The application of green NH₃-fuel on board has been widely regarded as a feasible way to realize the green and low-carbon transformation of the global shipping industry. However, the N₂O emission problem of marine NH₃-fuel engines has become one of the key technical bottlenecks hindering the development of ammonia-powered ships. To solve this problem, a series of TiO₂-supported transition metal oxide catalysts were prepared by impregnation method. The effect of transition metal element types on the N₂O removal performance of the catalysts was investigated, and the N₂O removal performance of Cu_x/TiO₂ catalysts was optimized. The results show that compared with Fe₅/TiO₂, Mn₅/TiO₂, Co₅/TiO₂ and Ni₅/TiO₂ catalysts, Cu₅/TiO₂ catalyst shows excellent catalytic activity, the N₂O conversion efficiency can reach 100% at 350 ℃. In addition, Cu₅/TiO₂ catalyst also has good water resistance. The experimental results show that 5% is the best Cu loading amount. X-ray diffraction, N₂ adsorption-desorption, H₂ temperature programmed reduction, O₂ temperature programmed desorption, and in-situ diffuse reflectance infrared Fourier transform spectroscopy were used to characterize the physicochemical properties and surface reaction intermediates of Cu₅/TiO₂ catalyst, and the relevant catalytic reaction mechanisms were discussed in depth from multiple perspectives. The characterization results show that compared with other Cu_x/TiO₂ catalysts, Cu₅/TiO₂ catalyst has higher dispersion of active species, specific surface area, oxygen vacancy content and stronger redox performance, which is conducive to its better catalytic activity. The main active species on the surface of Cu₅/TiO₂ catalyst are Cu²⁺ and Cu⁺ species, and the adsorption and deionization of N₂O is a key step in the catalytic reaction.

An adaptive predefined-time prescribed performance backstepping fault-tolerant control strategy is presented based on radial basis function (RBF) neural networks, event-trigger mechanism and hysteresis quantizer for the attitude control problem of quadrotor unmanned aerial vehicle (UAV) with actuator faults. Firstly, the dynamic model of the quadrotor UAV system was constructed, and the attitude model was reconstructed by incorporating the actuator fault model. Secondly, by designing a class of time-varying functions, the error variables required for backstepping control were transformed. Thirdly, the nonlinear function approximation capability of RBF neural networks was utilized to estimate derivatives of virtual control laws and the actuator fault with unknown parameters. Finally, to reduce the update frequency of the actuator, a combination of event-trigger mechanism and hysteresis quantizer was used to design the control input. Stability of the closed-loop system was demonstrated through Lyapunov stability theory. The effectiveness of the proposed algorithm was verified through MATLAB. It is concluded that the designed event-triggered quantized controllers have a lower update frequency compared to controllers designed using only event-triggered techniques.

During tunnel construction, the deformation of surrounding rock and the mechanical response of the supporting structures are significantly influenced by the lateral pressure coefficient λ. Accurate determination of the on-site lateral pressure coefficient is essential for guiding tunnel design and construction. Firstly, the impact of the lateral pressure coefficient on settlement displacement of the tunnel vault and horizontal displacement of the side walls was analyzed theoretically. Secondly, the ratio between horizontal displacement of the side walls and settlement displacement of the vault was monitored, and a numerical simulation was employed to establish a mathematical relationship between the horizontal-vertical displacement coefficient K and the lateral pressure coefficient λ, enabling the inversion of the lateral pressure coefficient. Finally, the inverted lateral pressure coefficient was applied to optimize tunnel cross-section design. The results indicate that, under the same geological conditions, an approximately linear relationship exists between K and λ. Regardless of changes in tunnel depth or surrounding rock conditions, a proportional relationship between horizontal and settlement displacements is maintained, which can be used to invert the lateral pressure coefficient at the tunnel site. By adjusting the tunnel axis ratio m to gradually approach λ^-1, deformation is effectively controlled and the proportion of lining damage is reduced.

Machine learning technology is a hot research topic at present. It is widely used in various prediction, recognition and classification tasks with its strong learning ability and high versatility. The application of machine learning in computational structural mechanics was discussed, with emphasis on its role in material property prediction, structural damage analysis, improvement of traditional methods, constitutive equation establishment and differential equation solving. Through literature review, the advantages of machine learning algorithms such as neural networks, support vector machines and random forests in improving computational efficiency and design process optimization were summarized. It is pointed out that the combination of machine learning and classical computing methods provides a new way to solve engineering problems. Future research will focus on algorithm optimization, model improvement and interdisciplinary technology integration.

“Large-difference annulus” is a common characteristic encountered in complex wellbore structures with “varying diameters” during (ultra-)deep well drilling. This characteristic leads to slow drilling fluid velocity in the upper large-diameter annulus, posing challenges for cuttings removal, while the higher velocity in the lower small-diameter annulus results in significant circulating pressure loss. To address these issues, a novel flow diverter tool was designed to carry cuttings in the upper section and the loss of circulating pressure in the lower section. However, the lack of a specific wellbore flow model tailored for this tool in current research has hindered its design and optimization. Based on the fundamental principles of fluid flow and hear transfer, a valid mathematical model was proposed to be compatible with the flow diverter tool. Then, via a case study on Well ZS102, the tool was proved to be effective and perform well in practice. The results show that with the installation of the flow diverter tool, the bottomhole pressure is lowered from 85.08 MPa to 80.30 MPa, the standpipe pressure is significantly reduced from 20.97 MPa to 7.22 MPa, and the annulus pressure loss is decreased from 7.16 MPa to 2.40 MPa. The research presents a novel approach for optimizing cuttings removal parameters and preventing leaks in complex wellbore structures during deep and ultra-deep well drilling operations, contributing significantly to the advancement of related drilling technologies.

Aiming at the problems of nonlinearity, large delay, uncertain model parameters and weak anti-interference ability in the temperature control system of variable air volume air conditioning supply air, a closed-loop control system of supply air temperature based on active disturbance rejection control (ADRC) was designed. In order to overcome the difficulty in parameter adjustment of active disturbance rejection controller, an improved grey wolf optimization (IGWO) algorithm was proposed to optimize controller parameters. By introducing chaotic mapping, nonlinear convergence factors, dynamic weights and dimensional learning strategies into grey wolf optimization (GWO), the population diversity was increased and the balance between search and exploitation was taken into account. The advantages and feasibility of the proposed algorithm were verified by MATLAB simulation. The experiment further proves that compared with the traditional proportional integral derivative (PID) controller and the traditional gray wolf algorithm, the IGWO algorithm can shorten the supply air temperature overshoot by 45.3% and 8.9%. The adjustment time is reduced by 34.8% and 11.2%, the steady-state error is smaller, and the system is more energy efficient.

On December 18, 2023, a M_S6.2 earthquake occurred in Jishishan County, Gansu Province, marking the largest earthquake recorded in the area since seismic observations began. To investigate the practical application of interferometry synthetic aperture radar(InSAR) technology in monitoring surface deformation in Jishishan County and its surrounding areas before and after the earthquake, 13 C-band Sentinel-1A SAR images covering the earthquake event and study area were utilized. D-InSAR and SBAS-InSAR techniques were employed to process the data, obtaining surface deformation information along the radar line of sight before and after the earthquake, and a comparative analysis of the deformation rates before and after the event was conducted. The results show that the monitoring results of the two techniques show a bulge phenomenon centered in Liugou Township (the epicenter), which gradually expands outward in an elliptical shape, and then evolves into irregular subsidence. The maximum line-in-line shape variables before and after the earthquake are 41 mm and 16 mm, respectively. The overall deformation of the whole region after the earthquake is relatively stable, which is consistent with the relevant data. The D-InSAR and SBAS-InSAR technologies can be used to monitor the long-term surface deformation process and abnormal conditions before and after earthquakes, and provide effective support for quickly obtaining the distribution range of coseismic geological disasters and guiding post-earthquake emergency rescue and post-disaster recovery and reconstruction.

