skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.

Abstract

Brittle failure is often influenced by difficult to measure and variable microstructure-scale stresses. Recent advances in photoluminescence spectroscopy (PLS), including improved confocal laser measurement and rapid spectroscopic data collection have established the potential to map stresses with microscale spatial resolution (%3C2 microns). Advanced PLS was successfully used to investigate both residual and externally applied stresses in polycrystalline alumina at the microstructure scale. The measured average stresses matched those estimated from beam theory to within one standard deviation, validating the technique. Modeling the residual stresses within the microstructure produced general agreement in comparison with the experimentally measured results. Microstructure scale modeling is primed to take advantage of advanced PLS to enable its refinement and validation, eventually enabling microstructure modeling to become a predictive tool for brittle materials.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1377754
Report Number(s):
SAND2017-8965
656428
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Teague, Melissa Christine, Teague, Melissa Christine, Rodgers, Theron, Rodgers, Theron, Grutzik, Scott Joseph, Grutzik, Scott Joseph, Meserole, Stephen, and Meserole, Stephen. Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.. United States: N. p., 2017. Web. doi:10.2172/1377754.
Teague, Melissa Christine, Teague, Melissa Christine, Rodgers, Theron, Rodgers, Theron, Grutzik, Scott Joseph, Grutzik, Scott Joseph, Meserole, Stephen, & Meserole, Stephen. Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.. United States. doi:10.2172/1377754.
Teague, Melissa Christine, Teague, Melissa Christine, Rodgers, Theron, Rodgers, Theron, Grutzik, Scott Joseph, Grutzik, Scott Joseph, Meserole, Stephen, and Meserole, Stephen. Tue . "Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.". United States. doi:10.2172/1377754. https://www.osti.gov/servlets/purl/1377754.
@article{osti_1377754,
title = {Microstructural Modeling of Brittle Materials for Enhanced Performance and Reliability.},
author = {Teague, Melissa Christine and Teague, Melissa Christine and Rodgers, Theron and Rodgers, Theron and Grutzik, Scott Joseph and Grutzik, Scott Joseph and Meserole, Stephen and Meserole, Stephen},
abstractNote = {Brittle failure is often influenced by difficult to measure and variable microstructure-scale stresses. Recent advances in photoluminescence spectroscopy (PLS), including improved confocal laser measurement and rapid spectroscopic data collection have established the potential to map stresses with microscale spatial resolution (%3C2 microns). Advanced PLS was successfully used to investigate both residual and externally applied stresses in polycrystalline alumina at the microstructure scale. The measured average stresses matched those estimated from beam theory to within one standard deviation, validating the technique. Modeling the residual stresses within the microstructure produced general agreement in comparison with the experimentally measured results. Microstructure scale modeling is primed to take advantage of advanced PLS to enable its refinement and validation, eventually enabling microstructure modeling to become a predictive tool for brittle materials.},
doi = {10.2172/1377754},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Aug 01 00:00:00 EDT 2017},
month = {Tue Aug 01 00:00:00 EDT 2017}
}

Technical Report:

Save / Share: