Research and Prediction on the Properties of Concrete at Cryogenic Temperature Based on Gray Theory.

To solve the cryogenic temperature problems faced by all-concrete liquefied natural gas (ACLNG) storage tanks during servicing, a low temperature resistant and high strength concrete (LHC) was designed from the perspectives of reducing water-binder ratio, removing coarse aggregates, optimizing composite mineral admixture and utilizing steel fibers. The variation laws of compressive and tensile strength, elastic modulus and Poisson's ratio for C60 concrete and LHC were compared and analyzed under the temperatures from 10 to −165 °C through uniaxial compression and tensile tests. The rapid freezing method was adopted to analyze the evolution process of mass and relative dynamic elastic modulus loss rates for C60 and LHC in 0–300 freeze-thaw cycles. The gas permeability test was carried out, and the laws of gas permeability coefficient varied with temperature and cryogenic freeze-thaw cycles were obtained. Then, the grey dynamic model GM (1,1) was used to predict the variation laws of physical and mechanical parameters on the basis of the test data. The test results demonstrate that the compressive strength, elastic modulus and Poisson's ratio for both C60 and LHC increase significantly from 10 to −165 °C, but the specific variation laws are different, and there is a phenomenon that some parameters decrease after reaching a critical temperature range for C60. The uniaxial tensile strength increases first and then decreases as temperature decreases, and finally increases slightly at −165 °C for both C60 and LHC. The mass and relative dynamic elastic modulus loss rates of LHC are much lower than that of C60 under different freeze-thaw cycles. The gas permeability coefficient of C60 declines gradually with the drop of temperature, and increases gradually with the number of freeze-thaw cycles while the gas permeability coefficient of LHC basically remains stable and is much lower than that of C60. Therefore, such a conclusion can be drawn that LHC has better properties at cryogenic temperature. On the premise of providing consistent functional mode, GM (1,1) can predict the test data with high accuracy, which well reflects the variation laws of relevant parameters. [ABSTRACT FROM AUTHOR]