World Journal of Engineering Research (WJER) is an international peer-reviewed, open access journal.
DYNAMIC EARLY WARNING MODELING OF PASSENGER AGGREGATION RISK AT RAILWAY PASSENGER HUBS
Under conditions such as holiday travel peaks, concentrated train arrivals and departures, and operational disturbances, railway passenger hubs are prone to localized passenger aggregation in key areas such as security checkpoints, waiting halls, ticket gates, and platforms, which may further lead to congestion propagation and operational risk. To address the limitations of existing studies, including insufficient focus on railway passenger hub scenarios, inadequate dynamic characterization of risk identification, and limited management orientation of warning results, this study investigates the dynamic early warning of passenger aggregation risk at railway passenger hubs. First, the formation mechanism of passenger aggregation risk is analyzed from the perspectives of passenger demand fluctuations, facility service capacity constraints, and operational disturbance propagation, and a risk indicator system is established from three dimensions: passenger-state conditions, facility operations, and disturbance factors. On this basis, a dynamic early warning framework consisting of data input, state identification, risk assessment, and warning output is proposed to support graded identification and dynamic response for passenger aggregation risk in key functional areas. Finally, an illustrative case study is conducted to demonstrate the applicability of the proposed framework. The results show that passenger aggregation risk at railway passenger hubs exhibits significant time-varying, spatially heterogeneous, and propagative characteristics, while bottleneck areas such as security checkpoints and ticket gates are more sensitive in both risk formation and escalation. The proposed framework is capable of representing the evolution of risk and translating operational states into graded warning results with direct managerial relevance. This study provides theoretical support and methodological guidance for passenger flow safety management and operational optimization at railway passenger hubs.
Copyright (c) 2026 Yuan Fang; Zheng Han; XinShan An; Jie Liu; Liang Zhu https://creativecommons.org/licenses/by/4.0
CURRENT HARMONIC SUPPRESSION STRATEGY OF PERMANENT MAGNET SYNCHRONOUS MOTOR BASED ON MULTI-SYNCHRONOUS ROTATING COORDINATE SYSTEM
This paper focuses on the harmonic problems of stator current in permanent magnet synchronous motor (PMSM) caused by factors such as magnetic circuit saturation and inverter nonlinearity, and conducts research on harmonic suppression strategies based on multiple synchronous rotating coordinate systems. Firstly, the hazards of harmonics to motor efficiency, torque stability, and system reliability are analyzed, and the engineering significance of harmonic suppression technology is expounded. On this basis, a mathematical model of PMSM containing 5th and 7th harmonics is established, and a harmonic extraction and compensation method combining low-pass filtering and closed-loop PI control in multiple synchronous rotating coordinate systems is proposed. By constructing a coordinate system that rotates synchronously with the harmonics, the harmonic components are converted into direct currents for precise suppression, and the corresponding control structure is designed to achieve harmonic voltage compensation. Simulation results show that this strategy can effectively reduce the total harmonic distortion of stator current and improve the current waveform quality at different speeds of 500 r/min and 1500 r/min, verifying the effectiveness and practicality of the proposed method under different operating conditions, and providing a feasible control solution for high-performance and low-harmonic operation of PMSMs.
Multiple synchronous rotating coordinate systems
Copyright (c) 2026 Zhi Tan; QinFeng Hu https://creativecommons.org/licenses/by/4.0
INFRARED SPECTROSCOPY-BASED ONLINE MONITORING SYSTEM FOR MICROBUBBLE CONCENTRATION
To address the urgent need for the real-time and precise monitoring of microbubble concentrations in industrial fluids, an online monitoring system for microbubbles was developed based on the principles of infrared spectroscopy sensing and light intensity attenuation, featuring an architecture that integrates array-based infrared photoelectric sensing with cloud collaboration. A 'three-emitter, three-receiver' array-based infrared detection scheme is adopted to effectively mitigate the issue of poor sample representativeness associated with single-optical-path detection in complex fluid phases. Centered around a Raspberry Pi as the primary controller, the system incorporates precise photoelectric signal conditioning circuitry, high-resolution analog-to-digital conversion modules, and industrial communication links. A dual-channel data communication architecture based on the RS485 bus and the MQTT IoT protocol was established. Testing demonstrates that the system exhibits high real-time performance, strong anti-interference capability, and excellent digital management features, enabling both on-site real-time monitoring of microbubble concentrations and remote visualization via a cloud dashboard.
Copyright (c) 2026 Peng Liu; ChangCheng Wan; Long Xie https://creativecommons.org/licenses/by/4.0
HEALTH‑MONITORING‑BASED INVESTIGATION OF THERMAL EFFECTS ON DOUBLE‑RIBBED PLATE GIRDERS OF CABLE‑STAYED BRIDGES
To investigate the temperature-induced effects on double-ribbed plate girders in cable-stayed bridges, this study leveraged health-monitoring data from the Poyang Lake Bridge. The temperature field distribution was analyzed using ABAQUS, and a full-bridge model was established in Midas/Civil 2021 to examine the mechanical responses of the main girder under overall temperature differences and temperature gradients. The results showed that under the overall temperature drop of 19 °C, the main girder experienced a maximum tensile stress of 6.44 MPa, with extreme vertical and longitudinal displacements of 21.3 mm and 54.6 mm, respectively. Under the overall temperature rise of 21 °C, the maximum compressive stress reached -7.12 MPa, and the extreme vertical and longitudinal displacements were 23.5 mm and 60.4 mm, respectively. Under a positive temperature gradient, the maximum compressive and tensile stresses were -5.47 MPa and 3.52 MPa, respectively, with extreme vertical and longitudinal displacements of 55.1 mm and 26.5 mm. Under a negative temperature gradient, the maximum tensile and compressive stresses were 1.81 MPa and -3.03 MPa, respectively, with extreme vertical and longitudinal displacements of 32.8 mm and 13.5 mm. A comprehensive comparison reveals that the overall temperature difference exerts a more pronounced influence on longitudinal displacement, whereas the vertical temperature gradient, has a more dominant effect on vertical displacement.
Copyright (c) 2026 Bo Liu; XiaoQiang Xue; WenQiang Huang https://creativecommons.org/licenses/by/4.0
THE DYNAMIC MECHANISM OF HEAVE IN OSCILLATING BUOY-TYPE WAVE ENERGY DEVICES AND THE OPTIMIZATION OF ENERGY HARVESTING SYSTEMS
This paper presents a systematic study on dynamic modeling and parameter optimization to address the energy capture efficiency of wave energy conversion devices in the vertical oscillation mode. Based on Newton’s second law, the study establishes a coupled second-order nonlinear differential equation system describing the motion of the float and the embedded oscillator, comprehensively considering the interactions among wave excitation forces, wave-induced damping forces, hydrostatic restoring forces, and the energy output system. To solve this strongly coupled system of equations, the fourth-order Runge-Kutta method was employed to calculate time-domain responses, yielding precise dynamic characteristics of system displacement and velocity at extremely small time steps. For evaluating energy conversion efficiency, a single-objective optimization model was formulated to maximize steady-state average output power, utilizing Riemann integration and approximation methods to handle the discretized integration of instantaneous power. By introducing a Bayesian optimization algorithm, the study achieved efficient heuristic search within the complex damping parameter space. Experimental results show that under two typical operating conditions—constant damping and power-law damping—the system achieved the expected power capture targets through optimal damping coefficient configuration, with a maximum average power of 228W. These findings provide quantitative evidence for the structural optimization of wave energy devices and the formulation of PTO system strategies.
Copyright (c) 2026 YuHang Xiao https://creativecommons.org/licenses/by/4.0
UNMANNED LEAF SWEEPING AND CRUSHING VEHICLE
In urban and campus environments, fallen leaves accumulate extensively. The research team has developed an unmanned leaf sweeping vehicle to improve cleaning efficiency and reduce labor costs. The innovative features of this unmanned leaf sweeping vehicle lie in its unmanned driving software technology and built-in navigation function. The hardware design adopts corrosion-resistant hard materials, high-speed and energy-saving motors, adjustable cleaning brushes, vacuum cleaners, and large-capacity lithium batteries, enabling the sweeping vehicle to achieve intelligence, high performance, high efficiency, energy saving, and environmental protection. The core contents of the unmanned leaf sweeping vehicle include: control of driving speed and sweeping speed; calculations for movement and sweeping to minimize leaf sweeping time and movement path; mathematical model prediction; real-time sensor feedback; intelligent machine learning; and predicted movement path. The control system includes driving control, sweeping control, and crushing control. The motor provides power, the ball screw converts motion, and the sensor provides real-time feedback. Autonomous navigation technology and deep learning algorithms are introduced to enhance intelligence. Users can control the vehicle and realize remote monitoring through a mobile phone APP.
Copyright (c) 2026 ZhaoMing Li https://creativecommons.org/licenses/by/4.0
THE KEY TECHNOLOGIES FOR RISK IDENTIFICATION OF "TWO PASSENGER AND ONE HAZARDOUS" VEHICLES BASED ON MULTI-SOURCE DATA FUSION
"Two passenger and one hazardous" (TPOH) vehicles are primary targets of road traffic safety supervision. Jilin Province, located in the northeastern seasonal frozen region of China, experiences severe winter conditions, including icy and snow-covered roads and extremely low temperatures, which substantially increase the operational safety risks of these vehicles.This study proposes a risk identification framework based on multi-source data fusion. The framework integrates GPS positioning data, on-board OBD data, meteorological information, and road infrastructure data to construct a multidimensional risk identification model. The model captures five categories of abnormal driving behaviors: speeding, harsh acceleration, harsh braking, vehicle vibration, and abrupt lane changes.An improved sliding-window feature extraction method and a hybrid XGBoost–LSTM classification model are employed to achieve accurate vehicle risk identification under complex seasonal frozen conditions. In addition, a system management and control platform is developed to provide decision-support tools for the transportation authorities of Jilin Province.
Copyright (c) 2026 HengBo Zhang; WanMiao Yu; Long Peng; ChunFu Jia; ZhiGang Wei; Miao Li https://creativecommons.org/licenses/by/4.0
MONOCULAR 3D BINAURAL LOCALIZATION AND DYNAMIC TRACKING FOR EAR-SIDE ACTIVE NOISE CONTROL IN VEHICLE CABINS
Accurate three-dimensional ear-position tracking is a prerequisite for ear-side active noise control in vehicle cabins, because natural head motion can directly shift the control target region and degrade the spatial consistency between the actual ears and the modeled control points. To address this problem, this study proposes a monocular-vision-based method for binaural three-dimensional localization and dynamic tracking in cabin scenes. A unified mapping among the pixel coordinate system, camera coordinate system, and cabin coordinate system is first established through camera calibration and geometric modeling. Facial landmark detection is then used to infer the two-dimensional locations of the left and right ears, after which cabin-feature-constrained monocular depth estimation is introduced to recover ear-region depth in a spatially aligned manner. The binaural three-dimensional coordinates are further refined through head-pose compensation, temporal filtering, and short-term prediction, so that the final output can be directly used as a control-oriented ear-state sequence. Multi-condition experiments under different illumination, occlusion, and head-pose variations show that the proposed method maintains good localization accuracy and trajectory continuity in all six tested cases. The root-mean-square error of binaural three-dimensional localization ranges from 18.40 to 25.57 mm, while the mean interaural distance error remains within 0.37 to 3.33 mm. Even under adverse conditions such as weak illumination and partial occlusion, the processed ear-state output remains continuously available to the downstream active noise control interface. These results indicate that the proposed method provides a low-cost and practically deployable solution for monocular binaural ear tracking in vehicle cabins and can serve as an effective perception front-end for ear-side active noise control.
Copyright (c) 2026 Cong Zhang https://creativecommons.org/licenses/by/4.0
ENHANCING WIND TURBINE PERFORMANCE AND SUSTAINABILITY THROUGH 3D-PRINTED BLADE OPTIMIZATION: A STUDY ON MATERIAL AND SHAPE EFFICIENCY
The growing demand for sustainable energy solutions has driven innovation in wind turbine design, particularly in optimizing blade performance and environmental impact. We investigate the application of 3D printing technology to fabricate wind turbine blades, focusing on material selection and geometric design to balance efficiency and sustainability. Two widely used thermoplastics, polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS), are evaluated for their environmental footprint using Global Warming Potential (GWP), where PLA exhibits a significantly lower carbon footprint (500g CO₂ eq/kg) compared to ABS (2900g CO₂ eq/kg). The study employs a material extrusion-based 3D printer to produce four blade configurations, combining these materials with distinct shapes, and assesses their power generation efficiency through electrical power, thrust, voltage, and vibration measurements. Our experimental results demonstrate that PLA-based blades not only reduce environmental impact but also achieve competitive performance, suggesting their viability as a sustainable alternative. Furthermore, the flexibility of 3D printing enables rapid prototyping and iterative design improvements, which are critical for advancing wind energy technology. The findings highlight the potential of additive manufacturing to enhance turbine sustainability without compromising functionality, offering a practical pathway for greener energy systems. This work contributes to the broader discourse on renewable energy innovation by bridging material science, manufacturing technology, and environmental considerations.
Copyright (c) 2026 Chun-Kit He; Dawson Wai-Shun Suen; Chi-Ying Vanessa Li; Juan Zhang; Xuejuan Cui; Wei Liu; Chi-Wing Tsang; Xiao-Ying Lu https://creativecommons.org/licenses/by/4.0
GUANGYUE MOJIE: AN INTELLIGENT AGRICULTURAL MANAGEMENT DEVICE BASED ON THE STM32 MICROCONTROLLER
Addressing the limitations of traditional greenhouse light management—reliance on weather, high energy consumption of artificial lighting, and inflexible spectra—this paper presents an intelligent agricultural device named "Light Film Realm" based on an STM32 microcontroller. Its core innovation is an automatically switchable intelligent film system that dynamically filters specific spectra according to crop needs, enabling precise regulation of optimal photosynthetic light combinations. The system integrates STM32 with multiple sensors (light intensity, temperature, humidity) and a 5G module for real-time data collection and cloud transmission. A remote monitoring platform, including WeChat mini-programs and web interfaces, combines local automatic control with remote manual intervention for intelligent human-machine-environment interaction. At the server end, machine learning algorithms analyze the collected data to dynamically optimize light regulation strategies and provide scientific decision support. Additionally, an online-merge-offline (OMO) business model was designed, encompassing online product display and technical consultation alongside offline installation, maintenance, and after-sales service, facilitating market promotion and technology transfer. Experimental results demonstrate the system's superior performance in enhancing light regulation precision, reducing energy consumption, and improving user interaction experience, offering a viable pathway toward more intelligent, precise, and sustainable agricultural production.
Copyright (c) 2026 ShiYu Jiao; ZeXu Du https://creativecommons.org/licenses/by/4.0
A STATISTICAL MICROMECHANICS FRAMEWORK FOR PIEZORESISTIVITY IN VISCOELASTIC FOAMS: UNIFYING STRUCTURAL EVOLUTION FROM CRACK TO CONTACT REGIMES
We introduce a comprehensive computational framework to simulate the complex electro-mechanical response of flexible, porous piezoresistive sensors. Existing simulation approaches face a critical bottleneck: they either rely on homogenized material properties that ignore the determinative porous micro-architecture, or they employ simplified, idealized geometries that fail to capture the stochastic nature of real foams. Most critically, prior models have overwhelmingly neglected the intrinsic viscoelasticity of the polymer matrix, a fundamental property governing the material's time-dependent mechanical response. Our framework overcomes these limitations by integrating three key elements within a Finite Element (FE) environment: (1) A stochastic 2D Representative Volume Element (RVE) based on a novel, computationally-stable abstracted pore geometry; (2) A Generalized Maxwell model to capture the experimentally-verified viscoelastic stress relaxation of the polyurethane (PU) substrate; and (3) A "segmented quasi-static" (SQS) solution strategy, developed to circumvent the documented limitations of commercial FE software in handling fully-coupled dynamic, conductive-contact simulations. The model is built by generating an ensemble of over 200 RVEs, each with randomly-distributed internal pore geometries, to represent the foam's statistical heterogeneity. By performing an ensemble average of the simulation results, our model successfully generates a macroscopic resistance-strain curve that is in high agreement with experimental observations. Crucially, this work provides a unified, structure-based origin for the two distinct sensing regimes widely reported in the literature: the initial, high-sensitivity "crack effect" (GF > 25) is shown to be a statistical emergent property of the initial contact events of the most vulnerable pores in the stochastic distribution, while the stable, high-strain "contact effect" corresponds to the progressive, large-scale pore collapse and contact area growth across the ensemble. This framework bridges the gap between stochastic microstructure and predictable macroscopic performance, opening a pathway for the inverse design of foam-based sensors.
