Fangxin Fang

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 9

Top Topics

Reduced Order Model

Financial Forecasting

Top Venues

J. Comput. Phys.

J. Comput. Sci.

Publications

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 (2024)
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 (2023)
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 (2021)
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 (2020)
Rossella Arcucci, César Quilodrán Casas, Dunhui Xiao, Laetitia Mottet, Fangxin Fang, Pin Wu, Christopher C. Pain, Yi-Ke Guo
A Domain Decomposition Reduced Order Model with Data Assimilation (DD-RODA). PARCO (2019)
Claire E. Heaney, P. Salinas, Fangxin Fang, Christopher C. Pain, I. M. Navon
Goal-based sensitivity maps using time windows and ensemble perturbations. CoRR (2018)
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 (2017)
Alexandros Adam, Dimitris Pavlidis, James R. Percival, P. Salinas, Ziqing Xie, Fangxin Fang, Christopher C. Pain, A. H. Muggeridge, Matthew D. Jackson
Higher-order conservative interpolation between control-volume meshes: Application to advection and multiphase flow problems with dynamic mesh adaptivity. J. Comput. Phys. 321 (2016)
Pan Yang, Jiansheng Xiang, Fangxin Fang, Dimitris Pavlidis, John-Paul Latham, Christopher C. Pain
Modelling of fluid-structure interaction with multiphase viscous flows using an immersed-body method. J. Comput. Phys. 321 (2016)
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 (2015)
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 (2014)
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) (2013)
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) (2013)
Fangxin Fang, Christopher C. Pain, I. M. Navon, A. 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 (2013)
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) (2006)