Browse Topic: Data exchange

Items (1,365)
Find
Preliminary Design and Analysis of Dual Throat Fluidic Thrust Vectoring Nozzle for Supersonic Aerospace Application2026-28-0106To be published on 02/12/2026
The project investigates the performance characteristics of dual-throat nozzle used for fluidic thrust vectoring (FTV) in supersonic aircraft applications, offering a potential alternative to mechanical vectoring methods. Fluidic thrust vectoring provides benefits such as reduced weight, lower radar signature, and improved manoeuvrability and control. Computational methods are used to study the effects of geometric and operational parameters, including nozzle pressure ratios and secondary injection rate and injection angle, on thrust-vectoring efficiency and system dynamics. The study aims to develop optimized design configurations and validate using computational models.
Suresh, Vignesh, M, Akash, SENTHILKUMAR, NIKIL, Sundararaj, Senthilkumar, A, Garry Kiristen, Singh, Swaraj
Automotive Ethernet Proxy-Based Security Architecture In Vehicle Computers2026-28-0121To be published on 02/12/2026
Modern vehicles require sophisticated, secure communication systems to handle the growing complexity of automotive technology. As in-vehicle networks become more integrated with external wireless services, they face increasing cybersecurity vulnerabilities. This paper introduces a specialized Proxy based security architecture designed specifically for IP-based communication within vehicles. The framework utilizes proxy servers as security gatekeepers that mediate data exchanges between Electronic Control Units (ECUs) and outside networks. At its foundation, this architecture implements comprehensive traffic management capabilities including filtering, validation, and encryption to ensure only legitimate data traverses the vehicle's internal systems. By embedding proxies within the automotive middleware layer, the framework enables advanced protective measures such as intrusion detection systems, granular access controls, and protected over-the-air (OTA) update channels. This strategy
M, Arvind, Praneetha, Appana Durga, Remalli, Ravi Teja
TOPSIS-Based Multi-Criteria Optimization of WAAM Parameters for Automotive Component Fabrication2026-28-0026To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) can make huge, complicated metal parts quickly and cheaply, making it popular in the automobile sector. This study uses TOPSIS, a multi-criteria decision-making method, to improve WAAM process parameters such wire feed rate, travel speed, and current. Automotive applications need surface roughness, deposition rate, and dimensional precision, which WAAM-fabricated components must meet. TOPSIS normalizes and ranks experimental findings to find parameter combinations that perform best across many quality metrics. The results show that integrated optimization improves component quality and consistency, making WAAM a feasible and economical sustainable vehicle manufacturing option.
Pasupuleti, Thejasree
Parameter Optimization for Improved Surface Finish in WAAM-Fabricated Steel Structures2026-28-0023To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) is a cost-effective and scalable metal additive manufacturing technique widely used for fabricating large metallic components. However, surface finish remains a critical challenge, especially for structural applications where post-processing needs to be minimized. This study focuses on optimizing key process parameters to improve the surface finish of ER70S-6 steel structures fabricated using the WAAM process. Experiments were designed using a statistical approach to systematically vary parameters such as wire feed rate, travel speed, voltage, and inter-pass cooling time. Surface roughness was measured using standard metrology tools, and the results were analyzed to identify the most influential parameters. An optimized parameter set was proposed based on the experimental outcomes, leading to a significant reduction in surface roughness without compromising the structural integrity of the deposited material. The findings contribute to enhancing
PN, Vani
Experimental Investigation of Process Parameter Effects in WAAM of Nickel-Based Alloys2026-28-0027To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) is an evolving discipline in metal additive manufacturing characterized by rapid deposition, cost-effectiveness, and centrality to the near-net-shape fabrication of large-scale components. This study will concentrate on WAAM application to deposit nickel alloys, which find extensive use in aerospace, power generation, and marine industries, due to their good mechanical strength, corrosion resistance, and thermal stability. However, some drawbacks in WAAM processing of nickel alloys include thermal distortion, porosity, and residual stress. The research looks at how key WAAM process parameters, including wire feed rate, travel speed, current, and interpass temperature affect geometric accuracy, surface integrity, and mechanical performance of the fabricated components. Microstructural characterization was done using optical microscopy, and hardness distribution was measured as an indication of mechanical uniformity throughout the builds. It is
Natarajan, Manikandan
Effect of Minimum Quantity Lubrication during Machining of Incoloy 800H Using Vegetable Oil Enriched With Nano Particles2026-28-0038To be published on 02/12/2026
In this experimental work an effort has made to investigate the machining of difficult to machine Incoloy 800H super alloy. Cryogenically treated textured cutting inserts and vegetable oil enriched with nano particles were used for this study. The turning experiments were performed with different parameters such as Cutting speed, feed rate and depth of cut. Surface Roughness, Cutting Force, Tool-Tip Temperature and Power were the output responses considered. Grey Relational Analysis (GRA) and Analysis of Variance (ANOVA) analysis were used to optimize the machining parameters and to find the most influencing machining parameter on the output responses. The results showed that the optimal machining conditions considered were cutting speed at 35 m/min, feed rate at 0.06 mm/rev and depth of cut at 0.5 mm for the multiple-characteristic performances and it was improved by 3.86 % with this approached method. Also, Tool-tip temperature and Power were reduced during machining with cryo
Natarajan, Manikandan
Effect of Sebastiana rostrata Fiber Loading on the Tribological Behaviour of Polycaprolactone Biocomposite.2026-28-0021To be published on 02/12/2026
This study investigates the tribological performance of Sesbania rostrata fibers (SRFs) reinforced polycaprolactone (PCL) composites, focusing on the effects of fiber loading under varying normal loads. Composite samples with fiber contents of 10%, 20%, and 30% were tested at sliding velocities of 0.5 m/s and a fixed sliding distance of 500 m. Results show that the inclusion of SRFs significantly reduces the coefficient of friction (COF) and specific wear rate (SWR) compared to neat PCL, particularly at fiber loadings up to 20%. Beyond this threshold, fiber agglomeration leads to increased wear. The results highlight the potential of SRF/PCL composites for use in wear-critical automotive and orthopedic applications due to improved load-bearing capability and surface resistance.
Raja, K., Senthil Kumar, M.S.
Multi-Objective Optimization of WAAM for Sustainable Production of Automotive-Grade Components2026-28-0030To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) has emerged as a promising technology for fabricating large-scale metal components with reduced material waste and lead time, aligning with the goals of sustainable manufacturing. This study presents a multi-objective optimization approach for WAAM to enhance both the manufacturing efficiency and sustainability of automotive-grade components. Key process parameters such as travel speed, wire feed rate, and current were systematically varied to evaluate their impact on dimensional accuracy, mechanical performance, and energy consumption. A statistical design of experiments framework was employed, and multiple performance objectives were optimized simultaneously using suitable decision-making techniques. The results demonstrate that optimized WAAM settings not only meet structural and functional requirements for automotive applications but also contribute to material and energy savings. This approach supports the integration of sustainability into
Pasupuleti, Thejasree
Statistical Optimization of Wire Arc Additive Manufacturing Parameters Using Taguchi Methodology2026-28-0035To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) is an emerging metal additive manufacturing process known for its high deposition rates and cost-effectiveness in fabricating large-scale components. However, the quality of the final build is highly sensitive to process parameters such as wire feed rate, travel speed, voltage, and current. In this study, the Taguchi method is employed to statistically optimize key WAAM process parameters with the aim of improving surface finish and mechanical integrity of the deposited parts. An L9 orthogonal array was used to design experiments, and signal-to-noise (S/N) ratios were analyzed to identify optimal parameter settings. Analysis of variance (ANOVA) was performed to determine the significance of each factor on the selected output responses. The results demonstrated that specific combinations of process parameters can significantly reduce surface roughness and enhance bead geometry. The optimized settings obtained through the Taguchi approach provide a
PN, Vani
Parameter Selection Strategies for High-Performance WAAM Structures in Automotive Engineering2026-28-0033To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) has gained traction as an advanced fabrication technique for producing large, structurally demanding components in the automotive industry. Achieving high-performance WAAM structures requires precise control and selection of key process parameters, which directly influence mechanical strength, dimensional accuracy, and surface quality. This study investigates the effect of critical process variables—including wire feed rate, travel speed, current, voltage, and inter-layer cooling time—on the structural integrity of WAAM-fabricated components designed for automotive use. A systematic experimental approach, supported by statistical modeling and optimization tools, was employed to identify parameter combinations that yield optimal results. The outcomes demonstrate improved microstructural uniformity, reduced residual stresses, and enhanced tensile properties in the fabricated parts. The findings serve as a foundation for developing robust parameter
V, Aravind
Statistical Modeling of Wire Arc Additive Manufacturing Parameters Using Regression Analysis2026-28-0024To be published on 02/12/2026
Wire Arc Additive Manufacturing (WAAM) is gaining prominence for fabricating large metal components due to its high deposition rate and cost-effectiveness. However, the quality and performance of WAAM-fabricated parts are strongly influenced by process parameters such as wire feed rate, travel speed, arc voltage, and current. This study presents a statistical modeling approach using regression analysis to predict the effects of these key parameters on critical output responses, including bead geometry, surface roughness, and material deposition rate. Experiments were designed using a structured methodology, and the collected data were analyzed to develop linear and multiple regression models. The accuracy and reliability of the models were evaluated using statistical metrics such as R² and p-values. The results demonstrate that regression-based models can effectively predict WAAM outcomes, enabling process optimization and quality control. This approach provides a valuable tool for
Pasupuleti, Thejasree
A Performance-driven Numerical Approach for Optimizing the Plenum Opening Area of Cowl Box2026-26-0461To be published on 01/16/2026
There is a scarcity of research in literature regarding the determination of Plenum Opening Area of cowl box. The area of the plenum opening in the cowl box significantly affects the airflow rate in fresh airflow modes, such as face and defrost modes, as well as issues related to water ingress. Primarily, the size of the plenum opening is determined by the necessary HVAC airflow rate. This study aims to investigate how the plenum opening area impacts both airflow discharge and the water ingress issue in the HVAC module. A novel approach is introduced in this research to determine the optimal plenum opening area of the cowl box, taking into account both airflow rate and water ingress concerns. The ANSYS FLUENT software is utilized to analyze airflow discharge in both face and defrost modes, while the SPH (Smooth Particle Hydrodynamics) based Preonlab tool is employed for water ingress analysis. Airflow discharge is evaluated for various plenum opening sizes in both modes, and the area
Baskar, Subramaniyan, Mahesh, A, Gopinathan, Nagarajan
Leveraging Telematics Big Data Analytics for Real-Time Monitoring of Catalytic Converter Failures and Root Cause Identification for Emission Compliance2026-26-0591To be published on 01/16/2026
