Yanjin Liu, Jiu Luo, Mingming Huang, Hong Liu, Zhiwei Wang, Yi Heng
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引用次数: 0
Abstract
Solving three-dimensional (3D) multi-physics forward and inverse problems is indispensable for fundamental understanding and optimal design of membrane-based desalination systems. Unfortunately, it is computationally expensive when applying traditional numerical methods. Herein, a modified Fourier neural operator (FNO)-based method is proposed to efficiently solve complex 3D multi-physics problems. The intelligent solver solves the 3D forward problems in seconds, which is approximately 105-106 times faster than traditional finite-element based method with a comparable solution quality. The average prediction accuracy is more than 96%. Moreover, the proposed FNO-based method is mesh-independent and has zero-shot super-resolution ability. It can be used to provide a fast solution for the optimal design of membrane module to mitigate concentration polarization and membrane fouling for next-generation ultrapermeable membrane system.
npj Clean WaterEnvironmental Science-Water Science and Technology
CiteScore
15.30
自引率
2.60%
发文量
61
审稿时长
5 weeks
期刊介绍:
npj Clean Water publishes high-quality papers that report cutting-edge science, technology, applications, policies, and societal issues contributing to a more sustainable supply of clean water. The journal's publications may also support and accelerate the achievement of Sustainable Development Goal 6, which focuses on clean water and sanitation.