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Due to significant population concentration and capital influx in Guangdong-Hong Kong-Macao Greater Bay Area, the construction of cross-sea tunnels with significant consumption of various resources and materials, has been frequently witnessed. However, there is a lack of knowledge regarding how carbon emissions of cross-sea transportation infrastructure are generated across its life-cycle stages. This study proposes a life cycle assessment (LCA) approach for quantifying the carbon emissions and exploring the carbon reduction potentials with a case study of a world-renowned cross-sea tunnel project in Guangdong-Hong Kong-Macao Greater Bay Area. The results find that this project contributes approximately 849 kilotons CO2eq of carbon emissions with an emission intensity of 1.1 kilotons CO2eq per meter. The materialization stage is the largest contributor of carbon emissions (474.9 kilotons CO2eq), followed by service stage (248.3 kilotons CO2eq, accounting for 29.2 %). Some carbon emissions of raw materials can be offset by using recycled materials. The discarded concrete, block, stone, and sand, occupying over 90 % of the total recycled waste in weight could achieve a 93.5 % of carbon reduction potentially. It provides the opportunity to reveal the engineering details and carbon emission for a world-class super complex cross-sea transportation infrastructure. This study makes one of the first attempts to quantify life-cycle carbon emissions of cross-sea transportation infrastructure, which enriches foundational dataset for environmental impact assessment in this emerging field. The findings of this study can provide scientific references for formulating targeted low-carbon strategies for cross-sea transportation infrastructure across its different life-cycle stages.

Recycled aggregate concrete (RAC) has multiple interface transition zones (ITZs) due to its complex composition, providing convenient ion transfer channels. Therefore, it is significant to explore the changes of the internal pore structure in RAC under ion erosion conditions for quantifying and predicting ion transfer mechanisms. This paper innovatively utilizes the seepage effect for investigating the evolution of pore structures in RAC under sulfate attack. We conduct a systematic experimental study on the transport of sulfate ions in RAC with different fly ash (FA) substitution rates under dry-wet cycles. Combining backscattered electron imaging (BSE), permeation and fractal characteristics, this paper deeply explore the relationship between pore structure feature, sulfate percolation mechanism and the macroscopic properties of RAC incorporated with different amount of FA.

Magnesium phosphate cement (MPC) is a promising material known for its rapid hardening and high early-strength properties. However, its potential in engineering applications is hindered by its harden at an uncontrolled rate, considerable volumetric distortion and poor water resistance. To address the limitations, this study investigates the influence of sintered sludge ash (SSA) modification on the setting time, volume deformation, mechanical strength and water resistance of MPC composites. Experimental reveals that the setting time of MPC composites increase with higher SSA content, and the inclusion of SSA significantly mitigate volumetric deformation. Moreover, the mechanical strength exhibits improvement at all ages, and combine with water resistance analysis, 15% SSA content is the optimal level. Based on the XRD, TG, MIP and SEM, the enhanced properties of the MPC composites may be attributed to the reaction of SSA in the MPC system, leading to the resulting aluminum-containing gel phase acting as a binder along with guano to densify the microstructure.

Magnesium phosphate cement (MPC), as a new type of cementitious material, is difficult to be popularized in practical applications due to its short setting time, high cost, and poor water resistance. Dredged silt (DS) is a kind of hazardous waste, which may cause serious damage to the ecological environment if it is not disposed of properly. The treatment of DS and its reuse in building materials is an economical and environmentally friendly treatment method, which not only realizes the recycling of DS but also avoids secondary pollution. Using the treated DS as a mineral admixture for modified MPC not only recycles the DS but also improves the properties of MPC. In this paper, the effect of DS modification on the properties of MPC was investigated by setting time test, mechanical property test, water resistance test, and RCM test, and also compared with the modification effect of common mineral admixtures, such as fly ash (FA) and metakaolin (Mk), and finally analyzed by combining with SEM pictures. With the increase of the dosage of FA, Mk, and DS, the compressive strength of the modified MPC all showed the trend of increasing and then decreasing, and the optimal dosage was 5%, 10%, and 15%, respectively. At the optimum dosage, Mk and FA could improve the resistance of MPC to chloride erosion, but DS could not. The three kinds of admixtures could prolong the setting time of MPC, with DS having the best effect, followed by FA, and Mk having the smallest effect. All three admixtures could improve the water resistance of MPC, and the effect of improvement was Mk > DS > FA. The microstructure of the specimen was denser when the dosage of DS was low, and when the dosage was too much, the hydration reaction of MPC was affected, resulting in incomplete hydration and reduced hydration products. This research has significant guiding significance for the treatment of DS and the modification of MPC.