The automotive industry is continuously evolving at high pace to meet rising customer expectations, reliability, reduced maintenance, and most relevant, compliance with stringent emission norms. Traditionally, the analysis of vehicle emissions relies heavily on periodic inspections and manual checks. These conventional methods are often time-consuming, prone to human error, and lack the ability to provide real-time insights. Also, identifying Catalytic converter failures due to non-manufacturing issues require meticulous physical inspections and historical data reviews, which are not always accurate or timely. Telematics or Connected cars technology being one of the major technological innovations in recent times revolutionizes these processes by enabling real-time data exchange between vehicles and external systems. The current study presents an innovative approach to utilizing telematics data for real-time monitoring of vehicle emissions and pinpointing Catalytic converter failures
Dev, Triyambak, Prasad, Kakaraparti Agam, Kalkur, Varun, Modak, Saikat, AGARWAL, Shashank, Chandra, Animesh, Paul, Varsha, Garg, Amit, Sundararaman, Venkataraman, Bose, Sushant
High-Performance Computing for Software-Defined EV Powertrains: Design and Real-Time Validation with NXP S32E278 Domain Controller2026-26-0684To be published on 01/16/2026
Software-Defined Vehicles (SDVs) are redefining the automotive landscape by decoupling hardware from software and enabling dynamic, over-the-air updates, advanced control strategies, and real-time decision-making. To support this transformation, EV powertrain systems require high-performance computing (HPC) platforms capable of real-time control, data processing, and cross-domain communication. This paper introduces a fully SDV-compatible EV powertrain architecture built around the NXP S32E278 domain controller, which integrates a multi-core, lockstep-enabled processor specifically designed for zonal control and automotive functional safety. To meet the bandwidth and latency demands of modern SDV applications, the system replaces conventional CAN-based communication with automotive Ethernet, enabling gigabit data transfer, Time-Sensitive Networking (TSN), and low-latency coordination across software-defined control domains. The S32E executes critical functions such as field-oriented
Pawar, Ganesh, Inamdar, Sumer Deepak, Kumar, Mayank, Deosarkar, Pankaj, Tayade, Nikhil, Kanse, Dattatray, Chopade, Vipul
Johnson-Cook model calibration for brittle materials under impact loads2026-26-0367To be published on 01/16/2026
In the assessment of parts subjected to impact loading, the current process relies on static analysis, which overlooks the significant influence of high strain rate on material hardening and damage. The omission of these effects hinders accurate impact simulations, limiting the analysis to comparative studies of two components and potentially misidentifying critical hot spot locations. To address these limitations, this study emphasizes the importance of incorporating the effects of high strain rate in impact simulations. By utilizing the Johnson-Cook material calibration model, which includes both material hardening and damage models, a more comprehensive understanding of material behavior under dynamic loading conditions can be achieved. The Johnson-Cook material hardening model accounts for the strain rate sensitivity of the material, providing an accurate representation of its behavior under high strain rate conditions. This allows for improved prediction of material response
Pratap, Rajat, Apte, Sr., Amol, Babar, Ranjit, Dudhane, Karan, Poosarla, Shirdi Partha Sai, Tikhe, Omkar
Digital Twin-Enhanced Chassis Dynamometer for EV Drivetrain Testing2026-26-0363To be published on 01/16/2026
Accurate prediction of drivetrain performance and energy efficiency in electric vehicles (EVs) remains a challenge due to the limitations of conventional chassis dynamometer testing, which often overlooks dynamic vehicle-roller interactions, suspension responses, and regenerative braking effects. This paper presents a novel digital twin-enabled testing framework using a compact, two-roller chassis dynamometer integrated with real-time multibody dynamics and electromechanical co-simulation. The physical test bench is coupled with a virtual model of the EV, including suspension geometry, rear-to-front axle load distribution, tire–roller contact mechanics, and motor-inverter dynamics. By enabling bi-directional data exchange between the physical and virtual domains, the system emulates real-world load shifts, torque demand variations, and energy recovery under standardized drive cycles. This integrated approach enhances simulation fidelity, supports certification-compliant testing, and
Kumar, Akhilesh, V, Yashvati
Development of a High-Fidelity Vehicle Dynamics Model with Rear-Wheel Active Roll Control for Improved Stability2026-26-0093To be published on 01/16/2026
This work introduces a unified vehicle dynamics framework that combines detailed modeling and active control to enhance ride comfort and handling stability. A full 12-degree-of-freedom vehicle model is developed to simulate dynamic responses across a range of driving conditions. Unlike conventional approaches, this model incorporates both linear and nonlinear tire behavior, enabling more accurate prediction of vehicle motion. To further improve performance, an active roll control mechanism is proposed, utilizing rear-wheel suspension actuators to counteract undesired body roll and yaw instabilities. A novel co-simulation environment is established by coupling MATLAB/Simulink-based control strategies with high-fidelity multibody dynamics from ADAMS Car. The model is calibrated and validated using experimental data from an instrumented test vehicle. Results show that the integrated control system significantly reduces critical parameters such as roll angle, yaw rate deviation, and
Duraikannu, Dinesh, Dumpala, Gangi Reddi
STGT-Gen: Spatio-Temporal Graph Transformer for Multi-Vehicle Traffic Scenario Generation2025-01-731612/31/2025
In the testing and validation of autonomous driving systems, scenario-based simulation is crucial to address the high costs and insufficient scene coverage of real-road testing. However, existing simulators rely on handcrafted rules to generate traffic scenarios, failing to capture the complexity of multi-agent interactions and physical rationality in real traffic. This paper proposes STGT-Gen, a data-driven Spatio-Temporal Graph Transformer framework, to generate realistic and diverse multi-vehicle traffic scenarios by integrating spatio-temporal interaction modeling, physical constraints, and high-definition (HD) map information.STGT-Gen adopts an encoder-decoder architecture: The encoder captures temporal dependencies of vehicle trajectories and spatial interactions via a Temporal Transformer and a Spatial Graph Transformer, respectively, while a hierarchical map encoding module fuses lane topologies and traffic rules. The decoder ensures physical feasibility during long-term
Qin, Xupeng, Lu, Chao, Wei, Yangyang, Fan, Sizhe, Song, Ze, Gong, Jianwei
Kinematics-Based Differential In-Situ Steering Control for Distributed-Drive Electric Vehicles2025-01-733312/31/2025
In-situ steering can significantly improve the vehicle's maneuverability in narrow spaces, especially suitable for extreme scenarios such as off-road driving and professional operations. For distributed drive electric vehicles, kinematics-based left and right wheel differential control and dynamics-based vehicle yaw control can achieve in-situ steering, however, the two methods have different effects on in-situ steering performance. This paper proposes a kinematics-based distributed drive electric vehicle differential in-situ steering control method, which first establishes the functional relationship between the drive pedal and the expected yaw rate, so that the driver can adjust the steering speed. The initial reference wheel speed is calculated from the expected yaw rate, and the reference wheel speed is adjusted by feedback from the actual and expected yaw rate errors to improve the tracking accuracy. On this basis, the sliding mode control algorithm is used to calculate the
Chen, Jingxu, Li, Yang, Zhang, Yi, Zhao, Hongwang, Qiao, Miaomiao, Wang, Beibei, Wu, Dongmei
Experimental Investigation of Stress Distribution Characteristics in Surrounding Rock during Unloading in Oblique Upper Crossing Tunnel2025-99-024212/23/2025
λλλλ
Wu, Hao, Qin, Shuzhen, Li, Guofeng, Dong, Tianwen, Shi, Yongyue
Research on Dynamic Adjustment Mechanism of Railway Freight Pricing Based on NSGA-II Algorithm2025-99-024812/23/2025
With the implementation of the "road-shift-to-rail" policy and the intensification of competition in the freight transport market, establishing a scientific and effective dynamic pricing mechanism has become a crucial factor in enhancing the competitiveness of railway freight. To address this, this paper constructs a multi-objective dynamic pricing model that comprehensively considers the interests of railway transport enterprises, shippers, and societal externalities. A new multi-objective genetic algorithm (NSGA-II) is designed to solve the model, and an empirical analysis is conducted based on real-world data from "road-shift-to-rail" projects. The research results indicate that the proposed method aligns closely with the current pricing practices of railway transport enterprises. For goods with low time sensitivity, greater freight rate discounts should be offered to shippers, whereas for high time-sensitive goods, the time gap between rail and road transport should be minimized.
Zhang, Hengyuan, Feng, Zhichao, Wu, Xu
Research on Civil Aviation Transportation Scheduling Optimisation System Based on Artificial Intelligence2025-99-023312/23/2025
The rapid development of civil aviation industry makes it difficult for traditional flight scheduling methods to cope with the increasingly complex air transport demand. In this study, an AI-based civil aviation transportation scheduling optimisation system is designed, integrating a novel deep reinforcement learning framework with a validated multimodal fusion algorithm (MMFA) to address spatiotemporal dependencies in aviation data to construct the core architecture of the system. Measurement results show that the system effectively reduces the average flight delay time by 58.1%, improves the slot utilisation rate by 21.3%, increases the flight punctuality rate to 93.7%, and shortens the response time to emergencies by 62.5%. The high performance and significant economic benefits demonstrated by the system in the real environment provide a feasible solution for the intelligent upgrading of civil aviation transport.
Li, Mohan
Trajectory Reconstruction at Signalized Intersections in a Vehicle-to-Infrastructure Environment2025-99-021712/23/2025
Vehicle trajectories encapsulate critical spatial-temporal information essential for traffic state estimation, congestion analysis, and operational parameter optimization. In a Vehicle-to-Infrastructure (V2I) environment, connected automated vehicles (CAVs) not only continuously transmit their own real-time trajectory data but also utilize onboard sensors to perceive and estimate the motion states of surrounding regular vehicles (RVs) within a defined communication range. These multi-source data streams, when integrated with fixed infrastructure-based detectors such as speed cameras at intersections, create a robust foundation for reconstructing full-sample vehicle trajectories, thereby addressing data sparsity issues caused by incomplete CAV penetration. Building upon classical car-following (CF) theory, this study introduces a novel trajectory reconstruction framework that fuses CAV-generated trajectories and infrastructure-based speed detection data. The proposed method specifically
Bai, Wei, Fu, Chengxin, Yao, Zhihong
Research on the Visibility Attenuation Model of Pavement Markings for Older Drivers Based on Retroreflective Luminance Coefficient2025-99-022012/23/2025
222
Cheng, Lizhi, Guan, Yanyan, Cheng, Xinyu, Hu, Jiangbi, Fu, Youlei, Yang, Biyu, Song, Shousong
Development of a Localized Heat Treatment Route for Stamped Automotive Parts2025-36-008912/18/2025
2
Santana, Jessica, Curti, Gustavo, Lima, Tiago, Sarmento, Matheus, Callegari, Bruna, Folle, Luis
Technical management: Focus Matrix Methodology Applied to the 2° GEN of Bosch Flex Fuel Pump2025-36-005212/18/2025
