Unsteady Aerodynamics - Work Unit 2300-FF-07.

Abstract

This task addressed basic research to better understand unsteady, separated flows and to utilize this understanding to develop innovative concepts to control unsteady aerodynamic phenomena to enhance flight vehicle maneuverability. This effort sought to expand the flight performance boundaries by developing a capability to maneuver in the high-angle-of-attack, post-stall flight regime. The research was organized around two broad topical areas: (1) understanding and predicting the dynamics of unsteady, separated flows and (2) controlling unsteady, separated flows to enhance aerodynamic performance. Several types of flow fields were studied to gain an understanding of unsteady, separated flows. These included flow over rectangular wings, flow over delta wing, flow over forebodies and flow in the vicinity of the tail on a fighter type aircraft. The studies were both computational and experimental. Control efforts focused on the pulsed blowing to maintain attached flow, continuous blowing to control vortex breakdown on delta wing, and the use of neural networks to predict and control unsteady aerodynamic forces. (AN - analyst's abstract; delete this message when done)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1995
Accession Number
ADA294782

Entities

People

  • Eric J. Stephen

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Aerodynamic Configurations
  • Air Force
  • Aircrafts
  • Boundary Layer
  • Computational Fluid Dynamics
  • Computational Science
  • Flow Visualization
  • Fluid Dynamics
  • Fluid Flow
  • Fluid Mechanics
  • Geometry
  • Hydrodynamics
  • Mechanical Phenomena
  • Mechanical Properties
  • Mechanics
  • Physics Laboratories
  • Turbulent Mixing

Fields of Study

  • Physics

Readers

  • Aerodynamics.
  • Aerodynamics/Aeronautics.
  • Research Science/Academic Research

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems