Browse Topic: Optimization

Items (8,107)

Short-Term Load Forecasting of Sustainable Power Systems Based on Newton–Raphson-Based Optimizer–Extreme Gradient Boosting under Extreme Weather Events

13-07-02-0008

9/17/2026

With continuous advancements in load-side resources such as distributed photovoltaic systems, electric vehicles, and virtual power plants, the low-carbon and sustainable development attributes of power systems have been significantly enhanced. Meanwhile, the coupling intensity between sustainable power systems and meteorological conditions has been further consolidated. Considerable impacts are exerted by weather variations, particularly extreme weather events, on the dispatching and operation of sustainable power systems. Accurate load forecasting is critical for enabling sustainable power systems operators to optimize power generation strategy, ensuring supply stability and resilience against extreme weather-induced disruptions. However, the intrinsic non-stationarity and volatility of extreme weather events present significant challenges to conventional forecasting approaches. Herein, we introduce a hybrid algorithm integrating Newton–Raphson-based optimizer (NRBO) with extreme gradient boosting (XGBoost) to enhance short-term load predictions under such conditions. The model uses optimally selected meteorological and load features as inputs, while NRBO systematically tunes XGBoost’s hyper-parameters to maximize performance. Evaluated on an Irish dataset, the proposed framework is quantitatively compared against five baseline models, including traditional decision trees and neural networks. The case studies show that the mean absolute percentage error (MAPE) of the proposed model is 2.57%, which is the lowest among these decision tree and neural network algorithms.

Wang, Yi, Zhou, Jian, Wu, Gang, Ma, Tiannan, Ma, Ruiguang, He, Chuan, Zhu, Huixian

Predicting Wear of NAO Brake Pad Using Scaled-Down FMVSS 135 Testing and Machine Learning

2026-01-0808

9/14/2026

Brake pad wear is a major and growing source of non-exhaust particulate emissions, projected to reach 1.3 million tons annually by 2030 and contributing up to roughly 55% by mass of non-exhaust traffic-related PM10 in urban environments, underscoring the need for improved durability and material optimization. This study investigates a three-stage eXtreme Gradient Boosting (XGBoost) ensemble paired with a residual Fully Connected Neural Network (FCNN) corrector to predict brake pad wear rate and support formulation optimization. Experiments used a simplified FMVSS 135 protocol on a Universal Mechanical Tester (UMT) simulating realistic braking across eight friction regimes. Wear rate was the sole machine-learning prediction target, while coefficient of friction (CoF) was retained as an input feature rather than a target. Despite a limited but high-quality 280-cycle dataset, regime-aware stratified splitting, sample reweighting, and hyperparameter optimization enabled robust generalization. The three-stage XGBoost ensemble with residual FCNN correction achieved a global held-out test R2 of 0.976 for wear rate prediction. A Taguchi L8 design of experiments defined the brake pad compositions, reducing experimental time and material consumption compared to conventional approaches. The framework demonstrated strong agreement between measurements and predictions for the dominant low-severity regime, while per-regime analysis identified the high-severity minority regimes as the priority for additional data collection, since within-regime R2 remains negative for every regime given current sample sizes. A sequence-aware mean absolute scaled error (MASE) analysis further shows that, despite the high global R2, none of the four pipeline stages currently outperforms a naive one-cycle persistence forecast on absolute error, a distinction reported here for transparency. The scalable architecture enables straightforward integration of additional material and process parameters, supporting iterative brake formulation development in industrial settings and, by reducing empirical testing requirements, sustainable brake material development with reduced replacement frequency and associated emissions.

Katakam, Abhishek, Eslamiat, Hossein, Kancharla, Sai Krishna, Filip, Peter

Current Situation of Ship Navigation and Research on the Route Reform Scheme in Typical Tributary-Confluence Waters of the Lower Yangtze River

2026-99-1572

9/11/2026

The thalweg at the outlet of the Yuxikou Waterway transitions from right to left, forming a 90-degree bend. It then merges with the Xihua Waterway after passing Xiliang Mountain, creating a main-branch confluence water area. Taking a typical main-branch confluence water area in the lower reaches of the Yangtze River as the research object, this paper reflects the current navigation status and existing problems of ships in the area through the analysis of ship traffic flow. It classifies the risk levels of passing ships, proposes suggestions for route reform and optimization, and uses a model to verify the probability of collision accidents in the area after the implementation of the round-island navigation method, providing a reference for the navigation safety of passing ships.

Liu, Ka, Xu, Yerong

Study on Nonlinear Dynamic Characteristics of High-Speed Train Braking Systems

2026-99-1141

9/11/2026

To address the oversimplification in prior brake system models, this study develops a 10-degree-of-freedom (DOF) dynamic model of a disc brake system. A control-variable approach is employed to numerically simulate the effects of braking force, rotational inertia, brake pad tangential stiffness, suspension stiffness, and damping. The vibration responses under different braking conditions and in the presence of multi-parameter coupling are analyzed through bifurcation diagrams, phase trajectories, and Poincaré sections. The main findings indicate: (1) Increasing braking force induces a transition from period-1 to higher-order periodic motions (e.g., period-6), accompanied by significant vibration amplification; (2) Enhanced brake pad tangential stiffness suppresses vibration amplitude but extends the sticking phase duration; (3) Exceeding a critical primary suspension stiffness threshold triggers system instability. These results suggest that structural optimization of suspensions and reasonable selection of brake pad support stiffness are important measures to prevent stick-slip vibrations.

Li, Songge, Wang, Jingyue

Optimization of Order Picking in an AMR-Assisted Picker-to-Parts System

2026-99-1567

9/11/2026

With global retail sales expanding and same-day delivery demand on the rise, efficient order picking operations in warehouses have become critical to success. To improve order picking processes, warehouse managers increasingly rely on autonomous mobile robots (AMRs), which improve the performance of traditional picker-to-parts systems. This paper investigates an AMR-assisted picker-to-parts system in which a set of customer orders must be fulfilled. The orders are first batched, and the resulting batches are assigned to individual pickers. Each picker works in a batch-by-batch manner, manually retrieving items from picking aisles and handing over the completed batch to an AMR waiting at the cross aisle. After receiving a full batch, the AMR transports it to the designated depot before returning to serve the next batch. The objective is the minimization of the total tardiness of all orders. The problem is formulated as a mixed-integer programming (MIP) model, and several effective heuristic algorithms are developed. Extensive computational experiments are conducted to evaluate the performance of the proposed algorithms and compare them with a commercial MIP solver.

Jin, Bo, Peng, Jianxin

Integration of Configuration Management into the RFLP Process in the Development of Civil Aircraft

2026-99-1417

9/11/2026

In the forward development process of civil aircraft, traditional configuration management, which primarily focuses on the physical implementation end, often leads to inconsistencies between functions, requirements, design configurations, and physical realizations. This study optimized the principles of configuration item identification by refining the logic, timing, and sequence for identifying different types of configuration items. It proposed a product structure centered on the Logical Identification Number (LIN), which explicitly represents the mapping relationships from functional to physical elements. Additionally, the research established the logic for change propagation and validity calculation. Using an air-conditioning refrigeration system as a case study, the model was validated, demonstrating its advantages for improving the efficiency of change-impact analysis, enhancing compliance verification, and ensuring scenario reproducibility.

Xie, Xiang, Meng, Xu, Zhang, Xinyuan, Wu, Binbin

Research on Passenger Flow Prediction of Urban Rail Transit Based on Grey Improvement Model

2026-99-1564

9/11/2026

In recent years, China's urban rail transit sector has undergone rapid expansion, with passenger demand consistently increasing. Accurate passenger flow forecasting is essential for ensuring efficient and safe metro operations. This paper takes Nantong Metro Line 1 as a case study and applies an optimized forecasting approach that integrates a grey metabolism model with the Holt double-parameter exponential smoothing method. Based on an analysis of Automated Fare Collection (AFC) data from March 2023 to February 2024, passenger flow on this line demonstrates a clear linear growth trend, which aligns well with the assumptions of the grey metabolism model. The results indicate that the optimized grey metabolism model not only significantly enhances prediction accuracy but also greatly reduces the variance ratio, demonstrating high reliability in forecasting outcomes. This improved methodology provides a more robust tool for metro operators in planning services, managing capacity, and optimizing resource allocation.

