With steel fiber and basalt fiber volume dosing serving as variation parameters, a total of 200 d cycles of acid rain corrosion cycle tests were conducted on fiber concrete in this study. We selected three durability evaluation parameters to assess the degree of damage deterioration on fiber concrete, used scanning electron microscopy, mercury intrusion porosimetry, and a dimensional microhardness meter to analyze the concrete micromorphology, and established a GM(1,1)-Markov model for life prediction of its durability. Results reveal that the acid rain environment is the most sensitive to the influence of the relative dynamic elastic modulus evaluation parameter, and concrete has specimens that show failure damage under this parameter evaluation. Incorporation of fibers can reduce the amount of corrosion products inside the concrete, decrease the proportion of harmful pores, optimize the mean pore-size, and significantly improve the resistance to acid rain attack. Concrete with 2% steel fiber and 0.1% basalt fiber by volume has the least change in durability damage, and the predicted service life by GM(1,1)-Markov model is 322 d.

This study was designed to solve the problem of magnesium hazards due to potash extraction in the salt lake region. Using basalt fiber (BF) as the reinforcement material and magnesium oxychloride cement (MOC) as the gelling material, a BF/MOC composite material was prepared. Firstly, the effect of BF addition content on the basic mechanical properties of the composites was investigated. Then, through the salt spray corrosion test, the durability damage deterioration evaluation analysis was carried out from both macroscopic and microscopic aspects using mass change, relative dynamic modulus of elasticity (RDME) change, SEM analysis and FT-IR analysis. Finally, a GM(1, 1)-Markov model was established to predict the durability life of composite materials by using durability evaluation indicators. The results show that: when the BF content is 0.10% (by volumetric content), the composites have the best mechanical properties and resistance to salt spray corrosion. However, when the volume of BF content exceeds 0.10%, a large number of magnesium salt crystallization products are observed from the microscopic point of view, and the corrosion of the main strength phase of MOC is more serious. The prediction results of the GM(1, 1)-Markov model are highly identical with the raw data. In addition, using the change of RDME as a predictor, RDME is more sensitive to environmental factor compared to the change of mass. Predictions using the change of RDME as a threshold indicate that MOC-BF0.10 has the longest durability life, which is 836 days. The model is important to promote the application of MOC composites in the salt lake region and to promote the healthy development of green building materials.

Utilizing recycled aggregate concrete (RAC) for cyclic usage in building materials is one of the most feasible methods for reducing the demand for natural aggregates in the construction sector and disposing of construction and demolition trash in landfills. Previous research has demonstrated that the weak freeze-thaw (F-T) resistance of RAC poses a significant threat to the safety of RAC structures in severe cold regions. Therefore, this paper explores the influence of ceramic waste powder (CWP) at various replacement rates on the freeze-thaw resilience of RAC. In this experiment, six groups of CWP doping ratios of 0%, 10%, 20%, 30%, 40, and 50% were designed. Before the F-T cycling test, each group of specimens’ basic mechanical and physical performance data was measured throughout the regular curing age. At the conclusion of each F-T cycle, the durability performance of RAC was tested using the impact-echo method and compressive strength test. To predict the lifetime of RAC mixtures, a Grey-Markov model was created. It was found that the impact-echo method is more appropriate for assessing the durability of RAC in a freeze-thaw condition. The RAC’s F-T resistance is greatest when the CWP content is 20%. The Grey-Markov model has a high degree of predictive accuracy, effectively reflecting the relationship between RAC durability and F-T cycles, and has wide practical applications.

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