Reliability and performance are critical for product success in engineering. With this aim, the Focus Matrix is a strategic tool designed to enhance the development process by effectively managing technical requirements and prioritizing resources. This paper outlines the application of the Focus Matrix in product development to organize technical packages based on complexity and the technical expertise of the project team. The methodology will be illustrated through a case study on the second-generation Flex Fuel (EVO) fuel pump developed by Bosch. The Fuel pump is responsible for delivering fuel to the engine while maintaining optimal pressure and flow rate. Transitioning to a second generation of a fuel pump focuses on optimizing performance to keep the product relevant in the market, necessitating a thorough analysis of lessons learned and current technological trends. Throughout the development phase, the Focus Matrix provided a structured approach for identifying and mitigating
de Souza, Ana Laura Lima, de Oliveira Melo, Lazaro Benedito, Aguiar, Rayssa Moreno Silva, Azevedo Fernandes, Luiz Eduardo de, Boa, Nathan Barroso Fonte
Design and Construction of a Bench Test System for Elastomers Suspension2025-36-004112/18/2025
This study presents the design, construction, and experimental validation of a test bench for characterizing elastomer-based torsion suspensions in light vehicle applications. The system replaces conventional spring-damper assemblies with viscoelastic elements that simultaneously absorb and dissipate road-induced vibrations. We developed a scaled prototype instrumented with an Arduino-based data acquisition system and analyzed results using Octave®. The experimental protocol comprised: (1) tribological tests to identify optimal friction pairs through coefficient of friction (μ) and wear rate measurements, and (2) dynamometric evaluations of torque transmission capacity, power output, and efficiency across gear ratios (2.03-6.34). Results indicate that a steel-steel friction pair under a normal force of 250-300 N achieves optimal performance, delivering an output power of 1706 W (84.8% efficiency) and a torque of 30.25 Nm. Comparative analysis shows this configuration reduces wear rates
Silva, Diego Bruno, Grandinetti, Francisco José, Castro, Thais Santos, Dias, Érica Ximenes, Souza Soares, de Álvaro Manoel, Martins, Marcelo Sampaio, Reis de Faria Neto, dos Antônio
Analyzing the Operation of Road Cold Chain Transportation Using Big Data in the Context of Cost Reduction, Quality Improvement, and Efficiency Enhancement2025-99-030312/17/2025
In recent years, the market size of cold chain transportation in China has been expanding, but the industry has problems such as low cold chain circulation rate, low efficiency, high damage rate, and high cost. Under the background of reducing costs and improving quality and efficiency in transportation and logistics, an index set for operational analysis covering average freight rates, daily average number of over-temperature alarm incidents, daily average driving distance, and daily average driving time was established from the perspectives of economic efficiency, quality, and efficiency. Based on data from a third-party platform, including vehicle trajectories, temperatures, speeds, and freight rates, the running situation of road cold chain transportation industry was analyzed. The analysis results show that in 2023, the average freight rate of China’s highway cold chain will rebound, the fluctuation range will significantly narrow, the standardization level of temperature control
Li, Sicong, Ye, Jing, Cao, Mengfei
Study on the Performance of High-Pressure Oxygen Cylinder Oxygen Supplemental System in Civil Aircraft Lavatories Based on Airworthiness Oxygen Requirements2025-99-030712/17/2025
This paper focuses on the performance of the high-pressure oxygen cylinder oxygen supplemental system in the lavatory of civil aircraft. Due to the potential safety hazards of chemical oxygen generators in the lavatory, high-pressure gaseous oxygen cylinders are used instead. Through theoretical and study, the influence of the orifice on the oxygen flow rate is thoroughly investigated. Based on relevant principles, the calculation method of the gas flow characteristics in the orifice is determined. Considering the high initial pressure of the oxygen cylinder, the supersonic flow condition within approximately 20 minutes is mainly considered. The Simulink is used to simulate the system flow rate under different temperatures during cabin depressurization. Experimental verification shows that the oxygen flow rate under different temperatures meets the minimum oxygen demand, and the simulation results are highly consistent with the experimental results, indicating that the simulation
Wan, Shuting, Lei, Mingjun, Yu, Xiaoying
Research and Application of Contribution Rate of Acoustic Transfer Function in Vehicles2025-99-034312/17/2025
How to quickly identify weak areas and design redundancies in vehicle acoustic package design is an industry challenge. To address this issue, this paper investigates the relationship between acoustic parts and acoustic transfer function of vehicle. The contribution rates of each acoustic part to acoustic transfer function are calculated, and the area with the highest contribution rate is the weak area of the acoustic package. The area with the lowest contribution rate based on vehicle positioning can be identified as design redundancy. Firstly, establish a three-level architecture of acoustic transfer function - system - acoustic parts, determine the relationship formula between adjacent levels, and then establish the contribution rate relationship formula. Through simulation method, the contribution rate of each acoustic part to acoustic transfer function is obtained. Through test method, the contribution rate of each system to acoustic transfer function is analyzed. And optimize
Liu, Xiaona, Pan, Dianlong, Zhao, Wei, Yang, Xiaotao, Feng, Yihao, Chen, Zuozhong, Zhao, Minghao, Wu, Haichuan
Study on the Wear Resistance of Aggregates Based on Surface Abrasion Characteristics2025-99-031112/17/2025
HmaxWVWmWR
Liu, Yong, Tian, Tao, Hou, Jianwei, Chen, Geng, Wang, Anping
Research on Floating Pricing Strategy of Railway Coal Transportation Considering the Competition of Road and Railway2025-99-035212/17/2025
The market-oriented reform of railway coal transport price is a key initiative to optimize the transport structure and enhance the railway’s market share in coal transport. Based on the competitive relationship between road and railway, this paper explores the impact of the floating pricing mechanism of railway coal transport on the allocation of capacity and enterprise benefits. Firstly, we construct a model to consider the selection behaviour of highway and railway freight transport modes to reveal shippers’ choice of coal transport modes, and analyse shippers’ preference for highway and railway based on transport cost, timeliness and price elasticity; secondly, we combine railway coal transport clearing rules with market-oriented floating pricing policy, establish a pricing decision model with the goal of optimizing transport volume and carrier revenue, and quantify the full railway tariff, transport time and volume, surplus and so on. Secondly, we establish a pricing decision model
Liu, Li, Yang, Lei, Cai, Zhenghong
Vehicle Abnormal Detection Based on Multi-Source Data Fusion and Graph Neural Networks2025-99-043012/10/2025
Traffic abnormal detection is crucial in intelligent transportation systems, while the heterogeneity and weak spatio-temporal correlation of multi-source data make it difficult for traditional methods to effectively fuse and utilize multimodal information. Most of the existing studies use data-level or decision-level fusion, which fails to fully exploit the feature complementarity of multi-source data, resulting in limited detection accuracy. To this end, we propose a multi-source data fusion anomaly detection method based on graph autoencoder (GAE) and diffusion graph neural network (DiffGNN). First, a unified data preprocessing and fusion strategy is designed to perform feature-level fusion of data from on-board sensors, infrastructures, and external environments to eliminate inconsistencies in data format, temporal alignment, and spatial distribution. Then, GAE is employed for potential graph structure feature extraction to enhance the global representation of the data on the basis
Wang, Yaguang, Xiao, Yujie, Ma, Ying
Risk Assessment and Identification of Freight Vehicle Trip Chains2025-99-042112/10/2025
Although the number of trucks is low, their accident rate is high, and the consequences of accidents are severe. This paper is based on GPS data from 100 trucks, with each trip chain defined by a vehicle’s stay time greater than 20 minutes. The kinematic parameters for each trip chain are then extracted, and the entropy weight method is used to calculate the weights of various parameters. A random forest model is applied to select 11 key indicators, including speed and acceleration. The entropy weight-TOPSIS algorithm is used to assess the risk of each trip chain for the trucks. Different combinations of continuous and discontinuous trip chain scenarios are constructed. Finally, support vector machines (SVM) and decision tree methods are used for risk prediction under different trip chain combinations. The results show that the 11 selected key indicators provide an accuracy of 95.74% for describing the sample. In general, the SVM model shows better prediction accuracy than the decision
Huang, Yunhe, Xiong, Zhihua, Li, Jiayu
Research on the Optimization of Cigarette Distribution Route Based on Improved NSGA-II2025-99-043712/10/2025
To address the rigid single-route adjustment problem in China's tobacco logistics, this work proposes an Improved NSGA-II and applies it to optimize cigarette distribution routes. First, a bi-objective model is established that comprehensively considers transportation costs and risks. Second, the algorithm is enhanced by introducing a multi-modal initialization strategy and adaptively adjusting crossover and mutation rates based on population entropy. Finally, validation through simulated data demonstrates that the Improved NSGA-II significantly enhances solution quality and diversity compared to traditional NSGA-II, highlighting its critical significance in the planning of cigarette distribution route.
Li, Wenyong, Sun, Qi, Li, Jiawei, Lu, Rui, Lian, Guan
Impact of Maximum Platoon Size of Connected and Automated Vehicles on Safety of On-Ramp Mixed Traffic2025-99-045412/10/2025
This study investigates how the maximum platoon size (MaxPS) of Connected and Automated Vehicles (CAVs) influences traffic safety within mixed traffic environment on freeway on-ramps. Built upon the SUMO simulation framework, a mixed traffic flow model involving CAV platoons is developed for on-ramp scenarios. This paper examines traffic conditions under varying on-ramp inflow volumes and evaluates upstream speed fluctuations in the merging area. Safety indicators such as Time Exposed Time-to-Collision (TET) and Time-Integrated time-to-Collision (TIT) are employed to assess overall traffic safety. Additionally, collision types are analyzed. Results indicate that under low on-ramp inflow conditions, a moderate MaxPS with low CAV penetration rates significantly enhances safety, whereas a larger MaxPS is preferable with high penetration rates. Under moderate on-ramp inflow, limiting the CAV MaxPS to 2 reduces conflicts. As on-ramp inflow increases further, a MaxPS of 1 or 2 leads to a
Pan, Gongyu, Huang, Yujie, Xie, Junping
Research on the Evaluation System for the Digital Transformation Level of Traffic Infrastructure in the National Integrated Multi-Dimensional Transportation Network2025-99-041712/10/2025
The traffic infrastructure of the National Integrated Multidimensional Transportation Network is a crucial foundational support for building a strong transportation country and a key element in the digital transformation strategy of transportation. This paper focuses on the National Integrated Multi-dimensional Transportation Network and, covering the five sectors of railways, highways, waterways, civil aviation, and postal express, proposes a digital evaluation system for transportation infrastructure. By using an indicator system for the digitalization rate, the study constructs a digitalization rate indicator system for transportation infrastructure through methods such as the Analytic Hierarchy Process (AHP) and Principal Component Analysis (PCA). Historical data from 2013 to 2022 are used for analysis and evaluation. Based on the evaluation results, effective measures and recommendations for the digital transformation of transportation infrastructure are proposed.
Wang, Na, Liu, Na
Research on Urban Traffic Congestion Optimisation Strategies Based on V2X Technology2025-99-011711/11/2025
This study investigates urban traffic congestion optimisation strategies based on V2X technology. V2X technology (Vehicles and Internet of Everything) aims to alleviate urban traffic congestion, improve access efficiency, and reduce tailpipe emissions through real-time collection and fusion of traffic data to optimise traffic signal control and path planning. The efficacy of the optimisation strategies under different V2X penetration rates is evaluated by conducting multi-factor orthogonal experiments in different typical congestion scenarios. The experimental results show that the V2X-based signal optimisation, path induction, and event response combination strategies exhibit significant optimisation effects in all three scenarios: node bottleneck, corridor congestion, and event induction. Under the condition of 100% penetration, the combined strategy reduces delay by 41.9% in the node bottleneck scenario, improves accessibility by 28.1% in the corridor congestion scenario, and
Xi, Chaohu, Li, Jiasheng, Qu, Fengzhen, Liu, Hongjun, Liu, Xiaorui, Wang, Chunpeng
Multi-Objective Optimization-Based Vehicle-Cargo Matching and Route Collaborative Decision Modeling2025-99-011911/11/2025
Aiming at the problem of efficiency loss caused by the independent optimization of traditional vehicle - cargo matching and route planning, this paper proposes a spatio - temporal collaborative optimization model. By constructing three - dimensional decision variables to describe the “vehicle - cargo - route” mapping relationship, a multi - objective mixed - integer programming model considering transportation costs, time - window constraints, and carbon emissions is established. An improved NSGA - II algorithm is designed to solve the Pareto optimal solution set, and the TOPSIS method is combined to achieve scheme optimization. Experiments show that the collaborative optimization model reduces the comprehensive cost by an average of 12.7% and the vehicle empty - running rate by 18.4% compared with the traditional two - stage method.
Yang, Meiru, Liu, Jian
Research on Ship Network Security Situation Awareness and Defense Mechanism Based on Improved Spatiotemporal Attention and Deep Reinforcement Learning2025-99-012611/11/2025
With the development of ship intelligence, network security threats are increasing day by day. This paper proposes a ship network security situation awareness algorithm based on an improved spatiotemporal attention mechanism, and constructs a supporting defense mechanism. The algorithm accurately captures changes in network security situation through dynamic weight allocation and multi-scale feature extraction. In the experimental simulation, OMNeT++ is combined with SUMO to build a ship network simulation environment, and Maritime - CPS - Dataset and other data sets are used for testing. The algorithm in this paper is compared with ARIMA, LSTM, GRU and other algorithms. The results show that in terms of situation awareness accuracy, the algorithm in this paper reaches 95.6%, which is 27.8% higher than ARIMA, 12.3% higher than LSTM, and 10.1% higher than GRU respectively; the average response time of the defense mechanism is shortened to 2.3 seconds, which is 40% faster than the
Kong, Zeyu, Zhou, Bofei, Wan, Shiyao
DriVE-Net: A Multi-Objective Framework for Generating Diverse, Realistic, and Hazard-Aware Driving Scenarios2025-99-013311/11/2025
.
Xie, Dongxuan, Li, Dongyang, Zhang, Youkang, Zhao, Yingjie, Hong, Baofeng, Wang, Nan
Intelligent Decision-Making and Trajectory Planning of Semi-Trailer Trains Under Multi-Vehicle Interference2025-99-012511/11/2025
Semi-trailer trains are the main force of highway freight. In a complex environment with multiple vehicles, accidents are easily caused by complex structures and driver operation problems. Intelligent technology is urgently needed to improve safety. In view of the shortcomings of existing research on its dedicated models and algorithms, this paper studies the intelligent decision-making and trajectory planning of semi-trailer trains under multiple vehicles. A local trajectory planning method based on global path planning and Frenet coordinate decoupling based on the improved A* algorithm is proposed. The smooth weight transition function and B-spline curve are introduced to optimize the global path. The polynomial function is combined with the acceleration rate to optimize the local trajectory. TruckSim, Prescan and Simulink are used to build a joint simulation platform for multi-condition verification. The simulation results show that the search efficiency of the improved A* algorithm
Song, Zeyuan, Geng, Shuai
Research on Irregular ITS-Assisted Covert Communication in High-Speed Railway Environments2025-99-014111/11/2025
To address the high security demands of HSR communication, this letter proposes a covert communication scheme using irregular intelligent transparent surfaces (ITSs) deployed on train windows. A joint optimization framework is developed to enhance covert rate under element constraints, involving ATS for topology design and NECE for beamforming and phase shift. Gradient descent is used to handle covert constraints. Simulations confirm that the proposed irregular ITS outperforms regular ITS in performance and robustness, offering a promising solution for future HSR covert communication.
Jia, Jingwen, Gao, Yunbo, Xie, Jianli
Optimization System of E-commerce Logistics Distribution Path Based on Data Analysis2025-99-010811/11/2025
With the rapid development of e-commerce, the logistics industry also presents new features such as multi-level, integrated upstream-downstream operations, increasingly perfect service quality and low logistics costs. The exponential growth in online transactions and consumer expectations for faster, more reliable deliveries intensifies the pressure on logistics systems. The last-mile service network refers to the logistics nodes that have direct contact with consumers, and its geographical location and quantity will directly affect the service level, cost and customer service mode of the distribution network. However, with the rapid growth in the number of online shoppers and their imbalance on the Internet, these factors have gradually become an important basis for influencing the layout of terminal outlets. This imbalance, coupled with dynamic urban traffic conditions, renders traditional distribution planning methods inadequate. Therefore, in the e-commerce environment, how to
Tong, Tong, Gu, Xuefei, Li, Lingxiao
Big Data Trajectory Analysis and Traffic Flow Framework Construction for Ship Manipulation Decision-Making2025-99-013411/11/2025
We present a novel processing approach to extract a ship traffic flow framework in order to cope with problems such as large volume, high noise levels and complexity spatio-temporal nature of AIS data. We preprocess AIS data using covariance matrix-based abnormal data filtering, develop improved Douglas-Peucker (DP) algorithm for multi-granularity trajectory compression, identify navigation hotspots and intersections using density-based spatial clustering and visualize chart overlays using Mercator projection. In experiments with AIS data from the Laotieshan waters in the Bohai Bay, we achieve compression rate up to 97% while maintaining a key trajectory feature retention error less than 0.15 nautical miles. We identify critical areas such as waterway intersections and generate traffic flow heatmap for maritime management, route planning, etc.