Fan, Fan, Zhao, Zeheng, Zhang, Jin, Ma, Junhao, Qian, Beiyue

Research on the Application of Multi-Source Data in Bus Route Network Optimization

2026-99-1566

9/11/2026

This research aims to optimize the bus route network in Shiyan City using bus Origin-Destination (OD) data. By integrating multi-source data, including GDP, population, and bus OD big data from 2018 to 2022, short-term and long-term indicators are forecasted by time-series methods. Shiyan city is divided into 77 Traffic Analysis Zones (TAZs) considering its mountainous terrain, population-industry distribution, and urban planning. A conventional four-stage traffic demand model is applied, calibrated with bus OD data in 2021. The investigation reveals peak-hour bus passenger travel demand of 29,700 short-term and 31,800 long-term person-trips in the city center and key corridors. Bus passenger travel forms a four-vertical and five-horizontal layout in the short term, evolving to a five-vertical, five-horizontal, and two wings pattern in the long term with eastward urban expansion. Accordingly, an optimized and upgraded bus route improvement strategy is devised. In the short term, there are seventy existing bus routes that are adjusted, creating a five-layer bus route network with diverse functions. Long-term plans involve optimizing twenty bus routes and adding eight new routes to align with urban development. This research not only aids an integrated bus route network optimization framework using bus OD data in a time-consuming way, but also provides a sample of bus route network adjustment for a typical mountainous city.

Ye, Qian, Chang, Sheng, Shen, Yucan, Li, Tanfeng, Tian, He, Tian, Shimo, Cen, Jian

Vehicle Multi-Target Tracking Algorithm Based on Improved CenterTrack

2026-99-1102

9/11/2026

With the rapid increase in the number of vehicles worldwide in recent years, multi-vehicle tracking has become a critical and challenging research topic in smart transportation. Although many researchers have constructed classical multi-object tracking (MOT) models, these models often lose trajectories of objects in challenging traffic environments with frequent occlusions and high object density. This significantly hinders the practical deployment of such tracking systems. In order to improve tracking robustness and accuracy when faced with these challenges, we propose a new multi-vehicle tracking algorithm built upon the CenterTrack framework. The core of our work lies in three key improvements. Each overcomes a distinct weakness in existing approaches, and together they work to improve performance. First, we use the Wise Intersection over Union (WIoU) loss to guide the model optimization and reduce the impact of label noise during training, which results in better convergence. Second, we apply an attention mechanism to reduce feature interference caused by multiple inputs (current frame, previous frame, and heatmap) of the model. Third, we employ the Sigmoid Linear Unit (SiLU) in the backbone network to further improve nonlinear feature representation. We evaluate our algorithm on the standard KITTI multi-object tracking benchmark. Experimental results show that our method achieves a Multi-Object Tracking Accuracy (MOTA) of 65.94% and an Identification F1 (IDF1) of 84.01%. This represents an improvement of 2.93% in MOTA and 2.36% in IDF1 over the baseline method. The results demonstrate not only the effectiveness of our method but also its practical usefulness and robustness in challenging road environments.

Zhang, Hao, Huai, Chongfei, Wang, Ziming, Zhao, Zexuan, Ye, Shuai, Du, Xiaobing, Sun, Shenghai

An Improved Multi-Object Vehicle Detection Algorithm Based on YOLOv11s

2026-99-1129

9/11/2026

For object detection in complex road situations, such as inadequate detection performance and difficulties caused by vehicle occlusion and cluttered environments, this paper pursues a YOLOv11s-based object detection framework. The algorithm successfully designed a novel PEConv module. This module integrates a partial convolutional network with an efficient multi-head attention mechanism. Through a Split operation, the input image is divided into locally enhanced channels and original channels. The locally enhanced channels undergo partial convolution and feature weight allocation via the efficient multi- head attention mechanism for feature extraction. Finally, these channels are fused with the original channels before undergoing convolution. This approach preserves the original features while minimising feature loss caused by the series of operations. Therefore, the PEConv module is based on a partially convolutional network and efficient multi-head attention. It improves the detection ability by precisely giving more weight to small objects and occluded parts with augmented partial channel attention and original channel fusion. This study further enhances the model’s detection precision and improves its performance in addressing small target vehicles and severe occlusion issues by refining and upgrading the original C3K2 architecture. The LSBlock is integrated into the original model’s bottleneck structure, replacing the traditional 3x3 convolution to create the C3K2 - LSBlock module. Experimental results show that on the UA - DETRAC dataset, compared with the original YOLOv11s, the optimized YOLOv11s has improved the original mAP @ 50 by 3.4%, reaching 61.3%, and improved the original mAP @ 50: 95 by 2%, which verifies the correctness of it.

Chen, Yulin, Wang, Yini, Wang, Jianwei, Zhang, Xin

Structural Design and Stability Research of a Two-DOF Transformable Wheel for Enhanced Obstacle-Crossing Performance on Complex Terrain

2026-99-1130

9/11/2026

Under the constraints of conventional chassis layouts, traditional wheeled vehicles struggle to maintain stable obstacle-crossing performance on complex terrain. This study aims to enhance both the obstacle-crossing capability and stability of such vehicles. First, a transformable wheel capable of varying its effective radius and actively adjusting the wheel–ground contact configuration is designed, and its degrees of freedom are analyzed using screw theory. Next, based on screw theory and Lie group theory, position-level and velocity-level kinematic models of the transformable wheel are established, and system-level performance indices—including workspace, singular configurations, and force-transmission characteristics—are formulated. Finally, taking these performance indices as optimization objectives, a constrained optimization model of the mechanism’s geometric parameters is constructed, from which an optimal dimension set for the transformable wheel is obtained. The results show that the optimized transformable wheel has significantly improved minimum singularity and dexterity. The designed transformable wheel can achieve changes in wheel radius and wheel rim inclination angle, improving the vehicle's passability in complex terrain.

Lu, Shichuang, Wang, Tie

A Method for Resolving Two-Vehicle Conflicts at Unsignalized Intersections Based on Adaptive TTC and Traffic Rules

2026-99-1140

9/11/2026

To address the challenges of unsignalized intersections—where the absence of traffic signals leads to high computational complexity and poor real-time performance in existing cooperative methods—this paper proposes a lightweight, real-time conflict resolution strategy for two-vehicle scenarios. First, a traffic rule matrix is constructed based on China’s Road Traffic Safety Law Implementation Regulations, digitizing right-of-way priorities to achieve millisecond-level conflict detection. Second, we introduce an adaptive TTC threshold function to dynamically adjust the warning time between vehicles based on the vehicle speed. Finally, based on the type and priority of the conflict, the speed adjustment value is obtained through the parsing method, enabling real-time calculation of the deceleration amount without the need for iterative optimization. Simulation results in SUMO demonstrate that, compared to the default uncoordinated mode, the strategy reduces the delay in converging conflicts from 4.87 s to 2.87ds and cuts the deceleration frequency by 37.5%. For crossing conflicts, high-priority vehicle deceleration events drop from 8 to 1, and speed standard deviation decreases from 1.27 m/s to 0.78dm/s. This method reduces the computational load while ensuring security, providing a practical solution for cooperative driving at unsignalized intersections in the V2X environment.