The construction of the pile-beam-arch-method(PBA method) exhibits a cluster-tunnel effect, which readily induces surface subsidence. To achieve safe construction and minimize surface settlement, the MatDEM discrete element software was employed to simulate the construction process of the PBA method. The potential deformation mechanism and metastable microstructure of soil were considered in the training of formation micromechanics parameters, and the variation rule of surrounding rock pressure under multi-guide tunnel construction was summarized. The research findings indicate that when adopting a construction sequence of “top-to-bottom and sides-to-center,” surface settlement is relatively small. When using the “center-to-sides” approach, the initially excavated central pilot tunnel leads to the formation of slip planes at 1.5 times the tunnel width. Conversely, with the “sides-to-center” method, the initially excavated side tunnels provide vertical support to the inner soil, reducing the surface settlement caused by the subsequent excavation of the central tunnel. During the construction of the upper pilot tunnels, the surrounding rock pressure at the vault and arch waist exhibits an increasing trend. The construction of the lower pilot tunnels results in stress concentration at the vault and inner arch waist of the upper tunnels. Approximately 72.65% of surface settlement occurs during the construction of the lower pilot tunnels, and the adoption of staggered construction can significantly mitigate soil disturbance.

Recently, the vessel-shaped aquacultural farm has received much attention from the academia and industry because of its importance in promotion and sustainability of marine fishery. Polluted surroundings unsuitable for fish growth are always introduced by traditional multiple point mooring system. Therefore, single point mooring system is more suitable for the aquacultural farm. In recent years, mooring scheme optimization and performance assessment was frequently investigated in most existing literature, while studies on design of the single point mooring system are rare. Based on the requirement of reducing hull reconstruction, an external turret single point mooring system was proposed, which is composed of the turret device, the mooring anchor, the truss structure and the bearings. And their working principle were also clearly illustrated. Then, three dimensional potential theory was applied to obtain the hydrodynamic coefficients of the ship by use of the software AQWA. Finally, in order to verify the positioning ability of the mooring system under both operational and survival conditions, the direction of wind, wave and current was combined according to the rules, and time-domain coupling analysis of the farm-mooring system was carried out. From the numerical results, it can be seen that yaw, relatively large sway and roll motions will be induced due to different direction of the wind, current and wave. The mooring line tension is adequate and safe under all conditions, indicating that this proposed single point mooring system exhibits good positioning performance.

Long-term stockpiling of coal fly ash releases a large amount of toxic and hazardous substances, posing a threat to the soil and water environment. In order to have a comprehensive understanding of the research progress in this field, a bibliometric method was conducted to systematically and deeply visualize and analyze the relevant literature in CNKI and Web of Science databases from the period of database construction to 2023. The results show that the annual total number of publications in this field is generally on the rise. Among them, Chinese scientists have conducted a substantial amount of research in this field, accounting for the highest publication volume, which makes up 18.87% of the total, providing important scientific foundation for subsequent studies. The betweenness centrality of publications from the United States (0.51) is significantly higher than that of other countries, and its research results have greater international influence. The research hotspots focus on contaminants like heavy metals in coal fly ash, investigating their leaching and release patterns under various conditions, and revealing the environmental impacts of contaminants migration from coal fly ash landfills. Based on high-frequency keyword analysis, the composition of contaminants in coal fly ash and the types of contaminants potentially released into the water environment were examined. A systematic review and analysis of contaminants release mechanisms, release regularity, key influencing factors, and the migration regularity of mechanisms in environmental media were conducted. Future research should further focus on the release of heavy metals such as Pb, Cr, and Hg, trace elements like As, Se, and Mo, and specific mechanisms such as F^-, Cl^-, and $\mathrm{SO^{2-}_{4}}$, $\mathrm{PO^{3-}_{4}}$ during the coal fly ash stockpiling. Studies should explore the release characteristics of these mechanisms under complex environmental conditions, investigate whether synergistic or inhibitory mechanisms exist between various factors, and establish quantitative relationships between mechanisms indicators in the solid phase of coal fly ash and their release into water environment. This will provide a theoretical basis for scientifically evaluating the environmental impacts of coal fly ash and effectively preventing potential threats to water environment.