This study presents a numerical simulation of large-scale shaking table tests on a superstructure supported by a pile group installed in an inclined liquefiable site, focusing on nonlinear interactions between piles and the soil. A three-dimensional finite element model of a soil-pile-superstructure system is developed using OpenSeesMP. The temporal and spatial evolution of the radial soil pressure around the pile is evaluated in both liquefied and nonliquefied sites. Results show that the soil pressure around the pile is significantly influenced by site inclination and soil lateral spreading. In liquefied sites, the soil pressure in the extruded zone of the upstream pile is significantly higher than that in the diffused zone. However, higher pressure occurs in the diffused zone for nonliquefied sites. Correspondingly, the liquefaction state significantly influences the force characteristics of the pile group system. Additionally, the group effect is more pronounced in liquefied sites. The results also indicate that the soil pressure distribution around the piles is closely related to the relative pile-soil displacement and reveals different on-pile force mechanisms under varying site conditions. These findings offer valuable insights into the seismic design of pile foundations in inclined liquefied sites.

Implementing the conventional total focus method (TFM) for visualizing internal damage in reinforced concrete (RC) is beset with computational challenges and a high dependence on physical principles. To overcome these challenges, an efficient total focus imaging method based on deep learning is proposed. This method deals with array ultrasonic time-domain signals from cracked RC beams. A deep neural network (DNN) employing a feature extraction + multilevel feature fusion + matrix construction architecture was developed; this architecture enabled the DNN to learn the underlying physical principles of the TFM. The architecture effectively transformed ultrasonic time-domain signals into a B-scan matrix. Training, validation, and testing data were collected by measuring eight RC beams with preset artificial cracks using a low-frequency shear wave array ultrasonic system. The results demonstrated that the reconstructed B-scan matrices had a peak signal-to-noise ratio of 26.94 dB and a structural similarity index of 0.978. Furthermore, the proposed method required 42% fewer floating-point operations compared with physics-based calculations, achieving total focus imaging with lower computational cost. The study facilitates the advancement of ultrasonic total focus imaging of RC structures from physics-based methods to data-driven methods without requiring prior physical knowledge, thereby providing robust support for further nondestructive evaluation and quantitative analysis.

To address the challenges of supply-demand imbalance in rail transit and the complex passenger flow interactions among multiple hub stations under high-passenger-volume scenarios, this study proposes an optimized rail transit scheduling method based on a flexible train formation strategy (FTFS). By constructing interaction parameters that characterize the coupling effects of high passenger flow across multiple hubs, a multiobjective optimization model is developed to minimize passenger waiting time at hub stations and operational costs. An improved nondominated sorting genetic algorithm incorporating chaotic mapping and adaptive evolutionary parameters is designed for efficient solution optimization. This method overcomes the limitations of fixed train formations by supporting diversified modular unit detachment and reconnection, enabling dynamic capacity adjustment and efficient rolling stock circulation. A case study on Nanjing Metro Line 1 demonstrates that the FTFS reduces the average waiting time at hub stations by 47.2%, alleviates train congestion by approximately 18.6%, and reduces the operational costs under low-demand scenarios by 44.8%. Pareto frontier analysis further reveals the trade-off mechanism between transport capacity elasticity and operational costs. These findings validate the effectiveness of the flexible train formation model in mitigating platform congestion and enhancing passenger flow evacuation efficiency at transport hubs, providing multiobjective decision-making support for managing extreme passenger flow during holidays and peak events.

This paper proposes a data- and model-driven collaborative resource scheduling method to maximize the spectral efficiency (SE) of cell-free (CF) downlink multiuser multiple-input multiple-output (MIMO) systems, subject to delay violation probability and power constraints. The method integrates the weighted minimum mean square error (WMMSE) algorithm within the safety reinforcement learning (Safety-RL) framework. The original optimization problem is decomposed into two coupled subproblems. The Safety-RL algorithm leverages state features to determine user priority weights and allocate bandwidths, while the WMMSE algorithm calculates the precoding matrix and further schedules resources based on user priority weights to obtain the reward and costs of Safety-RL. Considering dynamic user access in CF systems, a distributed algorithm with user scalability is also proposed. Simulation results demonstrate that the proposed approach improves the SE while meeting the different delay violation probability constraints of users. Furthermore, the distributed algorithm offers comparable performance to the fully centralized method while considerably reducing model training overhead, particularly as users dynamically access the system.

To enhance the prediction accuracy of unsteady wakes behind wind turbines, a novel reduced-order model is proposed by integrating a multifunctional recurrent fuzzy neural network (MFRFNN) and proper orthogonal decomposition (POD). First, POD is employed to reduce the dimensionality of the wind field data, extracting spatiotemporally correlated modal coefficients and modes. These reduced-order variables can effectively capture the essential features of unsteady wake behaviors. Next, MFRFNN is utilized to predict the time series of modal coefficients. Finally, by combining the predicted modal coefficients with their corresponding modes, a flow field is reconstructed, allowing accurate prediction of unsteady wake dynamics. The predicted wake data exhibit high consistency with large eddy simulation results in both the near- and far-wake regions and outperform existing data-driven methods. This approach offers significant potential for optimizing wind farm design and provides a new solution for the precise prediction of wind turbine wake behavior.

To improve the safety of construction workers and help workers remotely control humanoid robots in construction, this study designs and implements a computer vision-based virtual construction simulation system. For this purpose, human skeleton motion data are collected using a Kinect depth camera, and the obtained data are optimized via abnormal data elimination, smoothing, and normalization. MediaPipe extracts three-dimensional hand motion coordinates for accurate human posture tracking. Blender is used to build a virtual worker and site model, and the virtual worker motion is controlled based on the quaternion inverse kinematics algorithm while limiting the joint angle to enhance the authenticity of motion simulation. Experimental results show that the system frame rate is stable at 60 frame/s, end-to-end delay is less than 20 ms, and virtual task completion time is close to the real scene, verifying its engineering applicability. The proposed system can drive virtual workers to perform tasks and provide technical support for construction safety training.

Ensuring independent mobility for older adults has become a public health and social concern in China owing to its rapidly aging population. To explore independent mobility trends among older adults and the impact of sociodemographic characteristics in recent years, this study used data from the Chinese Longitudinal Healthy Longevity Survey from 2012 to 2018, combined with binomial logit regression and CatBoost-Shapley additive explanation (SHAP) method to analyze the relationship between independent mobility and sociodemographic characteristics under bus- and walking-oriented environments. Study findings indicated that age and gender significantly affected the independent mobility of older adults. Policymaking should prioritize the needs of older adults, focusing on age and gender differences. Additionally, living expense adequacy significantly influenced independent mobility. Policies should substantially support economically disadvantaged older adults, ensuring their basic needs are met through subsidies and other measures. Moreover, the study found a notable impact of widowhood on independent mobility, suggesting enhanced social care and mental health support for widowed older adults, especially those who are long-lived. The outcomes of this study provided evidence for policymakers, which are beneficial for developing elderly-friendly travel policies to ensure and enhance the quality of life and independent mobility of older adults.

In recent years, offshore wind turbines have rapidly developed, and many pile foundations installed earlier are now approaching decommissioning. Thus, the efficient removal of pile foundations has become a critical issue for the sustainable development of offshore wind energy. To address this issue, this paper systematically investigates three methods for the recovery of pile foundations using physical model experiments: water injection + lifting, air injection + lifting, and air retention + water injection. The experimental results show that the water injection + lifting method exhibits remarkable advantages in recovering large-diameter and inclined pile foundations; however, realigning inclined piles during recovery remains challenging, and a risk of pile overturning exists. The air injection + lifting method proves effective for realigning inclined piles but presents a risk of air expulsion failure, which may affect the continuity and stability of the recovery process. By contrast, the air retention + water injection method combines the characteristics of water injection and air injection techniques, effectively avoiding air expulsion failure and exhibiting pronounced displacement jumps during pile uplift. These findings provide a valuable reference for future decommissioning practices of offshore wind pile foundations, offer important engineering application value, and contribute positively to the sustainable development of the offshore wind industry.

A numerical simulation approach was adopted to investigate the uplift bearing characteristics of helical anchors in Nantong silty sand and to predict their uplift bearing capacity. Finite element model validation was performed, and the uplift bearing mechanism of helical anchors was analyzed. The current code’s uplift bearing capacity calculation formula was optimized, and the accuracy and reliability of the modified formula were evaluated. The results indicate that the critical embedment depth ratio of the anchor plate in Nantong silty sand is 5, and the critical spacing ratio ranges from 3 to 4. The current code’s formula underestimates the uplift bearing capacity of helical anchors under these conditions. To improve the prediction accuracy, the optimization coefficients M and L, which account for the embedment depth ratio of the anchor plate, are introduced, and fitting formulas for these coefficients are provided to improve the prediction of uplift bearing capacity in Nantong silty sand and to serve as a reference for similar engineering applications.

The widespread presence of organophosphate flame retardants (OPFRs) in aquatic environments has raised significant concerns regarding environmental and human health risks. In this study, the adsorption behavior of two representative aromatic OPFRs, triphenylphosphine oxide (TPPO) and triphenyl phosphate (TPhP), was systematically investigated using organically modified montmorillonite (MMT). The effects of various environmental and operational parameters, including cationic surfactant dosage, temperature, pH, ionic strength, and humic acid (HA) concentration, on OPFR adsorption were thoroughly examined. Results revealed that modification with hexadecyltrimethylammonium bromide enhanced the TPPO and TPhP adsorption capacities of MMT. The adsorption process was largely independent of pH and HA concentration, and the presence of inorganic cations significantly improved the adsorption efficiency. Adsorption equilibrium was achieved within 30 min, with kinetics best described by a pseudo-second-order model. The adsorption isotherms exhibited a linear relationship, and the distribution coefficients for TPPO and TPhP were 0.16 and 0.51 L/g, respectively. Thermodynamic analysis indicated that the considered adsorption was more favorable at lower temperatures. The primary adsorption mechanism was attributed to the partitioning behavior facilitated by the organophilic nature of the modified MMT. Moreover, the adsorbent demonstrated excellent regeneration performance, with its adsorption capacity remaining stable over five consecutive cycles. Overall, these findings show that cationic surfactant-modified MMT has a promising potential for application in wastewater treatment to effectively remove OPFRs from aqueous systems.

To investigate the influence of the shear lag effect on the bending shear stress of single-box multicell box girders (MCBG), the shear lag warping additional deflection is selected as the generalized displacement. The governing differential equations and boundary conditions for the shear lag of the MCBG are derived using the energy variational method. Based on the shear lag warping deformation state of the MCBG and by employing the microelement equilibrium differential equation and the coordination conditions for shear lag warping deformation, the calculation method for the bending-warping shear stress of the MCBG is derived, and the influence of the width-to-span and height-to-span ratios on bending-warping shear stress is analyzed. Example analysis shows that the bending-warping shear stress of the MCBG calculated by the proposed calculation method coincides with the finite element solution, and the warping shear stress satisfies the self-balancing condition of shear warping, thus verifying the accuracy of the proposed method. The warping shear stress exhibits an antisymmetric distribution about the vertical axis of symmetry and has a weakening effect on the shear stress of the elementary beam (EB). The larger the width-to-span ratio is, the larger the proportion of the warping shear stress of the EB. The larger the height-to-span ratio is, the smaller the proportion of the warping shear stress and the more significant the influence of the width-to-span ratio. The more the number of cells is, the smaller the influence of the warping shear stress on the total bending shear stress. The influence of the shear lag effect can be ignored in the calculation of the bending shear stress of three or more cells in the MCBG.

To integrate insulation and load-bearing functions in prefabricated composite wall structures, a novel design based on fiber-reinforced expanded polystyrene (EPS) concrete is proposed. The research focuses on three key aspects: material properties, seismic performance, and thermal performance. Firstly, the compressive strength and thermal conductivity of fiber-reinforced EPS concrete were analyzed at different sand ratios, leading to the development of an optimal mix design and a damage constitutive model. Secondly, a combination of experimental and numerical analysis methods was used to investigate the seismic performance of prefabricated composite walls with different infill materials, including autoclaved aerated fly ash and fiber-reinforced EPS concrete. Finally, thermal performance studies were conducted on prefabricated composite wall panels with different infill materials. The results indicate that the specimens underwent elastic, elastoplastic, and failure stages during loading. While specimens using EPS concrete exhibited a slightly lower overall bearing capacity, they demonstrated superior ductility, energy dissipation capacity, and enhanced insulation and thermal stability.

To reduce the risk of traffic accidents significantly caused by the speeding behavior of electric bicycles, this study focuses on the Beijing Yizhuang Economic and Technological Development Zone. This work relies on high-precision shared electric bicycle Global Positioning System trajectory data, integrating a spatiotemporal analysis model and geographic information system (GIS) technology to explore the spatial and temporal variability law and formation mechanism of speeding behavior. Through data preprocessing, speeding events are identified, and weekday features are extracted. Four periods are identified: morning peak, midday minipeak, evening peak, and nighttime flat peak. Using the GIS platform, global spatial autocorrelation and local clustering analysis are conducted to identify the spatial clustering characteristics of speeding behaviors and hotspot areas. The coldspot and hotspot patterns of speeding events and the dynamic trajectories of their evolution are analyzed using spatiotemporal cube technology. The results show that speeding behaviors are strongly correlated with the commuting peak in time and spatially concentrated in the intersections of urban main roads, the periphery of commercial complexes, and industrial parks, with a diffusion tendency. The results of this study provide novel insights into the research and analysis of the spatial and temporal characteristics of speeding risk behaviors of electric bicycles and effective technical support for nonmotorized traffic safety management.

Connected and autonomous vehicle formation (CAVF) technology is considerably important for improving transportation efficiency, optimizing traffic flow, and reducing energy consumption. Despite the extensive research conducted on trajectory tracking control and other aspects of CAVF, the quality of the extant literature varies considerably, and research content remains scattered. To better promote the sustainable and healthy development of the CAVF field, this paper employs the mapping knowledge domain (MKD) methodology to comprehensively review and visualize the current research status in this domain. Based on this review, research themes, hotspots, research challenges, and future development directions are proposed. The findings suggest that the research on CAVF can be categorized into three primary developmental stages. China and the United States are the primary countries conducting CAVF research. There is a positive correlation between economic development and the generation of scientific research outcomes. Research institutions are predominantly concentrated in universities. The field exhibits significant interdisciplinary and integration characteristics, forming key research personnel and teams. It is expected that future research will concentrate on topics such as deep learning, trajectory optimization, energy management strategy, mixed vehicle platoon, and other related subjects. Research on cognition-driven intelligent formation decision-making mechanisms, resilience-oriented formation safety assurance systems, multiobjective collaborative formation optimization strategies, and digital twin-driven formation system validation platforms represents key future development directions.

Structural mapping is an important method for studying algebraic structures. Hom-algebra and monoidal Hom-group are new structures produced by algebra and group structural mappings, respectively. These structures are important algebra and group generalizations and are closely related to them. Let (A,β) be a Hom-algebra and (G,α) a monoidal Hom-group. A structure of (A,β) graded by (G,α) is introduced; this structure is called Hom-group graded algebra. This study presents the definition of Hom-group graded algebra, provides some examples, and discusses its basic properties. Furthermore, a sufficient and necessary condition that makes (A,β) a strongly (G,α)-graded algebra is explored using a structure map β and unit 1_A. Finally, by using different maps, two sufficient and necessary conditions for a Hom-algebra to be a (G,α)-graded algebra are expressed in different ways.