Wang, Xinxin, Zhang, Xin

Analysis of Traffic Capacity at the Intersection of Xiyou Road and Qianshan Road in Hefei City

2026-99-1551

9/11/2026

With the advancement of urbanization and the popularization of automobiles, the traffic load on urban roads is becoming increasingly heavy, resulting in many traffic problems. Road intersections serve as crucial linchpins in the urban transportation grid, wielding considerable influence over the overall traffic capacity of a city’s road network. Enhancing intersection efficiency and cutting down on delays stand at the heart of tackling urban congestion challenges. This study zeroes in on the crossroads where Xiyou Road intersects with Qianshan Road in Hefei City. Employing hands-on observation and photographic documentation, the research examines traffic flow and signal configurations during the peak demand period (7:30-8:30). The analysis evaluates traffic capacity and utilization rates for through, left-turn, and right-turn lanes at this intersection. Findings reveal that the right-turn lane at the southern entrance and the left-turn lanes at both northern and eastern entries show relatively low saturation levels, while the saturation of other lanes is greater than or close to 1. Therefore, this intersection does not have sufficient capacity. The actual traffic operation at the intersection, particularly during peak traffic times, is analyzed to identify the reasons for congestion Finally, improvement plans for optimizing traffic organization at intersections are proposed, such as optimizing signal timing schemes and transforming traffic channelization. Simulation analysis using VISSIM shows a 9.34% reduction in total intersection parking time, a 34.26% decrease in average queue length, and an 8.12% reduction in average vehicle delay. These results provide a reference for future optimization work, including intersection signal timing and channelization.

Wang, Yanmei, Wang, Chen, Fu, Ziyue, Meng, Xianglong

Numerical Calculation of The Ice-Breaking Resistance of the Icebreaker

2026-99-1517

9/11/2026

This study investigates the governing characteristics of ice resistance encountered by icebreakers operating in multi-year ice regions, with particular emphasis on the effects of bow truncation length, vessel speed, and ice thickness. A numerical simulation framework was developed using the finite element platform LS-PrePost to reproduce ice bending, failure, and ship–ice interaction throughout the icebreaking process. The numerical predictions were subsequently validated against physical model test data. The results indicate that ice resistance exhibits an increasing trend as the bow truncation length, navigation speed, and ice thickness increase. The ice resistance of different bow truncation lengths in the multi-year ice area is different. By truncating the model ship at different positions from the bow and analyzing the ratio of the ice resistance of the truncated models to that of the full-scale model, researchers can better understand the effects of bow size. This can provide a theoretical basis for conducting ice resistance tests with truncated model ships in a limited-scale ice water tank, and has certain practical value for the design and optimization of the icebreaker’s hull lines.

Liu, Yanwei, Zhang, Xiufeng, Yu, Yingjie, Wang, Lucai, Zhao, Weihang

Safety Assessment Model for Airborne Time-Sensitive Networking Based on Analytic Hierarchy Process

2026-99-1414

9/11/2026

With the growing demand for high real-time performance and high reliability in airborne networks, Time-Sensitive Networking (TSN) has been widely adopted as a core technical basis for deterministic Ethernet for next-generation avionics systems. This paper proposes an AHP-based safety assessment model for airborne TSN, introducing a hybrid evaluation strategy that integrates both subjective and objective factors. By constructing a comprehensive evaluation index system, the model quantifies the weights of traffic attributes—including time sensitivity, priority level, and bandwidth guarantee requirements—and combines them with the degree centrality of network nodes to achieve a holistic assessment of TSN safety. The proposed model not only provides theoretical support for the safety-oriented design optimization of avionics systems but also offers practical guidance for the airworthiness verification of airborne networks. Feasibility and effectiveness are verified by applying the proposed method to a representative case scenario. Moreover, the model’s scalability supports its application in more complex network environments, meeting the broader assessment needs of airborne TSN safety.

Wang, Penghui, Mei, Yanan, Fu, Jinhua

Study on Shaking Table Model Test of Seismic Dynamic Response of Loess Multi-Arch Tunnels

2026-99-1584

9/11/2026

Taking the Nieye Multi-Arch Tunnel in Zhuoni County as the engineering background, this study systematically explores the seismic dynamic response characteristics of loess multi-arch tunnels through shaking table model tests. The test results show that: (1) The strain distribution of the surrounding rock is significantly different. Under a peak acceleration of 0.6 g, the maximum strain in the tunnel portal section is concentrated on the right side, which is related to the incident direction of seismic waves and the stress concentration at the bottom of the central wall; the maximum strain in the tunnel body section is located on the left side, affected by the propagation characteristics of seismic waves, burial depth, and unsymmetrical pressure. (2) The acceleration amplification factors in the Z and ZX directions show nonlinear changes. Under bidirectional excitation, the Wenchuan wave-ZX combination exhibits the strongest response. The variation trend of acceleration at the soil-rock interface varies with wave types, and the slope damage undergoes three stages: elastic stage, elastoplastic stage, and plastic damage stage. (3) The ratio ω of tunnel burial depth to central wall thickness is positively correlated with the strains at key positions. For the seismic design of loess multi-arch tunnels, special attention should be paid to sensitive areas such as the bottom of the central wall and the left side of the tunnel body. It is suggested to improve the structural seismic performance by optimizing the lining reinforcement and adapting to regional seismic wave types. The research conclusions provide a reference for the seismic design of such tunnels under complex geological conditions.

Han, Tao, Cao, Xiaoping, Zhang, Shulin, Yang, Zibin

Evaluation Method for Driving Safety on Highway Successive Curves

2026-99-1568

9/11/2026

To evaluate the driving safety performance of continuous curves, this study developed a safety assessment model using a human-computer interaction simulation platform. First, three indicators are selected, including the driver’s heart rate variability, the rate of change in steering wheel angle, and trajectory lateral deviation, which together form a driving safety evaluation indicator system. Secondly, through significance testing and range analysis. Through analysis, four key curve-related elements are identified as having a notable influence on the overall evaluation indicators. A global optimization algorithm using multivariate nonlinear regression is then applied to establish the driving safety model. Finally, taking a dual four-lane highway in Sichuan province as an example, the safety of the successive curve in the project is evaluated. Empirical results show that when the intermediate straight line section H ≤ 4.23, driving is hazardous; 4.23 < H ≤ 4.46, driving is relatively hazardous; 4.46 < H ≤ 4.78, driving is relatively safe; H > 4.78, driving is safe. For oval-shaped curve segments, when H ≤ 4.53, driving is hazardous; 4.53 < H ≤ 5.32, driving is relatively hazardous; 5.32 < H ≤ 5.86, driving is relatively safe; H > 5.86, driving is safe. Through this method, the driving safety of successive curves can be effectively evaluated, particularly with a focus on driver comfort and safety. This provides valuable references for assessing driving risks associated with different combinations of curve elements.

Huang, Yongheng, Zhang, Ruizheng, Sun, Chao, Zeng, Xinjie, Zheng, Liwen

Research on Interference Management of Shared Collection and Transportation Vehicle Scheduling of Bulky Garbage with Order Changes

2026-99-1519

9/11/2026

This study presents a shared vehicle scheduling model designed to tackle scheduling conflicts arising from changes in orders for bulky waste collection and transportation. The model accounts for five types of interference events: alterations in the original order location, modifications to the time window, changes in waste size, the inclusion of new orders, and order cancellations. The goal of the model is to reduce variations in the frequency of collection and transportation, minimize costs, and meet the three requirements of three-dimensional loading for shared trucks, as well as satisfy user time windows. To solve this complex combinatorial optimization problem, the sparrow search algorithm is employed. Numerical studies indicate that the proposed method outperforms the genetic simulated annealing algorithm in objective function value and computational efficiency under the five interference scenarios. These results also confirm the model’s efficacy.

Xu, Chen, Ma, Huimin

Research on Heavy-Haul Train Operation Adjustment Considering the Degree of Chaos in Train Timetable

2026-99-1522

9/11/2026

Heavy-haul railway development is as important a strategic direction for China’s railway sector as high-speed railway development. With the continuous expansion of heavy-haul railway operational mileage and the growing transportation demand, the complexity of operational adjustment in heavy-haul railways continues to escalate. The operational adjustment for heavy-haul trains subjected to speed restrictions following maintenance windows, aimed at maximizing the restoration of timetable regularity and guaranteeing freight volume, constitutes a critical and urgent research problem. Grounding on the operational principle of heavy-haul railways that prioritizes freight volume preservation over strict punctuality, this paper proposes a rescheduling model that incorporates the timetable disruption level. By adopting the order entropy theory, the model is formulated to minimize the total system disruption level and freight time cost, thereby framing the rescheduling problem as an order entropy optimization problem. The train disruption level is a metric that quantifies the perturbation intensity of a rescheduled timetable relative to the original operational plan within a given railway section. By initializing the entropy value of the pristine operational order to zero, any subsequent entropy variation directly facilitates a systematic investigation into the evolution of train operational order. Effective timetable adjustment strategies are subsequently derived, contingent upon the available buffer time and freight volume constraints. Guided by actual operational timetables and sectional line characteristics, this research designs a case study. The Gurobi solver is employed to obtain a rescheduled heavy-haul train timetable that successfully restores the original freight volume. The proposed methodology contributes to the enrichment of railway transportation organization theory and provides robust decision-making support for the strategic deployment of heavy-haul train services.

