| 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 | 199 | 2018 |
| 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 | 172 | 2014 |
| 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 | 168 | 2015 |
| 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 | 148 | 2015 |
| 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 | 105 | 2017 |
| 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 | 97 | 2019 |
| 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 | 94 | 2016 |
| 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 | 88 | 2013 |
| 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 | 71 | 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 | 57 | 2019 |
| Landslide susceptibility mapping using the stacking ensemble machine learning method in Lushui, Southwest China X Hu, H Zhang, H Mei, D Xiao, Y Li, M Li Applied Sciences 10 (11), 4016, 2020 | 54 | 2020 |
| Non‐intrusive reduced‐order modeling for multiphase porous media flows using Smolyak sparse grids D Xiao, Z Lin, F Fang, CC Pain, IM Navon, P Salinas, A Muggeridge International Journal for Numerical Methods in Fluids 83 (2), 205-219, 2017 | 48 | 2017 |
| Machine learning-based rapid response tools for regional air pollution modelling D Xiao, F Fang, J Zheng, CC Pain, IM Navon Atmospheric environment 199, 463-473, 2019 | 47 | 2019 |
| Natural ventilation in cities: the implications of fluid mechanics J Song, S Fan, W Lin, L Mottet, H Woodward, M Davies Wykes, R Arcucci, ... Building Research & Information 46 (8), 809-828, 2018 | 41 | 2018 |
| A non-intrusive reduced-order model for compressible fluid and fractured solid coupling and its application to blasting D Xiao, P Yang, F Fang, J Xiang, CC Pain, IM Navon, M Chen Journal of Computational Physics 330, 221-244, 2017 | 41 | 2017 |
| A domain decomposition method for the non-intrusive reduced order modelling of fluid flow D Xiao, F Fang, CE Heaney, IM Navon, CC Pain Computer Methods in Applied Mechanics and Engineering 354, 307-330, 2019 | 38 | 2019 |
| Supporting an integrated transportation infrastructure and public space design: A coupled simulation method for evaluating traffic pollution and microclimate L Yang, L Zhang, MEJ Stettler, M Sukitpaneenit, D Xiao, KH Van Dam Sustainable Cities and Society 52, 101796, 2020 | 36 | 2020 |
| Error estimation of the parametric non-intrusive reduced order model using machine learning D Xiao Computer Methods in Applied Mechanics and Engineering 355, 513-534, 2019 | 30 | 2019 |
| Non‐intrusive reduced order modelling with least squares fitting on a sparse grid Z Lin, D Xiao, F Fang, CC Pain, IM Navon International Journal for Numerical Methods in Fluids 83 (3), 291-306, 2017 | 30 | 2017 |
| Non-intrusive reduced order models and their applications D Xiao Imperial College London, 2016 | 29 | 2016 |
Fangxin FangSenior Research Fellow, Earth Science and Engineering, Imperial College LondonVerified email at imperial.ac.uk
