最新刊期
卷 57 ， 期 4 ， 2025
- 摘要：In recent years, the material point method (MPM) has become an important large-deformation numerical simulation method in geotechnical engineering and is widely utilized to study issues such as landslides, foundations, dam failures, and water-soil gushing in shield tunnels. As the scale and complexity of application scenarios increase, the accuracy requirements and efficiency needs for numerical methods also rise, resulting in higher computational costs that restrict the further application of MPM in large-scale geotechnical engineering problems. The simulation efficiency of MPM improves significantly by introducing parallel acceleration technology; however, specific issues, such as program architecture and extensibility, still limit their development in engineering applications. This study proposes an improved GPU acceleration strategy for MPM by incorporating modular programming concepts, efficient data structures, and data competition handling methods to establish a high-performance and easily extendable program architecture. The software's performance is evaluated by simulating aluminum rod collapse experiments and the slope failure process. The results indicated that the software achieves effective parallelization and demonstrates approximately a 10% improvement over the existing Taichi-GPU MPM. Finally, the proposed MPM method is applied to simulate the Xinmo landslide, and the computational efficiency improves by approximately 20 times when the number of material points increases by about 2.5 times.关键词：GPU-accelerated;material point method;landslide;large deformation numerical simulation1201|1071|0更新时间：2026-05-23
- 摘要：ObjectiveLandslides represent a severe and frequent natural hazard, posing significant threats to human life and property. Current models for predicting landslide susceptibility exhibit two primary limitations: the inability to fully capture the spatial heterogeneity of environmental factors such as terrain, soil, and vegetation, and the failure to accurately distinguish between landslides induced by extreme and non-extreme rainfall events. These shortcomings hinder accurate forecasting and reduce the models' adaptability to diverse environmental conditions and rapidly changing climatic patterns. Therefore, this study introduces an innovative approach that combines Deep Embedded Clustering (DEC) with a Dynamic Rainfall Threshold (DRT) model based on a mixed distribution. In addition, a Multi-Task Learning Adaptive Neural Tree (MLANT) model has been developed to enhance model flexibility and prediction accuracy, particularly in varying environmental conditions and during extreme weather events.MethodsThis research applied three key methodologies to address the limitations of existing landslide susceptibility models. Deep Embedded Clustering (DEC): DEC was utilized to resolve spatial heterogeneity issues. Using deep learning techniques, environmental variables such as terrain, soil, and vegetation were embedded into a low-dimensional space to capture their complex, nonlinear relationships. The model clustered these representations to identify sub-regions with similar geological and environmental features. This clustering-based zoning enhanced the model's capability to analyze landslide susceptibility by managing spatial heterogeneity more effectively than traditional methods. Dynamic Rainfall Threshold (DRT) model: The DRT model was introduced to improve forecasting accuracy by distinguishing between the effects of extreme and non-extreme rainfall on landslide initiation. It integrated Gamma and Generalized Pareto Distributions (GPD) to represent rainfall events of varying intensities. Bayesian methods were employed to dynamically update model parameters, enabling real-time adaptation to changing rainfall conditions. This allowed for greater prediction precision and timeliness under both extreme and non-extreme rainfall events. Multi-Task Learning Adaptive Neural Tree (MLANT): The MLANT model was developed to address the inflexibility and limited adaptability of traditional prediction models. Unlike conventional models, which struggled to adjust to diverse prediction tasks and shifting environmental conditions, MLANT dynamically modifies its processing strategies to match specific tasks and environmental variations. This multi-task learning approach enhances the model's accuracy and flexibility in predicting landslides, particularly in nonlinear environments with complex terrain and rapidly changing weather conditions. The models were validated using real-world data from Tongjiang County, a region prone to landslides. Inputs such as terrain features, soil characteristics, vegetation indices, and rainfall patterns were utilized to train and evaluate the models. The DEC, DRT, and MLANT models were compared to traditional susceptibility models to assess improvements in prediction accuracy and adaptability.Results and DiscussionsThe results demonstrated significant improvements in prediction accuracy when using the proposed models. DEC-Based Clustering: The DEC model predicted higher landslide densities in high- and very-high-susceptibility zones by capturing spatial heterogeneity. Specifically, it predicted landslide densities of 0.036 92 and 0.046 92 events per square kilometer in high and very high-risk zones, respectively, identifying a total of 59 landslide events. This marked an improvement over traditional models that did not consider spatial heterogeneity, such as the overall effective rainfall coefficient model, which predicted fewer events and lower densities. These findings highlighted the importance of integrating spatial heterogeneity in susceptibility modeling. Dynamic Rainfall Threshold Model (DRT): The DRT model further enhanced accuracy by effectively distinguishing the effects of different rainfall intensities. Its mixed-distribution approach, incorporating both Gamma and GPD distributions, improved the accuracy of landslide predictions under dynamic climatic conditions. In the practical application to Tongjiang County, the DRT model also predicted 59 landslide events in high and very high susceptibility zones, with densities of 0.036 92 and 0.046 92 events per square kilometer, respectively. This outperformed the DEC-based effective rainfall coefficient model, which exhibited lower accuracy and fewer correctly identified events. MLANT Performance: The MLANT model significantly improved flexibility and prediction performance across varied tasks. MLANT efficiently addressed various environmental conditions by dynamically adjusting its internal strategies, particularly in response to landslides triggered by extreme rainfall. Evaluation metrics, such as precision, F1 score, and ROC-AUC, demonstrated that MLANT outperformed traditional models that rely on static thresholds. In Tongjiang County, MLANT increased predicted landslide density from 0.038 events/km² and 44 events (using traditional methods) to 0.044 events/km² and 59 events, demonstrating superior performance in both frequent and rare landslide scenarios.ConclusionsThe models developed in this research effectively overcome the limitations of traditional landslide susceptibility prediction approaches by integrating Deep Embedded Clustering (DEC), a Dynamic Rainfall Threshold (DRT) model based on mixed distributions, and a Multi-Task Learning Adaptive Neural Tree (MLANT). Spatial heterogeneity is addressed through DEC clustering, which dynamically partitions regions based on environmental characteristics, improving prediction accuracy. Rainfall differentiation is achieved through the DRT model, which significantly improves the model's capability to predict landslides triggered by both extreme and non-extreme rainfall events by adapting to varying climatic conditions. The MLANT model provides flexibility and adaptability, delivering improved accuracy across multiple prediction tasks and in rapidly changing environmental conditions, outperforming traditional single-task models. These findings demonstrate the critical importance and effectiveness of integrating DEC, DRT, and MLANT models in enhancing landslide susceptibility prediction, particularly in areas characterized by complex environmental conditions and frequent extreme weather events. This research contributes both theoretical and practical advancements, providing valuable tools for enhancing landslide risk management and mitigation strategies.关键词：landslide susceptibility;Deep Embedded Clustering (DEC);Spatial heterogeneity;Mixed distribution rainfall threshold;Multi-task learning adaptive neural tree model900|979|0更新时间：2026-05-23
- 摘要：ObjectiveThis study clearly determines the physical characteristic factors that govern the displacement and burial of buildings by debris flow, and clarifies the impact patterns of these physical characteristic factors on the deposition positions of buildings in debris flow. Provides specific guidance for post-disaster emergency rescue positioning of trapped individuals in debris flow depositions.MethodsFirstly, the force analysis of buildings buried by debris flow was simplified by assuming 1) they are situated in a channel with a uniform slope, 2) they are regular-shaped building blocks, and 3) they are displaced by a certain distance and halted in the debris-flow deposition under the steady motion of a uniform and stable debris flow. Based on these assumptions, the key physical characteristic factors influencing the forces acting on the building blocks were extracted: Froude number, degree of liquefaction, density ratio between the block and the debris flow, height ratio between the block and the debris flow, and the aspect ratio of the block itself. Secondly, small-scale flume experiments were conducted with high precision and distributed measurement capabilities. The experimental sensors included ultrasonic sensors, three-axis force sensors, and pore water pressure sensors, along with high-speed cameras for observing the displacement process. These experiments enabled the measurement of normal stress, shear stress, pore water pressure, debris flow depth, and velocity. Finally, the impact patterns of factors characterizing the physical characteristics of debris flow-building interactions on the relative deposition positions of building blocks in the debris flow accumulation area were studied based on experimental measurement results.Results and Discussions1) Changes in the solid concentration of debris flow affected its flow regime; higher solid concentration weakened the flow mobility of the debris flow. The reduction in flow mobility led to building blocks being positioned closer to the deposition front in the debris-flow deposition. The influence of the flow regime on relative position primarily manifested in experiments involving high-density blocks, while its effect was less pronounced in experiments involving low-density blocks. Based on the theoretical force analysis of building blocks, high-density blocks exhibited greater self-weight and basal friction, making them more difficult to be displaced Thus, their deposition positions were significantly influenced by the flow mobility of the debris flow. In contrast, low-density blocks exhibited lower self-weight and basal friction, making them more easily displaced by the debris flow. In addition, their density was similar to that of the solid-phase particles in the debris flow, causing these building blocks to become part of the solid phase of the debris flow. Therefore, the influence of the flow regime on the relative position of low-density blocks was less significant. 2) Block density and size were the primary factors affecting relative position. For blocks with the same density, those with larger sizes in the flow direction and flatter shapes were more difficult to be displaced. In debris flows with 45% and 50% solid concentration, high-density blocks were more difficult to displace compared to low-density blocks, resulting in relatively smaller relative positions. However, in debris flow displacement experiments with 53% solid-phase concentration, high-density blocks were displaced farther, positioning relatively closer to the front in the deposition. This behavior was related to the dominant forces, physical mechanisms, and specific motion modes of building blocks displaced by debris flows with different solid concentration and required further investigation. 3) The relationship between the relative position of building blocks in the debris flow deposition and both the flow regime of the debris flow and the physical characteristics of the building blocks was elucidated. The experimental results demonstrated a qualitative comparison of the influence of various physical parameters on relative position. Further research was required to quantitatively analyze the impact of each physical parameter on relative position, enabling theoretical prediction of the positions of building blocks in debris flow debris-flow deposition. This study focused on the movement distance and deposition extent of destroyed building blocks under the action of debris flow displacement without considering the process of building destruction. Therefore, the experimental setup considered only the geometric shapes and densities of the building models, neglecting the structural foundations of buildings, which can differ from real conditions. The experimental results of this study can provide a reference for the movement distance and deposition extent of destroyed buildings in debris flows. However, in practical applications, factors such as the structural foundations of buildings must be comprehensively considered.ConclusionWith the increase in solid concentration of debris flow volume, the reduction in flow mobility results in building blocks being deposited nearer to the deposition front. Under identical inflow conditions, flatter block shapes exhibit greater resistance to displacement, resulting in shorter movement distances after displacement and relative positions farther from the deposition front. In experiments with 45% and 50% volume solid concentration, blocks with lower density are displaced farther and positioned relatively closer to the deposition front. In contrast, for debris flows with 53% solid concentration, blocks with higher density tend to position relatively closer to the deposition front. This study, based on flume experiments, identifies the factors influencing the displacement process and examines the impact patterns of debris flow on building displacement. It provides valuable guidance for post-disaster emergency rescue operations, particularly in locating and rescuing trapped individuals.关键词：debris flow;displacement;building;theoretical analysis;flume experiments843|893|0更新时间：2026-05-23
- 摘要：ObjectiveLandslide dams are natural blockages formed by the rapid accumulation of slope failure materials, typically resulting from mass movements such as rockslides or debris avalanches. Due to gravitational sorting during downslope transport and complex topographic constraints in narrow valleys, these dams generally exhibit inherently three-dimensional (3D), spatially heterogeneous internal structures. However, most existing breach simulation models assume material homogeneity for computational convenience, neglecting the influence of real-world structural non-uniformity. This simplification results in significant deviations in breach morphology and peak discharge predictions, ultimately impairing the reliability of hazard assessments and early warning systems for downstream communities. This study clarifies the fundamental influence of 3D material heterogeneity on the breach process of landslide dams, enhancing the predictive capabilities of numerical models in geohazard risk ma-nagement.MethodsA novel 3D landslide dam breach model was developed by coupling Large Eddy Simulation (LES) with sediment mass conservation equations that incorporated phase transitions between solid and suspended states, accurately capturing the erosion dynamics in heterogeneous dams. The model considered the non-directional transport and deposition behavior of sediment under complex flow conditions. A Volume-of-Fluid (VOF) method was employed to simulate the evolution of the free surface and interface, enabling the precise tracking of water-sediment interactions. The model was validated through physical model experiments simulating three structural types: homogeneous, vertically heterogeneous, and laterally heterogeneous dams. Key breach parameters, including incision rate, breach geometry, and outflow hydrographs, were compared to experimental data to verify the model's reliability and accuracy.ResultsFor homogeneous dams, breach behavior varied significantly with the material grain size. Fine-grained dams exhibited rapid, layered erosion, forming triangular longitudinal profiles, with breach durations under 60 seconds and peak discharges reaching 3.32 L/s. In contrast, coarse-grained dams underwent multistage headcut erosion, requiring higher flow shear stress for sediment entrainment. This delayed breach development resulted in longer times to peak (up to 120 s) and reduced peak discharge (2.1 L/s). Reverse vortices formed at the headcut bases enhanced local scouring but exerted limited influence on overall erosion rates. Medium-grained dams exhibited intermediate characteristics, characterized by single-stage headcuts and corresponding breach metrics that fell between those of fine- and coarse-grained dams. As the median grain size increased, breach morphology transitioned from uniform scouring to progressively complex headcut erosion patterns, with delayed peak times and reduced peak flows. For vertically heterogeneous dams, the breach process was susceptible to the configuration of layered materials. The upper layer (V1) influenced breach initiation: in tests where it consisted of fine particles, breach formation was accelerated; in contrast, coarse-grained V1 layers delayed erosion onset and increased upstream impoundment volumes by up to 40%. The middle layer (V2) governed vertical incision rates: fine-grained layers accelerated downward erosion, whereas coarse layers formed headcuts that restricted further deepening. The lower layer (V3) controlled basal stability: coarse-grained foundations enhanced dam resistance to scouring, while fine-grained ones raised undercutting and subsequent collapse of the overlying mass. In addition, an interactive effect was observed between the various layer combinations. For example, "inverse grading" structures (coarse-over-fine) tended to form armor layers on the surface, delaying breach initiation and leading to sudden failure modes with elevated peak discharges. In contrast, "normal grading" (fine-over-coarse) favored headcut erosion. These structural patterns critically influenced both the erosion mechanisms and the hydraulic response. In laterally heterogeneous dams, spatial variability in material properties across dam zones significantly altered breach morphology and flow dynamics. The breach core zone (C1) determined incision and discharge characteristics, while adjacent zones (C2 and D1) influenced breach asymmetry and propagation direction. The D1 zone played a major role in controlling breach widening, whereas D2 exhibited minimal influence. Comparative simulations (Tests 7~9) revealed differences: Test 7 yielded a wide breach, Test 8 produced a narrow and deep breach, and Test 9 exhibited slow incision but extensive lateral expansion. In addition, the deposition of coarse particles within the breach resulted in a reduction of the slope angle and flow velocity, which suppressed the initiation of further coarse particle entrainment and impeded upstream headward erosion. These feedback mechanisms resulted in a lower peak discharge and a more gradual evolution of the breach.ConclusionThis study demonstrates that the spatial heterogeneity of dam materials is a primary factor governing the evolution of breaches in landslide dams. Vertically inverse grading structures (coarse-over-fine) contribute to delayed breach initiation and energy storage, often resulting in abrupt failure events with peak discharges exceeding those of homogeneous dams by more than 30%. In laterally heterogeneous dams, the sorting of materials on the overtopping side directly influences the breach depth-to-width ratio (ranging from 0.8 to 2.5), controlling the discharge capacity. A positive feedback mechanism associated with coarse sediment deposition is identified: the accumulation of sediment reduces the breach slope, which in turn decreases flow velocity and further enhances deposition, transforming the breach mode from rapid incision to a slow-release erosion regime. The developed 3D VOF-LES-based hydro-sediment coupled model overcomes the limitations of the traditional homogeneous assumption and, for the first time, enables high-resolution simulation of breach morphology evolution under realistic heterogeneous conditions. With prediction errors maintained within 10% under complex experimental conditions, this model provides a robust tool for enhancing risk assessments and emergency planning in regions prone to landslide dam breaches.关键词：landslide dam;heterogeneous structure;three‒dimensional numerical simulation;breaching erosion;outflow discharge762|1075|0更新时间：2026-05-23
- 摘要：ObjectiveThe 5·12 Wenchuan earthquake triggered extensive secondary geological disasters and cascading effects. Wenchuan County, which was severely impacted by the earthquake, exhibits widespread unstable slopes and areas prone to landslides and collapses. In mountainous regions, the occurrence of extreme rainfall events precipitates extensive landslides and collapses. The copious loose material produced constitutes a substantial sediment source, exacerbating the magnitude of flash flood disasters under the coupling effect of water and sediment movement, and particularly heightening the risk of debris flows and debris floods. Given these circumstances, it is imperative to develop assessment models for landslide and collapse susceptibility to facilitate early prevention of compound flash flood disasters in Wenchuan County. Conventional susceptibility assessment approaches often rely on expert experience and subjective judgment; alternatively, they encounter difficulties in adequately fitting high-dimensional complex data. As a result, the precise delineation of the actual spatial distribution of areas susceptible to landslides and collapses remains a formidable challenge. Recent advancements in data science and machine learning provide promising solutions. Two state-of-the-art ensemble learning algorithms, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM), are introduced to formulate dependable models for appraising susceptibility to landslides and collapses within the confines of Wenchuan County.MethodsA comprehensive evaluation of factors related to topography, geology, meteorology, and hydrology was conducted to select ten evaluative factors: Elevation, slope, aspect, terrain relief, distance to rivers, distance to faults, normalized difference vegetation index (NDVI), land cover type, average annual precipitation, and lithology. Data preprocessing procedures were implemented to ensure the effectiveness and stability of model training. The data were standardized to mitigate the impact of differing scales among the dependent factors on the model. Factors displaying significant multicollinearity were identified and excluded using the Variance Inflation Factor (VIF), ensuring the independence of each feature in the analysis. In addition, the Information Gain Ratio (InGR) was utilized as a metric to evaluate the importance of each factor, facilitating the preliminary selection of explanatory variables. Then, two advanced ensemble learning algorithms (XGBoost and LightGBM) were applied alongside two traditional algorithms (logistic regression and random forest) to construct landslide and collapse susceptibility assessment models for Wenchuan County. Quantitative metrics, including accuracy, precision, recall, F1 score, and receiver operating characteristic (ROC) curves, were employed to enable a comparative and evaluative analysis of the performance of each model. These models were then utilized to predict the probabilities of landslide and collapse occurrences across the designated study area. The natural breakpoint method was employed to demarcate susceptibility zones, resulting in the development of a map delineating areas vulnerable to landslides and collapses. Additional qualitative and quantitative analyses were performed on the resulting susceptibility maps, with particular attention given to the correspondence between predicted results and actual landslide and collapse events, evaluating the predictive reliability of the proposed models.Results and DiscussionsThe results indicated that both ensemble learning models demonstrated superior classification prediction capabilities when compared to traditional models. XGBoost and LightGBM achieved accuracies of 0.903, surpassing random forest (0.900) and logistic regression (0.864). In terms of precision, LightGBM (0.887) slightly outperformed XGBoost (0.882), while both outperformed random forest (0.872) and logistic regression (0.802). The F1 score metric placed XGBoost at the forefront with 0.899, closely followed by LightGBM (0.898) and random forest (0.897), while logistic regression yielded the lowest F1 score (0.866). Evaluation of the area under the ROC curve (AUC) indicated that XGBoost and LightGBM achieved nearly identical high classification performance (0.904), outperforming random forest (0.902), with logistic regression trailing at the lowest AUC (0.869). The examination of the constructed susceptibility zoning maps, coupled with quantitative analysis of the area proportions attributed to each zone, disclosed disparities in the partitioning outcomes from the XGBoost and LightGBM models in comparison to those produced by logistic regression and random forest models. These disparities were primarily attributed to the divergent data processing strategies inherent to each algorithm. In an effort to substantiate the reliability of the models’ predictions, the density of landslide and collapse points within each susceptibility zone was quantitatively scrutinized. XGBoost, LightGBM, and random forest models consistently reflected the general trend of increasing landslide and collapse point density with higher susceptibility levels, aligning with the typical pattern of disaster susceptibility. LightGBM performed best in identifying high and extremely high susceptibility areas, with landslide and collapse point density ratios of 1.844 and 3.079, respectively, the highest among all models evaluated. In contrast, logistic regression did not adhere to this increasing trend, presenting an anomalous ratio of 0.588 in zones of very low susceptibility, a figure surpassing that within zones of high susceptibility (0.528). This anomaly indicated the presence of prediction bias in the logistic regression model, potentially ascribable to the limitations of the logistic regression algorithm and the lack of representative data.ConclusionsThe predictive capabilities of the advanced ensemble learning models in assessing landslide and collapse susceptibility in Wenchuan County surpassed those of the two traditional models. These models outperformed the traditional approaches in terms of accuracy, precision, F1 score, and area under the Receiver Operating Characteristic. LightGBM demonstrated higher precision, while XGBoost yielded superior results in the F1 score. In terms of reliability, both ensemble learning models, particularly LightGBM, exhibited advantages in identifying high and very high susceptibility areas, reinforcing their superiority in landslide and collapse susceptibility assessment. The research findings provide a more accurate tool for evaluating landslide and collapse susceptibility in Wenchuan County and similar areas affected by earthquakes, supporting the development of disaster prevention and mitigation measures. Future research can involve more comprehensive data collection methods and investigate broader applications of ensemble learning models, improving the reliability and practical implementation of predictions in disaster management.关键词：Wenchuan earthquake-damaged area;landslide;Collapse;flash flood disaster;machine learning902|920|0更新时间：2026-05-23
MECHANISM OF LANDSLIDE\-DAMMED LAKE AND ITS CONTROL
- 摘要：ObjectiveTraditional energy dissipation technologies provide an effective solution to mitigate the seismic responses of buildings. There are two types of energy dissipation devices based on their operational characteristics: velocity-dependent dampers and displacement-dependent dampers. Friction dampers (FDs), as a category of displacement-dependent energy dissipation devices, exhibit several common advantages, such as good energy dissipation capacity, satisfactory mechanical performance, and ease of fabrication and installation. Therefore, they have received extensive attention from researchers in recent years. Buildings can require large damping forces under extremely rare or near-fault earthquake events, which necessitate that existing FDs apply a high preload to deliver sufficient reaction forces. However, introducing an excessive preload force can be impractical and uneconomical for current FDs. For example, the damping force of existing FDs can need to reach 1 000 kN for buildings subjected to a severe or near-fault earthquake event, resulting in a required preload force of 10 000 kN when the friction coefficient is assumed to be 0.1. In addition, FDs with a specified preload force still face durability issues such as cold bonding, cold solidification, and preload relaxation. Therefore, this study aims to develop a non-preload variable friction inerter (NVFI), which provides satisfactory damping force and significant energy dissipation without relying on preload force.MethodsThe proposed NVFI mainly consisted of a ball screw, rotational plate, friction plate, spring, and two thrust bearings. One terminal of the ball screw was fixed to the structure using an ear plate. The ball screw of the NVFI generated axial motion when the structure reciprocally shook under seismic earthquakes, and the springs were driven to reciprocal motion, resulting in a variable positive pressure of the friction plate. Therefore, the butterfly-shaped hysteretic behavior of the proposed NVFI was found based on the friction mechanism mentioned above. Then, the restoring force formula of the proposed NVFI was further established. Then, seismic performance mitigation of a single-degree-of-freedom (SDOF) system under different hazard levels was conducted to evaluate the effectiveness and advantages of the proposed NVFI quantitatively. A 5% damping SDOF system with a mass of 50 660 kg and elastic stiffness of 2 000 kN/m was adopted as the analytical model. A Bouc‒Wen elastoplastic model was employed in the SDOF system with a yield strength of 24 kN and post-elastic stiffness of 200 kN/m. The SDOF system with and without the proposed NVFI was considered and denoted as SDOF‒NVFI and SDOF, respectively. Three groups of different ground motion records, including far-field, near-fault pulse, and near-fault non-pulse ground motion records, were selected to perform the nonlinear dynamic analysis, and the peak ground acceleration (PGA) scaled to multiple intensity levels was 0.2g, 0.4g, and 0.6g for design level earthquake (DLE), maximum considered earthquake (MCE), and extremely rare earthquake (ERE), respectively.Results and DiscussionsThe results illustrated that NVFI significantly reduced the displacement, velocity, and acceleration responses of the SDOF systems subjected to different earthquake records at different hazard levels. The average displacement reduction ratios were 46%, 56%, and 34% for the SDOF‒NVFI subjected to far-field, near-fault pulse, and near-fault non-pulse ground motions at the DLE hazard level, respectively. Similar reductions were also observed in the velocity and acceleration results. Compared to the results of the far-field and near-fault non-pulse ground motions, the displacement and velocity responses of the SDOF systems subjected to near-fault pulse ground motions were more effectively decreased using the proposed NVFI while maintaining a basically approximate acceleration mitigation effect. This is attributed to the fact that the proposed NVFI exhibits good energy dissipation capacity, which was induced by its unique friction mechanism. The satisfactory and variable friction force made the NVFI more suitable for buildings under seismic earthquakes with strong uncertainty, especially for near-fault pulse-such as earthquake events. On the other hand, the seismic input energy of the SDOF system was also decreased through the proposed NVFI. The seismic input energy of the SDOF‒NVFI system was less than 15 kJ at the MCE hazard level, while the seismic input energy of the SDOF system was greater than 24 kJ. This indicated that the fundamental frequency of the SDOF system can be effectively shifted from the dominant frequency of external disturbance by introducing the proposed NVFI, thus improving the overall performance of the structure. Finally, the parameter analysis of the SDOF‒NVFI systems considering different inertance-to-mass ratios was further performed to reveal the influence of the inerter mechanism from the proposed NVFI. The results illustrated that increasing the inertance-to-mass ratio of the proposed NVFI has a significant influence on the velocity and acceleration responses of the SDOF systems at the DLE hazard level while showing a slight but visible influence on the displacement response. Specifically, more than a 10% increase in the velocity and acceleration responses of the SDOF systems subjected to far-field ground motions at the DLE hazard level was observed, with the inertance-to-mass ratio increasing from 0.1 to 0.5.ConclusionsThe results indicated that the energy dissipation of the SDOF system primarily depends on the superior energy dissipation capacity of the NVFI due to the effectiveness of its variable friction mechanism, whereas the inerter serves only to transform the seismic input energy.关键词：non-preload;variable friction;inerter;extremely rare earthquake;seismic performance560|592|0更新时间：2026-05-23
- 摘要：ObjectiveThis study addresses the issue of immature vertical and three-dimensional seismic isolation technologies both domestically and internationally. A composite seismic isolation device that integrates linear guides and constant-force springs is designed and developed. This device, intended for the seismic isolation of artifacts in museum display cases, aims to mitigate potential earthquake-induced damage to artifacts.MethodsFirstly, two models of museum display cabinets and cultural relics, both at the same scale, were created based on those of a specific museum. One of the cultural relic models within the display cabinet was outfitted with a composite seismic isolation device incorporating linear guides and constant-force springs. The linear guide rail seismic isolation device was positioned at the bottom of the display cabinet, while the vertical constant-force spring seismic isolation device was placed at the base of the cultural relics. In contrast, the other system lacks a seismic isolation device. Secondly, two sets of cultural relic display cabinet systems were tested on a shaking table. The dynamic characteristics of both the seismic isolation-equipped display cabinets and the non-seismic isolation display cabinets were examined using white noise with an amplitude of 0.1g. Then, seismic waves of varying intensities and from different locations were applied. The acceleration response of the shaking table, the surface of the seismic isolation device, the top surface of the display cabinet, and the displacement response of the linear guide's horizontal seismic isolation device were measured. Finally, the acceleration at the top of the isolated display cabinet was compared to that of the non-isolated display cabinet. The horizontal and vertical isolation rates were calculated, and the displacement response of the vibration isolator was analyzed.Results and DiscussionsThe effectiveness of the isolation device in reducing seismic acceleration was clearly observed by comparing the top acceleration of isolated display cabinets with non-isolated ones. When comparing typical acceleration responses, under the EI‒Centro wave (0.4g) effect, the peak acceleration response in the X direction at the top of the non-isolated display cabinet was 1.68g, and in the Y direction was 1.89g. In contrast, on the isolated device platform, the peak acceleration response in the X direction was only 0.35g, and in the Y direction was only 0.36g. These results indicated that the isolation device effectively mitigated seismic acceleration. Through calculations, it was evident that the isolation efficiency of the linear guide's horizontal isolation device increased with the magnitude of seismic activity, ranging from 65% to 90%. This demonstrated the device's capability to effectively isolate vibrations in all horizontal directions. The isolation efficiency of the constant-force spring vertical isolation device ranged from 30% to 40%. The lower isolation efficiency in the vertical direction compared to the horizontal direction can have been attributed to different reference accelerations: Vertical isolation efficiency employed the Z-axis acceleration of the platform as a reference, while horizontal isolation efficiency used the acceleration of the non-isolated display cabinet as a reference. In terms of absolute acceleration values, the acceleration of the vertical isolation device was similar to that of the non-isolated horizontal display cabinet, indicating that this vertical isolation device effectively isolated vibrations in the vertical direction. The relative displacement of the horizontal isolation device on the linear guide increased with the intensity of the earthquake. At a seismic intensity of 0.1g, the relative displacement ranged from 5.9 to 24.9 mm in the X direction and from 5.4 to 21.1 mm in the Y direction. For a seismic intensity of 0.1g, the relative displacement was minimal for the Wenchuan wave in both the X and Y directions and maximal for the artificial wave in both the X and Y directions. Under a seismic intensity of 0.2g, the relative displacement ranged from 12.4 to 66.4 mm in the X direction and from 12.3 to 62.9 mm in the Y direction. For a seismic intensity of 0.2g, the relative displacement was minimal for the Wenchuan wave in both the X and Y directions, maximal for the artificial wave in the X direction, and maximal for the EI‒Centro wave in the Y direction. Under a seismic intensity of 0.3g, the relative displacement in the X direction ranged from 20.6 to 108.0 mm, and in the Y direction from 18.9 to 118.0 mm. The relative displacement was minimal for the Wenchuan wave in both the X and Y directions, maximal for the artificial wave in the X direction, and maximal for the EI‒Centro wave in the Y direction. Under a seismic intensity of 0.4g, the range of relative displacements in the X direction was between 31.4 and 140.0 mm, while in the Y direction, it spanned from 33.8 to 146.0 mm. For a seismic intensity of 0.4g, the relative displacement was minimal for the Wenchuan wave in both the X and Y directions, maximal for the artificial wave in the X direction, and maximal for the EI‒Centro wave in the Y direction. In all scenarios, the displacement of the isolation device did not exceed the designed effective stroke of 200 mm, indicating the reasonableness of the effective stroke design for the isolation device.ConclusionsThe conclusion indicates that the three-dimensional composite isolation system, which comprises a linear guide and a constant force spring, demonstrates a favorable isolation effect. This system has the potential to enhance the seismic safety of cultural relics during earthquake events. It exhibits strong innovation and practical applicability, fulfilling the three-dimensional isolation requirements of cultural relic display systems.关键词：collection of cultural relics;three-dimensional seismic isolation;linear guide rail;constant force spring;vibration table test388|525|0更新时间：2026-05-23
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Control Performance and Preliminary Application Investigation of Novel Rotational Impact Dampers AI导读
摘要：ObjectiveA new type of control device, the Rotational Impact Damper (RID), is proposed. This device is developed based on two types of mass dampers and consists of multiple rotating bodies that rotate about a fixed axis within the same plane. Adjacent rotating bodies rotate and collide when excited, dissipating energy without inducing excessive acceleration in the structure.MethodsFirstly, the working principle of RID was introduced. The working principle of RID was divided into two aspects, namely, non-collision and collision states. For the non-collision state, the equations of motion (EOMs), including the EOM for the main structure and the EOMs for each rotating body in RID, were established. For the collision state, a collision model was established. In particular, when adjacent rotating bodies collided in RID, their motion followed the law of conservation of momentum and accounted for the coefficient of restitution. Secondly, dynamic tests were conducted to compare the experimental and numerical responses of three rotating bodies. As the collision of RID under dynamic loading was random, the numerical responses were not the same as the experimental responses. However, remarkable similarities were observed in their response tendencies and statistics. Therefore, it was considered that the numerical results accurately reflected the physical reality, predicting the rotation angle and rotational angular velocity with relatively good consistency. Following the verification of the effectiveness of the numerical model and the correctness of the theoretical model, the numerical model of the RID was used for subsequent numerical simulation research. Thirdly, for main structures with similar dynamic properties in the two horizontal directions, a simplification was conducted to model the structure as a unidirectional structure. Numerical optimization was conducted to determine the control parameters of the RID under simple excitation. The numerical optimization method was divided into six steps. Step 1: RID mass, rotational collision angle, and recovery coefficient were set. Step 2: All possible initial angles for each rotating body were determined based on the collision angle. Step 3: The inspection range for the radius and damping coefficient of the rotating body was set. Step 4: A pair of rotating body radius and damping coefficients were selected for the numerical simulation, and the structural response under all possible initial angle conditions was obtained. Step 5: The root mean square of the structural response under various initial angle conditions was calculated, and the average value was taken as the vibration reduction index. Step 6: all radii and damping coefficients of the rotating body were traversed, repeating the fourth and fifth steps, with the optimization goal of achieving the minimum vibration reduction index. The radius and damping coefficient of the rotating body corresponding to this minimum value were the optimal control parameters for this RID. Finally, to explore the potential application scenarios of RID, two main structures were selected and analyzed through numerical simulation. The first structure was a flexible structure with a period greater than 1 second, such as a wind turbine structure. The finite element model of the wind turbine structure was established in SAP2000 finite element software, and the finite element model was simplified as a lumped-mass model with 10 degrees of freedom for MATLAB numerical simulation. Three representative earthquake records were selected to analyze the control performance of RID under seismic excitations, and the peak ground accelerations were scaled to match the structural response under the load used in the optimization, corresponding to strong seismic excitations. In addition, the wind turbine structure maintained strong vibration even after the earthquake, so an additional 60 seconds were added to the original earthquake records. The other study investigated the RID vibration reduction performance when applied to a rigid structure (such as mechanical equipment) with a period of less than 1 second under harmonic resonance excitation. Considering the changes in the structural dynamic characteristics of mechanical equipment due to differences in load, clamping tightness, and output, this study also examined three additional structures with natural vibration periods reduced to 67%, 50%, and 40% of the original structure period, in addition to the original structure. A tuned mass damper (TMD) with a mass ratio of 5% was also considered in the resonance response analysis to study the control effect of RID on resonance response under harmonic base displacement excitation and to explain the characteristics of RID vibration reduction control. TMD was numerically optimized using the same primary structure, installation position, load, and response indicators as RID.Results and DiscussionsThe analysis results indicate that in the seismic control of flexible structures, when the seismic response closely aligns with the optimized response amplitude, the seismic reduction effect of the RID is substantial. However, as a passive control device, the RID requires a specific response time, and its seismic performance is influenced by the time-domain characteristics of earthquakes. Furthermore, a considerable reduction in seismic effects leads to decreased rotational motion and fewer collisions of the RID, which results in a significant degradation in control effectiveness and highlights the RID’s strong dependence on energy input. Given the stochastic nature of seismic excitations, the seismic control performance of the RID still presents opportunities for improvement. In the context of resonance response control for rigid structures, when the structural dynamic characteristics remain unchanged, the vibration reduction performance of the RID is not as strong as that of the TMD. However, as the structural dynamic characteristics vary, the effectiveness of the TMD gradually diminishes, whereas the vibration reduction capability of the RID remains largely unaffected by such changes, demonstrating a more stable vibration reduction performance. Additionally, the spatial requirements of the RID do not increase with growing loads, unlike those of the TMD, for which the stroke increases proportionally with the load increment. Under significant excitation, the primary structure controlled by the RID exhibits strongly modulated responses that facilitate targeted energy transfer under impulsive loads, emphasizing the necessity for further investigation in future RID research efforts.ConclusionsIn summary, the RID shows significant seismic reduction effects when seismic responses approximate optimized amplitudes, especially in flexible structures. The RID’s performance is influenced by earthquake time-domain characteristics and depends heavily on energy input due to reduced rotational motion and collisions under diminished seismic effects. While it is less effective than TMDs under unchanged structural dynamics in rigid structures, the RID maintains stable vibration reduction as structural characteristics vary and does not require increased spatial capacity with load increments. The strongly modulated responses under high excitations enhance targeted energy transfer, illustrating the RID’s potential and the need for continued research. These findings underline the RID’s theoretical and practical value in seismic control applications.关键词：vibration control;rotating mass damper;impact mass damper;parameter optimization560|780|0更新时间：2026-05-23
SEISMIC ISOLATION AND ENERGY DISSIPATION FOR ENGINEERING STRUCTURES
- 摘要：ObjectiveThe technology of underground coal mine reservoirs has become an effective method for protecting and utilizing mine water resources. Among these, the stability of the coal pillar is critical to the safe operation of underground coal mine reservoirs. The coal pillar is subjected to the long-term and repeated action of various mining stresses. The water-bearing state of the coal pillar varies significantly at different periods of water storage in coal mine underground reservoirs, and the influence of the long-term and repeated mining stresses also differs accordingly. Therefore, studying the deformation and mechanical characteristics of coal samples under different water content conditions and subjected to cyclic loading and unloading contributes to a better understanding of the coal pillar failure mechanism.MethodsCylindrical standard specimens in three water-containing states, dry, natural, and saturated, were fabricated, respectively. First, the appropriate cyclic load was selected for the cyclic loading and unloading test through a preloading test. Then, the uniaxial graded cyclic loading and unloading test was conducted, and the number of cycles at each load level was increased to analyze the complete process of fatigue damage in coal and rock under multiple cyclic loads. The damage characteristics of coal samples were monitored using acoustic emission (AE) equipment, and the pore development of the coal samples was detected using nuclear magnetic resonance (NMR) equipmentResults and DiscussionsThe average maximum loads of the dried, natural, and saturated coal samples, measured through the preloading experiment, were 32.77, 27.69, and 22.45 kN, respectively. Compared to the dried coal samples, the average maximum load of the saturated coal samples decreased by 31.49%, indicating that water deteriorated the strength parameters of the coal samples. The acoustic emission signals of coal samples with varying water content states increased gradually with the number of circulation stages, and the degree of fracture development also increased accordingly. Under the action of cyclic stress, the damage and failure of coal mainly occur when the peak load of each level is reached for the first time. The water-rock interaction exhibited a weakening effect on acoustic emission. Under cyclic stress, water-containing coal samples were prone to stress-induced mutations, resulting in instantaneous damage and destruction to the coal body. In addition, with the increase of water content, the number of stress mutations also increased. Under the same load, the damage degree of saturated coal samples was higher, resulting in the further development of internal microfissures and the generation of more acoustic emission signals, which partially counteracted the weakening effect of water on the acoustic emission signals. Both natural and saturated coal samples experienced further damage and destruction during the loading and unloading of the third-level cycle, with the saturated coal samples exhibiting a higher degree of damage. After cyclic loading and unloading, the pore number of the dried coal samples increased with the number of cycle stages. After the first two stages of cyclic loading and unloading, the natural and saturated coal samples developed pores with varying diameters, and the number of internal pores increased. However, after the third stage of cyclic loading and unloading, the number of medium and micropores significantly decreased. The number of large pores has increased slightly, resulting in an overall decrease in the number of internal pores. During the first-stage cyclic loading period, dried coal samples primarily showed growth in macropores, while natural and saturated coal samples primarily exhibited growth in micropores, though the growth was not substantial. After the loading and unloading of the second-level cycle, the bimodal growth area of the dried coal samples was slightly larger than that observed in the first-level cycle. The number of small and medium pores in the natural and saturated coal samples increased significantly, with the growth in medium pores being slightly higher than that of micropores. The number of micropores in the dried coal samples increased significantly, while the growth in medium pores remained relatively low. After the third-level cycle, the number of micropores and medium-large pores in natural coal samples decreased. In saturated coal samples, the total number of internal pores decreased, whereas the number of medium and large pores increased slightly. In dried coal samples, the number of pores with different diameters continued to increase. Pore changes in water-bearing coal bodies exhibited a low-range trend of "increase—decrease—increase" with increasing cyclic stress. After the loading and unloading of stage Ⅰ and stage Ⅱ cycles, the porosity of each coal sample increased. After stage Ⅲ cycles, the porosity of the dried coal sample continued to increase, while that of the natural and saturated coal samples decreased. In addition, the reduction in porosity of the coal sample in its natural water-containing state was greater, by 0.45%. The decrease in the porosity of the saturated coal sample was smaller than that of the natural coal sample. Combined with the T2 spectrum, The number increase of macropores in saturated coal samples isgreater, which reduces the porosity decrease. The compressive strength of the dried coal sample after grade Ⅲ cyclic loading and unloading was 14.27 MPa, which was 9.85% lower than the average value before cyclic loading and unloading. The compressive strength of the saturated coal sample was 8.49 MPa, which was 24.87% lower than the average value under initial conditions without cyclic loading and unloading. The strength of the coal samples decreased with the increase in water content and the number of cycles.ConclusionsThis study reveals the damage and failure mechanisms of coal subjected to hierarchical cyclic loading conditions by analyzing the acoustic emission characteristics and pore evolution patterns of coal samples with different water contents under cyclic loading关键词：coal pillar;water immersed coal body;cyclic loading and unloading;pore change;damage evolution574|1223|0更新时间：2026-05-23
- 摘要：ObjectiveShale gas fracturing constitutes the cornerstone of contemporary energy extraction, with horizontal well-staged multi-cluster fracturing technology emerging as a pivotal technique for achieving efficient shale gas development. Despite its critical role in meeting global energy demands, the industry faces a persistent challenge: the lack of cost-effective, quantifiable methodologies to assess the effectiveness of fracturing. Conventional approaches rely predominantly on post-fracturing active perforation counts as a proxy for stimulation effectiveness. Although empirical evidence indicates a positive correlation between the number of active perforations and production enhancement, this oversimplified metric fails to capture the inherent complexity of hydraulic fracturing dynamics. The process involves complex interactions among geological formations, fluid rheology, wellbore configurations, and operational parameters. Practical limitations at field sites, where only total friction and flow rate are measurable, further compel engineers to neglect quantitative analysis of individual friction components (wellbore friction vs. perforation friction). Hence, traditional methods rely heavily on subjective experiential judgment, resulting in compromised accuracy in active perforation assessment and suboptimal fracturing design. This study develops a comprehensive, physics-based quantitative model to accurately evaluate the effectiveness of fracturing stimulation, enabling data-driven optimization of shale gas extraction processes.MethodsThis study established a novel quantitative evaluation model based on principles of fluid mechanics and mathematical optimization theory. The methodology utilized nonlinear least squares optimization and proceeded through two integrated computational phases: 1) Friction coefficient fitting: A dedicated nonlinear least squares objective function was constructed to resolve friction components during staged multi-cluster fracturing. Using data obtained from step-down discharge tests, the model analyzed the relationship between total friction (comprising wellbore friction, perforation friction, and near-wellbore friction) and the fracturing fluid flow rate. The optimization targeted the perforation friction coefficient kperf as the primary unknown variable. Engineering-informed constraints, such as realistic friction ranges and fluid behavior boundaries, were incorporated to ensure physically meaningful solutions. Advanced global optimization algorithms, including the Levenberg-Marquardt method, were applied to effectively address this non-convex problem. 2) Active perforation assessment: A computational method was developed based on the fitted perforation friction coefficient and established perforation erosion equations. This method identified the precise number of active perforations and calculated their average diameter after erosion during the fracturing process. Advanced optimization algorithms were employed to efficiently address both the fitting and calculation tasks. The model integrated comprehensive fluid mechanics theories related to downhole friction with existing perforation erosion models.Results and DiscussionsThe model was deployed in shale gas wells across the Sichuan Basin in China. During the step-down tests, a high level of agreement was observed between the predicted and measured friction pressure curves, confirming the model's robustness under complex field conditions. It delivered accurate quantitative outputs for both the number of active perforations and their average diameter after abrasion, overcoming the subjectivity and inaccuracy associated with traditional methods. The proposed model demonstrated several advantages over conventional approaches: 1) Enhanced accuracy and relevance: The model ensured highly accurate and practically applicable results by carefully defining fitting parameters and incorporating engineering constraints. 2) Robust theoretical foundation: It was grounded in established mathematical theory and principles of fluid mechanics. 3) Practicality and efficiency: The model featured low implementation costs and high computational efficiency, presenting a viable and promising alternative for field evaluations. Its significance to the industry lay in addressing the major challenge of the absence of a cost-effective, quantifiable assessment method. It offered detailed insights into the effectiveness of fracturing (in terms of the number and quality of perforations), enabling engineers to improve the fracturing stimulation process for improved production results. As the demand for shale gas continued to increase, this innovative approach proved critical to improving industry efficiency and sustainability. The model established a foundation for future developments, supporting more efficient and environmentally sustainable shale gas extraction practices by enabling a deeper understanding of the fracturing process and its results.关键词：shale gas extraction;horizontal well staged multi-cluster fracturing;friction fitting;nonlinear least squares;active perforations498|691|0更新时间：2026-05-23
DEEP UNDERGROUND SCIENCE AND ENGINEERING
- 摘要：ObjectiveIn the artificial bee colony (ABC) algorithm, employed bees search the entire search space while onlooker bees concentrate their efforts near high-quality food sources. From the perspective of exploration and exploitation, employed bees primarily handle exploration, whereas onlooker bees are responsible for exploitation. However, the basic ABC algorithm prioritizes exploration during the search process and performs poorly in exploitation, leading to slow convergence speed and low solution accuracy. Therefore, this study proposes an artificial bee colony algorithm based on the division between exploration and exploitation (called ABC_DEE), which consists of three stages: employed bees for exploration, onlooker bees for exploitation, and scout bees for supplementation.MethodsIn the exploration stage, excessive reliance on random solution information biased the process toward random search. Therefore, a solution-search equation guided by diverse elites was designed for employed bees, along with the introduction of a breadth-first search strategy to enhance exploration. In the exploitation stage, overutilization of optimal solution information led to premature convergence. Hence, a solution-search equation guided by objective-oriented elites was designed for onlooker bees, using a depth-first search strategy to strengthen exploitation. Considering that the random initialization method of scout bees discarded the previous search experience, and the search equation of employed and onlooker bees was singular, a neighborhood search equation was designed for scout bees. This equation considered the optimal solution based on objective value, the optimal solution based on diversity, and the previous search experience.Results and DiscussionsThe performance of ABC_DEE was assessed on both the CEC2021 test set and the esophageal cancer prediction problem, with comparisons made against six ABC variants. In numerical optimization problems with D=10, ABC_DEE outperformed ABC, GABC, REABC, ENABC, NSABC, and RNSABC on 49, 46, 51, 61, 52, and 48 functions, respectively. In contrast, ABC_DEE performed worse than these algorithms on 26, 26, 24, 12, 22, and 23 functions, respectively. The Friedman test results indicated that ABC_DEE ranked first. The Wilcoxon test results indicated that there was no significant difference between ABC_DEE and GABC, but ABC_DEE significantly outperformed the other algorithms. When D=20, ABC_DEE was superior to the comparison algorithms on at least 47 functions and inferior on at most 26 functions. The results of both the Friedman test and the Wilcoxon test were consistent with those when D=10. In addition, ABC_DEE exhibited superiority in terms of convergence speed and time efficiency. Regarding the optimization problem of the esophageal cancer prediction model based on Kernel Extreme Learning Machine (KELM), in terms of accuracy, ABC_DEE‒KELM achieved 85.83%, which was 3.00% higher than the second-ranked RNSABC‒KELM and 15.72% higher than ABC‒KELM. Regarding sensitivity, ABC_DEE‒KELM reached 91.98%, outperforming the second-ranked ENABC‒KELM by 0.61% and ABC‒KELM by 20.14%. In terms of specificity, ABC_DEE‒KELM attained 79.31%, exceeding the second-ranked RNSABC‒KELM by 0.70% and ABC‒KELM by 15.03%. Regarding the F1 score, ABC_DEE‒KELM achieved 85.49%, showing a lead of 2.54% over the second-ranked RNSABC‒KELM and 16.23% over ABC‒KELM.ConclusionsThe classical ABC suffers from an imbalance between exploration and exploitation. Regulating the relationship between exploration and exploitation is an effective method for improving the performance of ABC. This study proposes a novel ABC based on the separation of exploration and exploitation without altering the original ABC framework. Under the "base vector + perturbation" search mode, the proposed approach strengthens the division of labor between employed bees and onlooker bees in terms of exploration and exploitation through a dual-elite-guided strategy based on diversity and objective values. Simultaneously, a search equation is formulated for scout bees that incorporates both search experience and diversified optimal solution information. The proposed algorithm is compared to six other ABC algorithms across 80 benchmark functions, with its superiority evaluated in terms of solution quality, non-parametric tests, convergence speed, and time efficiency. In addition, its effectiveness in practical optimization problems is validated using esophageal cancer prediction as an example. Future research can be approached from two perspectives. First, the proposed algorithm will be applied to address more practical problems such as path planning and image processing. Second, by exploring strategies such as neighborhood topology and inertia weights to fine-tune the balance between exploration and exploitation in ABC.关键词：artificial bee colony algorithm;exploration and exploitation;elite guidance;search equation416|537|0更新时间：2026-05-23
