi.org/10.1002/nme.6713

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