Advanced Concepts For Boundary Layer Control

Abstract

New concepts for turbulent boundary layer control for viscous drag reduction have been explored through numerical experiments. Direct numerical simulations of a turbulent channel flow have been conducted to develop new robust control strategies. Three different control schemes have been developed. These include applications of neural networks, a suboptimal control theory, and systems control theory. The first two approaches were developed for viscous drag reduction in turbulent boundary layers, while the third approach was developed for delay of transition to turbulence. In all cases, surface blowing and suction was used as control input. All three approaches led to simple feedback control laws, which led to substantial viscous drag reduction (neural network and suboptimal control theory) and delay of transition (systems control theory). Implication of these results as well as issues regarding practical implementation are discussed.

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Document Details

Document Type
Technical Report
Publication Date
Oct 27, 1998
Accession Number
ADA355992

Entities

People

  • John J Kim

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Boundary Layer
  • Boundary Layer Control
  • Computational Fluid Dynamics
  • Computational Science
  • Control Systems
  • Control Theory
  • Differential Equations
  • Drag Reduction
  • Flow Fields
  • Fluid Dynamics
  • Fluid Mechanics
  • Jet Propulsion
  • Mechanics
  • Poiseuille Flow
  • Turbulence
  • Turbulent Boundary Layer
  • Turbulent Flow

Fields of Study

  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Fluid Mechanics and Fluid Dynamics.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks