Steel slag is the waste slag generated after steel smelting, which has cementitious activity. However, untreated steel slag can damage the integrity of steel slag concrete due to its harmful expansion. This study prepared porous aggregates by mixing powdered steel slag, fly ash, and cement and carbonated them with CO₂ under high pressure conditions (0.2 MPa). The effect of carbonation on the performance of steel slag aggregate was studied using volume stability and crushing value. The effect of different carbonation conditions on the products was studied using X-ray diffraction (XRD) and thermogravimetric (TG) analyses, and the carbon sequestration efficiency of steel slag under different treatment methods was quantitatively evaluated. The research results indicate that untreated steel slag was almost completely destroyed and lost its strength after autoclave curing. With the increase in temperature and carbonation time, the performance of steel slag aggregate gradually improved and the pulverization rate, expansion rate, and crushing value gradually decreased. According to the experimental results of XRD and TG, it was found that the reaction between f-CaO (free CaO) and CO₂ in steel slag generated CaCO₃, filling the pores inside the aggregate, which was the internal reason for the improvement of aggregate performance. After comparison, the best carbonation method was maintained at 55 °C for 72 h. After carbonation, the steel slag aggregate had a pulverization rate of 2.4%, an expansion rate of 0.23%, a crushing value of 23%, and a carbon sequestration efficiency of 11.27% per unit weight of aggregate.

Reactive rice husk ash (RHA) is used as a supplementary cementitious material (SCM) to prepare cement composite pastes. The impact of RHA content and the internal curing effect on the hydration process of the cementitious system was studied. The hydration heat, degree, and product content of the cement–RHA composite system at 3, 7, and 28 d were analyzed using hydration microcalorimetry, thermogravimetry, and XRD (Rietveld) analysis. The results show that with the increase in RHA, the main exothermic peaks move forward, and the values increase. The induction period is prolonged, and the acceleration period is shortened. The induction period of 15% RHA is extended to 3 h. The hydration heat of cement composite pastes is mainly divided into three stages. Namely, the first stage (0–18 h) is the superposition of the RHA nucleation effect and chemical effect, the second stage (18–51 h) is the superposition of the dilution effect and internal curing effect, and the third stage (51–72 h) is the internal curing effect with the water-release. The internal curing effect of RHA has a certain periodicity, which is related to its content. The water-release age in the early stage (24 h) advances with the increase of content, and the water-release effect in the later stage (7–28 d) is also significant with the increase of content. The higher the content, the more significant the promotion of the internal curing effect on cement hydration and the pozzolanic reaction of RHA.

As a key guarantee and cornerstone of building quality, the importance of deformation prediction for deep foundation pits cannot be ignored. However, the deformation data of deep foundation pits have the characteristics of nonlinearity and instability, which will increase the difficulty of deformation prediction. In response to this characteristic and the difficulty of traditional deformation prediction methods to excavate the correlation between data of different time spans, the advantages of variational mode decomposition (VMD) in processing non-stationary series and a gated cycle unit (GRU) in processing complex time series data are considered. A predictive model combining particle swarm optimization (PSO), variational mode decomposition, and a gated cyclic unit is proposed. Firstly, the VMD optimized by the PSO algorithm was used to decompose the original data and obtain the Internet Message Format (IMF). Secondly, the GRU model optimized by PSO was used to predict each IMF. Finally, the predicted value of each component was summed with equal weight to obtain the final predicted value. The case study results show that the average absolute errors of the PSO-GRU prediction model on the original sequence, EMD decomposition, and VMD decomposition data are 0.502 mm, 0.462 mm, and 0.127 mm, respectively. Compared with the prediction mean square errors of the LSTM, GRU, and PSO-LSTM prediction models, the PSO-GRU on the PTB0 data of VMD decomposition decreased by 62.76%, 75.99%, and 53.14%, respectively. The PTB04 data decreased by 70%, 85.17%, and 69.36%, respectively. In addition, compared to the PSO-LSTM model, it decreased by 8.57% in terms of the model time. When the prediction step size increased from three stages to five stages, the mean errors of the four prediction models on the original data, EMD decomposed data, and VMD decomposed data increased by 28.17%, 3.44%, and 14.24%, respectively. The data decomposed by VMD are more conducive to model prediction and can effectively improve the accuracy of model prediction. An increase in the prediction step size will reduce the accuracy of the deformation prediction. The PSO-VMD-GRU model constructed has the advantages of reliable accuracy and a wide application range, and can effectively guide the construction of foundation pit engineering.

To prevent cracks caused by shrinkage of the deck of the Xiaoqing River Bridge, MgO concrete (MC) and steel fiber reinforced MgO concrete (SMC) were used. The deformation and strength of the deck were measured in the field, the resistance to chloride penetration of the concrete was measured in the laboratory, and the pore structure of the concrete was analyzed by a mercury intrusion porosimeter (MIP). The results showed that the expansion caused by the hydration of MgO could suppress the shrinkage of the bridge deck, and the deformation of the deck changed from −88.3 × 10⁻⁶ to 24.9 × 10⁻⁶, effectively preventing shrinkage cracks. At the same time, due to the restriction of the expansion of MgO by the steel bars, the expansion of the bridge deck in the later stage gradually stabilized, and no harmful expansion was produced. When steel fiber and MgO were used at the same time, the three-dimensional distribution of steel fiber further limited the expansion of MgO. The hydration expansion of MgO in confined space reduced the porosity of concrete, optimized the pore structure, and improved the strength and durability of concrete. The research on the performance of concrete in the in-situ test section showed that MgO and steel fiber were safe for the bridge deck, which not only solved the problem of shrinkage cracking of the bridge deck but also further improved the mechanical properties of the bridge deck.

To reduce the cracking caused by shrinkage and avoid the brittle behavior of concrete, MgO expansion agent and steel fibers were used in this paper. Firstly, the effect of MgO and steel fibers on the compressive strength of concrete was compared. The results showed that the compressive strength of steel fibers reinforced concrete (SC) and steel fiber reinforced MgO concrete (SMC) was significantly improved. Compared with ordinary concrete (OC), SMC’s 28 days compressive strength increased by 19.8%. Secondly, the influence of MgO and steel fibers with different contents on the self-volumetric deformation of concrete was compared through the experiment. The results showed that as a result of the hydration expansion of MgO, MC and SMC both showed obvious expansion, and their 190 days expansion was 335 $\mu \epsilon$ and 288 $\mu \epsilon$ , respectively. Lastly, through a scanning electron microscope (SEM) test, it was found that the constraint effect of steel fibers changed the expansion mode of MgO from outward expansion to inward extrusion, thus improving the interfacial bond strength of concrete.