- 摘要：ObjectiveIn the vast expanse of the boundless sea, the capricious and ever‒shifting interplay of wind and waves often presents unpredictable challenges to maritime operations. Particularly in the midst of an ever‒changing marine environment, ships frequently encounter powerful gusts and tumultuous swells, whose restless and complex movements not only pose a significant threat to the secure installation of offshore wind turbine units but also introduce considerable uncertainty to maritime operations and personnel transfers. These destabilizing elements result in operational delays, equipment damage, or even harm to personnel, necessitating utmost emphasis on dependability, safety, and stability in offshore operations. Thus, in the quest to address these concerns and bolster the efficiency and safety of maritime endeavors, researchers actively explore and pioneer diverse techniques aimed at compensating for the vertical motion of vessels. The underlying objective of these techniques lies in precisely governing vessel movements and counteracting heave provoked by wind and waves, ensuring the steadfastness and security of offshore operations. However, despite the immense potential and value that this technology holds, it encounters significant challenges in practical application. The inherent complexity and inscrutability of vessel systems introduce obstacles in modeling and control. In addition, the ability to swiftly and accurately adjust compensation strategies during actual operations to accommodate ever-changing oceanic conditions remains an exigent conundrum in need of resolution. Therefore, this study presents a compensation control method for ship heave under complex sea conditions using an improved reinforcement learning approach.MethodsThis novel method imparts fresh insights into addressing heavy compensation in offshore operations and heralds a new trajectory for the evolution of future offshore operation technologies. The study employs principles of mechanics to furnish a comprehensive model of the wave compensation system, encompassing servo drives, servo motors, encoders, and hydraulic cylinders. This model serves a dual purpose: it simulates various performance indicators of the vessel heave compensation system and functions as the training environment for reinforcement learning. With the mechanical model of the vessel heave compensation system firmly established, the study applies the Markov decision process to determine the agent’s strategy and reward mechanism. Within this process, the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm assumes a central role as the core control strategy. The TD3 algorithm approximates the value function and policy by harnessing deep neural networks, equipping it to tackle complex and nonlinear sea condition challenges. Aligned with the uncertainty and complexity entailed by the maritime milieu, this study specifically fine‒tunes the output layer of the Actor network by amplifying the amplitude of the TanH function. This adjustment endows the Actor network with the ability to generate more versatile and extensive control actions, adeptly adapting to the capriciousness of the sea. During the training process, the study employs two independent network structures, the main network and the target network, each comprising an Actor and a Critic network, amounting to a total of six networks. Through iterative updates of these networks, the system continually learns and optimizes its control strategies, culminating in the generation of self-learning optimal control actions. The study incorporates Ornstein‒Uhlenbeck (OU) action noise into the target policy to enhance the adaptability of the agent amidst complex sea conditions. OU noise is a specialized form of stochastic process that engenders smooth and correlated random oscillations over continuous time, making it particularly suited for exploration within continuous state spaces. In reinforcement learning environments, the inclusion of OU noise aids the agent in broader exploration during the nascent stages of training, facilitating the discovery of potentially advantageous state-action pairs that augment task completion. In addition, the study devises a reward function that integrates linear and Gaussian components to guide the agent's learning and decision-making processes. This composite reward function not only reflects the quality of current state‒action pairs but also incorporates predictions and evaluations of future states. This design augments the agent’s understanding of task objectives and enables it to formulate effective strategies during protracted learning processes. By adopting this approach, the agent gradually adapts to the demands of reinforcement learning tasks amid dynamically shifting sea conditions, evading the pitfalls of local optima. Even in the face of variable and complicated sea conditions, the agent continually optimizes its compensation strategies through self‒learning and adaptive adjustments, heightening accuracy in compensation and assuring the secure installation of offshore wind turbine units. In turn, this fortifies the bastion of offshore operations and safeguards personnel transfers.Results and DiscussionsSimulation experiments demonstrate the outstanding effectiveness of the improved TD3 algorithm in compensation control when confronted with adverse and complex sea conditions. The study applies the trained model to a simulated vessel heave compensation system, subjecting it to a range of complex sea conditions, spanning sea states classified from level three to level six, as well as varying marine environments. In these diversified test scenarios, the improved TD3 algorithm exhibits remarkable adaptability and stability. Particularly noteworthy is its exceptional compensation efficiency, attaining a maximum of 99.95%. This accomplishment highlights the algorithm’s superb compensation control capabilities, furnishing a high degree of safety to the installation of offshore wind turbine units. This algorithm surpasses step control methods optimized through particle swarm optimization and outperforms traditional TD3 reinforcement learning methodologies. In addition, the improved TD3 algorithm boasts favorable generalization capabilities, indicative of its capacity to swiftly adapt and generate effective compensation control strategies even in untrained and novel sea conditions.ConclusionsTherefore, the improved TD3 algorithm opens up vast potential and application value in the field of vessel heave compensation, furnishing robust technical support to the installation of offshore wind turbine units and the safety of offshore operations. Through its complex melding of mechanics, reinforcement learning, and innovative control strategies, this study advances the creation of an advanced and dependable system for maritime operations, bound to reshape the landscape of offshore endeavors.关键词：complex sea conditions;heave motion of ship;compensation control system;TD3 reinforcement learning611|818|0更新时间：2026-05-23
- 摘要：ObjectiveThe movement of sediment particles significantly affects riverbed evolution, establishing it as a central concern and ongoing challenge in fluvial dynamics research. Although image processing methods provide efficient means for acquiring and analyzing data on sediment transport characteristics, their accuracy is often compromised by water waves, bubbles, and threshold errors. Therefore, continuous improvements and refinements remain essential to ensure the acquisition of accurate and reliable particle state data. This study integrates deep learning networks with existing image processing techniques to enable more precise and comprehensive identification of suspended sediment particles. It further investigates the relationship between turbulent coherent structures and the intensity of particle movement, clarifying the mechanism through which turbulent coherent structures influence sediment transport.MethodsThe optimization algorithm developed in this study aims to maximize the detection of moving particles, providing more accurate data to support understanding sediment transport patterns at the particle scale and their association with turbulent coherent structures. This research provides new insights for advanced measurement techniques and the exploration of sediment transport mechanisms. Bedload equilibrium sediment transport experiments are conducted under medium to low flow conditions (Θ = 0.052 to 0.071). High-speed cameras are utilized to capture images of bedload particles during water flow scouring processes. An optimized method for identifying bedload particle motion is proposed by combining the grayscale subtraction method with deep learning techniques. The grayscale subtraction method identifies regions of particle motion by calculating differences in grayscale values between consecutive frames and separately analyzing the centroids of moving particles in each frame. However, because this method depends solely on grayscale variations, it presents limitations in identifying regions with minor grayscale changes. The YOLOv5 (you only look once) method is designed to rapidly and accurately detect specific target objects and their locations in images after training on a sampled dataset. The YOLOv5 algorithm adopted in this study excels at detecting small targets and provides multi-scale detection, strong versatility, fast training, inference speeds, and adaptable fine-tuning capabilities. The YOLOv5 deep learning network structure is enhanced by improving convolutional blocks, incorporating attention mechanisms, and optimizing loss function processing, boosting the detector's overall performance in accurately capturing the motion of particles over short distances. The particle tracking velocimetry method and Kalman filtering algorithm are employed to calculate the trajectories of bedload particles.Results and DiscussionThe improved YOLOv5 model demonstrates significant enhancements in loss function handling, detection accuracy, and precision. The detection accuracy of the improved model for suspended sediment particles reaches 94.9%, with a 2.3% increase in average precision and respective gains of 1.1% and 1.0% in precision and recall rates. The weighted harmonic mean of the comprehensive verification index, F1 score, increases by two percentage points. This enhanced performance in practical detection surpasses that of the original YOLOv5 model. The number of observed particle chains increases following optimization by integrating the improved YOLOv5 model with the grayscale subtraction technique for detecting particle motion. Analyses of cumulative centroid counts and particle chain node counts reveal an ascending trend as the number of frames increases. The cumulative centroid count and particle chain node count obtained through the optimization method remain stable at approximately 59% and 80%, respectively, contrasting with the growth percentages of the individual methods. It is proposed that the formation of sediment particle motion bands is associated with Q2/Q4 bursting events of coherent turbulent structures based on the results of particle motion. During Q4 events, the average flow velocity exceeds that observed during Q2 events. Under identical water depth conditions, the shear force in the Q4 region surpasses that in the Q2 region, resulting in a higher concentration of sediment particles in the corresponding Q4 region. The bed surface structure exhibits convex grooves in the Q4 region and concave grooves in the Q2 region, extending across the entire bed surface in the spanwise direction of the channel. Characteristics of coherent turbulent structures provide a more comprehensive explanation for the mechanism underlying the formation of sediment transport belts.ConclusionThis study concludes the following: 1) The grayscale subtraction technique effectively identifies particles with significant motion distances, while deep learning methods excel at recognizing particles with smaller motion distances. Through comparative analysis, data evaluation, and experimental observations, it becomes evident that the integrated algorithm, which combines both approaches, enhances the accuracy of bedload particle and trajectory identification under moderate to low flow conditions. 2)Under conditions of moderate to low flow intensity, the motion intensity of bedload sediment particles is influenced by coherent turbulent structures, resulting in a laterally banded structure. As flow intensity increases, the banded structure becomes sparser and wider. However, further intensification of the flow leads to vigorous turbulent mixing, which weakens the coherent turbulent structures and ultimately causes the banded structure to disappear. 3)Overall, sediment particle motion primarily concentrates in the central region of the channel, with reduced motion observed near the sidewalls due to lower flow velocities within the boundary layer. This observation aligns with practical scenarios and hydraulic theory. In addition, the morphology of the sediment-streaky structure typically exhibits a wider middle section and narrower sides, indicating that the formation of the banded structure is primarily influenced by large-scale coherent turbulent structures rather than secondary flow structures. This study introduces deep learning into conventional bedload particle motion recognition, improving the accuracy of bedload particle identification from a higher-resolution perspective. It addresses the challenge of detecting multiple moving sediment particles and provides a useful reference for research in fluvial dynamics.关键词：bedload;grayscale subtraction;YOLOv5;particle motion trajectory;streaky structure564|1003|0更新时间：2026-05-23
- 摘要：ObjectiveDifferent from the basic layout of traditional automated three-dimensional warehouses, steel plate goods are often stacked in the automated storage and retrieval system (AS/RS) rather than stored on high-rise shelves. This difference renders the classic AS/RS storage allocation model and job scheduling strategy inapplicable in steel plate warehouses. This study analyzes the overall warehouse layout and operational flow, proposes a multi-objective optimization model, and designs an efficient multi-objective algorithm to address the problem.Methods Based on the actual demand of the principle of priority in warehouse delivery, the principle of stacking safety, the principle of minimum stacking amount, and the principle of inventory balance, three indices were proposed: warehouse delivery efficiency, plate and stack difference, and inventory balance. First, warehouse delivery efficiency was one of the important indicators utilized to measure the palletizing plan. Since the warehouse served production purposes and was based on the principle of efficiency priority, the steel plate delivery time was minimized as much as possible. The influencing factors were primarily determined by the equipment operation mode and the palletizing position. Second, in order to ensure the stability of steel plate stacking and reduce the frequency of stacking, the steel plate and stacking position were assigned characteristic indices based on length, width, and item number to classify the steel plate and stacking type and to establish the difference degree index of plate stacking. The inventory balance index was established based on the standard deviation of the number of steel plates allocated to each reservoir to fully mobilize and balance material storage resources during operation. These three indices were utilized to evaluate the degree of stack allocation and served as the objective function to establish a multi-objective decision optimization model for the stack allocation problem of steel plates. This problem was classified as a Type A packing problem with constraints. In addition, when multiple conflicting optimization objectives were present, it was difficult to construct a single mathematical model and apply traditional analytic algorithms to solve it. A multi-objective particle swarm optimization algorithm (PCDMOPSO) based on species clustering degree was designed to solve this model using the concept of Pareto dominance and the classical particle swarm optimization algorithm. The algorithm adopted convergence and diversity of the solution as basic requirements and used the species clustering degree mechanism to monitor and adjust the algorithm's cognitive parameters and the evolution state of particles in real time. Convergence and diversity of solutions were adaptively adjusted, and a local search strategy was introduced to improve the diversity of the Pareto solution set distribution in the external archive after population updates. Then, the crowding distance strategy was utilized to maintain the external archive. The improved algorithm addressed problems such as high dependence on parameter setting, unstable solving efficiency, and a tendency to fall into local optimality.Results and DiscussionsThe automatic steel plate warehouse of a steel structure intelligent processing and manufacturing base was taken as the research object to verify the practical performance of PCDMOPSO in solving the steel plate loading and palletizing problem. Parameters and data under actual working conditions were used for simulation. The simulation results showed that compared to the classical multi-objective algorithms NSGA‒Ⅱ, MOEA/D‒DE, and MOPSO, PCDMOPSO demonstrated clear advantages in optimization ability for each target under different storage scales. Although NSGA‒Ⅱ achieved a better minimum value than PCDMOPSO in the index of the difference degree of plate and stack in 20 tests, PCDMOPSO showed stronger overall optimization ability. However, the difference was slight. Since the output of the multi-objective algorithm was a Pareto solution set, four indices, uniformity, convergence, diversity, and dominance, were selected to evaluate the distribution in the solution space and to compare the solution results of each algorithm. Among the convergence indices, NSGA‒Ⅱ yielded slightly better results than PCDMOPSO with small batch data scales. However, as batch size increased, the mean and variance of the S value obtained by PCDMOPSO significantly outperformed the other algorithms. PCDMOPSO showed clear advantages in the remaining three indicators, demonstrating high solving efficiency under varying input data as well as strong adaptability and robustness. The distribution of Pareto solution sets from different algorithms further illustrated these conclusions. Then, to verify the feasibility of the improved strategy in the proposed multi-objective particle swarm optimization algorithm, a comparative test of the algorithm improvement strategy was conducted. The Levy flight speed update mode, which served as the core of the improvement, and the local search strategy of the external archive were removed separately. The simulation was conducted using a small-batch data scale that best fit the actual production requirements of the steel sheet stock warehouse. The algorithm without the Levy flight speed update strategy exhibited significantly reduced convergence, while the algorithm without the local search strategy showed a marked reduction in diversity. The evaluation indices solved by the improved algorithm were optimized to varying degrees. Finally, the stacking situations before and after optimization were compared. Compared to the traditional stacking method used before optimization, the optimized stacking distribution scheme improved by 19.35%, 4.97%, and 62.23% under the three objectives, respectively, indicating a more significant optimization effect.ConclusionsBased on the actual demand of enterprises for optimizing automatic steel plate warehouse loading decisions, the PCDMOPSO algorithm has demonstrated good performance in the simulation test of solving the stack allocation model. The results indicate that the levy flight update strategy and the local search strategy are significant for maintaining population diversity and assisting in escaping local optima, respectively. The proposed improvement measures have an apparent positive effect on the quality of the solution. In addition, satisfactory solutions can be obtained for warehousing tasks of different scales, and the quality of the output Pareto solution set is obviously superior to that of the traditional algorithm. This effectively meets the practical requirements of various evaluation indicators in the steel plate warehousing problem and provides a valuable reference for research in the same field. It also provides strong decision support for pallet distribution and warehouse management of steel plate goods in the AS/RS.关键词：steel plates storage warehouse;stacking distribution;particle swarm optimization;multi-objective optimization;Pareto-optimal solution601|853|0更新时间：2026-05-23
INTELLIGENCE INTERDISCIPLINARY SCIENCE AND ENGINEERING
- 摘要：ObjectiveThe accuracy of comprehensive dam safety assessment remains critical to national economic development and the safety of people's lives and property downstream. This study addresses the distortion of evaluation results caused by overlapping information among evaluation indices and the use of constant weights assigned manually in the comprehensive evaluation of the operational safety of earth and rock dams. An optimization weight approach is proposed to mitigate this issue.MethodsThe initial weights of the indices were calculated using the analytic hierarchy process, and the connections among the indices were analyzed with the help of the decision-making trial and evaluation laboratory. The initial weights were then corrected based on the independence of the indices from DEMATEL to reduce the effect of overlapping evaluation index information on the evaluation results. In addition, the safety state of the dam was a dynamic process that changed over time, and the deterioration of the dam often presented as local damage in the early stages. The use of constant weight can cause these disadvantageous indicators to be overshadowed by other advantageous indicators, thus failing to detect local damage problems. Therefore, it is necessary to revise the weights of the indicators based on the variable weight theory. The weights of the indicators were optimized based on their state values, resulting in an optimized weight that accounted for both the correlation of the indicators and their state values, to address the uncertainty in the monitoring information and evaluation process, the cloud model was adopted to extract the index characteristic values and carry out a comprehensive evaluation. The influence of the number of cloud drops on the comprehensive similarity was explored to resolve the issue that the selection of the number of cloud drops was mainly subjectively determined by the decision-maker and lacked a theoretical basis. The membership degree was calculated by generating different numbers of cloud droplets through the forward cloud generators, which were taken as the model solution under each number of cloud droplets. The expected value of the membership degree was derived based on the normal distribution probability density function and was taken as the theoretical solution. It was found that in 20 random experiments, the model solution consistently fluctuated around the theoretical solution under the same cloud droplet number. As the cloud droplet number increased from 500 to 10 000, this fluctuation decreased and gradually converged to the theoretical solution, with the corresponding variance decreasing from 20.86 to 0.80. Taking 95% engineering accuracy as the measurement standard, it was found that among these 20 random experiments, three experiments failed to satisfy the condition when the cloud droplet number was 2 000, and all experiments met the requirement when the cloud droplet number was 5 000. Since the error did not change significantly when the number of cloud drops continued to increase, 5 000 was taken as the optimal number of cloud drops to balance computational efficiency and accuracy.Results and DiscussionsThe established evaluation model was applied to the earth and rock dam of the Helong Reservoir in Guangdong Province. The results showed that the optimization weight reduced the weights of indicators that were easily influenced due to a certain degree of information overlap between these indicators and others. Based on this, the variable weight theory was further integrated, and the weights of the advantageous indicators were reduced to prevent the disadvantageous indicators from being overshadowed. Therefore, the role of disadvantageous indicators in the evaluation was highlighted, and the operation status of the dam was reflected from a safer perspective. Most of the cloud drops generated by the evaluation cloud of the Helong Reservoir fell between "safety" and "basically safety". Combined with the results of the membership degree calculation, the membership degree of the Helong Reservoir Dam to "safety" and "basically safety" was 32.5% and 16.3%, respectively, and the evaluation result was determined to be "safety" by the principle of maximum similarity. Compared to the constant weights, the two evaluation results were the same, but the affiliation degree of "safety" was reduced from 40.7% to 32.5%, which reflected the influence of the correlation of the indicators and the state value of the indicators on the evaluation results. The method considers the correlation of the indices and the influence of the measured indices on the weights. It combines with the cloud model to evaluate the operation state of earth and rock dams from both quantitative and qualitative perspectives, which more realistically and effectively reflects the safety condition of the dams and provides a reference for the safety evaluation of the dam.ConclusionsThe results indicated that this method is applicable to the comprehensive evaluation of the operational safety of earth and rock dams. Fuzzy comprehensive evaluation and set pair analysis are utilized to compare the evaluation results with those of the proposed model to verify the reliability of the proposed model. All of the evaluation models indicate a status of "safety". The evaluation results are consistent and align with the actual condition of the dam, confirming the accuracy and feasibility of the proposed model.关键词：earth and rock dams;comprehensive evaluation;decision-making trial and evaluation laboratory;analytic hierarchy process;variable weight theory;cloud model482|839|0更新时间：2026-05-23
- 摘要：Lateral discharge serves as the primary pathway through which rivers receive sewage, and the permitted pollutant loadings, determined based on the pollutant mixing zone, represent critical parameters in discharge management. The adjoint equation method demonstrates substantial benefits in solving inverse problems in hydraulics. However, optimization objectives that rely on discrepancies between predicted and observed concentrations cannot be directly applied to determine the permissible loadings, limiting the application of the adjoint equation method to this issue. This study applies the adjoint equation method to derive both the control equation and boundary conditions specifically suited to lateral effluents utilizing the depth-averaged pollution transport equations for lateral discharges. Considering the narrow and elongated characteristics of the pollutant mixing zone in lateral discharges, a new formula for the error source term is introduced, with the length of the pollutant mixing zone defined as the primary objective. The adjustment value for lateral effluents is calculated by solving the adjoint equations and employing the BFGS optimization algorithm, which iteratively determines the permitted pollutant loadings from lateral discharges. The simulation of the forward problem establishes the foundation for solving the inverse problem. This research focuses on an outlet from a sewage treatment facility located in the upper reaches of the Yangtze River to evaluate the hydrodynamic and water quality model. The findings indicated that the water quality model accurately simulates the pollutant mixing zone, with the prediction error for the permanganate index (CODMn) maintained at 16.7%, meeting the precision requirements of water quality simulations in practical engineering. Following the accuracy verification in the forward problem, an experiment is conducted to evaluate the performance of the proposed inversion method. The inversion outcomes revealed that, after 18 iterations, the computational precision for the length of the pollutant mixing zone remains below 0.01 m despite two fluctuations during the convergence process due to inherent limitations of the BFGS method. In practical engineering applications, the required precision for controlling the mixing zone length is comparatively modest and is achieved within six iterations, reducing the error to 1 m. These results highlight the method's high computational accuracy and rapid convergence rate, providing valuable technical support for managing effluents in natural rivers.关键词：lateral effluents in rivers;permitting loadings of pollutant;adjoint equation;water quality simulation;inverse problems;BFGS method130|197|0更新时间：2026-05-23
- 摘要：The compression process of filled jointed rock under dry-wet cycles exhibits a distinct initial compaction stage; however, existing rock damage models rarely account for the filling characteristics of joints, making it difficult to accurately describe the nonlinear deformation during the initial compaction stage. In response to this, the present study conceptualizes the filled jointed rock as consisting of two components: voids and non-voids. The compaction deformation of the filled jointed rock is calculated based on the deformation coordination relationship of the voids. The study analyzes the mechanical deformation process of filled jointed rock by treating the micro-element strength as the limit using statistical damage theory and establishes a compression elastoplastic uniaxial compression damage mechanics equation for jointed rock. A method is provided for determining the parameters of the damage mechanics model, and the model is verified through parameter analysis and damage degree analysis using compression test data from filled jointed rock samples under dry-wet cycles. The results indicated that the degree of damage to rock samples caused by dry-wet cycles increases gradually with the number of cycles, demonstrating a continuous increase in the proportion of voids. However, the damage caused by compression gradually lags, reflecting the environmental deterioration characteristics of jointed rock. The model constructed in this study effectively analyzes the compressive mechanical properties of filled jointed rock under dry-wet cycles and holds practical engineering significance.关键词：filled jointed;initial compaction deformation;damage mechanics model;dry-wet cycles;cumulative damage339|849|0更新时间：2026-05-23
- 摘要：ObjectiveReinforcement method is utilized to treat the collapsible loess foundation in this study. The reinforced loess foundation is constructed by excavating a portion of the collapsible loess, laying geosynthetic reinforcement layers at specific spacing, and then backfilling and compacting the excavated soil. This study evaluates the improvement effect of geogrid reinforcements on the differential settlement of the collapsible loess foundation.MethodsPhysical model tests were conducted on reinforced loess foundations under wetting and loading to examine the influence of the compaction degree of backfill and the stiffness, number, and spacing of reinforcement layers on the earth pressures and deformation of reinforced loess foundations. The width (B) of the strip footing above the foundation is 90 mm. The model foundation has a length of 900 mm (10.0B), a height of 550 mm, and a width of 400 mm. The length of the model reinforcement layer is 450 mm (5.0B). The uppermost reinforcement layer is 27 mm (0.3B) away from the surface of the foundation. Loess from Yan’an was selected for the foundation soil, and biaxial geogrids with different stiffnesses were used as model reinforcements. Linear variable differential transformers were installed above the foundation surface to measure the settlements of the foundation. Earth pressure sensors were installed below the reinforced zone. The load was applied gradually. When the load reached 120 kPa, the deformation was wetted gradually under this load. Finite element numerical simulations were conducted to model the physical tests and analyze the optimal parameters and arrangements of reinforcement layers for reinforced loess foundations.Results and DiscussionsThe results showed that, compared to the pure loess foundation, the inclusion of geogrids within the collapsible loess foundation significantly improves the stress diffusion effect of the foundation and thus reduces the internal earth pressures and surface settlements within the width of the footing. After reinforcement with geogrids, the failure mode of the composite foundation shifts from the punching shear failure of the pure loess foundation to overall shear failure. During the process of wetting and loading, longitudinal cracks develop from the foundation surface into the internal soil on both sides of the reinforced zone. When the foundation was damaged, the crack depth equaled the depth of the entire reinforced zone, and the maximum crack width reached 2.5 cm. The occurrence of these cracks resulted from the inability of the soil adjacent to the reinforced zone to deform in coordination with it due to the large difference in deformation modulus between the two parts. The internal earth pressures of the reinforced loess foundation decrease with the increase in compaction degree of the backfill, the stiffness, and the number of reinforcements, whereas they increase with greater reinforcement spacing. The increased compaction degree of the backfill enhances the deformation modulus and the friction between the reinforcements and soil, which improves the stress diffusion effect and thus reduces the earth pressures below the reinforced zone. The greater the reinforcement stiffness, the higher the load borne by the reinforcements and the smaller the load transferred to the soil below the reinforced zone. The maximum earth pressures below reinforced foundations with reinforcement stiffnesses of 252 and 526 kN/m decreased by 14% and 29%, respectively, compared to the pure foundation. As the number of reinforcement layers increases, the proportion of the load carried by the reinforcements also increases, resulting in reduced load transmission to the soil beneath the reinforcement zone. In addition, increasing the number of reinforcement layers enhances the friction between the reinforcement and soil, which increases the stress diffusion effect and thus decreases the earth pressure within the width of the footing. As the vertical spacing between reinforcement layers increases, the restraint of the reinforcements on backfill deformation decreases, leading to a weakened stress diffusion effect of the foundation. Therefore, the earth pressures below the reinforced zone increased and became more unevenly distributed. Increasing the number of reinforcement layers proved most effective in reducing soil pressure, achieving a maximum reduction of 50% compared to the pure loess foundation. The reinforced loess foundation primarily relied on the bearing capacity and stress diffusion effect of the reinforcement layers within a specific depth range below the surface to reduce settlement, indicating the presence of an effectively reinforced depth. Altering reinforcement parameters beyond this depth does not affect reducing the differential settlement of the foundation. The effectively reinforced depth was approximately 0.5 times the width of the footing (0.5B). The optimal length and stiffness of the reinforcement layers were 3.0B and 500～700 kN/m, respectively.ConclusionsReinforced loess foundation represents an economical and environmentally friendly method for treating collapsible loess foundations. This study confirms that placing geosynthetic reinforcements in loess can effectively reduce the uneven settlement of collapsible loess foundations and the earth pressure beneath the footing. The reinforced loess foundation is suitable for treating collapsible foundations in engineering projects such as roads and oil and gas drilling platforms in the northwest loess region. It can also be applied to reduce the load above underground structures, including comprehensive pipe galleries. However, the longitudinal cracks observed on both sides of the reinforced zone constitute a disadvantageous factor during the working process of the reinforced loess foundation. Future research can consider overlapping geotextiles at both ends of the geogrids to reduce the modulus difference between the reinforced zone and the pure soil, enhancing the coordinated deformation ability of the reinforced and unreinforced zones. Therefore, the formation of cracks can be eliminated.关键词：collapsible loess;reinforced foundation;physical model test;wetting and loading379|1064|0更新时间：2026-05-23
- 摘要：ObjectiveStrain-hardening cement-based composites (SHCC) exhibit inherent characteristics of multiple microcracking under uniaxial tension and bending, which reduces stress concentration at the crack mouth and delays debonding failure between SHCC and externally bonded FRP plates during the bending of FRP plate-strengthened SHCC beams. This study conducts experimental investigation and theoretical analysis on SHCC beams reinforced with externally bonded FRP plates to examine their debonding behavior, providing guidance for the engineering application of such structural systems.MethodsThe mechanical model based on composite beam theory was developed by satisfying the requirements of force equilibrium and strain compatibility while simultaneously allowing for interfacial partial slip at the FRP-concrete interface. The theoretical analysis included two loading stages: before SHCC cracked and after SHCC cracked. Before SHCC cracked, SHCC and FRP were treated as Euler‒Bernoulli beams and were connected based on reasonable interface rules; the interfacial shear stress was then obtained using the linear elastic mechanics method. After SHCC cracked, to quantify the effect of SHCC multiple fine cracks on interfacial bond stress, segmental stiffness reduction was conducted based on the moment-curvature relation, which combined interface stress analysis and equations on sectional internal force balance to construct the mechanical analysis model. First, the cracked FRP‒SHCC beams were divided into two parts: the elastic part and the SHCC cracked part. Then, the SHCC cracked part was subdivided into several segments. Second, the bending stiffness and the height of the compression zone of SHCC at the joint between the elastic zone and cracked zone and at midspan were obtained by solving the equilibrium equation of the cross-section force system. Third, the bending stiffness and the height of the compressive zone of each segment were assumed to change linearly from the midspan to the elastic part. Finally, the simplified linear interface bond-slip relation, the constitutive relations of FRP and SHCC, and the control differential equations on the axial force of FRP were utilized to establish the analysis model for FRP-reinforced SHCC beams. The solution was programmed using MATLAB software. Three-point bending tests of FRP‒SHCC beams with different geometric dimensions and different FRP thicknesses were performed to verify the validity of the analysis model. Single-side shear tests on the FRP‒SHCC interface were performed to obtain the interfacial bond stress-slip relationship. The typical interface bond stress-slip curve included an ascending branch and a descending branch, which was similar to that of the FRP‒RC interface. Based on the fine finite element analysis by Lu et al., the interfacial shear stress near the crack zone exhibited a highly brittle descent after reaching its peak value. Further studies showed that the calculated results were only 3.7% lower than the test results when the curve with only the ascending branch was applied to the whole beam. The bond stress-slip relationship indicated by Lu et al. was a curve, and the shear stress dropped sharply to 0 after reaching the peak value. This study simplified the ascending curve to a straight line to simplify the calculationResults and DiscussionsThe deviations of the calculated peak load from the test values were in the range of -7.79% to 7.45%, the deviations of the calculated FRP strain from the test values were in the range of -11.52% to 8.13%, and the deviations of the calculated mid-span deflection from the test values were in the range of -7.33% to -22.03%. The calculation results showed that the tensile strain of FRP decreased linearly from the mid-span to the support during the elastic stage, and after the SHCC cracked, the distribution of FRP strain from the mid-span to the beam end indicated that its decreasing rate transitioned from slow to fast and then to slow. The strain of FRP did not reach its fracture strain, which implied that the failure of the composite beams was not due to the strength failure of FRP. The calculated deformation-load curve of the FRP-SHCC beam showed that the elastic stage was short, and the slope of the curve gradually decreased with the increase of the load, indicating that the stiffness of the composite beam gradually decreased as the crack opening of the SHCC increased. The calculated mid-span deflection results aligned with the test results for most of the loading process, except for a short segment near the peak load. In the test, when approaching the peak load, the slope of the load-deformation curve gradually decreased, indicating the occurrence of interface debonding. It was likely that the linear interface bonding stress-slip relationship adopted in the model used in this study could not reflect this process, which remained an issue requiring further investigation. The slope of the FRP strain-load relationship curve significantly decreased when the SHCC initially cracked and then approached a constant. The slope of the curve was also larger when the thickness of the FRP plate increased. The calculated values were in reasonable agreement with the test results. The calculated interface shear stress showed that during the elastic stage, the interfacial shear stress gradually increased from mid-span to the plate end. After the SHCC cracked, the interfacial shear stress first increased and then decreased from mid-span to the end of the plate. The interface shear stress reached its maximum at a position corresponding to the height of the beam from the mid-span, initiating FRP debonding. These results were consistent with the phenomena observed in the test.ConclusionsThis study quantifies the process of crack opening and development in different regions of cracked SHCC through segmental stiffness reduction, and the debonding failure load of FRP-reinforced SHCC beams is determined by combining internal force balance equations with interface stress analysis. The results showed reasonable agreement with the experimental data, indicating that the approach can be applied to the analysis of this type of new civil engineering structure.关键词：FRP plates reinforced SHCC beams;debonding;beam segment;bending stiffness;interface;bond stress207|344|0更新时间：2026-05-23
