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Thermal conductivity prediction model for compacted bentonites considering temperature variations
Nuclear Engineering and Technology ( IF 2.6 ) Pub Date : 2021-05-14 , DOI: 10.1016/j.net.2021.05.001
Seok Yoon , Min-Jun Kim , Seunghun Park , Geon-Young Kim

An engineered barrier system (EBS) for the deep geological disposal of high-level radioactive waste (HLW) is composed of a disposal canister, buffer material, gap-filling material, and backfill material. As the buffer fills the empty space between the disposal canisters and the near-field rock mass, heat energy from the canisters is released to the surrounding buffer material. It is vital that this heat energy is rapidly dissipated to the near-field rock mass, and thus the thermal conductivity of the buffer is a key parameter to consider when evaluating the safety of the overall disposal system. Therefore, to take into consideration the sizeable amount of heat being released from such canisters, this study investigated the thermal conductivity of Korean compacted bentonites and its variation within a temperature range of 25 °C to 80–90 °C. As a result, thermal conductivity increased by 5–20% as the temperature increased. Furthermore, temperature had a greater effect under higher degrees of saturation and a lower impact under higher dry densities. This study also conducted a regression analysis with 147 sets of data to estimate the thermal conductivity of the compacted bentonite considering the initial dry density, water content, and variations in temperature. Furthermore, the Kriging method was adopted to establish an uncertainty metamodel of thermal conductivity to verify the regression model. The R2 value of the regression model was 0.925, and the regression model and metamodel showed similar results.



中文翻译:

考虑温度变化的压实膨润土导热系数预测模型

一种用于高放废物 (HLW) 深部地质处置的工程屏障系统 (EBS),由处置罐、缓冲材料、填隙材料和回填材料组成。当缓冲器填满处理罐和近场岩体之间的空白空间时,来自罐的热能被释放到周围的缓冲材料中。这种热能迅速消散到近场岩体至关重要,因此在评估整个处置系统的安全性时,缓冲器的热导率是要考虑的关键参数。因此,考虑到此类罐释放的大量热量,本研究调查了韩国压实膨润土的热导率及其在 25°C 温度范围内的变化。 ° C 至 80–90 °C。结果,随着温度的升高,热导率增加了 5-20%。此外,温度在较高的饱和度下有更大的影响,而在较高的干密度下影响较小。本研究还对 147 组数据进行了回归分析,以估计压实膨润土的热导率,考虑初始干密度、含水量和温度变化。此外,采用克里金法建立导热系数的不确定性元模型,对回归模型进行验证。回归模型的R 2值为0.925,回归模型和元模型的结果相似。

更新日期:2021-05-14
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