Visual Inference of Flow Flux Via Free Surface PDE Model and Image Sequence Assimilation

Shan Guo, Chao Xu, Ka Fai Cedric Yiu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

The free-surface flows, such as flows in rivers, lakes, and tides, play an important role in hydraulic engineering and environmental monitoring. However, due to their complex and changeable characters, the precise evolution procedure is quite difficult to reconstruct. In this study, the authors propose a novel framework to reconstruct the free-surface flow modelled by the shallow water equations by assimilating the images sequences. In particular, the ensemble Kalman filter framework is employed to implement the assimilation process. The efficiency of the proposed strategy has been verified through numerical simulations in which the accurate flow field in different situations could be obtained within limited assimilation steps.

Original languageEnglish
Pages (from-to)20-27
Number of pages8
JournalIET Cyber-systems and Robotics
Volume1
Issue number1
DOIs
Publication statusPublished - Jun 2019

Keywords

  • accurate flow field
  • assimilation process
  • assimilation steps
  • changeable characters
  • complex characters
  • data assimilation
  • ensemble Kalman filter framework
  • environmental monitoring
  • flow flux
  • free-surface flow
  • hydraulic engineering
  • image sequence assimilation
  • image sequences
  • images sequences
  • Kalman filters
  • numerical analysis
  • partial differential equations
  • precise evolution procedure
  • shallow water equations
  • visual inference

ASJC Scopus subject areas

  • Information Systems
  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computational Theory and Mathematics
  • Artificial Intelligence

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