Fu, Lu, Lin, Li, Xu, Shichao, Ji, Guanggang, Li, Zheng

Optimizing Dispatch Frequency of Feeder Buses for Integration

2026-99-1574

9/11/2026

In the context of urban multi-modal transportation systems, the optimization of the integration between urban rail transit and feeder bus services remains a critical challenge for improving service quality and operational efficiency. The present study investigates the frequency optimization of a dedicated feeder bus line during the morning peak period, considering heterogeneous passenger arrival patterns from both random street arrivals and scheduled rail-to-bus transfers. A bi-objective non-linear programming model is proposed to minimize total passenger travel costs and operating costs for the bus system. The model incorporates heterogeneous passenger arrivals at stops, ensuring a realistic representation of feeder line usage. It also distinguishes between transfer and non-transfer passengers, who have different perceived waiting costs derived from queuing and scheduling principles. To evaluate the model, numerical experiments based on simulations are conducted under varying metro transfer intensities. These scenarios are created by applying scaling factors to the original station-level arrival data to approximate different levels of rail-to-bus demand propagation. Results demonstrate that Higher transfer intensity leads to shorter optimal dispatch intervals and a marginal increase in total operating cost, reflecting the additional service pressure from metro-induced demand. The framework provides flexible control through weighting parameters and can guide transit agencies in balancing service quality with cost-efficiency under different demand profiles.

Guo, Xiao, Zhang, Jing

Real-time Vehicle Speed Detection Based on YOLOv11 and DeepSORT

2026-99-1595

9/11/2026

The technology of real-time and effective vehicle speed detection is considered a key technology to improve traffic monitoring efficiency and traffic safety management grade. To address the limitations of traditional speed detection schemes—including reliance on dedicated hardware, poor environmental adaptability, and high construction and maintenance costs—this paper proposes a r10eal-time vehicle speed detection system based on YOLOv11 and the DeepSORT algorithm. The proposed system uses the YOLOv11 target detection algorithm as its primary model. DeepSORT multi-target tracking technology is integrated to enhance tracking performance. Speed measurement is implemented using a virtual detection line. This approach enables accurate vehicle detection, continuous tracking, and real-time speed measurement within video frames. Through the experiments, the result shows that the improved YOLOv11n model reaches mAP@0.5 of 0.982 and a recall rate of 0.956 in the test set, higher than the YOLOv8n and YOLOv5s models. The speed detection error can be restricted to 3 km/h, satisfying the real-time detection need. There is no need for road surface modification, and the detection system has a flexible layout, providing a dynamic basis for traffic law enforcement and traffic data support for road construction and traffic control optimization.

Jin, Guowei, Ma, Wenlong, Jiang, Dali, Li, Nan

Impact of Transient Driving Characteristics on Bench-to-Road Emission Consistency of Light-Duty Vehicles

2026-99-1573

9/11/2026

Qiao, Jiajun, Jin, Zhenhua, Huang, Qi, Li, Guohui, Zhang, Xinguo

Study on Rapid Formation Generation Method for Multi-UAV Swarms

2026-99-1421

9/11/2026

This paper presents a generalizable geometric framework for rapid on-demand generation of multi-UAV formations with arbitrary 2D geometries and user-specified scalable scales. First, vertices, edge intersections and edges are extracted from a user-defined formation template to enable parametric description of both simple and composite formation geometries. Second, boundary interpolation, edge expansion and recursive internal expansion are integrated to synthesize hierarchical multi-layer UAV deployment point sets under a controllable expansion ratio. Third, a geometric distortion metric is proposed to optimize UAV node indexing and formation reconstruction while preserving inter-node topological consistency. Algorithmic derivations, complexity analysis and simulation assumptions are further elaborated. Simulation results verify that the proposed method preserves geometric fidelity of target formations while delivering superior scalability and spatial coverage, rendering it well-suited for emergency transport, aerial surveying and low-altitude cooperative missions in dense urban environments.

Fu, Mingyi, Zeng, Guoqi, Gu, XinZhu, Wang, Jia

Experimental Study on Handling Stability of an 8×4 Heavy-Duty Truck

2026-99-1122

9/11/2026

To analyze the handling stability of an 8×4 heavy-duty truck, a multi- body dynamics model of the heavy truck was established in ADAMS. Simulation tests for minimum turning radius, double lane change, steering wheel step input, and steady-state returnability were conducted on this model. Analysis of the simulation and experimental results revealed that, except for the significant discrepancy between the rigid-flex coupling model simulation results and the actual values in the returnability experiment, other experimental results were relatively close to the simulation data, indicating that the established vehicle model has high accuracy. It can provide a basis for the subsequent optimization design of this vehicle type.

He, Wenjian, Dong, Fulong

Research on Torque Allocation Control of Multi-Articulated Vehicle

2026-99-1123

9/11/2026

The multi-articulated vehicle uses distributed drive mode. Due to its large degree of freedom of movement and the large number of driving shafts, different torque distribution methods affect the operational stability of the vehicle, how to coordinate and distribute the torque of each driving motor has become an urgent problem to be solved. To improve drive stability of the multi-articulated vehicles, propose a layered torque allocation control strategy. The upper-layer sliding mode controller determines the required additional yaw moments of each car body based on the linear reference model, the controller is characterized by swift response and a strong ability to resist interference. The lower-level allocation module comprehensively considers the torque output limitations of the electric hub motors, the prevailing road adhesion state, and the corrective yaw moment constraints given by the upper layer, and constructs an optimization objective function centered on the uniformity and stability of tire load. The optimal distribution of driving forces for each wheel is completed by solving this function dynamically. To validate the strategy's effectiveness, a vehicle dynamics model is built in the multi-body dynamics software ADAMS/View. Using a joint simulation framework integrating ADAMS/View and MATLAB®/Simulink, the effect of the layered control strategy is evaluated in comparative simulation with uncontrolled situation under U-turn and single lane change conditions. The simulation outcomes demonstrate that, compared to uncontrolled situation, the yaw rate deviation of each car body under the torque layered control are significantly reduced, and the adhesion utilization rate of tire is also effectively controlled, thereby the driving stability is improved.

An, Guanbo, Zhang, Liwei

Research on a Brake Energy Recovery Strategy Based on Improved ANFIS

2026-99-1134

9/11/2026

This paper addresses the issue of regenerative braking energy recovery in new energy vehicles and designs and optimizes a braking force distribution strategy. The strategy uses an ANFIS controller to dynamically optimize the proportion of front-axle regenerative braking force. The introduction of a pruning algorithm reduces computational complexity, thereby enabling a significant increase in mileage while maintaining stable driving performance. Co- simulations integrating Simulink and AVL Cruise, alongside Hardware-in-the-Loop (HiL) tests, the proof is that this strategy can still maintain excellent stability under different braking intensities. Moreover, it exhibits significantly higher energy recovery efficiency compared to benchmark strategies, while its effectiveness and real- time performance are successfully validated.

