A Study of Supermanuever Aerodynamics

Abstract

The objective of this work is to develop a novel technique for studying transient separated flows, such as those typical for maneuvering aircraft. The ultimate goal of this research is to develop flow control techniques using the boundary conditions in a Navier Stokes calculation. Once numerical boundary conditions are established, then their physical counterparts may be found. A subdomain technique was developed which allows the study of the effects of various boundary conditions on a local portion of the flowfield. A search technique, using artificial intelligence methods, was developed and was used to find the combination of boundary conditions that achieved the desired flow control. In addition, a two-dimensional boundary conditions theory for the steady Euler and Navier Stokes equations was derived. A wide range of boundary conditions for the subdomains were tried without significant success. However, a boundary condition, based on Duhamel's equation, was found to be very promising in leading to a reduction of computer time. (JHD)

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Document Details

Document Type
Technical Report
Publication Date
Jan 31, 1990
Accession Number
ADA218378

Entities

People

  • David Nixon
  • Laura C. Rodman

Organizations

  • Nielsen Engineering & Research (United States)

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Aerodynamic Characteristics
  • Artificial Intelligence
  • Computational Fluid Dynamics
  • Computational Science
  • Computations
  • Differential Equations
  • Euler Equations
  • Flow Fields
  • Fluid Dynamics
  • Fluid Flow
  • Frequency
  • Hypervelocity Flow
  • Mechanical Properties
  • Navier Stokes Equations
  • Two Dimensional
  • Unsteady Flow
  • Vortex Shedding

Fields of Study

  • Physics

Readers

  • Computational Fluid Dynamics (CFD)
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Fluid Mechanics and Fluid Dynamics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms