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Filters: Author is Giovanni Stabile [Clear All Filters]
. 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
. 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.
. 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
. 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
. Coupling effects on the dynamic response of moored floating platforms for offshore wind energy plants. Procedia engineering. 2017 ;199:3194–3199.
. 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.
. 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.
. 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
. 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.
. Bayesian identification of a projection-based reduced order model for computational fluid dynamics. Computers & Fluids. 2020 ;201:104477.
. 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
. 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