HYDRAULIC & CIVIL ENGINEERING
- 摘要：ObjectiveWaste-activated sludge (WAS) is a by-product of wastewater treatment plants (WWPTs), which seriously affects the operation of WWPTs and environmental safety. WAS is rich in protein, polysaccharides, and other macromolecular organic matter, but it also contains a significant amount of heavy metals and viruses. If not effectively treated, it causes severe secondary pollution in the environment and results in the waste of resources. The reduction, stabilization, harmlessness, and recycling of residual sludge represent the most critical challenges in sludge management. Anaerobic fermentation of sludge is the most common technology for treating and disposing of WAS, achieving the goals of sludge reduction and recycling. This study investigates the feasibility of nano zero-valent iron (nZVI) synergized with sodium percarbonate (SPC) to enhance the anaerobic fermentation performance of sludge using WAS from a municipal WWTP, and it also reveals the underlying fermentation mechanism. In addition, the optimal fermentation condition is identified.MethodsThe Fe2+ and Fe3+ derived from the hydrolysis of nZVI cooperated with the H2O2 produced by SPC to establish Fenton or Fenton-like systems. In addition, Fe3+ was reduced to Fe2+ by nZVI, establishing a cyclic reaction system that extended its action time within the fermentation system, enhancing the fermentation performance. In addition, Fe2+ and Fe3+ acted as catalysts to raise the decomposition of H2O2, resulting in the generation of many hydroxyl radicals (
- 摘要：ObjectiveThe lower reaches of the Yarlung Tsangpo River, characterized by a significant topographical gradient, play a crucial role in transporting moisture from the Indian Ocean through the Indian monsoon to the Tibetan Plateau. This study investigates isotopic altitudinal effects on atmospheric precipitation and the distribution characteristics of d-excess in this region. It compares the isotopic altitudinal gradients of atmospheric precipitation in the midstream and downstream regions of the Yarlung Tsangpo River to clarify the factors contributing to discernible differences. The study explores the complex dynamics of the Indian Ocean monsoon airflow as it traverses and circulates within this geographical expanse by carefully examining these disparities. This expanded investigation proves pivotal for advancing comprehension of the nuanced interactions between topography and meteorological phenomena, shedding light on the complex mechanisms influencing isotopic variations in precipitation and refining insights into broader climatic processes in the studied area.MethodsThe data source for this study included atmospheric precipitation and surface water samples collected through field surveys. The Karst Geological Resources and Environment Supervision and Testing Center of the Ministry of Land and Resources conducted sample testing using a liquid water isotope analyzer (L2130-i). Isotope results were expressed as the relative thousandth deviation value of the same isotope ratio Rsample and the international standard Rstandard (V‒SMOW, Vienna standard average ocean water): δ = (Rsample/Rstandard‒1) × 1 000. The primary research methodology employed in this study involved the simulation of isotopic altitudinal gradients using the Rayleigh distillation model. This model operated under the assumption of an idealized open system in which condensed rainwater promptly exited the atmospheric system, leading to variations in the stable isotopic content of hydrogen and oxygen in precipitation at different altitudes. The study aimed to capture the complex processes that contributed to observed isotopic differences in precipitation at various elevations utilizing the Rayleigh distillation model. This approach provided a theoretical framework for understanding the dynamics of isotopic fractionation in rainfall within the context of altitude, facilitating a comprehensive analysis of atmospheric conditions in the studied region. Building upon this theoretical framework, the study involved inputting actual isotopic initial values within the research area and simulating the altitudinal effects of precipitation isotopes under ideal conditions. The simulation assumed that for every 1 000 meters of elevation gain, 10% of the precipitation condensed, allowing for the verification of actual altitudinal gradient values within the study area. In addition, the backward trajectory model employed the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. This Lagrangian trajectory model analyzed atmospheric transport, providing insights into the composition of water vapor sources within the research area. The model served as a complementary tool to support the understanding of the transport processes of the Indian Ocean monsoon within the study area, enriching the interpretation of the complex dynamics that influenced isotopic variations in precipitation at different altitudes.Results and DiscussionsThe stable hydrogen and oxygen isotope analysis enabled the establishment of a local atmospheric precipitation line and isotopic altitudinal gradient. The equation representing the atmospheric precipitation line in the research area is δ(D) = 8.02δ(18O) + 13.21. The elevated d-excess in this region is attributed to the abrupt ascent of moist air encountering the topography upon entering the Tibetan Plateau, leading to a sudden decrease in temperature and relative humidity. Another contributing factor is the local vapor recycling within the large canyon, which contributes to the observed high d-excess. These findings provide valuable insights into the factors that influence isotopic variations in precipitation in the study area, highlighting the complex interplay between atmospheric dynamics and geographical features. Interpolation analysis was employed to discern the distribution pattern of d-excess in atmospheric precipitation within the study area. The findings revealed a distinctive low-high-low pattern of d-excess across the research region, with elevated d-excess observed in the Himalayan eastern tectonic zone. This geographical area exhibited a high d-excess, indicating unique atmospheric processes and moisture sources that contributed to the isotopic composition in this specific locale. Identifying such spatial variations in d-excess enhanced the understanding of regional atmospheric dynamics and the complex factors influencing isotopic characteristics in precipitation. Through regression analysis and validation using an ideal model, the altitudinal gradient in the Yarlung Tsangpo River Grand Canyon region was determined to be ‒1.43‰/km, while in the midstream, the altitudinal gradient was found to be 3.30‰/km. The primary drivers for this disparity were attributed to variations in topographical slopes and the influence of monsoons. The distinct altitudinal gradients were validated by the composition of airflow sources across different locations in the backward trajectory model. This analysis highlighted the significance of both topography and monsoonal patterns in shaping the isotopic characteristics of precipitation, providing valuable insights into the regional atmospheric dynamics within the Yarlung Tsangpo River basin.ConclusionsThrough an examination of atmospheric precipitation isotopes in the Yarlung Tsangpo River Grand Canyon region, this study,establishes the atmospheric precipitation line and the isotopic altitudinal gradient within the area. Compared to the midstream, the altitudinal gradient in this region is relatively modest and closely linked to variations in topography and water vapor composition. In addition, the research highlights the retention of Indian Ocean moisture within the Yarlung Tsangpo Grand Canyon region following its ingress into the Tibetan Plateau.关键词：The Yarlung Tsangpo River Grand Canyon;atmospheric precipitation;hydrogen and oxygen stable isotopes;d-excess;Water vapor transportation485|770|0更新时间：2026-05-23
- 摘要：Carbon dioxide electrochemical reduction (CO2RR) has great prospects in alleviating environmental problems caused by carbon dioxide emissions and achieving value-added products. Among these chemicals, formic acid is suggested to be one of the economically viable products for hydrogen storage material and chemical intermediates. The industrial production of formic acid is an energy-intensive process, so the production of formic acid in CO2RR under mild conditions has received extensive attention. The production of formic acid in the CO2RR depends on the development of highly active and selective electrocatalysts. In order to solve the electrocatalysts with low reaction activity, low formic acid formation rate and poor long-term stability in the CO2RR process, hollow nano-carbon sphere-supported bismuth oxide catalysts (Bi2O3@HCS) were prepared by template method. Metallic bismuth (Bi) has preferable HOCO* adsorption energy and hollow nanospheres have a good active component limiting effect. The chemical composition and surface morphology of the Bi2O3@HCS catalysts were in detail analyzed by scanning electron microscope (SEM), transmission electron microscope (TEM), X-ray powder diffractometer (XRD), and X-ray photoelectron spectroscopy (XPS). These results showed that the active components Bi0 and Bi2O3 were uniformly dispersed in the hollow carbon nanospheres, and in the Bi2O3@HCS-2 catalyst the highest Bi3+/Bi0 atomic ratio was achived. The sizes of Bi0 and Bi2O3 particles did not change significantly with increasing Bi loading from 2.0 to 3.0 mmol/L. The result was attributed to the confinement effect of hollow carbon nanospheres in the Bi2O3@HCS catalysts. The electrochemical capability of Bi2O3@HCS catalysts toward electrochemical CO2 reduction was investigated by Linear sweep voltammograms (LSV) test in phosphate solution (pH=6.8) saturated with CO2 or Ar. For Bi2O3@HCS-2 catalyst, the current density of CO2 reduction peak is the largest, which indicated that the higher activity of the Bi2O3@HCS-2 catalyst was obtained compared with both Bi2O3@HCS-1 and Bi2O3@HCS-3 in the CO2RR. Electrochemical impedance spectroscopy (EIS) was performed to investigate the electron transfer capability of the Bi2O3@HCS catalysts. The Bi2O3@HCS-2 catalyst exhibited a lower charge-transfer resistance, suggesting a more favorable electron transfer during CO2RR. The performance of Bi2O3@HCS catalysts in CO2RR for producing formic acid was investigated in a H-shaped electrolyzer. The Bi2O3@HCS-2 catalyst, with a Bi loading of 2.0 mmol/L, had the highest formic acid formation rate compared to Bi2O3@HCS-1 and Bi2O3@HCS-3 catalysts (the Bi loading was 1.0 mmol/L and 3.0 mmol/L, respectively). The effects of the reaction operating conditions (cathode potential, KHCO3 electrolyte concentration and pH) on the formation of formic acid were optimized in the CO2RR over the Bi2O3@HCS-2 catalyst. The results showed that the Bi2O3@HCS-2 catalyst with uniformly-sized particles showed the highest formic acid formation rate (1 108.11 μmol/L/h/cm2), and its Faradaic efficiency (FE) reached 54.73% in the H-type reactor under the condition of cathode potential of ‒1.1 V vs. RHE and electrolyte concentration of 0.1 mol/L KHCO3. In order to have an insight into the effects of formic acid formation rate under different pH conditions in the CO2RR over the Bi2O3@HCS-2 catalyst, phosphoric acid buffer solution was used as the electrolyte instead of KHCO3. The results showed that the Bi2O3@HCS-2 catalyst exhibited good adaptability in the CO2RR in a wide pH range. In addition, the good stability of the Bi2O3@HCS-2 catalyst in CO2RR for synthesis of formic acid was proved through the five successive cycle experiments. Compared with the formic acid formation rate in the literatures, the Bi2O3@HCS-2 catalyst showed good performance for the following reasons: 1) the hollow nanocarbon spheres with nanoconfinement effect inhibited the agglomeration of the active components of Bi0 and Bi2O3 nanoparticles; 2) the abundant Bi2O3 particles improved the reaction kinetics for the formic acid formation in the CO2RR; 3) the transition of the chemical valence state between Bi0 and Bi2O3 further accelerated the electron transfer capacity. This study on the electrochemical CO2 reduction for producing formic acid over the Bi2O3@HCS-2 catalysts provides a contribution for the synthesis of high-efficiency Bi-based nanocatalysts.关键词：Carbon dioxide;electrochemical reduction;formic acid;Bi-based catalyst276|624|0更新时间：2026-05-23
ENVIRONMENTAL ENGINEERING
- 摘要：ObjectiveThe single-inductance dual-output (SIDO) converter has gained increasing attention due to its reduced magnetic component count, compact size, low cost, and high efficiency. However, because both output branches share a single inductor, significant cross-coupling arises during input voltage transients and load disturbances, degrading output voltage performance. Enhancing the control strategy is crucial to addressing this issue. Given that the SIDO converter is a nonlinear time-varying system, conventional PI control proves inadequate. For such strongly coupled nonlinear systems, advanced nonlinear control techniques can substantially improve both dynamic response and control precision.MethodsActive disturbance rejection control (ADRC) has emerged as a promising strategy owing to its strong disturbance rejection capability and independence from precise system modeling. Nevertheless, conventional ADRC, being a linear approach, suffers from performance limitations. To overcome this, we propose an enhanced ADRC strategy integrating a cascaded reduced-order extended state observer (CRESO) with an improved nonsingular terminal sliding mode control (TSMC). This strategy is successfully applied to the SIDO Buck converter by improving both the disturbance observer and the state error feedback law. First, a state-space averaged model of the SIDO Buck converter in continuous conduction mode is developed, and the mechanism of cross-coupling between output branches is analyzed. The main and auxiliary circuits are then decoupled into two independent second-order ADRC canonical forms for separate controller design. To address the limited estimation accuracy of traditional extended state observers (ESO), a two-stage observer is implemented by cascading a secondary ESO to capture residual disturbances. While this improves estimation, it increases observer complexity. To mitigate this, we leverage reduced-order observer principles—when some system outputs are directly measurable, only the remaining states and disturbances need to be estimated. Based on this insight, the CRESO is formulated to estimate both state variables and total internal/external disturbances. Frequency-domain analysis confirms that the proposed observer enhances estimation accuracy and accelerates disturbance rejection within the same bandwidth. Next, the traditional PD-based ADRC feedback law is replaced with a sliding mode controller to improve system robustness and convergence speed, particularly under large deviations. Among various options, nonsingular terminal sliding mode control (TSMC) is chosen for its ability to drive system trajectories to the origin in finite time, thereby improving both rapidity and robustness. To address the chattering effect commonly associated with sliding mode control, we incorporate a super-twisting algorithm in place of the discontinuous sign function, yielding an improved TSMC with reduced chattering. The stability of both CRESO and the improved nonsingular TSMC is rigorously verified through the characteristic root criterion and Lyapunov stability analysis. Additionally, the steady-state error bounds of CRESO and the convergence time of the enhanced TSMC are derived.Results and DiscussionsA simulation and experimental platform for the SIDO Buck converter is established. Simulations are conducted using MATLAB/Simulink, while hardware implementation is performed using the DSP28335 and an MT 6020 HIL platform. Transient performance under input voltage and load disturbances is evaluated by comparing three control strategies: common-mode voltage/differential-mode voltage (CMV-DMV) control, conventional ADRC, and the proposed improved ADRC. The results show that the proposed control approach significantly reduces output voltage overshoot and shortens recovery time across both output branches.These improvements confirm the effectiveness and superiority of the proposed strategy and demonstrate its practical engineering applicability.ConclusionsThe control strategy in this paper reduces the cross-interference between the output branches of the SIDO Buck converter and improves the transient response performance of the system.关键词：single-inductance dual-output;cross influence;descending class expansion state observer;non-singular terminal sliding mode;super torque control algorithm487|750|1更新时间：2026-05-23
- 摘要：ObjectiveTo improve the technical economy of battery system applications, a temporal convolutional network (TCN) is employed to evaluate battery life from two perspectives: State of health (SOH) and remaining useful life (RUL). SOH is typically quantified by capacity, while RUL is measured in terms of the remaining number of charge-discharge cycles.MethodsFirst, the TCN-based approach to battery life assessment is introduced. Compared to classical recurrent neural networks, TCN has the advantages of improved gradient stability, faster data processing, and reduced memory consumption. Next, 14 indirect health-related features are extracted from readily available battery data including time, voltage, current, and temperature. The relevance of each feature to capacity is assessed using three correlation techniques: KL divergence, Pearson correlation coefficient, and gray relational analysis. Additionally, a polling strategy is employed using the TCN: each feature is used individually for capacity prediction, and the mean of six prediction outcomes per feature is taken as the final correlation score. Correlation results from all four methods are compared. Although Pearson correlation and TCN-based analysis yield similar rankings, both focus primarily on the top features. Due to the different principles of these methods, their outcomes often diverge significantly. Therefore, TCN-derived results are considered the most reliable for identifying factors influencing capacity prediction. For lithium-ion battery data from NASA, five features with the greatest impact on SOH are identified (in descending order of importance): cycle time, average voltage, voltage sample entropy, temperature sample entropy, and current.Results and DiscussionsTo address redundancy caused by overlapping information among these features, Kernel principal component analysis (KPCA) is applied for dimensionality reduction. The contribution rates of principal components are calculated, and the top two principal components (PC1 and PC2) are selected as inputs for simulation to eliminate noise and improve computational efficiency. A comparative analysis of three prediction models including TCN, long short-term memory (LSTM) networks, and Backpropagation (BP) neural networks shows that the TCN achieves the lowest root mean square error (RMSE) of 0.019 3, indicating the highest predictive accuracy. Battery capacity regeneration can result in similar capacities at different numbers of cycles or times. When SOH is used to characterize battery life, significant errors will be introduced. In contrast, RUL will irreversibly decrease as the service time increases, which can provide a more reliable criterion for evaluation. To predict RUL, the same five key features (cycle time, average voltage, voltage sample entropy, temperature sample entropy, current) along with capacity are used. Six principal components are obtained through KPCA analysis, and PC1 and PC2 are also selected for prediction. Among the three models compared, the RMSE of TCN is lowest (0.019 3), which further proves its outstanding accuracy in RUL estimation.ConclusionsThis study validates the effectiveness of TCN for battery life prediction. By evaluating both SOH and RUL, the proposed TCN-based framework provides a more accurate and robust assessment of battery health.关键词：battery;Temporal Convolution Network;Kernel Principal Component Analysis;state of health;remaining useful life475|958|1更新时间：2026-05-23