Lin, Hui, Zhao, Xuezhan, Tian, Jiahao

An Improved Genetic Algorithm for Multimodal Hinterland Empty Container Repositioning Considering Demurrage and Detention charges

2026-99-1527

9/11/2026

The imbalance of global trade exacerbates the mismatch between supply and demand of empty containers, requiring rapid repositioning from import to export regions, so empty container repositioning has long been a focus of research. Compared to maritime repositioning, hinterland empty container repositioning is more complex because it occurs over a sophisticated multimodal transport network. Rail and inland waterways typically offer high capacity at lower cost, and hinterland container operators often consolidate containers and move them in batches to achieve economies of scale. In addition, demurrage and detention (D&D) charges, imposed on operators for delayed container returns, have remained high in recent years. Traditional hinterland empty container repositioning approaches that focus solely on transportation costs often overlook these time-related penalties, leading to higher total repositioning costs. To address this, we first develop a generic hinterland empty container repositioning optimization model that integrates both transportation costs and demurrage and detention charges while capturing batch-based dispatching characteristics observed in practice. Second, due to the model’s non-convex and combinatorial nature, traditional solvers struggle to provide efficient solutions. We further develop an improved genetic algorithm (GA) to solve this non-convex MINLP problem. The results of numerical experiments showcase the benign performance of our improved GA. Finally, we conduct a real-world case study based on a 2025 operation in China. The results demonstrate that minimizing transportation costs alone results in higher total repositioning expenses, while jointly optimizing transportation and D&D costs leads to more balanced and cost-effective repositioning strategies. This highlights the practical necessity of incorporating D&D considerations into HECR decision.

Yu, Mingzhu, Yang, Haoran, Zhang, Lingge

A Maritime Occluded Ship Detection and Tracking Method Based on Improved YOLOv8 Fused with AIS Trajectory

2026-99-1549

9/11/2026

Typical maritime monitoring scenarios are usually constrained by factors such as multi-scale ship density, frequent motion overlap, and limited viewing angle of shore-based cameras. These challenges often lead to trajectory interruptions and identity mismatches in target detection and multi-target tracking tasks. In order to solve these problems, this study proposes a ship occlusion detection and tracking method based on the improved YOLOv8 model and further integrates an automatic identification system (AIS) trajectory reasoning. The method builds a unified perception framework with enhanced detection architecture, multi-source data fusion, and behavioral reasoning capabilities. First, in the target detection module, the improved SEConv structure is introduced into the YOLOv8 trunk network to address challenges caused by small-scale variations and severe occlusion in maritime scenes. The ReLU activation function in SEConv is replaced by the Swish activation function to enhance the nonlinear feature representation. In addition, the optimized SEConv is embedded in the C2f structure, and the convolutional block attention module (CBAM) attention mechanism is introduced to enhance the sensitivity of the model to the occlusion area. Next, for multi-target tracking, ByteTrack is used as the basic tracking framework. AIS trajectory data is introduced as auxiliary input to compensate for trajectory losses caused by occlusion. Finally, experimental results on the SeaShips public dataset and the self-built occlusion reference dataset show that the improved YOLOv8 detector achieves stable mAP gains in mild, moderate, and severe occlusion scenarios. The AIS enhanced tracking system improves the multi-target tracking accuracy (MOTA) and identification F1 score (IDF1) by about 6.3% and 8.1%, respectively, and the average occlusion reconstruction error is controlled within 1.4 seconds. The proposed method effectively enhances the perception ability of ships in complex occlusion environments and verifies the feasibility and superiority of the strategy of combining visual detection with AIS data assistance.

Guan, Keping, Chen, Miao, Zhou, Yue

Analysis of Latency-Influencing Factors in Vehicle-Road-Cloud Integrated Systems Based on Fault Tree Analysis and Analytic Hierarchy Process

2026-99-1543

9/11/2026

Vehicle–road–cloud integrated systems have great potential in terms of improving traffic efficiency and achieving intelligent automatic driving through the integration of on–board terminals, roadside facilities, and cloud computing. However, their operational capabilities are heavily reliant on ultra-low-latency collaborative communication. This paper constructs a latency fault tree model to comprehensively analyze multi-source triggering paths of computation delay and reveals the formation mechanism of the delay path from “germination–induction–evolution”. On this basis, the Analytic Hierarchy Process is used to construct a three-level evaluation framework, and the influencing factors are quantitatively evaluated using NS-3 simulation data of the 004-V2X Communication Performance Testing Dataset. The result shows that the weight value of the network communication layer is the largest, 0.498, which shows that the bottleneck of performance in network communication is the wireless link quality. The cloud processing layer is second 0.327, which is dominated by the computational complexity and resource allocation policy. The impact of the onboard terminal layer is the smallest, 0.175. The FTA–AHP framework supported by empirical data can find the key factors affecting delay, which can help engineering optimization. It is noted that the AHP consistency check (CR) just checks the inner transitivity of expert judgment (i.e., the matrix consistency), while it cannot assure the objectivity and the bias elimination. We reduce the subjectivity by combining multiple experts, anchoring judgment with the simulation data, and performing a sensitivity check on the perturbation of the weights.

Xu, Yunchuan, Wang, Xiaomeng, Wang, Yan

Data-Driven Robust Preview Control of Vehicle Active Suspension Considering Random Controller Area Network Communication Dropouts

10-11-01-0001

9/10/2026

With the shift to full-by-wire chassis architectures, active suspension control is progressively integrated into chassis domain controllers to achieve coordinated chassis management. However, random packet dropouts in controller area network (CAN) communication under high-load conditions can significantly degrade suspension control performance. To address this challenge, this study proposes a novel data-driven robust preview control method. First, the packet-dropout phenomenon in CAN communication is modeled as a Bernoulli random process, and an augmented state-space model of the active suspension system is constructed by incorporating road preview information. Second, based on zero-sum game theory, road disturbances and control inputs are modeled as adversarial players, leading to the formulation of a stochastic game algebraic Riccati equation (SGARE) for the suspension system. To improve data efficiency and reduce design complexity, a data-driven value iteration (VI) reinforcement learning algorithm is employed to approximate the optimal control solution, with rigorous proof of convergence. Simulation results demonstrate that the proposed algorithm provides effective and feasible solutions across different packet-dropout probabilities. Furthermore, hardware-in-the-loop simulations confirm the robustness and reliability of the proposed control scheme, showing that the active suspension system maintains stable performance even in the presence of random CAN communication losses.

Wang, Gang, Duan, Deyang, Zhou, Tingting, Liu, Suqi

Dynamic Characteristics Analysis of Needle Roller Bearings in Planetary Gear Trains with Consideration of Inner Bore Spalling Defects of Planet Gears

2026-99-1279

9/4/2026

Driven by the growing demand for higher efficiency and load-bearing capacity in fields such as new energy vehicles and heavy-duty engineering machinery, planetary gear sets are increasingly operating at elevated rotational speeds, coupled with a corresponding expansion of their revolution radii. This dual trend directly induces a substantial surge in centrifugal acceleration acting on the internal needle roller bearings. Under the cyclic stress inherent to transmission operations, such enhanced acceleration not only accelerates the initiation of spalling faults on the inner bores of planet gears but also exacerbates the propagation and deterioration of these faults throughout the service life. To elucidate the influence mechanism of inner bore spalling on the dynamic response of planetary gear bearings, this study develops a specialized dynamic model. This model explicitly incorporates the compound kinematic effects of simultaneous rotation and revolution, thereby ensuring a high-fidelity reconstruction of actual operating scenarios. The research systematically investigates how different spalling types and dimensional parameters affect the system’s dynamic behavior. Numerical results demonstrate a positive correlation between the severity of the spalling defect and the dynamic response intensity. Specifically, the expansion of defect dimensions under harsh operating regimes markedly exacerbates both the contact impulses at the needle-roller interface and the overall vibration acceleration amplitudes. Notably, the amplitude increment of the needle rollers is far more pronounced than that of other components. These findings enrich the theoretical understanding of fault-induced dynamic responses in planetary gear systems and provide a solid theoretical and model-based foundation for optimizing the fault diagnosis, condition monitoring, and maintenance strategies of the associated needle roller bearings.

Zou, Desheng, Lai, Junbin, Guo, Wei, Dong, Peng, Xu, Xiangyang, Sun, Qiang

Simulation and Structural Optimization Design of Thermal-Mechanical Coupling Performance of Supporting Components

2026-99-1293

9/4/2026

This research aims to develop a high-performance composite material support component that meets extreme performance requirements. It is used to solve the problem of protecting critical electronic control units (ECUs) and flight data recorders in aerospace and automotive safety systems under harsh combined conditions of high temperature and high shock. Its internal dimensions are 0.14 m × 0.08 m × 0.08 m. In addition, it is required to withstand a constant temperature of 65°C for 3600 seconds, with the internal core temperature not exceeding 35°C. It can withstand a static load of 1.8 kg and a transient impact acceleration of 1400 G. The dual-layer composite structure based on functional decomposition solves the problems of thermal insulation and load-bearing/impact resistance. The inner layer uses ultra-low thermal conductivity aerogel to form a thermal barrier. The outer layer is a load-bearing frame made of high-strength/high-modulus quartz fiber reinforced epoxy composite material. The study employs a systematic numerical simulation method to verify the optimized design parameters. The results show that the internal temperature remained stable at 34.173°C. The outer layer deforms only at the micrometer level under static load. The inner layer is under zero load and there is no distortion in the internal space. The integrated design method of “material-function-structure-simulation” proposed in this paper provides a research approach for the survivability design of mechanical structures of new-generation aircraft and ground vehicles under complex multiphysics constraints.

Liu, Jiaxin, Wang, Yi, Zhao, Xiaorong, Wu, Chaofu, Zhao, Zhuo, Chen, Long

Optimized Design of Vibration Reduction for the Frame Structure of Metering, Considering Ground Impact Load

2026-99-1233

9/4/2026

To effectively mitigate the adverse effects of impact loads on the operational quality of a planter, this paper focuses on precision metering with dual planting chambers, and a novel approach is proposed to concurrently consider static and impact loads in the design of the frame structure, aiming to achieve a balanced design that combines load-bearing capacity and vibration reduction effects. The methodology employs a dual-layer cyclic process, where the outer layer calculates equivalent static loads based on the structural nonlinear dynamic response, and the inner layer introduces these equivalent static loads into the objective function of the optimization model using a weight method. The design of the frame structure, which simultaneously accounts for static and impact loads, is established through a topology optimization model based on the parametric level-set method. The simulation-optimization results indicate that, within the two-dimensional plane, the optimized seed metering frame achieves a marked reduction in volume fraction while its compliance remains almost unchanged. When the solution is expanded from 2-D to 3-D, and the optimized volume is increased to match the original volume, the optimized stiffness becomes 1.92 times the initial stiffness. This demonstrates that the frame is substantially lightened yet its stiffness is effectively enhanced, confirming that the design concurrently offers improved vibration attenuation and load-bearing capacity. The proposed structural optimization method can provide a viable design for improving the quality of precision metering. Although physical tests are still lacking, the soundness and consistency of both the simulation outcomes and numerical analyses provide strong evidence for the feasibility of the proposed method. Future tests can further verify its effectiveness.

Zhang, Wenpeng, Zeng, Shan, Zang, Ying, Wang, Yu

Optimal Design of the Driving Axle Housing of a Heavy-duty Automobile

2026-99-1225

9/4/2026

As one of the important freight modes, heavy trucks need a high- strength and high-reliability drive system to carry huge goods. Therefore, the drive axle housing, a key component, significantly influences the performance and service life of vehicles, and its design and optimization have high practical significance. Firstly, this study begins by creating a geometric model of the axle housing using SW and analyzes its stress distribution under four typical operational conditions. Through static analysis, it is concluded that the most critical operational conditions are the maximum deformation of 2.151 mm and the peak stress of 272.3 MPa; in the fatigue analysis of ANSYS Workbench, the minimum life is 820,000 times. Results from both static and fatigue assessments indicate that the initial axle housing design satisfies stiffness, strength, and fatigue requirements. There is a large margin in the structure, which has certain optimization space. Considering the most dangerous working condition, the response surface optimization module of ANSYS Workbench is used with the objective of mass reduction. Finally, the axle housing is reduced by 4.09 kg; the corresponding maximum deformation is 2.262 mm, meeting stiffness criteria, while the peak equivalent stress reaches 280.3 MPa, remaining below the material's yield strength. The minimum life is about 620,000 times, and the maximum fatigue life is 1 million times, which still meets the requirements of the vertical bending fatigue test. This lightweight redesign reduces material and manufacturing costs while maintaining the requirements for deformation, stress, and fatigue strength.

Zhao, Shenglian, Zhong, Weijie, Zhang, Jian

An Experimental and Numerical Study on the Optimization of Quasi-static Energy Absorption Performance in Aluminum Alloy Thin-walled Tubes with Varied Notch Configurations

2026-99-1255

9/4/2026

Aluminum alloy thin-walled tubular parts play an important role in the energy absorbing elements of automotive passive safety. The number of geometry-trigger based notches is a factor in alleviate the initial force peak and shift the progressive buckling mode. However, until now, only limited work has been reported considering multiple notches. It is hard to clearly understand the impacts of the number of triggers on the buckling behavior and thresholds. Here, a mixture of quasi-static axial compression testing with high-fidelity finite element simulations is used to explore the influence of elliptical perforation number on AA6061-T6 tube crushing behaviour. For the first time, it is demonstrated that increasing the perforations leads to non-monotonic buckling evolution: from symmetry increasing → asymmetrical instability → optimal re-symmetrization → excessive weakening. We observe this transition from isolated holes to a collective “weakening hoop” controlling symmetric buckling as the number of holes increases. Our results give optima for separate objectives; T6 offers the best overall crashworthiness (45.2% less maximum force), with the other measures showing T4 with the best stiffness. We determine quantitative relationships between the number of holes and corresponding performance metrics. This gives practical design criteria for the design of energy absorbers.

Guo, Zifa, Jin, Ming

Ant Colony-Artificial Potential Field Fusion Path Planning Algorithm Based on a Maneuver Action Library

2026-99-1257

9/4/2026

The traditional Ant Colony Algorithm has defects such as easy entrapment in local optima due to a simplistic heuristic function and slow convergence due to excessive search directions. A fusion path planning algorithm integrating ant colony optimization and artificial potential field based on a maneuver action library is proposed. Firstly, a mathematical model for UCAV path planning is established. Considering the maneuverability constraints of UCAVs, and drawing on the concept of basic maneuver action libraries for fighter aircraft, an ant colony-potential field fusion path planning algorithm based on a maneuver action library is introduced. Simulation results demonstrate that compared to two other algorithms, the proposed method significantly improves the number of waypoints and planning completion time.

Li, Ruishen, Chen, Xiaogang

Research on Reliability and Durability Testing and Evaluation Technology for Hub Motor Corner Modules

2026-99-1236

9/4/2026

With the development of high-performance hub motors and modular assembly integration technologies, their reliability and durability have become key factors restricting industrial applications. Existing standards are mostly aimed at the hub motor itself, lacking systematic testing methods for highly integrated corner module systems. Based on a National Key Research and Development Program project, this paper conducts a series of research on reliability and durability test and evaluation technologies for the hub motor corner module system. By means of collecting vehicle-load spectra and combining user- relevance techniques, a multidimensional assessment framework is established, encompassing bench-scale axle-coupled tests, full- vehicle road reliability tests, and component-level environmental tests. The research outcomes have been applied to the testing and validation of actual prototype vehicles and components. Test results indicate that the developed testing methodology can effectively identify potential failure, providing crucial technical support for the optimized design and industrialization of hub motor corner modules.

Wu, Zhen, Liang, Dong, Gao, Fengling, Wang, Runze, He, Junnan

A Simultaneous Impulse and Oscillatory Component Decomposition Method for Fault Diagnosis of Rolling Bearings

2026-99-1204

9/4/2026

Due to the interference of oscillatory components and noise, the periodic impulses associated with localized bearing faults become difficult to extract, leading to unreliable diagnostic performance. To solve this problem, the study proposes a simultaneous impulse and oscillatory component decomposition method (SIOCD). The method designs and solves a novel optimization model to decompose oscillatory components and fault impulse components from noisy vibration signals. To achieve component separation in the optimization model, distinct penalty functions are introduced for oscillatory and impulse components. For oscillatory components, a regularization term is applied to achieve their extraction by minimizing the component bandwidth in the frequency domain. For impulse components, a penalty function is designed to achieve their decomposition by enhancing both sparsity within groups (SWG) and sparsity across groups (SAG) in the time domain. Then, an iterative solver is derived using an alternating minimization framework and the majorization-minimization (MM) algorithm. Finally, the proposed method’s effectiveness is demonstrated through comprehensive simulation and experimental analyses, and the results demonstrate that it achieves superior performance over existing approaches in fault feature extraction and enhancement.

