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A robotic Intelligent Towing Tank for learning complex fluid-structure dynamics.

D Fan1,2, G Jodin3, T R Consi4,2

  • 1Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. dfan@mit.edu george_karniadakis@brown.edu mistetri@mit.edu.

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This study introduces an Intelligent Towing Tank using active learning to reduce experiments for vortex-induced vibration (VIV) research. This automated approach accelerates discovery in complex fluid dynamics.

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Area of Science:

  • Fluid dynamics
  • Experimental physics
  • Robotics and automation

Background:

  • Traditional experimental approaches for fluid-elastic instabilities are time-consuming.
  • Exploring high-dimensional parametric spaces in fluid dynamics is challenging.
  • Vortex-induced vibration (VIV) involves complex nonlinear responses.

Purpose of the Study:

  • To develop an automated experimental facility for VIV research.
  • To implement active learning for efficient experimental design.
  • To reduce the number of experiments needed to map complex hydrodynamic mechanisms.

Main Methods:

  • Development of an Intelligent Towing Tank.
  • Utilizing active learning to select experimental parameters based on quantified uncertainties.
  • Employing an "explore-and-exploit" strategy in high-dimensional parametric spaces.

Main Results:

  • Significant reduction in the number of experiments required.
  • Effective exploration of complex parametric spaces.
  • Demonstration of active learning's efficacy in VIV research.

Conclusions:

  • The Intelligent Towing Tank represents a paradigm shift in experimental research.
  • Active learning accelerates discovery and optimizes exploration of complex systems.
  • This approach has potential applications across scientific disciplines for modeling nonlinear systems.