Kong, Xiangyu, Shao, Guoyu
Analysis of Injected Mass Shot-To-Shot Dispersion and Injection Rate Profile for a PFI Injector in Actual Operating Conditions2025-32-001911/03/2025
In order to improve engine emission and limit combustion instabilities, in particular for low load and idle conditions, reducing the injected fuel mass shot-to-shot dispersion is mandatory. Unfortunately, the most diffused approach for the hydraulic analysis of low-pressure injectors such as PFIs or SCR dozers is restrained to the mean injected mass measurement in given operating conditions, since the use of conventional injection analyzers is unfeasible. In the present paper, an innovative injection analyzer is used to measure both the injection rate and the injected mass of each single injection event, enabling a proper dispersion investigation of the analysed low pressure injection system. The proposed instrument is an inverse application of the Zeuch’s method, which in this case is applied to a closed volume upstream the injector, with the injector being operated with the prescribed upstream-to-downstream pressure differential. Further, the injector can inject freely against air
Postrioti, Lucio, Maka, Cristian, Martino, Manuel
Development of Capacitive Pressure Sensor for Automotives2025-28-038710/30/2025
Measurement plays a crucial role in the precise and accurate management of automotive subsystems to enhance efficiency and performance. Sensors are essential for achieving high levels of accuracy and precision in control applications. Rapid technical advancements have transformed the automobile industry in recent years, and a wide range of novel sensor devices are being released to the market to speed up the development of autonomous vehicle technology. Nonetheless, stricter regulations for reliable pressure sensors in automobiles have resulted from growing legal pressures from regulatory bodies. This work proposes and investigates a tribo electric nano sensor that is affected by a changing parameter of the separation distance between the device's primary electrode and dielectric layers. The system is being modeled using the COMSOL multiphysics of electrostatics and the tribo-electric effect. Open circuit electric potential and short circuit surface charge density are two of the
P, Geetha, K, Neelima, Sudarmani, R, C, Venkataramanan, Satyam, Satyam, Nagarajan, Sudarson
3D CFD Analysis of Flow and Thermal Dynamics of PEM Water Electrolyzer2025-28-035010/30/2025
The proton exchange membrane (PEM) water electrolyzer is an emerging technology to produce green hydrogen due to its compactness and producing high purity hydrogen. This study presents a numerical investigation on multiphase flow dynamics and heat transfer within the anode flow field of a PEM water electrolyzer. Two different channel configurations, i.e., rectangular, semi-circular are considered having same cross-sectional area while keeping the porous transport layer (PTL) thickness constant (which is within the commercially available ranges). Simulations are conducted for various oxygen generation rates and heat fluxes (corresponding to different current densities) and different inlet water flow rates. The effects of channel configurations on pressure drop, flow uniformity, and temperature distribution are illustrated pictorially and graphically. The impact of water flow rates and oxygen generation rates on phase distribution, pressure drop, and temperature profiles, particularly
Dash, Manoj Kumar, Bansode PhD, Annasaheb
Simulation of Hydraulic Retarder Using Particleworks2025-28-038210/30/2025
This study explores the application of Particleworks, a meshless CFD solver based on the Moving Particle Simulation (MPS) method, for simulating hydraulic retarders. Two distinct models were used: one for validating physical fidelity and another for conducting performance-focused design investigations. Validation results demonstrated that Particleworks closely aligns with experimental data from the reference literature, effectively capturing torque variations with rotor speed effect. A sensitivity study also emphasized the importance of particle resolution on accuracy and computational cost. Design studies using an in-house hydraulic retarder model assessed the influence of flow rate, rotor speed, working fluid, temperature, and cup geometry on braking torque. Notably, torque increased with rotor speed and steeper cup angles, while thermal effects and fluid properties significantly impacted performance trends. Comparative analysis with Star-CCM+ showed that Particleworks offers similar
Kumar, Kamal S., Chaudhari, Gunjan B.
Automotive Battery Thermal Management by Federated Learning Methodology - Real Time Thermal Runaway Detection2025-28-040810/30/2025
Modern battery management systems, as part of Battery Digital Twin, include cloud-based predictive analytics algorithms. These algorithms predicts critical parameters like Thermal runaway events, state of health (SOH), state of charge (SOC), remaining useful life (RUL), etc. However, relying only on cloud-based computations adds significant latency to time-sensitive procedures such as thermal runaway monitoring. This is a very critical and safety function and delay is not acceptable, but automobiles operate in various areas throughout the intended path of travel, internet connectivity varies, resulting in a delay in data delivery to the cloud and similarly delay in return of the detected warning to the driver back in the vehicle. As a result, the inherent lag in data transfer between the cloud and vehicles challenges the present deployment of cloud-based real-time monitoring solutions. This study proposes application of Federated Learning and applying to a thermal runaway model in low
Sarkar, Prasanta
Items per page:
1 – 50 of 1365