| 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 | 261 | 2018 |
| 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 | 205 | 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 | 192 | 2014 |
| 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 | 175 | 2015 |
| Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review S Cheng, C Quilodrán-Casas, S Ouala, A Farchi, C Liu, P Tandeo, ... IEEE/CAA Journal of Automatica Sinica 10 (6), 1361-1387, 2023 | 149 | 2023 |
| 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 | 136 | 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 | 134 | 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 | 122 | 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 | 94 | 2013 |
| 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 | 77 | 2020 |
| 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 | 77 | 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 | 75 | 2019 |
| Egret swarm optimization algorithm: an evolutionary computation approach for model free optimization Z Chen, A Francis, S Li, B Liao, D Xiao, TT Ha, J Li, L Ding, X Cao Biomimetics 7 (4), 144, 2022 | 72 | 2022 |
| A non‐linear non‐intrusive reduced order model of fluid flow by auto‐encoder and self‐attention deep learning methods R Fu, D Xiao, IM Navon, F Fang, L Yang, C Wang, S Cheng International Journal for Numerical Methods in Engineering 124 (13), 3087-3111, 2023 | 55* | 2023 |
| 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 | 55 | 2017 |
| An efficient digital twin based on machine learning SVD autoencoder and generalised latent assimilation for nuclear reactor physics H Gong, S Cheng, Z Chen, Q Li, C Quilodrán-Casas, D Xiao, R Arcucci Annals of nuclear energy 179, 109431, 2022 | 54 | 2022 |
| 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 | 53 | 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 | 51 | 2020 |
| 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 | 51 | 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 | 46 | 2018 |
christopher painHead of AMCG, Imperial College LondonVerifierad e-postadress på ic.ac.uk