Sun, Haoran, Zhang, Jinduo, Han, Tianyu, Shi, Xi

Assembly Accuracy Optimization of Aero-engine Section Based on Dynamic Weighting Multi-Objective Optimization Algorithm

2026-99-1272

9/4/2026

The pose-solving method for aero-engine component docking assembly often faces challenges such as slow convergence and susceptibility to local optima when dealing with complex optimization problems involving multiple features and constraints. This paper proposes an optimized assembly pose solution method for engine sections based on an improved multi-objective optimization algorithm. The method first preprocesses the high-density point clouds obtained from 3D scanning to extract geometry such as feature points, lines, and surfaces. It builds an assembly constraint model with geometric relations and process needs. It focuses on the pose solution phase: we transform the assembly problem into a nonlinear optimization problem to minimize parallelism error, gap error, and step error. In order to solve this multi-objective problem efficiently, we propose an iterative multi- objective optimization algorithm as the optimization engine and propose a dynamic weight allocation strategy. During iteration, the strategy adaptively adjusts the weight coefficients of three error terms in the overall fitness function due to the evolution of the population and convergence of each error term, guiding the search direction and balancing the algorithm's global exploration and local exploitation ability. Our results show that instead of adopting an optimization algorithm with fixed weights and a multi-Objective optimization system with fixed weight, the proposed pose solution method based on dynamic weight multi- objective optimization algorithm achieves a high accuracy and stability of the solution and can easily and accurately produce a good pose matrix which meets challenging assembly constraints, providing a practical theoretical framework and technical support for achieving high-quality automated engine assembly.

Huang, Mi, Wu, Guanghui, Su, Xun, Xu, Yongqian, Ding, Han, Liu, Xiaopeng

Numerical Simulation and Optimization Study of Direct-Fired Hot Blast Stove Based on Computational Fluid Dynamics

2026-99-1230

9/4/2026

Shantui Janeoo Machinery Co., Ltd developed a new direct-fired hot blast stove. However, experimental research was costly and failed to adequately capture the internal temperature distribution patterns. Therefore, computational fluid dynamics (CFD) was employed to conduct a numerical simulation of its three-dimensional model, analyzing its flow and heat transfer performance. The results indicated that the swirling cold air intake method caused local vortices and outlet backflow, leading to uneven temperature distribution. To address this issue, numerical simulation was used to investigate the influence of key geometric parameters on the stove’s performance. An improved design was proposed, and the performance differences between the optimized and original structures were compared and analyzed. The optimized hot blast stove showed a significant improvement in temperature distribution uniformity, with the outlet air temperature increasing by 59°C compared to the original structure.

Wu, Guoqing, Zhong, Wenzheng, Shen, Yuanlin, Chen, Ziyun

Study on the Vehicle Unsteady Vibration Control with a Semi-Active Strut

2026-99-1231

9/4/2026

Unsteady vibrations of vehicles, which can be easily perceived by the human body, may affect the driving experience and compromise driving comfort. However, the conventional three-point powertrain mounting system (PMS) often fails to offer a satisfactory solution. Here, a novel four-point PMS was proposed by introducing a semi-active strut (SAS), which can provide stronger damping in a low-frequency range to resolve this problem. Specifically, a thirteen degrees of freedom (DoFs) vehicle dynamic model (VDM) with four mounts was constructed, and the evaluation indices for unsteady vibration responses of the vehicle were determined and analyzed; Next, the PMS optimization design approach was employed to identify the proper position of installation and dynamic stiffness of the SAS, and meanwhile the 13 DoFs VDM and the force-sharing principle were used to identify the structural parameters of the strut; Last, comparative experiments were performed to analyze the effect of the strut on alleviating the unsteady vibration of the vehicle under varied unsteady vehicle states. The results showed that the SAS has significantly reduced the seat rail peak acceleration, verifying the effectiveness of our novel PMS in alleviating the unsteady vibration. The research provided a feasible solution to alleviate the unsteady vibration of vehicles and improve the driving experience.

Wang, Daoyong, Liu, Yongjiang, Ma, Bo

Fatigue Damage Analysis of a Wheeled Vehicle

2026-99-1207

9/4/2026

This article studies the fatigue damage problem of vehicles under air drop and off-road conditions. First, a multi-body dynamics model of the entire vehicle is established in ADAMS/View to obtain loads and center-of-gravity acceleration under off-road conditions. Subsequently, a finite element model of the vehicle air drop is created in HyperMesh and LS-DYNA to simulate the landing impact and extract loads on key components. By superimposing and spectrum processing the loads from the two conditions, a vehicle load spectrum is compiled and used as input for fatigue analysis. Based on the Miner linear cumulative damage criterion and the material S–N curve, fatigue life predictions are made for key areas of the frame and suspension. The results indicate that the front cross beam and auxiliary longitudinal beam at the bottom of the frame are the most vulnerable components, with the auxiliary longitudinal beam reaching failure under both conditions, but having a limited impact on the overall vehicle operation. Although the peak acceleration under air drop conditions is higher, the off-road conditions lead to more severe cumulative damage due to higher impact frequency and duration. This study provides references for vehicle structural optimization and service reliability enhancement.

Lin, Qingpeng, Zhang, Qiang, Fu, Lei, Huang, Jianbing, Qin, Weiwei, Sun, Xiaowang

Experimental Verification of Chatter Optimization for Deep Small Hole Micro-Boring Based on 05Cr17Ni4Cu4Nb

2026-99-1273

9/4/2026

Aircraft engine parts are extremely precise, and for deep, small-hole machining of the stainless steel 05Cr17Ni4Cu4Nb valve seat, the quality and sealing of the parts machined with current machining parameters are poor. This greatly affects production efficiency and quality. This article takes the optimization of the three elements of cutting as the starting point, uses the orthogonal experimental method to study which force most affects machining quality in the three directions of boring force, and selects the appropriate three elements of cutting to reduce cutting force. And analyzed the simulated chip shapes before and after optimization, and finally verified the optimization effect through the instrument equipment. A micro three- axis accelerometer was used to conduct machining experiments on deep small holes with cutting parameters before and after optimization. After optimization of cutting parameters, the tool's maximum axial deformation showed a reduction of about 51.60%, a reduction of approximately 58.75% was achieved in the maximum radial deformation, the maximum tangential deformation exhibited a decline of about 45.17%, and the peak overall deformation was reduced by approximately 50.66%. Compared with the pre-optimized state, using optimized cutting parameters to machine deep small holes resulted in a 72.31% reduction in the tool's axial acceleration, the radial acceleration by 63.36%, and the tangential acceleration by 71.68%, the tangential force by 65.29%, the axial force by 27.93%, and the radial force by 31.16%. Effectively reducing tool chatter and lowering chatter amplitude led to the disappearance of surface vibration patterns on the machined parts.

Liu, Xinwei, Shi, Guangfeng, Zhou, Yuning, Gao, Jinglong

Control of Heat Treatment Deformation in Thin-Walled Pipe Fittings and Optimization of Turning Processes

2026-99-1300

9/4/2026

A certain component features an overall thin-walled structure with a wall thickness less than 1 mm, manufactured from high-strength martensitic precipitation-hardening steel. This part demands extremely stringent dimensional accuracy, with circumferential wall thickness variation not exceeding 0.006 mm, making it a typical high- precision thin-walled component. To ensure component performance and material utilization, the primary forming processes include spin forming, solution heat treatment, and multiple turning operations. During actual machining, martensitic precipitation-hardening steel exhibits significant microstructural stress relaxation and uneven cooling after solution heat treatment, leading to substantial part deformation. This makes it difficult to control subsequent machining dimensions within tolerance limits. Additionally, conventional clamping methods during multi-pass turning operations often cause uneven stress distribution on components during processing, frequently resulting in dimensional deviations that severely impact finished product yield rates. To address this challenge, this study systematically developed specialized tooling design and optimized turning processes tailored to the structural characteristics and deformation mechanisms of these thin-walled tube blanks. Simultaneously, a gap-free turning fixture with uniform expansion and clamping capabilities was developed. Combined with optimized machining parameters during the turning stage, this significantly improved stress distribution during processing, preventing further deformation caused by localized stress concentration. Test results indicate that after process optimization, the overall machining accuracy of this component improved by approximately 70% compared to the original process. Critical geometric tolerances showed significant enhancement, with roundness error consistently controlled within 0.30 mm and diameter dimensional consistency markedly improved. These measures not only successfully addressed deformation control challenges during heat treatment and machining of thin-walled parts but also provided a viable process solution and technical reference for precision manufacturing of similar high- difficulty, high-precision components.