3D printing brings new opportunities for the development of civil engineering. Machine learning (ML) is also widely used in various fields of 3D printing. To describe the main research issues and potential future applications of ML for construction 3D printing, it is essential to comprehensively overview the current research topics. This paper aims to review, summarize, analyze, and introduce the research progress of ML applications in construction 3D printing, followed by a discussion of the current challenges and future research scope. Firstly, the classification and working principle of 3D printing and ML technology were introduced. Secondly, in the aspects of the design of construction materials, control of printing process, and quality inspection of construction components, the application status of ML in construction 3D printing was discussed. Based on this, in terms of interlayer bond performance enhancement, real-time status monitoring, and anisotropic behavior control, the future potential and challenges of ML in construction 3D printing were summarized, to provide a reference for promoting the realization of high-efficiency, intelligence, and sustainability in the field of civil engineering.

Abstract Carbonation induced corrosion is one of the major durability issues for reinforced concrete structures. To address this issue, it is essential to understand the underlying mechanism of carbonation by detecting the ingress of the CO2 and carbonation depth quantitatively. This paper demonstrates the potential of Raman spectroscopy, as a powerful technique, to implement quantification analysis of cement paste carbonation. In present work, the correlation between the content of the CO3 2− and the Raman peak intensity was initially established by using several standard specimens premixed with certain amount of CO3 2−. The established correlation was then used to investigate the carbonation of the cement paste in a CO2 diffusion scenario, and the results show a good agreement with that obtained by thermogravimetry measurements. Therefore, the feasibility of the Raman spectroscopy to quantify the carbonation degree of the cement paste can be demonstrated.

This paper proposes a novel output-only structural damage indicator by incorporating the pole-based optimal subpattern assignment distance with autoregressive models to localize and relatively assess the severity of damages for sheared structures. Autoregressive models can model dynamic systems well, while their model poles can represent the state of the dynamic systems. Structural damage generally causes changes in the dynamic characteristics (especially the natural frequency, mode shapes and damping ratio) of structures. Since the poles of the autoregressive models can solve the modal parameters of the structure, the poles have a close relationship with the modal parameters so that the changes in the poles of its autoregressive model reflect structural damages. Therefore, we can identify the damage by tracking the shifts in the dynamic system poles. The optimal subpattern assignment distance, which is the performance evaluator in multi-target tracking algorithms to measure the metric between true and estimated tracks, enables the construction of damage sensitive indicator from system poles using the Hungarian algorithm. The proposed approach has been validated with a five-story shear-building using numerical simulations and experimental verifications, which are subjected to excitations of white noise, El Centro earthquake and sinusoidal wave with frequencies sweeping, respectively; the results indicate that this approach can localize and quantify structural damages effectively in an output-only and data-driven way.

K-A-S-H (K2O-Al2O3-SiO2-H2O) gel is a key phase that forms in most alkali-activated binders (eco-friendly binders which utilize a substantial amount of industrial by-product). An in-depth understanding of the microstructure and performance of this nano-sized key phase facilitates better application to alkali-activated binders. However, such studies remain little and undetailed. Therefore, our research aims to provide insights into the microstructure of K-A-S-H particles synthesized with accurate stoichiometric control by the hydrothermal method through thermogravimetric analysis (TG), Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and BET surface area. The results show that for materials prepared at the curing temperature lower than 80 °C, the K-A-S-H products were completely amorphous. With increased curing temperature and time, the K-A-S-H products were transformed from the amorphous phase to the crystalline zeolite phase structure, with a reduction in the specific surface area. The TG results indicate that the crystalline phase contains more non-evaporated water or zeolite water for structural rearrangement. The degree of tetrahedral polymerization slightly decreased with an increase of the K2O/SiO2 ratio as the amount of non-bridged oxygen atoms increased, whereas it gradually increased with an increase of curing temperature and time, as suggested by the FTIR and NMR results. Various K2O/SiO2 ratios resulted in the formation of zeolite K-H and K-G zeolite, both of which exhibited highly polymerized three-dimensional network structures. However, there was no significant effect of the SiO2/Al2O3 ratio on the structure of K-A-S-H products. Overall, these results provide insight into understanding the chemical stability of K-A-S-H.