Nano-SiO₂ (NS) is widely used in cement-based materials due to its excellent physical properties. To study the influence of NS content on a cement paste and the interfacial transition zone (ITZ), cement paste samples containing nano content ranging from 0 to 2% (by weight of cement) were prepared, and digital image correlation (DIC) technology was applied to test the mechanical properties. Finally, the optimal NS content was obtained with statistical analysis. The mini-slump cone test showed that, with the help of superplasticizer and ultrasonic treatment, the flowability decreased continuously, as the NS content increased. The DIC experimental results showed that NS could effectively improve the mechanical properties of the cement paste and the ITZ. Specifically, at the content level of 1%, the elastic modulus of cement paste and ITZ was 20.95 GPa and 3.20 GPa, respectively. When compared to that without nanomaterials, the increased amplitude was 73.50% and 90.50%, respectively. However, with the further increase in NS content, the mechanical properties decreased, which was mainly caused by the agglomeration of nanomaterials. Additionally, the NS content did not exhibit a significant effect on the thickness of the ITZ, and its value was maintained at 76.91–91.38 μm. SEM confirmed that NS would enhance the microstructure of both cement paste and ITZ.

Understanding the enhancing mechanisms of graphene oxide (GO) on the pore structure characteristics in the interfacial transition zone (ITZ) plays a crucial role in cemented waste rock backfill (CWRB) nanoreinforcement. In the present work, an innovative method based on metal intrusion techniques, backscattered electron (BSE) images, and deep learning is proposed to analyze the micro/nanoscale characteristics of microstructures in the GO-enhanced ITZ. The results showed that the addition of GO reduced the interpore connectivity and the porosity at different pore throats by 53.5–53.8%. GO promotes hydration reaction in the ITZ region; reduces pore circularity, solidity, and aspect ratio; enhances the mechanical strength of CWRB; and reduces transport performance to form a dense microstructure in the ITZ. Deep learning-based analyses were then proposed to classify and recognize BSE image features, with a high average recognition accuracy of 95.8%. After that, the deep Taylor decomposition (DTD) algorithm successfully located the enhanced features of graphene oxide modification in the ITZ. The calculation and verification of the typical pore optimization area of the location show that the optimization efficiency reaches 9.6–9.8%. This study not only demonstrated the deepening of the enhancement effect of GO on the pore structure in cement composites and provided new insights for the structural modification application of GO but also revealed the application prospect of GO in the strengthening of CWRB composites and solid waste recycling.

This paper presents an evaluation of the bearing capacity of cross-bracing in steel transmission tower structures. Design guidelines (ASCE 10-15, BS EN 50341-1, GB 50017-2017, and DL/T 5486-2020) related to the buckling capacity of the cross-bracing are summarized and compared with the experimental results. The current design provisions obtained the bearing capacity from the equivalent slenderness ratio, and then the stability coefficient and buckling capacity were derived. The calculated bearing capacity based on the design code tends to be overly progressive for smaller slenderness ratios (particularly those below 100), except for EN 50341-1-2012. Conversely, for larger slenderness ratios, ASCE 10-15 and DL/T 5486-2020 Class A design codes lean towards being overly progressive, while GB 50017-2017 and EN 50341-1-2012 codes tend to be more conservative. The design standard appears to exhibit unsafe predictions for Class A and B connections with low slenderness ratios and Class C connections. It needs to be noted that the effects of torsional stiffness and joint connection type are not considered in the current design codes, which are proved to be nonnegligible by the test results. In this paper, the bearing capacity calculation formula is proposed by introducing a modified effective length coefficient (K), and both the torsional stiffness and joint connection type are taken into account. The modified bearing capacity is verified with the test results; the correlation coefficient is 0.997, and the coefficient of variation is 0.04. It can provide a reference for the engineering design of steel lattice transmission tower structures.