Kou, Yue, Zhao, Honglian

Optimal Design of Kinematic Characteristics for Rear Single-Trailing-Arm Suspension Based on NSGA-II

2026-99-1249

9/4/2026

Owing to its structural features, the single-trailing-arm suspension tends to exhibit excessive wheelbase variation and caster angle variation during wheel travel. To address this issue, this study proposes an optimization method for the hard point parameters of the non-steering rear single-trailing-arm suspension. Firstly, a mathematical model and a dynamic model of the single-trailing-arm suspension are established separately. The validity of the mathematical model is verified by comparing simulation results, and the model is revised using a correction coefficient. Sensitivity analysis of the suspension hard points is performed via ADAMS/Insight to screen out key design variables. Finally, the NSGA-II multi-objective genetic algorithm is employed for optimization, followed by simulation validation. The results demonstrate that this method effectively enhances the kinematic characteristics of the suspension, providing theoretical support for the optimization of hard point layout.

Wang, Zhidong, Xu, Zhenyu, Wang, Jianhua, Gao, Junfeng

Adaptive-Weighted Coupling-Aware Gaussian Processes for AFP

2026-99-1277

9/4/2026

Composite materials have gained widespread application in the aerospace field due to their advantages, such as high specific strength, high specific modulus, and corrosion resistance. Automated placement technology, as an emerging automated manufacturing method, is gradually replacing traditional manual placement processes and demonstrating significant advantages in composite manufacturing. Currently, the automated placement process for composite materials faces challenges such as insufficient experimental samples and strong coupling relationships between process parameters, leading to low fitting accuracy in process parameter optimization models. To address this, this paper proposes a placement process parameter optimization method based on model weight adaptive allocation. This method integrates three key technologies: a coupling-aware Gaussian process based on combined kernel functions, a weight allocation ensemble model based on leave-one-out cross-validation, and a multi-criteria adaptive sampling mechanism. Experimental validation demonstrates that the integrated model achieves a coefficient of determination R^2 = 0.82, which represents a superior fit compared to the R^2 = 0.65 achieved by a single-kernel Gaussian model and the 0.76 obtained from a single sampling. Furthermore, both the Root Mean Square Error (RMSE=0.92) and Mean Absolute Error (MAE=0.70) are lower than those of traditional baseline models. This framework provides an effective solution for optimizing parameters in the automated placement process for composite materials.

Zuo, Rui, Du, Tingting, Lv, Ruiqiang

Research on Multi-Condition Topology Optimization of Transport Ship Pillar Structure

2026-99-1228

9/4/2026

Structural optimization in shipbuilding represents a significant research focus within the fields of naval architecture and marine engineering. This study investigates multi-condition topological optimization for the deck pillar region of a transport ship's sectional structure. A mechanical model incorporating six typical load conditions was developed, and the Analytical Hierarchy Process (AHP) was employed to quantify the weighting coefficients for each condition. This enabled multi-condition collaborative topological optimization of the pillar layout. The optimized configuration underwent model reconstruction and finite element verification. Results demonstrate that the proposed multi-condition collaborative topology optimization method effectively balances structural performance and weight reduction requirements while satisfying strength specifications. This method yields optimal pillar layouts meeting multi-condition constraints, providing a reference for multi-condition topology optimization studies in ship structures.

Pei, Zihao, Wei, Yi, Feng, Ruge, Liu, Kun

An Energy Balanced Splitting Factor Calculation Method for Nonconforming Generalized Mixed Finite Elements with Distorted Meshes

2026-99-1223

9/4/2026

This paper presents an Energy-Balanced Splitting Factor Method (EBSFM) for nonconforming generalized mixed finite elements to enhance accuracy and stability under mesh distortion. The splitting factor significantly influences the numerical solutions. Traditional approaches employ a uniform splitting factor for all elements, neglecting their distinct characteristics and boundary conditions. Wang's geometry-based Stiffness–Compliance Splitting Factor Method (SCSFM) is adopted to obtain element-wise initial values. Building upon SCSFM, the proposed EBSFM optimizes the splitting factor through an energy balance criterion that minimizes the deviation between mixed energy and generalized strain energy, thereby improving the physical consistency of the finite element model. The method establishes an approximate mapping relationship between unknown variables and splitting factors via matrix decomposition and reconstruction techniques, enabling element-wise adaptive optimization. The EBSFM demonstrates consistent superiority in terms of displacement accuracy, stress accuracy, and energy balance.

Shang, Zhongxin, Wang, Zhenyu

Influence of Restraint System Angles on Impact Response and Protection of Child Occupants in Vertical Crash Conditions

2026-99-0413

8/28/2026

Focusing on the protection needs of child occupants in the scenario of aircraft vertical crashes, a finite element calculation model based on the cabin structure of a certain type of small electric aircraft was established. The child seat restraint system was coupled with the THUMS 3YO human body model, and the vertical 15 g condition meeting the requirements of Article 23.562 of CCAR-23-R3 was simulated. The influence law of the safety belt restraint angles (formed by different safety belt routing positions) on the dynamic response and injury indicators of child occupants was explored. To verify the rationality of the simulation results, a physical impact experiment was conducted using a Hybrid III 3YO child dummy and the same type of child seat, with key indicators (e.g., head acceleration, lumbar load) measured and compared with simulation data. The analysis results show that the effect of the safety belt restraint angle on the overall protective performance is less pronounced under vertical conditions, but a clear trend is observed: when the angle is in the range of 76°~84°, the head acceleration is relatively low and the brain tissue injury indicators are in the optimal state, which can effectively reduce the risk of head and neck injuries; when the restraint angle increases to 92°, the lumbar axial load and lung strain increase significantly, indicating a detrimental effect. The results of this study clarify the differences in the protective performance of child seats under different restraint angles, and provide a theoretical basis and technical guidance for the layout of safety belt anchors of aircraft seats and the optimal design of child seats.

Wang, Yafeng, Guo, Pan, Li, Weiliang, Shi, Xiaopeng

Dynamic Response and Energy Absorption of a Novel Arc-Shaped Hourglass Re-Entrant Honeycomb under Impact Loading

2026-99-0417

8/28/2026

This study introduces an arc-shaped hourglass re-entrant auxetic honeycomb (AHRH) and examines its impact-induced dynamic response and energy-absorption behavior via finite-element simulations. The conventional re-entrant honeycomb (RH) is adopted as the baseline, and side-by-side simulations are performed at impact speeds of 10, 20, and 30 m/s. The mechanical response of both lattices is assessed through force-displacement characteristics, absorbed-energy histories, and representative deformation modes. Results indicate that the AHRH significantly reduces the initial peak force, prolongs the plateau stage, and exhibits a distinct dual-plateau feature, thereby achieving the desirable crashworthiness mode of “low initial peak-extended plateau-high densification”. Compared with the RH, the AHRH achieves increases of approximately 42.9%-59.7% in total energy absorption and 42.8%-56.1% in specific energy absorption while maintaining nearly identical mass. The enhanced performance arises from the arc-edge geometry, which alleviates local stress concentrations, promotes progressive buckling, and generates multiple plastic hinges. These mechanisms lead to smoother load transfer, avoidance of excessively high initial impact loads, and more efficient crash energy management. Overall, the proposed AHRH structure demonstrates superior energy absorption capacity and deformation stability compared with the conventional RH, providing new insights and practical references for the lightweight design and optimization of advanced protective and crashworthy structures.

Jiang, Zhide, Chen, Long, Yu, Ping

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