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Filters: Author is Gianluigi Rozza  [Clear All Filters]
Book Chapter
Hess MW, Rozza G. A Spectral Element Reduced Basis Method in Parametric CFD. In: Radu FAdrian, Kumar K, Berre I, Nordbotten JMartin, Pop ISorin Numerical Mathematics and Advanced Applications - ENUMATH 2017. Vol. 126. Numerical Mathematics and Advanced Applications - ENUMATH 2017. Springer International Publishing; 2019. Available from: https://arxiv.org/abs/1712.06432
Ballarin F, Rozza G, Maday Y. Reduced-order semi-implicit schemes for fluid-structure interaction problems. In: Benner P, Ohlberger M, Patera A, Rozza G, Urban K Model Reduction of Parametrized Systems. Model Reduction of Parametrized Systems. Springer International Publishing; 2017. pp. 149–167.
Ballarin F, Rozza G, Maday Y. Reduced-order semi-implicit schemes for fluid-structure interaction problems. In: Benner P, Ohlberger M, Patera A, Rozza G, Urban K Model Reduction of Parametrized Systems. Model Reduction of Parametrized Systems. Springer International Publishing; 2017. pp. 149–167.
Devaud D, Rozza G. Reduced Basis Approximation for the Structural-Acoustic Design based on Energy Finite Element Analysis (RB-EFEA). In: CEMRACS 2013 - Modelling and simulation of complex systems: stochastic and deterministic approaches. Vol. 48. CEMRACS 2013 - Modelling and simulation of complex systems: stochastic and deterministic approaches. ; 2013. pp. 98-115.
Huynh DBP, Pichi F, Rozza G. Reduced Basis Approximation and A Posteriori Error Estimation: Applications to Elasticity Problems in Several Parametric Settings. In: Numerical Methods for PDEs. Vol. 15. Numerical Methods for PDEs. ; 2018. Available from: https://link.springer.com/chapter/10.1007/978-3-319-94676-4_8
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
Chinesta F, Huerta A, Rozza G, Willcox K. Model Reduction Methods. In: Encyclopedia of Computational Mechanics Second Edition. Encyclopedia of Computational Mechanics Second Edition. John Wiley & Sons; 2017. pp. 1-36.
Chinesta F, Huerta A, Rozza G, Willcox K. Model Order Reduction: a survey. In: Wiley Encyclopedia of Computational Mechanics, 2016. Wiley Encyclopedia of Computational Mechanics, 2016. Wiley; 2016. Available from: http://urania.sissa.it/xmlui/handle/1963/35194
Lassila T, Manzoni A, Quarteroni A, Rozza G. Generalized reduced basis methods and n-width estimates for the approximation of the solution manifold of parametric PDEs. In: Springer, Indam Series, Vol. 4, 2012. Springer, Indam Series, Vol. 4, 2012. Springer; 2012. Available from: http://hdl.handle.net/1963/6340
Rozza G. Fundamentals of Reduced Basis Method for problems governed by parametrized PDEs and applications. In: Separated representations and PGD-based model reduction : fundamentals and applications. Vol. 554. Separated representations and PGD-based model reduction : fundamentals and applications. Wien: Springer; 2014.
Auricchio F, Conti M, Lefieux A, Morganti S, Reali A, Rozza G, Veneziani A. Computational methods in cardiovascular mechanics. In: Labrosse MF Cardiovascular Mechanics. Cardiovascular Mechanics. CRC Press; 2018. p. 54. Available from: https://www.taylorfrancis.com/books/e/9781315280288/chapters/10.1201%2Fb21917-5
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.
Devaud D, Rozza G. Certi fied Reduced Basis Method for Affinely Parametric Isogeometric Analysis NURBS Approximation. In: Spectral and High Order Methods for Partial Differential Equations . Vol. 119. Bittencourt, Dumont, Hesthaven. (Eds). Spectral and High Order Methods for Partial Differential Equations . Heildeberg: Springer; 2017.
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

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