Specific heat capacity model for compacted bentonite buffer materials

被引:26
|
作者
Yoon, Seok [1 ]
Jeon, Jun-Seo [2 ]
Kim, Geon-Young [1 ]
Seong, Joo-Hyun [3 ]
Baik, Min-Hoon [1 ]
机构
[1] KAERI, Radioact Waste Disposal Res Div, Daejeon 34057, South Korea
[2] Korea Adv Inst Sci & Technol, Dept Civil & Environm Engn, Daejeon 34141, South Korea
[3] KISTEC, Inst Infrastruct Safety, Jinju 52856, South Korea
基金
新加坡国家研究基金会;
关键词
Compacted bentonite buffer material; Specific heat capacity; Regression analysis; Artificial neural network; WEATHERED GRANITE SOILS; THERMAL-CONDUCTIVITY; NEURAL-NETWORK;
D O I
10.1016/j.anucene.2018.10.045
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
A geological repository for the disposal of high-level radioactive waste is generally constructed in host rock at depths of 500-1000 m below the ground surface. A geological repository system consists of a disposal canister with packed spent fuel, buffer material, backfill material, and intact rock. The buffer is indispensable for ensuring the disposal safety of high-level radioactive waste, and it inhibits the release of radionuclides and protects the canister from the inflow of groundwater. Because the high temperatures generated in a disposal canister are released to the surrounding buffer material, the thermal properties of the buffer material are very important for determining disposal safety. Although there have been many studies on thermal conductivity, only a few studies have investigated the specific heat capacity of bentonite buffer materials. Therefore, this paper presents a specific heat capacity prediction model considering complex properties for compacted Gyeongju bentonite buffer material, which is a Ca-bentonite produced in Korea. The specific heat capacity of the compacted bentonite buffer material was measured using a dual probe method for varying degrees of saturation and dry densities. Models were suggested based on a regression analysis and an artificial neural network to predict the specific heat capacity of the compacted bentonite buffer material using 39 sets of data obtained by the dual probe method. Models developed by this research are expected to be used as input parameters in the performance assessment of entire disposal system. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:18 / 25
页数:8
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