Hydrodynamic object identification with artificial neural models

  title={Hydrodynamic object identification with artificial neural models},
  author={Sreetej Lakkam and B. T. Balamurali and Roland Bouffanais},
  journal={Scientific Reports},
The lateral-line system that has evolved in many aquatic animals enables them to navigate murky fluid environments, locate and discriminate obstacles. Here, we present a data-driven model that uses artificial neural networks to process flow data originating from a stationary sensor array located away from an obstacle placed in a potential flow. The ability of neural networks to estimate complex underlying relationships between parameters, in the absence of any explicit mathematical description… 

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Deep learning in fluid dynamics

  • J. Kutz
  • Computer Science
    Journal of Fluid Mechanics
  • 2017
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