TY - JOUR
T1 - A review on thermal conductivity of unsaturated bentonite
AU - Ye, W. M.
AU - Shao, C. Y.
AU - Lu, P. H.
AU - Liu, Z. R.
AU - Chen, L.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - As unsaturated bentonite is used a buffer/backfill material in the construction of engineered barriers for high-level nuclear waste disposal, understanding its thermal properties is crucial for maintaining the operational stability of the repository. This review paper synthesizes research on the thermal conductivity of unsaturated bentonite, encompassing aspects of heat transfer mechanisms, measurement techniques, influencing factors, and prediction models. The results highlight that the transient and steady-state methods have emerged as the predominant techniques for measuring the thermal conductivity of unsaturated bentonite owing to their efficiency and the prevention of water redistribution within the sample throughout the testing phase. Factors such as dry density, degree of saturation, additive content, and temperature were observed to positively influence the thermal conductivity of unsaturated bentonite, whereas an increase in the ion concentration of the pore fluid decreased the thermal conductivity. The prediction models for the thermal conductivity of unsaturated bentonite are categorized into empirical, normalized, and theoretical models. Although empirical and normalized models provide some insight, they suffer from a lack of theoretical foundation, and the parameters they incorporate often lack clear physical significance, complicating their practical application despite their capacity to represent the multifield coupling characteristics of thermal conductivity. The advancements in microscopic testing methods and computational technology herald the potential of mesoscale models and machine learning as formidable tools for predicting the thermal conductivity of unsaturated bentonite, suggesting a promising direction for future research.
AB - As unsaturated bentonite is used a buffer/backfill material in the construction of engineered barriers for high-level nuclear waste disposal, understanding its thermal properties is crucial for maintaining the operational stability of the repository. This review paper synthesizes research on the thermal conductivity of unsaturated bentonite, encompassing aspects of heat transfer mechanisms, measurement techniques, influencing factors, and prediction models. The results highlight that the transient and steady-state methods have emerged as the predominant techniques for measuring the thermal conductivity of unsaturated bentonite owing to their efficiency and the prevention of water redistribution within the sample throughout the testing phase. Factors such as dry density, degree of saturation, additive content, and temperature were observed to positively influence the thermal conductivity of unsaturated bentonite, whereas an increase in the ion concentration of the pore fluid decreased the thermal conductivity. The prediction models for the thermal conductivity of unsaturated bentonite are categorized into empirical, normalized, and theoretical models. Although empirical and normalized models provide some insight, they suffer from a lack of theoretical foundation, and the parameters they incorporate often lack clear physical significance, complicating their practical application despite their capacity to represent the multifield coupling characteristics of thermal conductivity. The advancements in microscopic testing methods and computational technology herald the potential of mesoscale models and machine learning as formidable tools for predicting the thermal conductivity of unsaturated bentonite, suggesting a promising direction for future research.
UR - https://www.scopus.com/pages/publications/85194476457
U2 - 10.1088/1755-1315/1330/1/012057
DO - 10.1088/1755-1315/1330/1/012057
M3 - Conference article
AN - SCOPUS:85194476457
SN - 1755-1307
VL - 1330
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012057
T2 - 5th GeoShanghai International Conference, GeoShanghai 2024
Y2 - 26 May 2024 through 29 May 2024
ER -