- 摘要：ObjectiveThe incipient fault of the cable occurs at the local insulation defect of the cable and constitutes an intermittent grounding arc fault. As the degree of cable insulation deterioration increases, the frequency of incipient faults continuously rises and eventually develops into a permanent fault. At present, positioning methods for cable incipient faults primarily rely on the impedance method and the traveling wave method. The cable incipient fault location method, based on the impedance method, constructs the circuit equation using the fault voltage and the transmission current at the head end, and estimates the fault distance based on the purely resistive nature of the arc resistance and its corresponding parametric formula. However, this model does not consider the attenuation and dispersion of the arc current during transmission, resulting in a decrease in positioning accuracy. The incipient fault location method based on the traveling wave requires an analysis of electromagnetic traveling wave propagation in the cable, which determines the fault location by calculating the time difference in wave transmission. However, the single-ended traveling wave positioning method results in misjudgments due to refraction and reflection at the defect position. In addition, the traditional double-ended positioning method can inaccurately identify the wavefront position due to noise or discharge interference when analyzing the signal's time-domain information, affecting location accuracy. Therefore, based on two-terminal traveling wave measurements, this study proposes an accurate positioning method for cable incipient faults by calculating the time-frequency distribution of the signals.MethodsInitially, the distributed parameter model of high-frequency electromagnetic wave transmission in cables was analyzed. Considering the skin effect and proximity effect of the cable, the distributed parameters were modified and expressed, and the propagation constant and traveling wave velocity of the electromagnetic wave in the cable were calculated. Then, by analyzing the transmission process of electromagnetic waves and the multiple refraction and reflection phenomena at the defect location in the cable, the corresponding relationship between the cable fault location and the time difference between the first transmission of the arc traveling wave to both ends of the cable was obtained. After that, considering the influence of noise on the time domain signal, the signal was analyzed in the time-frequency domain. The WVD algorithm formed the basis of the time-frequency distribution algorithm. However, due to the presence of cross-term interference, the accuracy of the positioning results was affected. The Hanning window exhibited good concentration capability for the main frequency of the signal and demonstrated strong attenuation for the secondary frequency. Therefore, the PWVD algorithm, incorporating the Hanning window, was employed to calculate the time-frequency distribution of the signal. Simultaneously, when calculating the time delay of the two signals, the time‒frequency cross-correlation function was utilized to determine the similarity of the time-frequency distribution, and the maximum value of the time‒frequency cross-correlation amplitude was adopted as the transmission delay of the signal, enabling the identification of the fault location.Results and DiscussionsFor the above scheme, the positioning algorithm was first verified through simulation. Based on the arc resistance formula, the cable incipient fault model was constructed in PSCAD. The total cable length was set to 4 km, and the arc fault was introduced at a distance of 3 km from the head end. The ground current waveforms transmitted to both ends of the cable were collected, and the time-frequency distribution and time-frequency cross-correlation results of the currents were calculated. The maximum value of the time-frequency cross-correlation amplitude occurred at 10.9 μs, indicating that the transmission delay was approximately 10.9 μs. Then, the wave velocity of the arc was calculated based on the center frequency of the signal's time-frequency distribution. When the center frequency was 20 kHz, the arc wave velocity was calculated to be 187.65 m/μs. After applying the formula transformation, the fault location result was 3 022.71 m, with a location error of 0.57%. The influence of noise on positioning accuracy was then examined. When the SNR of the current signals at both ends was set to 80, 50, and 30 dB, respectively, the positioning results were 3 027.21, 3 043.73, and 3 083.69 m, and the corresponding positioning errors were 0.68%, 1.09%, and 2.09%. The simulation effectively verified the algorithm's anti-noise capability. In the experimental validation, a 10 kV 105 m cable experimental platform was constructed, and the incipient fault was introduced at the 25 m position. Two current sensors were placed at both ends of the cable to collect the arc pulse. Due to the short cable length, the sampling rate was set to 500 MHz. At this setting, the incipient fault location of the cable was calculated to be 30.63 m, resulting in a positioning error of 5.36%. For the 105 m cable, the arc underwent multiple refractions in a very short time, affecting the accuracy of the positioning result; however, the outcome still demonstrated the feasibility of the proposed method.ConclusionsThis study proposes an incipient fault location method for cables by analyzing the transmission process of arc pulses within the cable. The PWVD algorithm, combined with the Hanning window and the time-requency cross-correlation function, is employed to calculate the fault location, effectively mitigating the issue of noise interference that typically affects time-domain signals. Simulation and experimental verification clearly demonstrate that the proposed method achieves high positioning accuracy and exhibits strong resistance to noise.关键词：cable incipient fault;traveling wave transmission;two-terminal current;pseudo Wigner‒Ville distribution;time‒frequency cross-correlation501|859|1更新时间：2026-05-23
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Development Process and Characteristics Study of Tree Line Discharge in 10 kV Overhead Power Lines 增强出版 AI导读
摘要：ObjectiveThis study focuses on the development process and mechanism of tree line discharge. It examines the development characteristics of 10 kV overhead line tree line discharge, investigates variations in temperature and water content across different stages of discharge, proposes the development mechanism of the charring channel, and introduces a feature extraction method based on these findings.MethodsBased on the characteristics of a 10 kV three-phase ungrounded distribution network system during single-phase ground faults, an experimental platform for 10 kV overhead line tree discharges was constructed. Voltage transformers and sampling resistors were employed to collect voltages and currents. A typical species of pine tree was selected as the main object of study, and the tree samples were inserted into moist soil to ensure effective grounding. The entire tree discharge process was monitored through a synchronized acquisition system, and changes in temperature and electrical signals were recorded. An analysis of the temperature and water content changes across various cortical tissues of the tree was conducted to examine the progression of the discharge process triggered by contact between the tree and the power line. Infrared thermography was employed to observe the complete development of the charring channel under the tree epidermis. The mechanism of charring channel development under the tree epidermis was proposed, and its accuracy was verified using microscope images. Based on the observed characteristics of the tree discharge process, feature extraction was performed using high-frequency signals that contained detailed information on high-frequency discharges. The effectiveness of this method was verified using experimental data.Results and DiscussionsBased on the overall change in leakage current during tree line discharge, the process was divided into four stages: the contact and warming stage, the water evaporation stage, the charring channel development stage, and the flame bridging and arc ignition stage. The moisture distribution within the tree affected the development of current channels. During the transition from the contact and warming stage to the water evaporation stage, the passage of electric current through the tree shifted from the sapwood to the vascular cambium due to a temperature increase that enabled water migration from the tree. The rise in temperature and the reduction in water content initially caused an increase in leakage current, followed by a decrease, during the first two stages, both of which simultaneously created favorable conditions for the development of charring channels. The localized drying, breakdown, and charring within the tree, resulting from the temperature rise and moisture loss in the early stages, repeatedly occurred to form a forward-progressing charring channel. Microscopic observation of the discharge process at the front end of the charring channel confirmed this conclusion. The charring channel acted as a series resistor in the fault path, exhibiting low resistance, which led to a reduction in ground impedance as the channel developed. The correlation between the charring channel and the leakage current amplitude further validates the changes in tree impedance due to the formation of the charring channel. As the charring channel crosses the tree, the larger leakage current further ignites the tree, and the resulting surface flames cause a rapid drop in ground impedance, resulting in line-to-ground arcing along the tree. Based on these findings and analyses, a fault signal feature extraction method was proposed using high-frequency signal transient intensity statistics. Regions of higher energy concentration were identified by analyzing the statistical distribution of transient intensity, enabling effective differentiation between tree line discharge signals and background noise. The results demonstrated that the transient intensity probability distribution curve progressively flattens as the fault develops, further indicating that the development of tree line discharge is accompanied by changes in high-frequency discharge energy. The described tree line discharge development process and the proposed feature extraction method provide a foundation for forest fire traceability and the development of tree line discharge monitoring devices.ConclusionsThis study shows the high-frequency discharge details during the tree line discharge process. Existing tree line discharge models do not consider the high-frequency details, which can result in the neglect of significant features within the high-frequency signals of tree line discharges. These features can be manifested in electrical signals, as well as in ultrasonic and ground waves. The effectiveness of both ultrasonic and ground waves for high-frequency feature extraction was validated through experimental results. In addition, several issues emerged during the experimental process that differ from conventional single-phase grounding faults. For instance, the voltage amplitude of the faulted phase is not the lowest, and the zero-sequence voltage, which is typically expected to increase upon fault occurrence, instead exhibits a decrease in amplitude. The above phenomena can lead to misinterpretation by existing fault detection equipment. Therefore, investigating the underlying mechanisms of these phenomena is essential for a deeper understanding of tree line discharge faults.关键词：charring channel;tree line fault;fault characteristic;wildfire;distribution network fault869|1475|1更新时间：2026-05-23
ELECTRICAL ENGINEERING
- 摘要：ObjectivePrecision design and kinematic calibration are two commonly utilized approaches to further improve the pose accuracy of parallel robots. Specifically, the cost of precision design is relatively high, and it is not suitable for some circumstances in which high precision is required. The most effective method with the lowest cost is to calibrate the robot's kinematics. However, problems exist in traditional calibration methods, such as excessive error parameters, error accumulation, and difficulty in obtaining the optimal solution of statically indeterminate equations. Considering the above problems, this study considers the benchmark 3‒PTT parallel robot as the research object, whose error analysis and error compensation are studied to avoid the shortcomings of traditional methods and improve the robot's motion accuracy.MethodsInitially, a simplified mathematical model of the 3‒PTT parallel robot is built, and its kinematic coordinate system is established. Then, topological structure analysis combined with the principle of spiral theory is carried forward to analyze the degree of freedom of the robot. The 3‒PTT parallel robot only has translational degrees of freedom along the three coordinate axes by referring to the velocity characteristic polynomial. Secondly, based on the structural characteristics of the 3‒PTT parallel robot, i.e., the distance between the hinge point of the static platform and the hinge point of the mobile platform being fixed to a constant value L by the rigid connecting rod, the inverse kinematics model of the robot is established. Then, based on the inverse kinematics analytic formula of the 3‒PTT parallel robot, the joint input is regarded as a known quantity, the position of the mobile platform is regarded as an unknown quantity, and the forward kinematics interpretation of the robot is solved through the inverse solution. In addition, the error source of the robot mainly consists of parts machining, assembly positioning, and others, and it is proposed in this study that the 3‒PTT parallel robot contains a total of 21 error terms, hinge point installation coordination error, and link length error. Based on the aforementioned kinematics equation, the error model is established and divided into three categories: the error of a single branch chain, the error of link length, and the error of three branch chains. Thus, the influence of the coordinate error and the link length error on the pose accuracy of the mobile platform is analyzed.Results and DiscussionsThe results of error analysis show that the length error of the link and the z‒coordinate error of the hinge point of the static platform have significant effects on the pose accuracy of the mobile platform (the average position error of the mobile platform in the three degrees of freedom directions is more than 1 mm), and appropriate attention is paid to the machining and assembly of robot parts. In addition, in order to overcome the shortcomings of traditional methods mentioned above, i.e., excessive error parameters, error accumulation, and difficulty in obtaining the optimal solution of statically indeterminate equations, an inverse kinematics error compensation algorithm is proposed in this study. The algorithm uses the inverse kinematics model of the robot to convert the mechanism error that causes the low operation accuracy of the end-effector into the joint input error of the robot. It focuses on compensating the joint input error after transformation, reducing the parameters in the error compensation algorithm, greatly reducing the difficulty of solving the error correction objective function, and effectively avoiding the problem of error accumulation. Thus, the algorithm is more feasible. In addition, to improve the efficiency of the aforementioned error compensation algorithm, the standard particle swarm optimization algorithm is further enhanced by integrating the dynamic inertia weight value and dynamic learning factor, thus overcoming the problems of precocious convergence to a local optimum and slow convergence in the later iteration of the standard particle swarm optimization algorithm. Then, the improved particle swarm optimization algorithm is utilized to optimize the error correction objective function, where the slider compensation is obtained, and the servo driver is utilized to complete the error compensation. Finally, 31 mobile platform position sampling points on both linear and circular trajectories in the workspace of the 3‒PTT parallel robot are selected for simulation and experimental verification. The simulation results show that the pose errors of the compensated mobile platform converge to zero asymptotically. Experimental results show that the maximum error of the mobile platform in the x, y, and z‒axis directions decreases from 10.89, 12.42, and 2.12 mm to 0.97, 1.14, and 0.72 mm, respectively. In addition, the maximum distance error decreases from 15.35 mm to 1.36 mm after compensation, and the effect is obvious. The mean error decreases from 5.86, 8.02, and 1.12 mm to 0.45, 0.46, and 0.33 mm, respectively, and the mean distance error decreases to 0.82 mm, increasing the operating accuracy of the robot by 92.1%.ConclusionsTherefore, through simulation and experimental results, the maximum and average position errors of the mobile platform after compensation are significantly reduced by more than one order of magnitude, indicating the effectiveness of the proposed compensation method. The salient feature of this study is the improved pose accuracy and operational efficiency in robotic systems through error analysis and compensation.关键词：parallel robot;error analysis;error compensation;improved particle swarm algorithm;pose accuracy465|1564|0更新时间：2026-05-23
- 摘要：ObjectiveThe material of nonmagnetic drilling tools is 316L stainless steel. When operating underground, nonmagnetic drilling tools are prone to wear and corrosion due to the poor wear and corrosion resistance of 316L stainless steel. Cladding a carbide alloy on the surface of nonmagnetic drilling tools serves as an effective method to enhance their wear and corrosion resistance. Ni60 alloy exhibits high hardness and wear resistance; however, it also presents high crack sensitivity, which seriously restricts its engineering application. This study aims to determine the optimal process parameters for preparing crack-free Ni60 alloy coatings on 316L stainless steel substrates to strengthen the surface of nonmagnetic drilling tools.MethodsLaser coaxial powder feeding technology was utilized to clad Ni60 alloy powder on the surface of 316L stainless steel. The process parameters, such as laser power, scanning speed, and powder feeding rate, were considered as influencing factors. First, orthogonal experiments of single-layer single-pass laser cladding were conducted. Sixteen sets of single-layer single-pass cladding layers were obtained, and penetration testing was employed to detect cracks in the cladding layers. An inverted metallographic microscope was then utilized to observe the microstructures of the cross-sections of the cladding layers, and a Vickers hardness tester was utilized to measure the microhardness of the cladding layers. The melting height, melting depth, and melting width of the 16 sets of single-layer single-pass cladding layers were measured to calculate the crack density, dilution rate, and forming coefficient. Some cladding layers with no cracks and a low dilution rate were selected from the 16 sets. Next, taking microhardness, dilution rate, and forming coefficient as quality indicators, a comprehensive weighted scoring method was proposed to select three sets of cladding layers with the highest scores. The process parameters of the selected three sets of single-layer single-pass cladding layers were then utilized to conduct single-layer multi-pass cladding tests with a 50% overlap rate. The microhardnesses and microstructures of the single-layer multi-pass cladding layers were measured. Based on the thickness, microstructure, and microhardness of the single-layer multi-channel cladding layers, the process parameters that met the requirements of the coatings for the nonmagnetic drilling tool considered were finally determined.Results and DiscussionsIn the results of the single-layer single-pass cladding experiments, crack defects were found in the cladding layers of A2, A3, A4, A7, A8, and A10. The laser energy analysis showed that their line energy and mass energy were low, which led to incomplete melting of the alloy powder and also caused the microstructures of the layers to be uneven. In addition, the cladding layers of A15 and A16 were also eliminated because their dilution rates were too high. The remaining eight sets of cladding layers, which exhibited no cracks or pores in their cross-sections, were selected for further analysis. The hardness of the Ni60 alloy coating ranged from 528 to 788 HV, while the hardness of the substrate ranged from 205 to 232 HV. Taking microhardness, dilution rate, and forming coefficient as quality evaluation indicators, with high hardness, low dilution rate, and high forming coefficient considered optimal, the comprehensive weighted scores of the selected eight sets of single-layer single-pass cladding layers were calculated. The three sets of cladding layers with the highest scores were A5, A9, and A1, and their process parameters were utilized to conduct single-layer multi-channel experiments. Therefore, three sets of single-layer multi-channel cladding layers, numbered G1, G2, and G3, were obtained. The crack penetration testing showed that there were no cracks in the cladding layers. The thicknesses of the G1, G2, and G3 cladding layers gradually increased due to the corresponding increases in laser power and powder feeding rate. The dilution rate of the G1 cladding layer remained between 17.8% and 20.7%, that of G2 remained between 15.3% and 18.9%, and that of G3 remained between 7.6% and 9.0%. The microhardness of the Ni60 alloy coating ranged from 638 to 882 HV, and the hardness of the substrate ranged from 218 to 273 HV. The microstructures of the G1 and G2 cladding layers exhibited typical rapid solidification characteristics. From the bonding zone to the surface of the cladding layers, the microstructures showed a transition from continuous planar crystals and dendritic crystals to equiaxed crystals. This illustrated that the Ni60 alloy powder formed a dense metallurgical bond with the 316L stainless steel substrate. However, no obvious and continuous planar crystal layer was found in the bonding zone of the G3 cladding layer, which was attributed to the low dilution rate and uneven temperature variation.ConclusionsThe Ni60 alloy coating of the G2 cladding layer meets the requirements of a 2.0～2.5 mm thickness and a 55～60 HRC hardness for the nonmagnetic drilling tool. When the dilution rate is approximately 15%～20%, the microstructure of the single-layer multi-channel cladding layer exhibits good formation without cracks or pores. The transverse microhardness of the single-layer multi-channel Ni60 alloy coatings ranges from 588 to 889 HV. At the middle width of the single-layer multi-channel cladding layer, the longitudinal microhardness of the Ni60 alloy coating ranges from 638 to 882 HV, while the longitudinal microhardness of the 316L substrate ranges from 218 to 273 HV. The microhardness of the Ni60 alloy coating is approximately four times that of the 316L substrate. The optimal process parameters, determined through experiments and analysis, are as follows: laser power of 1 600 W, scanning speed of 3 mm/s, powder feeding rate of 0.6 r/min, and overlap rate of 50%.关键词：nonmagnetic drillings;Ni60 alloy;comprehensive weighted scoring;process optimization490|874|0更新时间：2026-05-23
