Browse Topic: Design Engineering and Styling

Items (49,136)
A numerical study on the influence of annular gap variation in correctly expanded sonic coaxial jets, focusing on its effect on mixing characteristics and jet symmetry, is presented in this paper. The computational simulations were conducted using a three-dimensional steady-state compressible Reynolds-Averaged Navier–Stokes (RANS) framework with the Spalart–Allmaras (SA) turbulence model. Both symmetric (uniform gap) and asymmetric (nonuniform gap) configurations were simulated. Eccentricity was introduced by offsetting the secondary nozzle by 2 mm downward from the center of the primary nozzle. In symmetric configurations with uniform annular gaps, the jet exhibited balanced shear-layer development, uniform entrainment, and symmetric Mach decay characteristics. However, the asymmetric annular gap configuration exhibited approximately 25–30% earlier potential core breakdown, 30–35% greater radial jet spreading, and nearly 6–10% faster centerline velocity decay compared with the symmetric configuration. The streamline analysis revealed enhanced entrainment, localized recirculation regions, asymmetric vortex generation, and accelerated momentum diffusion caused by unequal shear-layer interaction. These results demonstrate that annular gap asymmetry can serve as an effective passive flow control strategy for enhancing jet mixing and directional momentum redistribution. Such configurations may be useful in practical applications including exhaust gas dilution, fuel–air mixing enhancement in combustors, thrust vectoring, and jet-noise suppression systems.
Chandra Bose, GurusamySudalaimuthu, Ganesan
Rising vehicle complexity and electrification increase the thermal loads on automotive components, making reliable temperature models essential for ensuring thermal operational safety over the vehicle lifetime. Existing approaches (experimental wind tunnel testing, numerical simulation, and purely data-driven methods) lack scalability to many operating conditions, do not provide physically interpretable parameters, or yield inconsistent results when applied across multiple experiments. This paper addresses the gap of fitting a single, physics-constrained temperature model simultaneously across multiple experimental measurements, enabling consistent parameter estimation and prediction of unseen operating conditions. A lumped parameter thermal network (LPTN) is parameterized using a global minimization approach that classifies each model coefficient as global, discrete-global, or local, depending on whether it is shared across all measurements, across a subset with the same design configuration, or varies individually. The method is evaluated on an electronic control unit (ECU) installed in the BMW 7 Series, using nine wind tunnel measurements covering three different cooling strategies (ventilation, heat pipe, metal insert). A single global model fitted to six measurements achieves a root-mean-square error (RMSE) of 1.09 K, while three unseen measurements are predicted with an RMSE of 1.19 K. Compared to conventional single-measurement fitting, global estimation reduces convergence time to 21.2%, while yielding physically interpretable and consistent parameters across experiments. These results demonstrate that global LPTN parameter estimation provides a fast, robust, and physically interpretable framework for automotive thermal operational safety, capable of reliable extrapolation to unseen conditions with sparse experimental data.
Kehe, MaximilianEnke, WolframRottengruber, Hermann
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, YiZhou, JianWu, GangMa, TiannanMa, RuiguangHe, ChuanZhu, Huixian
J1979 DBCJ1979DBC_2026099/16/2026
The SAE J1979 DBC file contains decoding rules for converting raw J1979 data to 'physical values' (Mph, %, etc.). This file lets you easily decode data from heavy duty vehicles (trucks, buses, tractors, etc.). This DBC file download includes: The SAE J1979 DBC file with Includes 2,400+ Parameter Group Numbers (PGNs) and 16,000+ Suspect Parameter Numbers (SPNs), derived from J1979-2 released in September 2026. One legal license (1 user, 1 PC) matching the DA license DECODE J1979: Convert J1979 data in wide range of software/API tools REVIEW FIRST: Use our CAN ID converter to check if your PGNs are covered CROWD INPUT: Benefit from free corrections based on large user base SAVE HOURS: Avoid manually constructing the DBC file from scratch Improved Accuracy & Reliability A fully standardized DBC file ensures precise signal decoding, eliminating errors and ensuring reliable data interpretation. Interoperability Seamlessly compatible with many different software stacks, enabling frictionless adoption and significantly expanding market reach. Partnership with Vector Informatik GmbH Works seamlessly with Vector’s free software (CANdb++), used by over 90% of the industry, with free download link provided on SAEI’s J1979DBC file landing page. What is a DBC file? A DBC file is a standardized method for storing the "rules" on how to interpret raw CAN bus data. It contains details on what 'signals' (e.g. RPM, Vehicle Speed, …) are contained within which 'messages' (i.e. CAN IDs). In the J1979 standard, messages are referred to as Parameter Group Numbers (PGN) and signals as Suspect Parameter Numbers (SPN). Further, a DBC file includes names, descriptions, positions, and lengths of the signals - as well as how to offset & scale them.
The Electro-Mechanical Brake (EMB) system is an essential technology for safe braking in modern vehicles. However, the adoption of multi-controller architectures has introduced new challenges to conventional Safe State strategies. Traditionally, the Safe State defined in functional safety means "function shutdown," and in accordance with ISO 26262-1:2018 (Part 1: Vocabulary), aims for an "operational mode without risks exceeding reasonable levels." However, in the multi-controller architecture of EMB systems, the Fail-Operational Safe State concept is applied, where the system continues to provide limited functions even in the event of faults. It is essential to verify whether such operational modes actually satisfy the safety requirements of ISO 26262-3 and ISO 26262-4. This paper redefines the Safe State according to failure modes in EMB systems, analyzes system state transitions, and presents a coherence analysis methodology for validating the availability of resources required to provide limited functions in the Fail-Operational Safe State. Through this approach, potential design defects in multi-controller-based EMB systems can be detected early, validated across 1,149,952 fault scenarios with zero total-failure outcomes, and traceability of functional safety requirements can be established.
Kim, Kang San
The Electro-Mechanical Brake (EMB) system is a dry-type Brake-by-Wire technology that eliminates hydraulic components and directly controls friction braking using electrical actuators at each wheel. The EMB architecture consists of a Main Center Control Unit, a redundant Backup Center Control Unit, and four Wheel Control Units communicating via CAN FD. Due to its direct involvement in vehicle braking, compliance with ISO 26262 functional safety requirements is critical. As system complexity increases, potential risks such as hardware failures and communication faults must be systematically addressed. The proposed TSC was developed according to ISO 26262, covering the concept phase (Part 3), system-level development (Part 4), and software implementation (Part 6). Safety goals and Functional Safety Requirements derived from HARA are used to guide system architecture design and TSC development. Key design principles include modularity, redundancy, fault detection, and fail-safe operation. Verification is conducted at both system and vehicle levels using ECU-in-the-Loop Simulation (EILS), Hardware-in-the-Loop Simulation (HILS), and real-vehicle tests. Fault scenarios, including Main Center Control Unit failures and CAN communication losses, are injected using a custom LabVIEW-based fault injection tool. The study evaluates Fault Tolerant Time Interval (FTTI) settings, error handling mechanisms, and control handover strategies under fault conditions. The results show that redundancy and localized communication enable stable operation and smooth control transfer within the FTTI window without noticeable impact on braking performance or driver awareness. This study demonstrates the robustness of the proposed EMB architecture. Future work will focus on prognostics and maintenance strategies to support safe deployment in autonomous and electric vehicles. [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
Kim, Dokun
It is hardly a new trend for on road, vehicle intensive tuning and testing of chassis control features such as Anti-Lock Brakes, Traction Control, and Electronic Stability Control to move away from vehicle testing and towards non-vehicle test platforms such as Hardware-In the Loop (HIL) simulations and even further into pure math-based simulations. However, a significant acceleration of these activities has been occurring recently in the automotive industry, reducing or eliminating calibration time on vehicles and amplifying the demand for highly representative, non-vehicle test platforms to validate and even calibrate chassis controls features. In current state of the art HIL simulation, the input (brake pressure) to output (brake torque) of each wheel brake in a vehicle’s brake system is modeled relatively simplistically, including at most pressure and brake temperature sensitivities, usually in lookup table form. Each brake corner contains over 20 different friction interfaces, which in turn can cause hysteretic behavior (a difference in the output for a given input, depending on whether the brake is applying or releasing against the hysteretic friction). This hysteresis is neglected in most state of the art HIL simulations. Past studies by General Motors have shown that the importance of brake corner hysteresis in vehicle level, customer facing performance of chassis controls features can range from inconsequential to significant. With the crescendo-ing demand for high quality non-vehicle based methods for assessing chassis controls function, the effect of hysteresis is no longer academic. The present study starts with HIL based simulations, establishing the effect of brake corner hysteresis on one of the most visible chassis controls behaviors. An inertia dynamometer-based test was developed to exercises the subject brake corners through apply and release cycles, thus enabling any hysteretic behavior to be observed and characterized. Machine Learning models were trained with these data to represent brake corner hysteretic behavior and then deployed into an HIL simulation rig. The impact of these models – representing brake corner hysteretic behavior – was characterized for straight line stopping distance on low, medium, and high coefficient road surfaces.
Antanaitis, DavidRidenour, NickMiller, BryanKarnjate, Timothy
Aiming at the industry pain points of low simulation accuracy and lack of authoritative closed-loop experimental verification for the drag torque of special brake calipers for in-wheel electric motors, this study takes the hub motor-integrated carbon-ceramic inboard caliper as the research object. The inboard caliper layout has been realized on Protean’s in-wheel motor products [12], while the matching integration of the C/C-SiC brake disc with such an inboard structure for a compact hub-motor layout is original and covered by Chinese invention patent CN120207087A[15]. The inboard caliper is defined as a special brake structure installed on the inner side of the brake disc/hub motor cavity (distinguished from the traditional outboard caliper mounted on the outer side of the brake disc), which is specially adapted to the compact assembly space of in-wheel motors and realizes structural integration of braking and driving systems. This study proposes a high-precision finite element simulation method coupling the nonlinearity of piston seal material with bilateral parallel return springs. The simulation boundary conditions are calibrated by matching the bench test working conditions. To verify the simulation results, the drag torque bench test is carried out in accordance with the industry standard [13], realizing a complete closed loop of simulation modeling and experimental verification. Although a certain numerical deviation exists, the high consistency in core trends and key evolutionary nodes, together with a low error (≈5.6%) within the initial 0.9–1 rotation regime, demonstrates that the model reasonably reproduces the generation and attenuation mechanisms of drag torque during the early rotation stage.
Meng, DejianLiu, Yuqihu, PengfeiLi, BiruiShao, Jiyong
Moan noise is a low-frequency noise occurring in the 170–500 Hz frequency ranges. While it frequently appears in vehicles equipped with a rear Coupled Torsion Beam Axle (CTBA), the exact cause, generation mechanism and clear solutions remain unidentified. For those reasons, we have developed a moan noise analysis method capable of representing the moan noise phenomenon in vehicles with rear CTBA along with an automation tool. From these results, we can use moan analysis models to reduce real moan noise problems. Consequently, this not only enhances customer satisfaction and vehicle quality but also significantly increases the work efficiency of vehicle designers through design modification in the preliminary stages of vehicle development
Kim, SunghoKim, JeongkyuHwang, JaekeunKang, Donghoon
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, AbhishekEslamiat, HosseinKancharla, Sai KrishnaFilip, Peter
The brake squeal noise arises from the complex phenomenon of the disc and the friction interface. In fact, even within the same shape of friction material, the noise characteristics vary based on the pattern of the friction interface. However, the current squeal noise simulation does not account for the effects of these friction interfaces; instead, it solely utilizes the friction coefficient and braking pressure to replicate the phenomenon. Consequently, the reliability of the complex eigenvalue analysis results is inevitably compromised. In this study, the complex eigenvalue analysis is conducted by incorporating the actual shape modeling technique of the friction interface, and the validity of the enhanced analysis method is validated through empirical testing. The friction surface modeling technique employed in this study is designed to randomly generate the friction interface of the analytical model by measuring the shape (form, waveform, roughness) of the actual friction surface. To accurately represent the actual friction surface shape in the analytical model, the size of the friction layer is also compactly constructed
Hwang, JaekeunKim, SunghoKim, JeongkyuKang, Donghoon
A unified thermomechanical fatigue (TMF) life-prediction methodology is presented for lamellar graphite (grey) cast iron brake rotors operating under the severe transient thermal loads that arise in brake dynamometer durability testing. The workflow links four ingredients within a single rotor-level framework: transient nonlinear finite-element analysis, temperature-dependent inelastic constitutive modeling, a mechanism-based short-crack TMF damage model, and an elastic-plastic (nonlinear) fracture-mechanics crack-growth simulation. Two constitutive descriptions are exercised for the structural analysis — the standard rate-dependent Chaboche viscoplastic model available in Abaqus, and a user material subroutine (UMAT) that couples Chaboche viscoplasticity with continuum damage in order to reproduce the tension–compression asymmetry of cast iron. The resulting stress, strain, and temperature histories drive a multiaxial thermomechanical fatigue Damage (DTMF) computation that estimates crack initiation and early extension, after which a nonlinear fracture-mechanics procedure simulates crack-front advance toward through-thickness failure. Both constitutive models correctly localize the crack-initiation site on the rotor inner diameter, consistent with the dynamometer observations; for the loading histories examined, the standard Chaboche model yields lives in closer agreement with test. The crack-growth simulation reproduces the rapid post-initiation propagation seen experimentally and resolves branch-wise differences in crack-front evolution through the rotor section.
Lee, HeewookGarcia, ArnoldoLiu, YiHazime, RadwanBoughanmi, HeniKassir, Abdallah
Recently, there has been a drastic shift in the industry towards wire architectures like steer-by-wire and brake-by-wire. For safe and accurate force control, diagnostics, and consistent performance over the operating envelope, accurate plant modeling of the Electro-Mechanical Brake (EMB) is important. Classical approaches involved linearized dynamic EMB models and the use of the characteristic stiffness curve for calibration at the operating points. These methods often perform poorly over regions where hysteresis, compliance, and friction are strongly nonlinear. Prior research on state or force estimation for EMB has focused on pad contact detection, thermal adaptation, and hysteresis-aware clamp force estimation. However, there are still accuracy gaps in practical applications during transients and under shifting friction regimes. In this work, a digital twin based on Physics-Informed Machine Learning is introduced, following the governing dynamics of the actuator-caliper assembly of EMB while learning (i) a physically significant parameter—system damping (Bsys) and (ii) a non-linear friction term constrained as a function of the actuator motion states and operating conditions. Non-linear friction is captured through gray-box friction formulation and learning unmodeled residual dynamics such as hysteresis and backlash. An EMB test stand is used to collect steps, ramps, holds/engagements, APRBS, and swept-sine excitations, with signals including time-aligned force command, motor torque/current, actuator position/velocity, and pad force measurement from a force sensor for model training. Results demonstrate a decrease in pad-force prediction error, along with non-linear and residual friction estimation. The resulting digital twin can enable sensor-less force estimation, friction compensation design, predictive analytics, and health monitoring through tracking parameter drift and friction signatures.
Rai, PrakharGadhvi, Tirth
Teardown evaluation of chassis system components plays a critical role in benchmarking, failure analysis, and competitive product assessment. These inspections rely heavily on experienced engineers who interpret visual defect patterns, material conditions, wear signatures, and manufacturing variations. However, expert driven evaluation processes are often subjective, difficult to standardize, and challenging to scale across global engineering teams. This paper presents a structured AI-assisted expert evaluation framework developed to enhance consistency, preserve institutional knowledge, and enable continuous improvement in chassis component teardown analysis. The proposed system integrates convolutional neural network architectures, including ResNet18 and its variants, into a human in loop inspection workflow. AI models perform initial classification of component images (e.g., OK/not OK and defect subclasses) and provide associated confidence scores. These predictions are presented as decision support, while final authority remains with the evaluating expert. Experts can confirm or override AI outputs, annotate defect regions using bounding boxes, assign subclass categories, and provide structured technical comments. All expert interactions, including AI disagreements, are systematically recorded. Correction instances are analyzed to identify model limitations, ambiguous defect conditions, and data gaps. Expert validated evaluations are incorporated into the training dataset to enable iterative model refinement. This closed loop process supports progressive improvements in model robustness and classification accuracy across varying teardown conditions and component types. A centralized cloud-based repository maintains full traceability of inspections, including timestamps, AI confidence levels, expert modifications, and annotation metadata. This structured knowledge capture converts tacit engineering judgment into a persistent digital asset, supporting auditability, cross-site alignment, and accelerated onboarding of new engineers. The framework demonstrates how AI can be effectively deployed as an assistive technology in chassis teardown evaluation, improving repeatability, enhancing data driven benchmarking, and enabling scalable knowledge preservation without displacing expert authority.
Divakaruni, SaikiranVaibhav, VeerHansen, ScottHood, TrevorAgrawal, Rahul
The current work presents a novel approach to estimating brake surface temperature in real-time to aid in brake wear prognostics. Brake prognostics involve estimating brake pad wear in real-time, which enables its predictive maintenance. Brakes are a safety-critical system for vehicles; therefore, they require accurate and robust pad wear estimation to ensure vehicle safety. However, it involves several challenges. The estimation of pad wear is fundamentally a two-stage process: the first stage involves the accurate prediction of brake pad surface temperature, while the second stage utilizes this thermal history to calculate cumulative material wear. A significant challenge in estimating brake pad wear without an expensive sensor is that it is sensitive to the surface temperature prediction; any error in the thermal model propagates and compounds in the wear prediction stage. To identify surface temperature, traditional physical sensors are often cost-prohibitive or prone to failure in the harsh thermal and mechanical environments of the wheel end, necessitating a robust virtual sensing solution that can capture complex, non-linear heat transfer dynamics. The current work addresses the above challenge of identifying temperature dynamics using a Physics-informed Machine Learning approach. We employ Symbolic Regression (SR), a data-driven method that discovers the underlying mathematical expression of the system dynamics by searching for the optimal functional relationship between variables. SR provides an interpretable model that can be generalized across automotive platforms, offering a transparent, computationally efficient, and analytically tractable alternative to traditional ‘black box’ models. To generate the temperature dataset, a test vehicles were equipped with thermal sensors and underwent various braking scenarios. The SR-based virtual sensing model demonstrated strong and consistent predictive fidelity across all braking conditions tested. Under mild braking scenarios, the model achieved a Mean Absolute Percentage Error (MAPE) of approximately 6.0% in predicting brake surface temperature. This performance remained highly robust under mixed and harsh, high-speed braking, the most thermally demanding scenario, yielding MAPEs of only 11.6% and 11.9%, respectively.. Across all regimes, this level of temperature estimation fidelity directly limits error propagation into the downstream brake pad wear prediction stage, enabling reliable, sensor-less, cloud-based brake health monitoring at scale.
Gannavarapu, ShivadathPal, AnujFan, Mengdi
Air tightness in brake calipers is a critical requirement for ensuring braking system reliability and safety. However, defining a clear and practical analytical criterion for air leakage prediction remains challenging due to the complex contact behavior at the seal–piston interface. This study presents a virtual methodology to define an air tightness criterion for brake calipers based on experimental evaluation and structural analysis. The seal squeeze ratio was selected as the primary design variable to evaluate its effect on sealing performance. Test samples with different seal squeeze ratios were manufactured, and air tightness was tested under controlled pneumatic pressure to determine when leakage occurred. In parallel, a finite element (FE) structural analysis was conducted to simulate the seal installation process and quantify the resultant contact pressure distribution between the seal and the piston surface. To support reliable structural analysis, preliminary experiments were performed to determine the hyperelastic properties of the seal elastomer. Furthermore, the seal squeezing force was experimentally verified. The experimental results showed that low seal squeeze ratio caused leakage, demonstrating that seal compression strongly affects sealing performance. Based on these observations, an analytical criterion was established using the contact pressure between seal and piston, with a minimum contact pressure defined to prevent air leakage. Although a direct quantitative correlation between air leakage and contact pressure was not determined, the proposed criterion provides a practical and physically meaningful basis for evaluating air tightness. This methodology allows designer to predict sealing performance during the product design, reducing a necessity for extensive testing and enabling more efficient and reliable brake caliper development.
