A mathematical and numerical study of the sensitivity of a reduced order model by POD (ROM–POD), for a 2D incompressible fluid flow N Akkari, A Hamdouni, E Liberge, M Jazar Journal of computational and applied mathematics 270, 522-530, 2014 | 20 | 2014 |

A nonintrusive distributed reduced‐order modeling framework for nonlinear structural mechanics—Application to elastoviscoplastic computations F Casenave, N Akkari, F Bordeu, C Rey, D Ryckelynck International Journal for Numerical Methods in Engineering 121 (1), 32-53, 2020 | 14 | 2020 |

On the sensitivity of the POD technique for a parameterized quasi-nonlinear parabolic equation N Akkari, A Hamdouni, E Liberge, M Jazar Advanced Modeling and Simulation in Engineering Sciences 1 (1), 1-16, 2014 | 13 | 2014 |

Time stable reduced order modeling by an enhanced reduced order basis of the turbulent and incompressible 3D Navier–Stokes equations N Akkari, F Casenave, V Moureau Mathematical and computational applications 24 (2), 45, 2019 | 11 | 2019 |

Model order reduction assisted by deep neural networks (ROM-net) T Daniel, F Casenave, N Akkari, D Ryckelynck Advanced Modeling and Simulation in Engineering Sciences 7, 1-27, 2020 | 10 | 2020 |

An error indicator-based adaptive reduced order model for nonlinear structural mechanics—application to high-pressure turbine blades F Casenave, N Akkari Mathematical and computational applications 24 (2), 41, 2019 | 6 | 2019 |

Stable pod-galerkin reduced order models for unsteady turbulent incompressible flows N Akkari, R Mercier, G Lartigue, V Moureau 55th AIAA Aerospace Sciences Meeting, 1000, 2017 | 5 | 2017 |

Geometrical reduced order modeling (ROM) by proper orthogonal decomposition (POD) for the incompressible Navier Stokes equations N Akkari, R Mercier, V Moureau 2018 AIAA Aerospace Sciences Meeting, 1827, 2018 | 4 | 2018 |

Mathematical and numerical results on the sensitivity of the POD approximation relative to the Burgers equation N Akkari, A Hamdouni, M Jazar Applied Mathematics and Computation 247, 951-961, 2014 | 4 | 2014 |

A novel Gappy reduced order method to capture non-parameterized geometrical variation in fluid dynamics problems N Akkari, F Casenave, D Ryckelynck | 2 | 2019 |

Data augmentation and feature selection for automatic model recommendation in computational physics T Daniel, F Casenave, N Akkari, D Ryckelynck arXiv preprint arXiv:2101.04530, 2021 | 1 | 2021 |

Deep Convolutional Generative Adversarial Networks Applied to 2D Incompressible and Unsteady Fluid Flows N Akkari, F Casenave, ME Perrin, D Ryckelynck Science and Information Conference, 264-276, 2020 | 1 | 2020 |

A velocity potential preserving reduced order approach for the incompressible and unsteady Navier-Stokes equations N Akkari AIAA Scitech 2020 Forum, 1573, 2020 | 1 | 2020 |

Mathematical and numerical results on the parametric sensitivity of a ROM-POD of the burgers equation N Akkari, A Hamdouni, M Jazar European Journal of Computational Mechanics 23 (1-2), 78-95, 2014 | 1 | 2014 |

Reduced Order Modeling Assisted by Convolutional Neural Network for Thermal Problems with Nonparametrized Geometrical Variability F Casenave, N Akkari, D Ryckelynck Science and Information Conference, 245-263, 2020 | | 2020 |

Nonintrusive approximation of parametrized limits of matrix power algorithms–application to matrix inverses and log-determinants F Casenave, N Akkari, A Charles, C Rey ESAIM: Mathematical Modelling and Numerical Analysis 53 (1), 219-248, 2019 | | 2019 |

Sur la sensibilité paramétrique de l'Hyper-réduction en Dynamique des structures N Akkari, F Daim, D Ryckelynck 12e Colloque national en calcul des structures, 4 p., 2015 | | 2015 |

Mathematical and numerical study on the parametric sensitivity of a structural dynamic hyper-reduction N Akkari, F Daim, D Ryckelynck CIMNE, 2015 | | 2015 |

Un résultat mathématique sur la sensibilité paramétrique du ROM-POD N AKKARI, A HAMDOUNI, E LIBERGE, M JAZAR Congrès français de mécanique, 2013 | | 2013 |

la POD N Akkari, A Hamdouni, M Jazar | | 2013 |