| Model identification of reduced order fluid dynamics systems using deep learning Z Wang, D Xiao, F Fang, R Govindan, CC Pain, Y Guo International Journal for Numerical Methods in Fluids 86 (4), 255-268, 2018 | 306 | 2018 |
| Long lead-time daily and monthly streamflow forecasting using machine learning methods M Cheng, F Fang, T Kinouchi, IM Navon, CC Pain Journal of Hydrology 590, 125376, 2020 | 289 | 2020 |
| Three-dimensional unstructured mesh ocean modelling CC Pain, MD Piggott, AJH Goddard, F Fang, GJ Gorman, DP Marshall, ... Ocean Modelling 10 (1-2), 5-33, 2005 | 239 | 2005 |
| Non‐intrusive reduced‐order modelling of the Navier–Stokes equations based on RBF interpolation D Xiao, F Fang, C Pain, G Hu International Journal for Numerical Methods in Fluids 79 (11), 580-595, 2015 | 224 | 2015 |
| Rapid spatio-temporal flood prediction and uncertainty quantification using a deep learning method R Hu, F Fang, CC Pain, IM Navon Journal of Hydrology 575, 911-920, 2019 | 211 | 2019 |
| Non-intrusive reduced order modelling of the Navier–Stokes equations D Xiao, F Fang, AG Buchan, CC Pain, IM Navon, A Muggeridge Computer Methods in Applied Mechanics and Engineering 293, 522-541, 2015 | 198 | 2015 |
| Non-linear model reduction for the Navier–Stokes equations using residual DEIM method D Xiao, F Fang, AG Buchan, CC Pain, IM Navon, J Du, G Hu Journal of Computational Physics 263, 1-18, 2014 | 197 | 2014 |
| Evolution, movement and decay of warm-core Leeuwin Current eddies F Fang, R Morrow Deep Sea Research Part II: Topical Studies in Oceanography 50 (12-13), 2245-2261, 2003 | 176 | 2003 |
| A reduced order model for turbulent flows in the urban environment using machine learning D Xiao, CE Heaney, L Mottet, F Fang, W Lin, IM Navon, Y Guo, OK Matar, ... Building and Environment 148, 323-337, 2019 | 171 | 2019 |
| A parameterized non-intrusive reduced order model and error analysis for general time-dependent nonlinear partial differential equations and its applications D Xiao, F Fang, CC Pain, IM Navon Computer Methods in Applied Mechanics and Engineering 317, 868-889, 2017 | 150 | 2017 |
| Non-intrusive reduced order modelling of fluid–structure interactions D Xiao, P Yang, F Fang, J Xiang, CC Pain, IM Navon Computer Methods in Applied Mechanics and Engineering 303, 35-54, 2016 | 142 | 2016 |
| A POD reduced‐order model for eigenvalue problems with application to reactor physics AG Buchan, CC Pain, F Fang, IM Navon International Journal for Numerical Methods in Engineering 95 (12), 1011-1032, 2013 | 120 | 2013 |
| A POD reduced order model for resolving angular direction in neutron/photon transport problems AG Buchan, AA Calloo, MG Goffin, S Dargaville, F Fang, CC Pain, ... Journal of Computational Physics 296, 138-157, 2015 | 116 | 2015 |
| Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network M Cheng, F Fang, CC Pain, IM Navon Computer Methods in Applied Mechanics and Engineering 365, 113000, 2020 | 114 | 2020 |
| Anatomy of three warm-core Leeuwin Current eddies R Morrow, F Fang, M Fieux, R Molcard Deep Sea Research Part II: Topical Studies in Oceanography 50 (12-13), 2229-2243, 2003 | 111 | 2003 |
| Non-linear Petrov–Galerkin methods for reduced order modelling of the Navier–Stokes equations using a mixed finite element pair D Xiao, F Fang, J Du, CC Pain, IM Navon, AG Buchan, AH Elsheikh, G Hu Computer Methods In Applied Mechanics and Engineering 255, 147-157, 2013 | 97 | 2013 |
| A domain decomposition non-intrusive reduced order model for turbulent flows D Xiao, CE Heaney, F Fang, L Mottet, R Hu, DA Bistrian, E Aristodemou, ... Computers & Fluids 182, 15-27, 2019 | 93 | 2019 |
| POD reduced-order unstructured mesh modeling applied to 2D and 3D fluid flow J Du, F Fang, CC Pain, IM Navon, J Zhu, DA Ham Computers & Mathematics with Applications 65 (3), 362-379, 2013 | 90 | 2013 |
| Reduced order modelling of an unstructured mesh air pollution model and application in 2D/3D urban street canyons F Fang, T Zhang, D Pavlidis, CC Pain, AG Buchan, IM Navon Atmospheric Environment 96, 96-106, 2014 | 88 | 2014 |
| Non-linear Petrov–Galerkin methods for reduced order hyperbolic equations and discontinuous finite element methods F Fang, CC Pain, IM Navon, AH Elsheikh, J Du, D Xiao Journal of Computational Physics 234, 540-559, 2013 | 80 | 2013 |
christopher painHead of AMCG, Imperial College LondonVerified email at ic.ac.uk