Cho, InyongKim, Beomseok
This study conducted a comprehensive economic evaluation of two major HEV architectures: the series-parallel configuration and the range-extended configuration. An analysis of these two configurations was performed using integrated vehicle and control models, allowing for a direct comparison of energy efficiency and operational economy. Findings show that the range-extended configuration has clear advantages in structural complexity, simplicity of control strategy, and development cost, while its energy consumption performance is similar to that of the series-parallel configuration. The results challenge the long-standing notion that range-extended configuration is less efficient, offering a new perspective on the design and configuration choices for hybrid electric vehicles.
Li, PingGuo, WencuiNie, GuoleNiu, YazhuoBai, Bateer
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, YonghengZhang, RuizhengSun, ChaoZeng, XinjieZheng, Liwen
Taking the newly constructed Maanshan Yangtze River Highway-Railway Dual-Purpose Bridge — a three-tower steel truss cable-stayed bridge with two main spans of 1120 meters — as the research object, this study systematically explores the influencing factors and evolutionary characteristics of hole wall stability for large-diameter bored piles in thick sand layers. The research results reveal the following mechanisms: with the expansion of pile diameter, the hole wall generates greater deflection, the soil’s internal arch effect is gradually attenuated, soil cohesion decreases, and the plastic zone of the soil surrounding the pile shows a tendency of outward extension, collectively increasing the susceptibility to hole collapse. To maintain hole wall stability, the resultant force of the internal circular arch support and mud pressure must exceed or equal the total lateral pressure, including active earth pressure, formation water pressure, and ground surcharge-induced lateral pressure. Notably, soil shear strength and mud relative density are two dominant factors controlling hole wall stability, and a positive correlation exists between these two parameters and stability. Specifically, a mud relative density range of 1.15–1.25 is recommended for practical construction. These findings offer valuable technical references for the design and construction of similar large-diameter bored pile projects in thick sand layers.
Ye, TaoWang, Ruyi
With the continuous improvement of ship intelligence, more intelligent onboard navigation equipment and intelligent navigation systems are used to assist in improving navigation efficiency. This study takes semi-autonomous navigation ships as research objects and adopts System-Theoretic Process Analysis (STPA) to model the complex interaction relationships of semi-autonomous navigation encounter scenarios and identify and analyze potential risks. To address the deficiency of STPA in human factors analysis capability, the Cognitive Reliability and Error Analysis Method (CREAM) is introduced to analyze human factors in semi-autonomous navigation. Finally, based on the results of the STPA-CREAM analysis, recommendations are provided to improve the safety of semi-autonomous navigation.
Zhang, Xiaojie
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, XiaoZhang, Jing
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, GuoweiMa, WenlongJiang, DaliLi, Nan
As system automation advances, the impact of human factors on human-machine system reliability becomes increasingly prominent. Given that the metro train dispatch system is central to metro operations, analyzing its human reliability aspects is crucial. Although human factor reliability analysis techniques have matured in fields like nuclear power and aviation, research on human-factor reliability analysis for metro train dispatch systems remains in its infancy. Based on this, the study proposes a method for identifying factors influencing human-factor reliability in metro train dispatch systems using exploratory factor analysis, grounded in survey data on such factors. Second, based on the identified factors, a structural equation model was constructed to identify the importance of human reliability factors in metro train dispatch systems. Through goodness-of-fit evaluation, the causal relationships among these factors were ultimately determined. The study indicates that individual, organizational, equipment, and environmental factors are the primary influences on human reliability in metro train dispatch systems, with 20 observable sub-factors under these main categories. The structural equation model results indicate that the relative importance of the four primary factors on human-factor reliability in the metro train dispatch system is: organizational factors > personal factors > equipment factors > environmental factors. This suggests organizational factors exert a relatively greater influence on human-factor reliability. This research provides a basis for enhancing the safety level and management decision-making of metro train dispatch systems.
Li, XinWang, LiangTang, ShuoYao, Zhenxing
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, GuanboZhang, Liwei
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, MingyiZeng, GuoqiGu, XinZhuWang, Jia
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, LuLin, LiXu, ShichaoJi, GuanggangLi, Zheng
To provide better data support for the aerodynamic design, flight control system design, and parameter optimization of helicopters, it is necessary to obtain the aerodynamic derivatives of the helicopter rotor based on flight test data and analyze the static stability of the helicopter rotor. This paper breaks through the limitations of aerodynamic testing of helicopter rotors and establishes a quantitative analysis method for the static stability of helicopter rotors in level flight based on flight test data. Based on the flight test data of the helicopter, this study establishes an aerodynamic model of the helicopter rotor and employs a genetic algorithm for parameter identification to obtain the aerodynamic derivatives of the rotor in level flight. The identified parameters are then used to quantitatively analyze the static stability of the helicopter rotor. The results show that the method developed in this study can accurately and effectively obtain the aerodynamic derivatives of the helicopter rotor from flight test data. Furthermore, this method can reliably evaluate the static stability of the helicopter rotor, demonstrating significant value for engineering applications.
Zhao, Jingchao
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, WenjianDong, Fulong
In view of the large volume and weight of the tires of mining dump trucks and the difficulty in replacing them, a large tire replacement robot is proposed based on the tire parameters and the tire replacement process. The overall research scheme for the robot was developed using the functional analysis method, and the functional element solution and combination were completed. Based on the best solution obtained, a three-dimensional model of the tire changing robot was established using the SolidWorks software, followed by control system design and workflow analysis. To investigate the robot's operational kinematics, a simulation was conducted in the SolidWorks Motion module. The motion curve of the flipping platform during its operational state was obtained. A finite element simulation of the robot's front support beam was performed using ANSYS Workbench to obtain its stress and deformation contours under both no-load and heavy-load conditions. The structural parameters of the front support beam were optimized, focusing on its mechanical characteristics under heavy-load conditions, and the response surfaces of different parameters were obtained. The optimization yielded a 9.599 kg reduction in the mass of the front support beam. The maximum stress of the grasping mechanism under static simulation analysis is 50.617 MPa, with the maximum deformation of 0.4221 mm occurring at the end of the mechanical hand. Ground contact simulation for the robot's walking tires was conducted with Abaqus. Employing the Mooney-Rivlin hyperelastic model, this study investigated the mechanical response of the tire to static and dynamic loading, leading to the identification of the optimal operational load. The simulation results show that there is no interference among the various mechanisms of the large tire changing robot during operation. It can quickly complete the tire installation and removal tasks with precise control, and its strength and rigidity meet the requirements. This verifies the rationality and feasibility of the robot. The research on the large tire changing robot can provide a new approach for the maintenance of large transport vehicles such as mining dump trucks.
Tian, LiyongZhang, Haijian
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.
Qiao, JiajunJin, ZhenhuaHuang, QiLi, GuohuiZhang, Xinguo
A nonlinear finite element model was applied to study the in-plane instability of steel portal piers, in which initial geometric imperfections, welding residual stresses, and material nonlinearity were considered. The modeling procedure was compared with experimental results from box-section members, and consistent tendencies in load level and deformation evolution were observed. In the numerical analyses, the initial elastic buckling configuration exhibited an in-plane antisymmetric form. As loading continued beyond the elastic range, this deformation pattern persisted. With further loading, the deformation remained purely axial while combining compression with bending. During this stage, plastic hinges appeared near the column tops, while lateral displacement became clearly observable. Comparison models with different geometric proportions show that variations in the span-to-height ratio and the beam–column stiffness ratio influence how instability develops and where plastic deformation tends to localize. From a design perspective, these trends can be considered when distinguishing instability characteristics and selecting stiffness proportions between beams and piers.
Li, JieShangguan, BingCheng, ZhangxuRuan, FurongBai, Fan
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, HuiZhao, XuezhanTian, Jiahao
A railway junction is a crucial point on a railway network where multiple routes intersect and many train services run through it. Its connectivity to different railway routes can increase demand and traffic in shared corridors, turning the junction into a bottleneck. Upgrading the signalling system is one of many solutions to manage the traffic utilization and increase the capacity at the junction. The Virtual Coupling System (VCS), as the latest signalling technology, has proven to improve the capacity of the railway. However, many junction-related factors remain inadequately addressed. In this paper, we introduce the constraint of differences in speed limits between the main route and the secondary route to design a merging process in which three trains from different routes can start merging or coupling into VCS mode as they approach the converging point at a junction under different train sequence scenarios. A Finite State Machine (FSM) model is developed to control the train motion under VCS. Secondly, simulations are performed to compare the travel time required for the following train to reach the last milepost under VCS with that under the traditional Moving Block (MB) system, as well as to compare overall capacity. The simulation results show that the second and third trains can arrive at the final milepost earlier under VCS mode than under the MB system. In addition, the theoretical operational capacity under VCS mode improves compared to MB mode when a proper train sequence design is selected.
Jaimonkong, NitipatKetphat, Naphat
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, ChenMa, Huimin
Point cloud registration represents a fundamental task in geospatial informatics and 3D computer vision, aiming to align heterogeneous point clouds through rigid transformation estimation. While Super-4PCS serves as an efficient coarse registration method, it exhibits limitations when handling large-scale datasets, planar-distributed point clouds, and scenarios with unknown scale differences. To overcome these challenges, this paper proposes the Nc-5PCS (Neighborhood-constrained 5-Point Congruent Sets) algorithm. Nc-5PCS first performs approximate scale estimation through concavity-convexity similarity analysis within coarse overlap regions, addressing the inherent scale limitation in 4PCS-based approaches. Subsequently, the algorithm employs 3D Harris feature point extraction to significantly reduce data volume while preserving critical geometric characteristics. The core innovation lies in designing a non-coplanar 5-point basis with a corresponding hash-based retrieval mechanism, effectively resolving the feature degradation problem caused by coplanar 4-point bases. Furthermore, normal vector angular constraints are incorporated to enhance consensus evaluation during correspondence selection, substantially improving registration accuracy. Experimental validation demonstrates that Nc-5PCS achieves a point-to-point RMS error of ≤ 0.227 m, outperforming Super-4PCS to provide superior initial alignment for subsequent ICP refinement.
Liu, LeiYu, KeguangLi, XinyiSun, GuangdeZhao, XinyuanZhu, DongniFan, YaboGuo, Shihao
This paper designs an onboard integrated liquid cooling system for a specific electronic device’s thermal management requirements. The system combines a turbo-turbo-compressor (TTC) turbine with a liquid-cooled subsystem through heat exchanger coupling. Building on previous research, the design schematic view is divided into two components. Using the Amesim simulation platform, we developed component-specific modules and established the system’s simulation module based on this schematic view. Performance simulations under various extreme operating conditions demonstrated the system’s effective applicability across the entire flight envelope.
Zhang, SunyanZheng, WenyuanZhan, Hongbo
During expressway reconstruction and extension, when a traffic accident occurs, how to make a scientific and reasonable allocation of emergency resources is the premise and basis for efficient rescue. In view of the reconstruction characteristics and the complexity of emergency rescue, the number of casualties, the damage degree of road facilities, the number of damaged vehicles, the range of hazardous chemicals, the size of the fire, and the traffic order were used as the accident attribute indexes to build a historical accident set (case database). The allocation of emergency rescue resources was predicted using case-based reasoning techniques. Also, the corresponding reasoning prediction method was proposed. The research shows that this model can accurately predict the demand for emergency rescue resources during the period of expressway reconstruction and extension, which has good availability and operability, and provides methodological and modeling support for the emergency rescue resource decision system.
Ran, JinZhan, ShiyangKadir, AhmetjanMa, JiaruiDai, Xiaomin
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, YanmeiWang, ChenFu, ZiyueMeng, Xianglong
With the advancement of computer vision technologies and the widespread deployment of video surveillance systems, traffic safety and the development of intelligent highways have been significantly enhanced. As a key component of the intelligent video analysis module in smart highways, person re-identification (re-ID) addresses critical challenges, including cross-segment tracking of pedestrians illegally using emergency lanes, multi-camera joint searches for lost persons in service areas, and trajectory tracing of individuals involved in traffic accidents. These functions directly support the core goals of "safety assurance and efficient service" for smart highways. However, due to the complexity of the application scene, its generalization to unseen environments remains a core challenge. This problem is formally studied under the setting of Single-Domain Generalizable Person Re-identification (SDG re-ID), which aims to train a model on a single source domain that can perform well on arbitrary unseen target domains. To handle this issue, this paper proposes a novel Disentangled Augmentation re-ID Framework (DisReID) that disentangles and augments both structure and style. Specifically, DisReID consists of two modules: Structure-aware Viewpoint Simulation (SVS), a novel pre-processing technique that simulates cross-camera perspective changes by perspective transformation, diversifying geometric structure without harming identity semantics; and Style-Dominant Frequency Perturbation (SFP), which selectively focuses on the style-dominant frequencies and applies perturbation to enable controllable style augmentation while preserving structure cues. Furthermore, to alleviate the BN-induced domain bias, we introduce a simple yet effective test-time adaptation strategy, termed Cluster Fine-tuning (CF), that performs unsupervised clustering on target-domain features to assign pseudo-labels and subsequently fine-tunes the model, enhancing adaptability to unseen domains. Extensive experimental results on four public datasets demonstrate that our DisReID achieves superior generalization performance compared to the state-of-the-art methods. This work provides key technical support for the large-scale application of re-ID in smart highways, advancing the goal of "full-domain perception and intelligent collaboration".
Pan, HongYu, Fangying
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, PenghuiMei, YananFu, Jinhua
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, TaoCao, XiaopingZhang, ShulinYang, Zibin
With the increasing demand for efficiency, flexibility, and cost-effectiveness in the aviation manufacturing industry, the prototyping cycles of aircraft development have significantly shortened. Traditional assembly fixtures, due to their high degree of customization and poor reconfigurability, struggle to meet the requirements for rapid prototyping of multiple aircraft models. To address this issue, research has been conducted on reconfigurable framework structures for aircraft assembly fixtures, and finite element analyses have been performed on different types of reconfigurable fixture frameworks. The study indicates that although the stiffness of reconfigurable frameworks is slightly lower than that of traditional welded framework structures, it still meets the requirements for rapid prototyping of development aircraft. By adopting standardized, low-cost reconfigurable assembly fixtures, the design and manufacturing cycle of tooling can be significantly shortened, and the reusability of tooling components can be enhanced, thus facilitating rapid and cost-effective development of prototype aircraft.
Wang, XingzhongWang, HongtaoLiu, BingBi, XinyingLiu, Zhanzhan
Aiming at the technology of electric intelligent working boat towing 4 ships in group lockage during the construction period of the Gezhouba Shipping Capacity Expansion Project, this paper, starting from ship dimensions, conducts an adaptability analysis on electric intelligent working boat towing ships in group lockage for all ships passing through Gezhouba No. 1 and No. 2 Ship Locks throughout 2024, based on the two-dimensional packing model, ship lock chamber scheduling model and algorithms, navigation scheduling rules and safety management regulations, the results show that ships unsuitable for being towed in group lockage through Gezhouba No. 1 Ship Lock account for approximately 26% of the total number of ships passing through it, while those unsuitable for being towed in group lockage through Gezhouba No. 2 Ship Lock account for approximately 57% of its total passing ships. Meanwhile, ships passing through the three Gezhouba ship locks on a specific day are selected, and an adaptability analysis on the dimensional suitability of electric intelligent working boat towing these ships in group lockage is carried out under the scenario where these ships only pass through Gezhouba No. 1 and No. 2 Ship Locks. The results show that the number of ships with suitable dimensions for group lockage accounts for the majority of the ships passing through the locks on a selected specific day. On this basis, combined with the operation modes of Gezhouba No. 1 and No. 2 Ship Locks, an analysis is carried out on the traffic organization, potential risks, corresponding countermeasures, and the required quantity of electric intelligent working boats for towing ships in group lockage, targeting the three main collaborative operation modes. The results can provide a basis for the future practical application of electric intelligent working boat towing ships in group lockage during the construction and operation periods of the Gezhouba Shipping Capacity Expansion Project.
