Integrated Microtransducer and Neural Networks System for Distributed Control

Abstract

For a phenomenon with a wide spread of length scales, e.g., turbulence, a large scale integrated transducer system can facilitate communication of the local information measured by individual sensors as well as identify the global characteristic through a collection of the sensors. The actuators then can, based on the local and global information, execute the proper control strategy. This concept is best illustrated by research in turbulence control. Surface shear stress reduction in the turbulent boundary layer is the grand challenge in fluid mechanics research. Many randomly distributed small flow structures in the boundary layer are responsible for drag production. In this project, we developed an integrated MEMS system to detect the high shear streaks and to reduce the surface shear stress.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1997
Accession Number
ADA349194

Entities

People

  • Ho Chih-ming

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Advanced Electronics
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Assembly
  • Boundary Layer
  • Chemistry
  • Computational Fluid Dynamics
  • Computational Science
  • Fabrication
  • Flow Visualization
  • Fluid Dynamics
  • Fluid Flow
  • Hydrodynamics
  • Manufacturing
  • Materials Science
  • Micro-Machines
  • Microelectromechanical Systems
  • Micromachining
  • Monte Carlo Method
  • Turbulent Mixing

Fields of Study

  • Physics

Readers

  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Robotics and Automation.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML