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    YANG Tianxia, QIAO Hongxia, WANG Penghui, LI Jinpeng, XUE Hao. Reliability Evaluation of Temperature Resistance of Magnesium Cement Coated Reinforced Concrete Based on Weibull Distribution[J]. Journal of Basic Science and Engineering, 2024, 32(2): 587-600. DOI: 10.16058/j.issn.1005-0930.2024.02.019
    Citation: YANG Tianxia, QIAO Hongxia, WANG Penghui, LI Jinpeng, XUE Hao. Reliability Evaluation of Temperature Resistance of Magnesium Cement Coated Reinforced Concrete Based on Weibull Distribution[J]. Journal of Basic Science and Engineering, 2024, 32(2): 587-600. DOI: 10.16058/j.issn.1005-0930.2024.02.019

    Reliability Evaluation of Temperature Resistance of Magnesium Cement Coated Reinforced Concrete Based on Weibull Distribution

    • In view of the phenomenon that the working life of building structures in the western salt lake area is shortened under the harsh climate environment, salt and halogen resistant magnesium cement coated reinforced concrete (CRMOCC) is proposed to extend its service life. Through the high and low temperature alternating heat and humidity accelerated test of the specimen with a protective layer thickness of 45 mm, the mechanism analysis was carried out by means of regular non-destructive testing and micro means. Finally, the Weibull distribution function was selected for reliability modeling, and the shape parameters and scale parameters of reliability were estimated by least square method, median rank and maximum likelihood. The results show that:The accelerated test conditions include needle-like hydration products and fiber flocculent corrosion products. With the increase of acceleration time, the volume expansion of internal products along the interface transition zone causes local cracking of components. The reliability of the three different parameter estimation methods are different to a certain extent:the shape parameter value m of the least square method is the smallest, the scale parameter of the median rank method is larger, and the maximum likelihood method is affected by the number of binary iterations. The shape parameter m is the largest, the scale parameter η is the smallest, the probability density function is larger, the shorter the failure time, the greater the failure rate.
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