Adjoint A Posteriori Error Measures for Anisotropic Mesh Optimisation. - P. W. Power; Christopher C. Pain; M. D. Piggott; Fangxin Fang; Gerard J. Gorman; A. P. Umpleby; Anthony J. H. Goddard; I. M. Navon (Comput. Math. Appl., 2006)

POD reduced-order unstructured mesh modeling applied to 2D and 3D fluid flow. - Juan Du 011; Fangxin Fang; Christopher C. Pain; I. M. Navon; Jiang Zhu; David A. Ham (Comput. Math. Appl., 2013)

Reduced order modeling based on POD of a parabolized Navier-Stokes equations model II: Trust region POD 4D VAR data assimilation. - Juan Du 011; I. M. Navon; Jiang Zhu; Fangxin Fang; Aleksey K. Alekseev (Comput. Math. Appl., 2013)

Non-linear Petrov-Galerkin methods for reduced order hyperbolic equations and discontinuous finite element methods. - Fangxin Fang; Christopher C. Pain; I. M. Navon; Ahmed H. Elsheikh; Juan Du 011; Dunhui Xiao (J. Comput. Phys., 2013)

Non-linear model reduction for the Navier-Stokes equations using residual DEIM method. - Dunhui Xiao; Fangxin Fang; Andrew G. Buchan; Christopher C. Pain; Ionel Michael Navon; Juan Du 011; G. Hu (J. Comput. Phys., 2014)

A POD reduced order model for resolving angular direction in neutron/photon transport problems. - Andrew G. Buchan; A. A. Calloo; Mark G. Goffin; Steven Dargaville; Fangxin Fang; Christopher C. Pain; Ionel Michael Navon (J. Comput. Phys., 2015)

Higher-order conservative interpolation between control-volume meshes: Application to advection and multiphase flow problems with dynamic mesh adaptivity. - Alexandros Adam; Dimitris Pavlidis; James R. Percival; Pablo Salinas; Ziqing Xie; Fangxin Fang; Christopher C. Pain; A. H. Muggeridge; Matthew David Jackson (J. Comput. Phys., 2016)

Modelling of fluid-structure interaction with multiphase viscous flows using an immersed-body method. - Pan Yang 014; Jiansheng Xiang; Fangxin Fang; Dimitris Pavlidis; John-Paul Latham; Christopher C. Pain (J. Comput. Phys., 2016)

A non-intrusive reduced-order model for compressible fluid and fractured solid coupling and its application to blasting. - Dunhui Xiao; Pan Yang 014; Fangxin Fang; Jiansheng Xiang; Christopher C. Pain; I. M. Navon; Min Chen (J. Comput. Phys., 2017)

Goal-based sensitivity maps using time windows and ensemble perturbations. - Claire E. Heaney; Pablo Salinas; Fangxin Fang; Christopher C. Pain; I. M. Navon (CoRR, 2018)

A Domain Decomposition Reduced Order Model with Data Assimilation (DD-RODA). - Rossella Arcucci; César Quilodrán Casas; Dunhui Xiao; Laetitia Mottet; Fangxin Fang; Pin Wu; Christopher C. Pain; Yi-Ke Guo (PARCO, 2019)

Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network. - M. Cheng; Fangxin Fang; Christopher C. Pain; I. M. Navon (CoRR, 2020)

Feasibility of DEIM for retrieving the initial field via dimensionality reduction. - Yuepeng Wang 002; Xuemei Ding; Kun Hu; Fangxin Fang; I. M. Navon; Guang Lin 001 (J. Comput. Phys., 2021)

Ensemble Kalman filter for GAN-ConvLSTM based long lead-time forecasting. - Meiling Cheng; Fangxin Fang; Ionel Michael Navon; Christopher C. Pain (J. Comput. Sci., 2023)

Advancing operational PM2.5 forecasting with dual deep neural networks (D-DNet). - Shengjuan Cai; Fangxin Fang; Vincent-Henri Peuch; Mihai Alexe; Ionel Michael Navon; Yanghua Wang (CoRR, 2024)

An AI-driven framework for the prediction of personalised health response to air pollution. - Nazanin Zounemat Kermani; Sadjad Naderi; Claire H. Dilliway; Claire E. Heaney; Shrreya Behll; Boyang Chen 002; Hisham Abubakar-Waziri; Alexandra E. Porter; Marc Chadeau-Hyam; Fangxin Fang; Ian M. Adcock; Kian Fan Chung; et al. (CoRR, 2025)