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ORCIDIonel Michael Navon
Person information
- affiliation: Florida State University, Tallahassee, USA
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2020 – today
- 2024
[j28]Yuepeng Wang, Jie Li, Wenju Zhao, I. M. Navon, Guang Lin
:
Accelerating inverse inference of ensemble Kalman filter via reduced-order model trained using adaptive sparse observations. J. Comput. Phys. 496: 112600 (2024)- [j27]Andrew G. Buchan, Ionel Michael Navon, Liang Yang:
A reduced order model discretisation of the space-angle phase-space dimensions of the Boltzmann transport equation with application to nuclear reactor problems. J. Comput. Phys. 517: 113268 (2024) - [i10]Shengjuan Cai, Fangxin Fang, Vincent-Henri Peuch, Mihai Alexe, Ionel Michael Navon, Yanghua Wang:
Advancing operational PM2.5 forecasting with dual deep neural networks (D-DNet). CoRR abs/2406.19154 (2024) - [i9]Diana Alina Bistrian, Gabriel Dimitriu, Ionel Michael Navon:
Reduced-order modelling based on Koopman operator theory. CoRR abs/2409.03549 (2024) - 2023
- [j26]S. Ashwin Renganathan, Vishwas Rao, Ionel Michael Navon:
CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis. J. Comput. Phys. 472: 111698 (2023) - [j25]Meiling Cheng, Fangxin Fang, Ionel Michael Navon, Christopher C. Pain:
Ensemble Kalman filter for GAN-ConvLSTM based long lead-time forecasting. J. Comput. Sci. 69: 102024 (2023) - 2022
- [j24]Mostafa Abbaszadeh, Mehdi Dehghan, Ionel Michael Navon:
A POD reduced-order model based on spectral Galerkin method for solving the space-fractional Gray-Scott model with error estimate. Eng. Comput. 38(3): 2245-2268 (2022) - [i8]Shady E. Ahmed, Omer San, Diana Alina Bistrian, Ionel Michael Navon:
Sketching Methods for Dynamic Mode Decomposition in Spherical Shallow Water Equations. CoRR abs/2201.04084 (2022) - [i7]Claire E. Heaney, Zef Wolffs, Jón Atli Tómasson, Lyes Kahouadji, Pablo Salinas, André Nicolle, Omar K. Matar, Ionel Michael Navon, Narakorn Srinil, Christopher C. Pain:
An AI-based Domain-Decomposition Non-Intrusive Reduced-Order Model for Extended Domains applied to Multiphase Flow in Pipes. CoRR abs/2202.06170 (2022) - [i6]S. Ashwin Renganathan, Vishwas Rao, Ionel Michael Navon:
CAMERA: A Method for Cost-aware, Adaptive, Multifidelity, Efficient Reliability Analysis. CoRR abs/2203.01436 (2022) - 2021
- [j23]Yuepeng Wang, Xuemei Ding, Kun Hu, Fangxin Fang, I. M. Navon, Guang Lin:
Feasibility of DEIM for retrieving the initial field via dimensionality reduction. J. Comput. Phys. 429: 110005 (2021) - 2020
- [i5]M. Cheng, Fangxin Fang, Christopher C. Pain, I. M. Navon:
Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network. CoRR abs/2004.00707 (2020)
2010 – 2019
- 2018
- [i4]Claire E. Heaney, Pablo Salinas, Fangxin Fang, Christopher C. Pain, I. M. Navon:
Goal-based sensitivity maps using time windows and ensemble perturbations. CoRR abs/1804.04457 (2018) - 2017
- [j22]Gabriel Dimitriu, Razvan Stefanescu, Ionel Michael Navon:
Comparative numerical analysis using reduced-order modeling strategies for nonlinear large-scale systems. J. Comput. Appl. Math. 310: 32-43 (2017) - [j21]Dunhui Xiao, Pan Yang, Fangxin Fang, Jiansheng Xiang, Christopher C. Pain, I. M. Navon, Min Chen:
A non-intrusive reduced-order model for compressible fluid and fractured solid coupling and its application to blasting. J. Comput. Phys. 330: 221-244 (2017) - 2015
- [j20]Razvan Stefanescu, Adrian Sandu, Ionel Michael Navon:
POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation. J. Comput. Phys. 295: 569-595 (2015) - [j19]Andrew G. Buchan, A. A. Calloo, Mark G. Goffin, Steven Dargaville, Fangxin Fang, Christopher C. Pain, Ionel Michael Navon:
A POD reduced order model for resolving angular direction in neutron/photon transport problems. J. Comput. Phys. 296: 138-157 (2015) - 2014
- [j18]Dunhui Xiao, Fangxin Fang, Andrew G. Buchan, Christopher C. Pain, Ionel Michael Navon, Juan Du, G. Hu:
Non-linear model reduction for the Navier-Stokes equations using residual DEIM method. J. Comput. Phys. 263: 1-18 (2014) - [i3]Razvan Stefanescu, Adrian Sandu, Ionel Michael Navon:
Comparison of POD reduced order strategies for the nonlinear 2D Shallow Water Equations. CoRR abs/1402.2018 (2014) - [i2]Razvan Stefanescu, Adrian Sandu, Ionel Michael Navon:
POD/DEIM Strategies for reduced data assimilation systems. CoRR abs/1402.5992 (2014) - 2013
- [j17]Juan Du, Fangxin Fang, Christopher C. Pain, I. M. Navon, Jiang Zhu, David A. Ham:
