Nondestructive Evaluation (NDE) of Sintered Silicon Carbide and its Correlation to Microstructure and Mechanical Properties

Abstract

High density is a critical acceptance criterion for armor ceramics. Quantifying the difference in density between what would be considered to be a "good" or "bad" region is complicated. As density is reduced from theoretical, does this infer the presence of defects? The minimum acceptable density that ensures favorable ballistic performance is unknown. This question concerns not only the presence of defective regions, which may include pores or inclusions, but also the spatial distribution of the defect within the sample. This study will seek to expand upon correlating the microstructural assessment, mechanical properties, and non-destructive evaluation results of ceramic armor tiles. This study will present the techniques necessary for microstructural analysis, which include nearest-neighbor distance distributions, tessellation analysis, average pore size, and pore size distributions. The ability of Knoop indentation and 4-pt flexure tests, combined with the results of ultrasound C-scans, to reliably predict ballistic performance of armor ceramics will be evaluated.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
ADA505772

Entities

People

  • Andrew Portune
  • Douglas M. Slusark
  • Ernest Chin
  • James Campbell
  • M. V. Demirbas
  • Raymond E. Brennan
  • Richard A Haber
  • Steven D. Miller
  • William H. Green

Organizations

  • Rutgers University–New Brunswick

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Ceramic Materials
  • Engineered Materials
  • Hardness
  • Image Processing
  • Materials
  • Materials Science
  • Materials Testing
  • Mechanical Properties
  • Microhardness
  • Modulus Of Elasticity
  • Silicon Carbide
  • Spatial Distribution
  • Test And Evaluation
  • Test Methods
  • Ultrasounds
  • Waves

Fields of Study

  • Materials science

Readers

  • Computer Vision.
  • Structural Health Monitoring of Composite Structures.
  • Thin Film Deposition Science.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference