Xiao-Dong Wen

The evaluation of the mechanical performance of fly ash-recycled mortar (FARM) is a necessary condition to ensure the efficient utilization of recycled fine aggregates. This article describes the design of nine mix proportions of FARMs with a low water/cement ratio and screens six mix proportions with reasonable flowability. The compressive strengths of FARMs were tested, and the influence of the water/cement ratio (w/c) and age on the compressive strength was analyzed. Meanwhile, a backpropagation neural network (BPNN) model optimized by the grey wolf optimizer (GWO), namely the GWO-BPNN model, was established to predict the compressive strength of FARM. The input layer of the model consisted of w/c, a cement/sand ratio, water reducer, age, and fly ash content, while the output layer was the compressive strength. The data set consisted of 150 sets from this article and existing research in the literature, of which 70% is used for model training and 30% for model validation. The results show that compared with the traditional BPNN, the coefficient of determination (R²) of GWO-BPNN increases from 0.85 to 0.93, and the mean squared error (MSE) of model training decreases from 0.018 to 0.015. Meanwhile, the convergence iterations of model validation decrease from 108 to 65. This indicates that GWO improved the prediction accuracy and computational efficiency of BPNN. The model results of characteristic heat, kernel density estimation, scatter matrix, and the SHAP value all indicated that the w/c was strongly negatively correlated with compressive strength, while the sand/cement ratio and age were strongly positively correlated with compressive strength. However, the relationship between the contents of fly ash, the water reducer, and the compressive strength was not obvious.

Cementitious concrete structures serving in sulfate environments suffer from serious durability challenges caused by chemical sulfate attacks (CSA), which lead to the volume expansion, cracking, and spalling of concrete and the early failure of structures. CSA on concrete involves the behaviors of ion transport, chemical reactions, the crystallization of reaction products, microstructural damage to the cement matrix, and the macroscopic deterioration of concrete, namely the transport-chemo-mechanical behaviors. This paper first introduces the reaction products, such as gypsum, ettringite, brucite, and thaumasite, between sulfate and concrete under different environmental conditions and their formation mechanism. Then, aiming at the ettringite type CSA, the theories of volume increase and crystallization pressure are elaborated to explain it-induced concrete degradation. Additionally, the crystallization pressure theory is used to describe the cracking behavior in the microstructure slurry caused by the ettringite crystal filling pore. Finally, a series of transport-chemo-mechanical models for ettringite type CSA are displaced module by module. It includes the sulfate diffusion-reaction model, the free expansion of concrete, and equivalent expansive force in concrete related to the reaction behavior: the model for chemo-mechanical behavior in concrete caused by CSA. These models can be used to analyze the distribution of sulfate ions and the reaction product content, expansive stress and strain in the concrete, and the cracking and spalling degree of the concrete, which is beneficial to evaluate the durability of concrete structures serving permanently in a sulfate environment.