POD reduced-order unstructured mesh modeling applied to 2D and 3D fluid flow. Comput. Math. Appl. 65(3): 362-379 (2013) - [j16]Juan Du, I. M. Navon, Jiang Zhu, Fangxin Fang, Aleksey K. Alekseev:
Reduced order modeling based on POD of a parabolized Navier-Stokes equations model II: Trust region POD 4D VAR data assimilation. Comput. Math. Appl. 65(3): 380-394 (2013) - [j15]Fangxin Fang, Christopher C. Pain, I. M. Navon, Ahmed H. Elsheikh, Juan Du, Dunhui Xiao:
Non-linear Petrov-Galerkin methods for reduced order hyperbolic equations and discontinuous finite element methods. J. Comput. Phys. 234: 540-559 (2013) - [j14]Razvan Stefanescu, Ionel Michael Navon:
POD/DEIM nonlinear model order reduction of an ADI implicit shallow water equations model. J. Comput. Phys. 237: 95 (2013) - [j13]Zhendong Luo, Hong Li, Ping Sun, Jing An, Ionel Michael Navon:
A reduced-order finite volume element formulation based on POD method and numerical simulation for two-dimensional solute transport problems. Math. Comput. Simul. 89: 50-68 (2013) - [c3]Gabriel Dimitriu, Ionel Michael Navon, Razvan Stefanescu:
Application of POD-DEIM Approach for Dimension Reduction of a Diffusive Predator-Prey System with Allee Effect. LSSC 2013: 373-381 - 2012
- [i1]Razvan Stefanescu, Ionel Michael Navon:
POD/DEIM Nonlinear model order reduction of an ADI implicit shallow water equations model. CoRR abs/1211.2521 (2012)
2000 – 2009
- 2009
- [j12]Aleksey K. Alekseev, I. Michael Navon, Jeff L. Steward:
Comparison of advanced large-scale minimization algorithms for the solution of inverse ill-posed problems. Optim. Methods Softw. 24(1): 63-87 (2009) - 2008
- [j11]Zhendong Luo, Jing Chen, I. M. Navon, Xiaozhong Yang:
Mixed Finite Element Formulation and Error Estimates Based on Proper Orthogonal Decomposition for the Nonstationary Navier-Stokes Equations. SIAM J. Numer. Anal. 47(1): 1-19 (2008) - 2006
- [j10]Aleksey K. Alekseev, I. M. Navon:
A posteriori error estimation by postprocessor independent of method of flowfield calculation. Comput. Math. Appl. 51(3-4): 397-404 (2006) - [j9]P. W. Power, Christopher C. Pain, M. D. Piggott, Fangxin Fang, Gerard J. Gorman, A. P. Umpleby, Anthony J. H. Goddard, I. M. Navon:
Adjoint A Posteriori Error Measures for Anisotropic Mesh Optimisation. Comput. Math. Appl. 52(8-9): 1213-1242 (2006) - [j8]I. Yu. Gejadze, G. J. M. Copeland, I. M. Navon:
Open Boundary Control Problem for Navier-Stokes Equations Including a Free Surface: Data Assimilation. Comput. Math. Appl. 52(8-9): 1269-1288 (2006) - [j7]Yanhua Cao, Jiang Zhu, Zhendong Luo, I. M. Navon:
Reduced-Order Modeling of the Upper Tropical Pacific Ocean Model using Proper Orthogonal Decomposition. Comput. Math. Appl. 52(8-9): 1373-1386 (2006) - 2005
- [c2]Ionel Michael Navon, Dacian N. Daescu, Zhuo Liu:
The Impact of Background Error on Incomplete Observations for 4D-Var Data Assimilation with the FSU GSM. International Conference on Computational Science (2) 2005: 837-844 - 2003
- [j6]Bedamati Das, Hagai Meirovitch, Ionel Michael Navon:
Performance of hybrid methods for large-scale unconstrained optimization as applied to models of proteins. J. Comput. Chem. 24(10): 1222-1231 (2003) - [j5]Chris Homescu, I. M. Navon:
Numerical and theoretical considerations for sensitivity calculation of discontinuous flow. Syst. Control. Lett. 48(3-4): 253-260 (2003)
1990 – 1999
- 1999
- [j4]Canan Baysal, Hagai Meirovitch, Ionel Michael Navon:
Performance of efficient minimization algorithms as applied to models of peptides and proteins. J. Comput. Chem. 20(3): 354-364 (1999) - 1995
- [j3]Zhi Wang, I. M. Navon, X. Zou, François-Xavier Le Dimet:
A truncated Newton optimization algorithm in meteorology applications with analytic Hessian/vector products. Comput. Optim. Appl. 4(3): 241-262 (1995) - 1993
- [j2]X. Zou, Ionel Michael Navon, M. Berger, Paul Kang-Hoh Phua, Tamar Schlick, François-Xavier Le Dimet:
Numerical Experience with Limited-Memory Quasi-Newton and Truncated Newton Methods. SIAM J. Optim. 3(3): 582-608 (1993) - 1990
- [j1]I. M. Navon, F. B. Brown, Daniel H. Robertson:
A combined simulated annealing and quasi-Newton-like conjugate-gradient method for determining the structure of mixed argon-xenon clusters. Comput. Chem. 14(4): 305-311 (1990)
1980 – 1989
- 1988
- [c1]Ionel Michael Navon, Paul Kang-Hoh Phua, M. Ramamurthy:
Vectorization of conjugate-gradient methods for large-scale minimization. SC 1988: 410-418
Coauthor Index
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