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

Title: Comparison of Different Upscaling Methods for Predicting Thermal Conductivity of Complex Heterogeneous Materials System: Application on Nuclear Waste Forms

Abstract

To develop a strategy in thermal conductivity prediction of a complex heterogeneous materials system, loaded nuclear waste forms, the computational efficiency and accuracy of different upscaling methods have been evaluated. The effective thermal conductivity, obtained from microstructure information and local thermal conductivity of different components, is critical in predicting the life and performance of waste form during storage. Several methods, including the Taylor model, Sachs model, self-consistent model, and statistical upscaling method, were developed and implemented. Microstructure based finite element method (FEM) prediction results were used to as benchmark to determine the accuracy of the different upscaling methods. Micrographs from waste forms with varying waste loadings were used in the prediction of thermal conductivity in FEM and homogenization methods. Prediction results demonstrated that in term of efficiency, boundary models (e.g., Taylor model and Sachs model) are stronger than the self-consistent model, statistical upscaling method, and finite element method. However, when balancing computational efficiency and accuracy, statistical upscaling is a useful method in predicting effective thermal conductivity for nuclear waste forms.

Authors:
; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1059182
Report Number(s):
PNNL-SA-85551
Journal ID: ISSN 1073-5623; NT0108060; TRN: US1400314
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Metallurgical and Materials Transactions. A, Physical Metallurgy and Materials Science
Additional Journal Information:
Journal Volume: 44; Journal Issue: 1 Supplement; Journal ID: ISSN 1073-5623
Publisher:
ASM International
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; thermal conductivity, heterogeneous materials, homogenization, statistical upscaling, correlation function

Citation Formats

Li, Dongsheng, Sun, Xin, and Khaleel, Mohammad A. Comparison of Different Upscaling Methods for Predicting Thermal Conductivity of Complex Heterogeneous Materials System: Application on Nuclear Waste Forms. United States: N. p., 2012. Web. doi:10.1007/s11661-012-1269-3.
Li, Dongsheng, Sun, Xin, & Khaleel, Mohammad A. Comparison of Different Upscaling Methods for Predicting Thermal Conductivity of Complex Heterogeneous Materials System: Application on Nuclear Waste Forms. United States. doi:10.1007/s11661-012-1269-3.
Li, Dongsheng, Sun, Xin, and Khaleel, Mohammad A. Sat . "Comparison of Different Upscaling Methods for Predicting Thermal Conductivity of Complex Heterogeneous Materials System: Application on Nuclear Waste Forms". United States. doi:10.1007/s11661-012-1269-3.
@article{osti_1059182,
title = {Comparison of Different Upscaling Methods for Predicting Thermal Conductivity of Complex Heterogeneous Materials System: Application on Nuclear Waste Forms},
author = {Li, Dongsheng and Sun, Xin and Khaleel, Mohammad A.},
abstractNote = {To develop a strategy in thermal conductivity prediction of a complex heterogeneous materials system, loaded nuclear waste forms, the computational efficiency and accuracy of different upscaling methods have been evaluated. The effective thermal conductivity, obtained from microstructure information and local thermal conductivity of different components, is critical in predicting the life and performance of waste form during storage. Several methods, including the Taylor model, Sachs model, self-consistent model, and statistical upscaling method, were developed and implemented. Microstructure based finite element method (FEM) prediction results were used to as benchmark to determine the accuracy of the different upscaling methods. Micrographs from waste forms with varying waste loadings were used in the prediction of thermal conductivity in FEM and homogenization methods. Prediction results demonstrated that in term of efficiency, boundary models (e.g., Taylor model and Sachs model) are stronger than the self-consistent model, statistical upscaling method, and finite element method. However, when balancing computational efficiency and accuracy, statistical upscaling is a useful method in predicting effective thermal conductivity for nuclear waste forms.},
doi = {10.1007/s11661-012-1269-3},
journal = {Metallurgical and Materials Transactions. A, Physical Metallurgy and Materials Science},
issn = {1073-5623},
number = 1 Supplement,
volume = 44,
place = {United States},
year = {2012},
month = {6}
}