- 摘要：ObjectiveEquine therapy, also referred to as therapeutic riding or equine-assisted therapy, is a clinical methodology that promotes physical, psychological, and social functioning through the integration of horse handling and riding skills. It is generally overseen by a qualified therapist or equestrian instructor, and serves as a rehabilitation tool amalgamating equine and therapeutic techniques to alleviate conditions such as cerebral palsy and autism. Whilst equine therapy has demonstrated efficacy in rehabilitating particular conditions, its dissemination is impeded by several constraints and challenges. Furthermore, equine therapy presents a number of limitations and challenges. High expenses, specialised facilities, and the specificity of horses impede the implementation of the therapy on a broader scale. Furthermore, challenges related to individual variations and the requirement for specialised therapist training need to be addressed, alongside cost, resource, and training concerns, to ensure wider adoption of equine therapy. To promote its application, an alternative to conventional biological equine exercise rehabilitation therapy could be a horse-riding rehabilitation robot. Such a development could improve the accessibility and effectiveness of equine therapy on a broader scale. The horse saddle during various gaits involves four primary movements: up and down, forwards and backwards, left and right tilting, and forward and backward tilting. These movements are integral to understanding the saddle’s function. Clear conceptualization of these movements is essential for riding and safely using the horse saddle.MethodsTherefore, the robot horse mechanism must possess the four degrees of freedom mentioned earlier. The high load and stiffness requirements when accommodating a person have been taken into account in the design process. As a result, a 3-RPS parallel mechanism is selected as the primary component, capable of carrying out up-and-down movement, left-right tilt, and forward-backward tilt of the saddle. The sketch of the mechanism is demonstrated in Fig. The saddle’s forward-and-backward movement is achieved through one moving vice, while another facilitates the up-and-down and back-and-forth movements. To reduce load and inertia, the mobile vice is mounted on the parallel mechanism’s moving platform. Together, the parallel mechanism and mobile vice comprise a 3-RPS-P hybrid robot. The mechanism possesses excellent stiffness, high load-carrying capacity, and remarkable flexibility, fulfilling the requirements for the saddle centre’s movement during rehabilitation therapy and load carrying capacity during horse riding. Firstly, the robot’s kinematic model was established, followed by deriving the analytical solution for the inverse kinematics. The positive kinematics solution was then obtained by utilising Newton’s iterative computation method. The relationship between the robot’s operational space and the joint space velocity Jacobian was investigated. Additionally, the robot’s workspace was analysed while considering the restriction of motion, and a spatial image was plotted accordingly. Finally, using Lagrange’s method, the dynamics of the parallel mechanism were established. Next, an examination is conducted on the correlation between the motion of the mechanism and the force applied. The motion theories outlined above have been compared and analyzed through examples, and the results have confirmed their validity and accuracy. These theories have then been transferred into MATLAB code, and the robot end’s path and trajectory planning and design have been carried out.Results and DiscussionsA joint motion simulation of the robot utilizing the SolidWorks Motion module has also been conducted, demonstrating a consistent and smooth trajectory in line with the planning and design objectives. This simulation showcases the robot’s ability to successfully attain its set goals and objectives. The simulation is seamlessly executed and aligns with the planned and designed objectives, demonstrating the robot’s capability to accomplish the designated position-planning motion. Furthermore, it verifies the theoretical analysis outcomes. Finally, the experimental platform for the horse-riding rehabilitation robot was established in order to conduct motion experiments for position planning in motion simulation. The experimental results confirmed the rationality of the mechanism, attained the intended motion trajectory, and showcased rapid response of the control system. Due to the complexity of its calculations, the kinematics of the positive solution is time-consuming, taking 2~3 ms. However, as the display and monitoring meet usage requirements, this signifies that the hybrid horse rehabilitation robot possesses the necessary movement ability for equestrian therapy.ConclusionsThe locomotive behavior of horses in various gaits, including fast walking, running, and jumping, will be further examined through the study of the robot. To analyse the impact of varying movement gaits, amplitudes and speeds on rehabilitation therapy and optimise mechanism and motion control with input from equestrian therapists’ riding feedback and suggestions. Additionally, establish a real-time feedback system within the machine’s simulation of horse movement to monitor and adjust the robot's motion status. To assess the effectiveness of robotic horse rehabilitation therapy, the performance and recovery of the experimental group will be compared to that of the control group. Furthermore, safety and stability will be prioritized in the mechanism and motion control design to prevent falls and potential injuries to users during rehabilitation therapy.关键词：hybrid ride-on-horse rehabilitation robot;mechanism design;kinematics;workspace;trajectory planning;motion simulation380|617|0更新时间：2026-05-23
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Deep Learning Based 3D Visualization Health Condition Monitoring Method for Anchor Digging Machines AI导读
摘要：ObjectiveIn coal mining, anchor digging machines operate under harsh and complex conditions. They are subjected to high-intensity loads, resulting in frequent failures, and the challenge of effective health management becomes increasingly prominent. Therefore, it is crucial to monitor the operational status of anchor digging machines and ensure their reliable performance. This study integrates deep learning and 3D visualization technology, designs a comprehensive health monitoring system framework, and proposes a health monitoring method for anchor digging machines.MethodsBased on deep learning, a data-driven remaining useful life (RUL) prediction method was proposed for key components of anchor digging machines. A dual time-length transformer (DT) RUL prediction model incorporating a stacked denoising autoencoder (SDAE) was constructed (SDAE‒DT Net), and particle swarm optimization (PSO) was used for model hyperparameter optimization. The model possessed the structure of dual time-length encoding, which meant that the features of long-time sequences were retained and allowed efficient processing of tightly connected short-time series data. SDAE improved the model, which accurately predicted the RUL in the presence of significant noise interference in the dataset. Experimental validation was conducted using the actual production dataset sourced from the coal mine and the Intelligent Maintenance System (IMS) dataset. The results showed that the SDAE‒DT Net model achieved the highest accuracy and the best prediction performance. On this basis, a 3D visualization health condition monitoring method of the anchor digging machine with data interaction was proposed. The 3D model of the anchor digging machine and the coal mining geological model were constructed using 3D visualization modeling technology. Finally, combined with examples, the 3D visualization health condition monitoring system of the anchor digging machine was developed, which realized the data mapping between the integrated coal mining working face and the 3D visualization model and verified the correctness and feasibility of the method proposed in this study.Results and DiscussionsFor the performance validation experiments of the SDAE‒DT Net model, the sensitivity analysis experiments for PSO hyperparameter optimization showed that the best results were achieved when the population size and inertia factor were 40 and 0.5, respectively. The optimal hyperparameters were: the number of iterations was 239, the number of coder/decoder layers was [4,4], the number of training samples was 153, and the number of hidden neurons was 107. At this point, the PSO‒SDAE‒DT Net model reached the optimal value of each evaluation index in the training set as 0.157, 0.899, 0.192, and 0.087. The ablation experiments explored the effects of the improvements on the model through DT and SDAE. The results showed that the SDAE‒DT Net model was significantly more stable during the training process than the other three experimental sets due to its ability to capture deep features and suppress noise, with a loss of 0.087. Comparison experiments of the prediction results with commonly used models, such as BiGRU, LSTM, and BiLSTM, similarly demonstrated the superiority of the proposed method. Compared with multiple existing methods, experiments were conducted using the IMS dataset. The results showed that the SDAE‒DT Net model has an RMSE value of 0.056 and the best prediction error of 48.36 min, which was the best performance among the models compared. The prediction time of the proposed model was 32 seconds, which was greater than the SVM model's 28 seconds, but the RMSE value was less than 1.214, so both models have their advantages. As a result, the proposed model has the smallest prediction error and higher prediction accuracy. The developed three-dimensional visualization health monitoring system of the anchor digging machine can display real-time environmental data and the operating status of the digging work. In actual production, the real-time monitoring operation status of the anchor digging machine was selected from the system at a specific moment, and the normal value of the operation indices was compared to the actual value. The results showed that all indicators were within the normal range. The vibration signals of the cut-off boom bearing were collected online for prediction to verify the real-time RUL prediction effect of the SDAE‒DT Net model. The results showed that the RMSE value during real-time prediction was 0.098, and the time required was 36 seconds. The predicted RUL value of the 85th sample was 917 min, and the true value was 1 009 min, with a prediction error of 2.94%. The experimental results were close to the results of the historical data.ConclusionsThe designed health condition monitoring framework for anchor digging machines is capable of real-time and accurate monitoring. The constructed SDAE‒DT Net model effectively integrates features from sequences of varying time lengths within the data, enhancing the RUL prediction accuracy even under noise interference. Utilizing cloud data storage and processing, the developed three-dimensional visualized health condition monitoring system for anchor digging machines enables data interaction and real-time monitoring. The proposed method supports the monitoring of operating status and coal mining anomalies and can serve as a theoretical basis for the efficient operation and maintenance of coal mining equipment.关键词：Anchor digging machines;3D visualization;Health condition monitoring;remaining useful life prediction;Transformer model291|909|0更新时间：2026-05-23
MECHANICAL ENGINEERING
- 摘要：The cracking heat transfer process of hydrocarbon fuel in the cooling channel of the combustion chamber wall is a key issue in engine regenerative cooling technology. Currently, there is limited experimental research on the coupling mechanism of n-decane cracking and heat transfer under supercritical pressure in rectangular tubes. This study constructs an experimental apparatus for the heat transfer of n-decane pyrolysis at supercritical pressure. During the experiment, the n-decane in the SS304 stainless steel tube is heated to the desired outlet temperature through two stages of alternating current heating. The mass flow rate at the inlet varies by adjusting the setting of the constant flow pump. Different system pressures inside the heating tube are achieved by adjusting the back pressure valve. First, the effects of flow rate, temperature, and operating pressure on the heat transfer characteristics of n-decane cracking in a rectangular tube are investigated. Second, the sensitivity analysis method is applied to evaluate the degree of influence of flow rate and operating pressure on the conversion rate and gas production rate. The research results indicated that the gas yield and conversion of n-decane decrease with an increase in mass flow rate at the same outlet temperature. When the outlet temperature ranges from 823 to 923 K, the gas yield and conversion initially increase slowly, then increase significantly, and finally exhibit a reduced rate of increase. At the same outlet temperature, the gas yield and conversion of n-decane increase with rising pressure. When the outlet temperature is approximately 873 K, and the pressure increases from 3 to 4 MPa, the gas yield and conversion rise from 21% to 27% and from 38% to 45%, respectively. The sensitivity analysis showed that the system pressure has a positive impact on gas yield and conversion, whereas the mass flow rate has a negative impact on gas yield and conversion. These research findings provide theoretical and data support for the design of rectangular cooling channels.关键词：n-decane;pyrolysis reaction;heat transfer;rectangular tube;sensitivity analysis359|1025|0更新时间：2026-05-23
- 摘要：Aerosol particles released into the atmosphere in industrial production cause significant harm to the environment and human health, and it is necessary to use a series of dust removal equipment at the source of aerosol emissions to control them effectively. The dust removal mechanism of inertial collision is one of the main mechanisms used in dust removal equipment commonly applied in modern industrial production. When the particle size distribution characteristics of aerosol particles to be removed are determined, this mechanism can be directionally strengthened by continuously increasing the gas velocity to improve the removal rate of both large and small particles. However, this approach results in considerable resistance loss (gas path pressure drop), and the higher the gas velocity, the greater the resistance loss becomes. After fully understanding the structural characteristics of the impingement flow dust collector, the research group proposes the arrangement of a multi-layer impingement flow dust collector array to balance the contradictory relationship between particle removal rate and pressure drop. The impingement flow dust removal array consists of dust removal columns, specifically composed of several dust removal columns uniformly arranged in three-dimensional space based on certain rules, with spacing between columns to allow the passage of dust-bearing gas. The computational fluid dynamics (CFD) method is utilized to simulate the particle removal process of the array to obtain a relatively better arrangement of the equidistant impingement flow dust collection array for subsequent experiments. The aim is to obtain the particle removal rate and gas path pressure drop under different arrangement spacing through simulation. The smaller the dust column spacing, the higher the particle removal rate, but the gas path pressure drop also increases. Therefore, to balance this contradiction, a more comprehensive evaluation of removal rate and gas path pressure drop under different spacing is conducted by introducing a filter quality factor (Q factor) to determine a better arrangement of the impingement flow dust collection array. After evaluating the final numerical simulation results using the Q factor, the arrangement mode with equal spacing of 6 mm is optimal under a gas velocity of 1.5 m/s, commonly used in industrial dust removal. Based on the numerical simulation results, the research group designs and produces a physical model of a 6 mm equidistant dust removal array for experiments. Based on the above steps, further dust removal experiments are conducted at Re = 2 131~2 787 to obtain the trend of unit discharge particle removal rate of the 6 mm equidistant array with the Stk number. Finally, the empirical formula between the removal rate of unit discharge particles and the Stk number in the range of Stk = 5.2×10-4~1.0 is obtained using a numerical fitting method, and the applicability of this empirical formula is preliminarily verified by another set of removal experiments under different Re values. At present, in the actual process of industrial dust removal, not only the removal rate and energy consumption of the gas path are considered, but also the space occupied by the equipment is a critical factor. Therefore, to adapt to the wide particle size range of dust-containing gas while considering removal rate, energy consumption, and occupied space, the research group further develops a dust collection array with cascaded impingement flow arrangement based on the previous simulation and experimental results. The main feature of this dust removal array is the uneven spacing between unit rows formed by the dust removal columns. Specifically, along the direction of the dust-laden airflow, the spacing between the unit rows gradually decreases, which narrows the flow channel, increases gas velocity between arrays, and strengthens the inertial collision mechanism, improving the overall removal rate of graded particle sizes. After preliminary optimization and design, the cascaded impingement flow dust collection array is tested in a dust collection experiment. Experimental results showed that, compared to the impingement flow dust collection array with equal spacing of 6 mm, the particle removal rate of the cascaded array is significantly improved. Taking 1 μm particles at a gas velocity of 1.5 m/s as an example, the removal rate of the cascaded impingement flow dust collection array with 15 unit rows increases by 126% compared to the 6 mm equispaced array with the same number of rows, and the correlation between removal rate and Stk number aligns with the predicted value of the previously mentioned empirical formula. The applicability of the empirical formula is further confirmed. Accordingly, the research group successively designs the equidistant and cascaded impingement flow dust removal arrays and derives the empirical formula of the removal rate through experiments. This work provides guidance for further development of dust removal arrays.关键词：impactor;inertial collision mechanism;dust removal array;aerosol;process intensification377|685|0更新时间：2026-05-23
CHEMICAL ENGINEERING AND TECHNOLOGY
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