Hydrodynamic Drag of Disks with Compliant Membrane/Substrate Faces.

Abstract

A disk with interchangeable faces of compliant membrane/substrate combinations was spin-tested in a water tank. A device for stretching a membrane uniformly and with repeatable results was designed, fabricated, and successfully employed. Six membrane materials and three substrate materials were utilized to fabricate over 36 differenent compliant disks. Each of these was tested in turbulent flow over a Reynolds number range of 1.77-2.95 x 10 to the 6th power. A maximum drag reduction of 19% is indicated from tests with a heavy polyurethane membrane unbonded to an organic rubber substrate. This amount of drag reduction is inferred from data taken with polyurethane sheet material which had a rough surface finish. Thus, additional tests with smooth polyurethane membranes are needed to verify the reported drag reductions. The present results tend to follow Ash's membrane frequency criterion, other data for similar membranes suggest this criterion may be a necessary but not sufficient condition. It is recommended that future exploratory studies of the hydrodynamic drag reduction potential of membrane walls be done with flat plates in order to facilitate more detailed flow measurements.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1977
Accession Number
ADA035865

Entities

People

  • T. D. Reed

Organizations

  • Vought

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Boundary Layer
  • Drag Reduction
  • Drive Shafts
  • Engineering
  • Fluid Mechanics
  • Frequency
  • Materials
  • Materials Science
  • Mechanics
  • Navy
  • Polyurethanes
  • Resonant Frequency
  • Reynolds Number
  • Standing Waves
  • Substrates
  • Surface Roughness
  • Turbulent Flow

Readers

  • Fluid Mechanics and Fluid Dynamics.
  • Pavement Materials Engineering.
  • Underwater engineering and Marine Technology.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference