Nissrine Akkari
Nissrine Akkari
Safran
Verified email at safrangroup.com
Title
Cited by
Cited by
Year
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
202014
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
142020
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
132014
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
112019
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
102020
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
62019
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
52017
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
42018
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
42014
A novel Gappy reduced order method to capture non-parameterized geometrical variation in fluid dynamics problems
N Akkari, F Casenave, D Ryckelynck
22019
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
12021
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
12020
A velocity potential preserving reduced order approach for the incompressible and unsteady Navier-Stokes equations
N Akkari
AIAA Scitech 2020 Forum, 1573, 2020
12020
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
12014
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
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Articles 1–20