Huang, ShaowenYang, XiWang, Jian
In order to solve the problems of long preheating time and high energy consumption caused by the traditional resistance heating track deicing technology and large power supply load, this paper presents a track deicing and road maintenance method based on electromagnetic induction heating. This paper studies the operational bottlenecks of the resistance heating system in a certain marshalling yard. It explains the eddy current heating from the principle of electromagnetic induction heating and designs an appropriate coil for turnouts and derives its power calculation formula. A mathematical model for the 'solid-liquid' phase transformation in the melting of snow is created and the melting parameter α = 0.623. In comparative experiments, compared to a 4kW electromagnetic induction heating device with no preheating time which melts snow up to 5cm in 40 minutes and consumes 40kW · h of energy in 1 hour, a 13kW resistance heating device needs 150 minutes to preheat, 180 minutes to melt, and consumes 130kW · h of energy. Use 70% less energy and help with track and road de-icing and upkeep with this technology.
Song, ZongyingLi, ZhongmingWei, DongYang, JinWang, XingzhongLiu, JingweiZhang, Xiaoyu
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, YanweiZhang, XiufengYu, YingjieWang, LucaiZhao, Weihang
In order to conduct more in-depth research on the driving sight distance of curved tunnels in mountainous highways, a systematic theoretical calculation model of spatial sight distance of curved tunnels based on three-dimensional characteristics is established, and the spatial sight distance value of curved tunnels in mountainous highways is recommended in combination with the changes of driving behaviour under different spatial sight distances. Firstly, the concept of spatial sight distance of curved tunnels is proposed, the theoretical calculation model of spatial sight distance of curved tunnels is established, and the model is verified by a multi-scale neural network; Secondly, five UC-win/road simulation models of curved tunnel with different spatial sight distances are established, and the simulation experiments are carried out in combination with mp160 multi-channel physiological recorder and SMI etgtm eye tracker; Finally, the mathematical statistics method and SPSS software are used to analyse the operation behaviour, psychological behaviour and eye movement behaviour of drivers in curved tunnels with different spatial sight distances, and to verify the different effects of the critical value of spatial sight distance on driving behaviour in the theoretical calculation. Furthermore, by taking the spatial sight distance as the independent variable, the regression model is established with the average speed, trajectory offset, heart rate change rate, and pupil diameter change rate as the dependent variables. Based on the driver’s behaviour threshold, the recommended spatial sight distance of a curved tunnel is proposed. The results show that the recommended range of spatial sight distance of the curved tunnel of mountainous highway with a design speed of 80 km/h is 125 m to 140 m, the limit value is 110 m, and the appropriate value is 155 m. There is a critical value between two-dimensional sight distance and spatial sight distance, which has a significant impact on the change of driving behaviour in a curved tunnel.
Tang, XieZheng, LiWenLin, GuoJinGao, YanYangLan, FuAn
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, YunchuanWang, XiaomengWang, Yan
Flared tube fittings are extensively utilized in pipeline systems due to their effective connection and sealing capabilities. However, during practical service conditions, transversal vibration frequently induces thread loosening, subsequently leading to seal failure and other malfunctions. Current research lacks a systematic investigation into the loosening behavior of flared tube fittings under transversal vibration conditions. This study establishes a precise finite element model of the flared tube fitting and systematically examines its loosening behavior under stress redistribution, plastic deformation, and fretting wear conditions by simulating the assembly process and applying cyclic transversal vibration loads. The research findings demonstrate that the loosening process of flared tube fittings occurs in two distinct stages. The initial stage primarily involves preload reduction caused by non-rotational factors such as stress redistribution, while the subsequent stage features continuous preload attenuation resulting from relative rotation between internal and external threads. Notably, a critical amplitude has been identified. When the actual transversal amplitude remains below this critical value, only non-rotational loosening occurs in the flared tube fitting, with no rotational loosening taking place. Further investigation into factors affecting the critical amplitude, including preload, friction coefficient, material properties, and thread type, reveals that preload, friction coefficient, and material elastic modulus significantly influence the critical amplitude, whereas thread type demonstrates a negligible impact. These findings provide valuable insights for enhancing the reliability of flared tube fittings in vibration-prone applications.
Liu, ChangLi, MuxiaoChen, HanlinXu, DongGong, Zhengchao
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, SonggeWang, Jingyue
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, KaXu, Yerong
Items per page:
1 – 50 of 49136