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Fast multi-physics simulation approach in underwater exploration via deep learning technique

  • Yue Zhu
  • , Yuanguo Zhou*
  • , Fawad Javaid
  • , Qiang Ren
  • , Wenyuan Liu*
  • *Corresponding author for this work
  • Xi'an University of Science and Technology
  • University of Gujrat
  • Shaanxi University of Science and Technology

Research output: Contribution to journalLetterpeer-review

Abstract

When underwater pressure wave is generated, moving water particles cut off the geomagnetic field and produce induced currents, which will simultaneously induce electromagnetic field in the whole space. Due to the large distribution range and slow attenuation of this pseudo-radiation, it is possible to observe above the sea surface. In this work, we introduce a novel long- and short-term memory neural network and the corresponding training algorithm, to model the multi-physics process instead of solving magneto-hydrodynamics equations via numerical methods. Compared with commercial software, the proposed approach is much faster and easier to apply, which puts forward a feasible alternative for predicting the electromagnetic field distribution excited by underwater pressure wave.

Original languageEnglish
Pages (from-to)200-202
Number of pages3
JournalElectronics Letters
Volume58
Issue number5
DOIs
StatePublished - Mar 2022

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