An Investigation of the Effects of Formulation Parameters on Erosive Burning of Composite Propellants

Abstract

A series of ten composite solid propellants with systematically varied formulation parameters has been characterized with respect to the dependence of burning rate on pressure and product crossflow velocity over a wide range of these variables. Predictions of erosive burning characteristics of these formulations made with a simple model based on columnar diffusion flame bending were found to agree fairly well with data except at low pressure conditions where propellant heterogeneity is relatively unimportant. A second- generation, considerably more fundamental model of composite propellant combustion (with and without crossflow) which includes both the flame bending mechanism and a turbulent transport property augmentation erosive burning mechanism also yielded predictions in good agreement with data, even in the low pressure region where the first generation model failed, for five of the six formulations against which it has been tested to date. The most important factor affecting the sensitivity of composite propellant burning rate to crossflow was found to be the base (no crossflow) burning rate versus pressure characteristics of the propellant, low burning-rate propellants being more sensitive to cross flow. As an important example, three formulations with widely different compositional and particle size parameters but essentially equal base burning rate behavior exhibited nearly identical erosive burning characteristics.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1979
Accession Number
ADA098087

Entities

People

  • Merrill K. King

Organizations

  • ARCO

Tags

DTIC Thesaurus Topics

  • Air Force
  • Burning Rate
  • Combustion
  • Composite Propellants
  • Cross Flow
  • Diameters
  • Diffusion
  • Erosive Burning
  • Flow
  • Governments
  • High Pressure
  • Mach Number
  • Particle Size
  • Pressure Measurement
  • Propellants
  • Solid Propellants
  • Transport Properties

Fields of Study

  • Physics

Readers

  • Computational Modeling and Simulation
  • Rocket Propulsion.

Technology Areas

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