Development of Methods for Assessment of Gliding Parachute Applications

Abstract

In order to assess the possible utility of gliding parachutes, it was necessary to develop a set of methods for predicting behavior of gliding parachutes. The extent of agreement between simulation and flight data indicates that the primary factors included in the longitudinal stability analysis and in the 6DOF simulation are correct. Although the stability analysis predicts only steady-state behavior, it forms the basis required for analysis of dynamic behavior in the body-fixed XZ plane. The agreement seen in descent rate would not be possible with an invalid stability model. Of course, in turning flight during the response immediately following the deflection, other factors such as the assumed spanwise distribution of lift and drag become predominant. The agreement in yaw rate best illustrates correctness of this aspect of the 6DOF model. The mechanics driving motion during a spin are quite difficult to understand; however, the agreement shown in the descent rate indicates that the mass ratios assumed are acccurate and further justifies the assumption of spanwise distribution of lift and drag. In further development activities on gliding parachute systems, the 6DOF model will serve to guide exploratory work and will be updated for more accurate application to different canopies and to larger systems.

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Document Details

Document Type
Technical Report
Publication Date
Jun 18, 1982
Accession Number
ADA117103

Entities

People

  • Thomas F. Goodrick

Organizations

  • United States Army Soldier Systems Center

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Aerodynamic Forces
  • Air Masses
  • Aircrafts
  • Computer Programs
  • Flight
  • Geometry
  • Geosynchronous Orbits
  • Guidance
  • Measurement
  • Mechanics
  • Parachutes
  • Parafoils
  • Recording Systems
  • Simulations
  • Tape Recorders
  • Trailing Edges
  • Wind Tunnels

Readers

  • Aerial Delivery - Logistics and Supply Chain Management.
  • Computational Modeling and Simulation
  • Control Systems Engineering.