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Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
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Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
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POD-Galerkin FSI Analysis for Flapping Motion.

Shigeki Kaneko1, Shinobu Yoshimura1

  • 1Department of Systems Innovations, School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan.

Biomimetics (Basel, Switzerland)
|November 24, 2023
PubMed
Summary

This study developed a reduced-order model for flapping motion simulations, significantly cutting computational time for flapping-wing micro air vehicle design. The efficient model preserves accuracy, enabling intensive parametric studies.

Keywords:
flapping motionfluid–structure interactionpartitioned iterative coupled analysisproper orthogonal decompositionreduced-order model

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Area of Science:

  • Computational Fluid Dynamics (CFD)
  • Fluid-Structure Interaction (FSI)
  • Aerospace Engineering

Background:

  • Flapping-wing micro air vehicles (FWMAVs) require extensive simulation for design.
  • Current Fluid-Structure Interaction (FSI) simulations are computationally intensive.
  • A computationally efficient model is crucial for parametric studies in FWMAV development.

Purpose of the Study:

  • To develop a reduced-order model for flapping motion.
  • To enable computationally efficient simulations for FWMAV design.
  • To facilitate intensive parametric studies for product optimization.

Main Methods:

  • Employed the Dirichlet-Neumann partitioned iterative method for FSI problems.
  • Utilized snapshot data from high-fidelity FSI analysis.
  • Developed low-dimensional surrogate systems using the Proper Orthogonal Decomposition (POD) under Galerkin projection (POD-Galerkin method).

Main Results:

  • Successfully created a reduced-order model for a 2D flapping motion FSI problem.
  • Demonstrated significant reduction in computational time.
  • Maintained desired accuracy in simulations with varying flapping frequency and amplitude.

Conclusions:

  • The POD-Galerkin reduced-order model is effective for flapping motion simulations.
  • This approach significantly reduces computational cost for FSI analysis.
  • The model supports efficient parametric studies essential for FWMAV design and optimization.