The preparation of ambient-cured fly ash-based geopolymer mortar (FAGM) with high strength by utilizing the high chemical reactivity of slag is key to realizing the sustainable and efficient application of solid waste resources. This paper investigates the influence of different type S95 slag contents (0%, 5%, 10%, 15%, 20%, 25%, and 30%) on the fluidity, setting time, and mechanical properties of FAGM at ambient temperature. The direct method is first adapted to monitor the influence of slag on geopolymerization. The results indicate that slag has a minimal effect on the fluidity of the mortar, while the setting time decreases and compressive strength increases with higher slag content. For FAGM with 30% slag content, the setting time is reduced from 3160 min to 140 min, with a decrease of 95.6%, and a 3-day and 28-day compressive strength increase from 1.5 MPa and 34.7 MPa to 33.5 MPa and 73.4 MPa, with enhancements of 2170.2% and 110.3%, respectively. Slag also exerts an internal curing effect, raising the internal curing temperature and accelerating the geopolymerization process of fly ash, thereby improving the compactness of FAGM and reducing its porosity. This approach successfully enables the production of high-strength, ambient-cured FAGM.

The seismic response of underground liquefied natural gas (LNG) storage tanks has been a significant focus in both academic and engineering circles. This study utilized Ansys (2021R1) to conduct seismic analyses of large-capacity LNG tanks, considering the fluid–structure–soil coupling interaction (FSSI), and it was solved using the Volume of Fluid model (VOF) and Finite Element Method (FEM). The mechanical properties of both the LNG tank structure and soil were simulated using solid elements, and seismic acceleration loads were applied. An analysis of liquefied natural gas was performed using fluid elements within FLUENT. Initially, a modal analysis of the tank was conducted, which revealed lower frequencies for a full-liquid tank (3.193 Hz) compared to an empty tank (3.714 Hz). Subsequently, the seismic responses of both the aboveground and underground LNG tank structures were separately simulated, comparing the acceleration, stress, and displacement of the tank wall structures. The findings indicate that the peak relative displacement of the aboveground empty tank wall is 122 mm, less than that of a full tank (136 mm), while the opposite holds true for underground tanks. The period and wave height of LNG liquid shaking in underground tanks are lower than those in aboveground tanks, which is more conducive to tank safety. The deformation and acceleration of underground tanks are lower than those of aboveground tanks, but the Mises stress is higher. The results indicate that underground LNG tank structures are safer under earthquake conditions.

In order to study the horizontal bearing characteristics of large-diameter rock-socketed rigid pile and flexible pile, two lateral loading tests in which the pile lengths are 5.2 m and 11.07 m were carried out. Unidirectional multi-cyclic loading was applied to the piles during the tests, with the maximum load reaching 3500 kN. The measured results are compared with the calculated results of Zhang’s method, m-method and the rigid pile method in the design codes. It is indicated that if the characteristic values of the horizontal bearing capacity of the large-diameter rock-socketed rigid pile and flexible pile are determined by the same horizontal displacement of the pile head, some risk will be brought to the design of the rigid pile. Compared with the rigid pile method, the m-method is more suitable for calculating the rotation angle of the pile head. In terms of the maximum bending moment of the large-diameter rock-socketed flexible pile under the critical load, the calculated result of Zhang’s method is less than the measured result, while the calculated result of the m-method is the largest. However, for the rigid pile, both Zhang’s method and m-method underestimate the maximum bending moment of the pile body. In summary, when a large-diameter rock-socketed pile is designed, reasonable calculation method and failure discrimination standard should be chosen according to the actual conditions.

Due to the extensive utilization of liquid nature gas (abbreviated as LNG) resources and a multitude of considerations, LNG storage tanks are gradually transitioning towards smaller footprints and heightened safety standards. Consequently, underground LNG storage tanks are being designed and constructed. However, underground LNG storage tanks release a considerable quantity of cold into the ground under both accidental and normal conditions. The influence of cold results in the ground freezing, which further compromises the safety of the structure. Existing research has neglected to consider the effects of this. This oversight could potentially lead to serious safety accidents. In this work, a complete set of experiments using a novel LNG underground storage tank fluid-solid-thermal coupled cryogenic leakage scale model were conducted for the first time to simulate the effect of the tank on the soil temperature field, stress field, and displacement field and to analyze the development of the three fields and the results of the effect. This research helps the related personnel to better design, construct, and evaluate the LNG underground storage tanks to avoid the catastrophic engineering risks associated with cryogenic leakage and helps to improve the design process of LNG underground storage tanks.

The thermal insulation integrity of liquefied natural gas storage tanks is essential for their life-cycle safety. However, perlite settlement (insulation material) can result in thermal leaks and lead to engineering risks. The direct measurement of perlite settlement is difficult due to the enclosed structure of these tanks. To address this challenge, this study presents a data-driven approach based on machine learning and real-time monitoring data. This study proposes a multi-fidelity machine learning framework to enhance generalizability and leverage multi-fidelity data effectively. Low-fidelity data are readily available but contain systematic errors, while high-fidelity data are accurate but limited in accessibility. By combining both types of data, this framework enhances the generalisability and prediction accuracy of trained models. The results of the data experiments demonstrate that the multi-fidelity framework outperforms models trained solely on low- or high-fidelity data, achieving a coefficient of determination of 0.980 and a root mean square error of 0.078 m. Three machine learning algorithms—Multilayer Perceptron, Random Forest, and Extreme Gradient Boosting—were evaluated to determine the optimal implementation. This approach provides a reliable method for the real-time monitoring of thermal insulation integrity in liquefied natural gas storage tanks, contributing to improved industrial safety and operational efficiency.

In this work, field-scale experiments were carried out on two energy piles to investigate the mechanical behavior of the piles when subjected to thermomechanical loads under a liquefied natural gas tank. The results showed that the super-long and large-diameter energy pile exhibited a better heat transfer performance. After pile heating or cooling, the temperature in the mid-depth of the pile increased or decreased rapidly, and at the two ends, the temperature varied relatively slowly. Regarding the observed axial strain, energy pile 1 exhibited predominately compressive deformation during the coupled heating–loading process, while a certain tensile deformation was found near the pile toe of energy pile 2 during the coupled cooling–loading process. Moreover, for both energy piles, positive shaft resistances appeared predominately under both the pure mechanical and coupled thermomechanical conditions, and occasional and local occurrences of negative resistances could be related to the ground conditions on site. The settlement and bearing capacity values of the two energy piles were not significantly affected by the coupled thermomechanical loads, and thus, the serviceability of the gas tank would not diminish.