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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.
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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
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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.
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Strazzullo M, Ballarin F, Rozza G. POD-Galerkin Model Order Reduction for Parametrized Nonlinear Time Dependent Optimal Flow Control: an Application to Shallow Water Equations. 2020 .
Ballarin F, D'Amario A, Perotto S, Rozza G. A POD-selective inverse distance weighting method for fast parametrized shape morphing. International Journal for Numerical Methods in Engineering [Internet]. 2019 ;117:860-884. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056396233&doi=10.1002%2fnme.5982&partnerID=40&md5=6aabcbdc9a0da25e36575a0ebfac034f
Strazzullo M, Ballarin F, Rozza G. POD–Galerkin Model Order Reduction for Parametrized Time Dependent Linear Quadratic Optimal Control Problems in Saddle Point Formulation. Journal of Scientific Computing. 2020 ;83.
Ballarin F, Rozza G. POD–Galerkin monolithic reduced order models for parametrized fluid-structure interaction problems. International Journal Numerical Methods for Fluids. 2016 .
Karatzas EN, Ballarin F, Rozza G. Projection-based reduced order models for a cut finite element method in parametrized domains. Computers and Mathematics with Applications [Internet]. 2020 ;79:833-851. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070900852&doi=10.1016%2fj.camwa.2019.08.003&partnerID=40&md5=2d222ab9c7832955d155655d3c93e1b1
R
Karatzas EN, Nonino M, Ballarin F, Rozza G. A Reduced Order Cut Finite Element method for geometrically parametrized steady and unsteady Navier–Stokes problems. Computer & Mathematics With Applications [Internet]. 2021 . Available from: https://www.sciencedirect.com/science/article/pii/S0898122121002790
Zainib Z, Ballarin F, Fremes SE, Triverio P, Jiménez-Juan L, Rozza G. Reduced order methods for parametric optimal flow control in coronary bypass grafts, toward patient-specific data assimilation. International Journal for Numerical Methods in Biomedical EngineeringInternational Journal for Numerical Methods in Biomedical EngineeringInt J Numer Meth Biomed Engng [Internet]. 2020 ;n/a(n/a):e3367. Available from: https://onlinelibrary.wiley.com/doi/10.1002/cnm.3367?af=R
Strazzullo M, Zainib Z, Ballarin F, Rozza G. Reduced Order Methods for Parametrized Non-linear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences. In: Numerical Mathematics and Advanced Applications ENUMATH 2019. Vol. 139. Numerical Mathematics and Advanced Applications ENUMATH 2019. Springer; 2021. pp. 841–850. Available from: https://arxiv.org/abs/1912.07886
Strazzullo M, Zainib Z, Ballarin F, Rozza G. Reduced Order Methods for Parametrized Non-linear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences. In: Vermolen FJ, Vuik C Numerical Mathematics and Advanced Applications ENUMATH 2019. Numerical Mathematics and Advanced Applications ENUMATH 2019. Cham: Springer International Publishing; 2021. Available from: https://www.springerprofessional.de/en/reduced-order-methods-for-parametrized-non-linear-and-time-depen/19122676
Stabile G, Ballarin F, Zuccarino G, Rozza G. A reduced order variational multiscale approach for turbulent flows. Advances in Computational Mathematics [Internet]. 2019 ;45:2349-2368. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068076665&doi=10.1007%2fs10444-019-09712-x&partnerID=40&md5=af0142e6d13bbc2e88c6f31750aef6ad
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.

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