Copyright (c) 2026 Jie Lv https://creativecommons.org/licenses/by/4.0
WINCH-BASED AND CABLE-DRIVEN JOINT ACTUATOR WITH TWO-STAGE REDUCTION MECHANISM
This paper presents a compact winch-based, cable-driven joint actuator with a two-stage reduction mechanism aimed at improving weight, backdrivability, and impact tolerance of robotic joints within constrained volumes. The design integrates primary and secondary reduction stages with an optimized winding scheme and an in-situ tensioning mechanism for stable transmission. A practical dual-encoder scheme provides an absolute output angle after power cycling. We detail the mechanical structure, winding/tensioning strategy, and electronics, and report measurements of reduction ratio, required pre-tension, and output stiffness. Experiments show a highly effective reduction ratio and predictable output stiffness consistent with modeling, with improved backdrivability under comparable size and mass. The module is suitable for compact legged/humanoid systems.
Copyright (c) 2026 RongChuan Huang; LiJun Zhu https://creativecommons.org/licenses/by/4.0
A FINITE-ELEMENT-BASED PRESSURE ALLOCATION STRATEGY BETWEEN SEALANT AND MEMBRANE ELECTRODE IN PEM FUEL CELL STACKS
Sealing reliability is essential to the safe and efficient operation of proton exchange membrane fuel cell (PEMFC) stacks. In practical stack assembly, however, increasing the seal compression to improve gas tightness may simultaneously raise the mechanical stress in the membrane electrode assembly (MEA), especially in the membrane and gas diffusion layer region. This trade-off makes conventional seal design based solely on leakage prevention insufficient for high-performance stack packaging. In this study, a finite-element-based pressure allocation strategy is developed to coordinate the mechanical requirements of the sealant and the MEA. A two-level modeling framework is adopted. First, a local metal bipolar plate-sealant-MEA frame model is established to verify sealing feasibility and evaluate the force requirement of the seal line under different compression ratios. Then, a refined full model including the flow-field ribs, seal groove, sealant, proton exchange membrane, frame region, and gas diffusion layer is built to investigate the coupling between seal compression, bipolar-plate displacement, and membrane stress. The results show that although a semicircular sealant can satisfy the sealing criterion in the local model, it becomes unsuitable in the full structure because the compression required to ensure gas tightness leads to excessive membrane stress. Under a 20% compression ratio, the maximum equivalent stress in the proton exchange membrane reaches approximately 4.8 MPa, which is far above the desired level of about 1.4 MPa. An improved pressure allocation strategy is therefore proposed by controlling bipolar-plate displacement rather than directly preserving the seal compression state. Based on this strategy, an optimized rectangular sealant section at a compression ratio of 17% achieves both adequate gas tightness and acceptable membrane stress. The study provides a practical finite-element-guided route for coordinated seal and MEA design in PEMFC stacks.
Copyright (c) 2026 QiXin Liang; XinFeng Zhang https://creativecommons.org/licenses/by/4.0
VISION-GUIDED SECONDARY-PATH MODEL UPDATING FOR PLAYBACK-REFERENCED ACTIVE HEADREST NOISE CONTROL
Time-varying secondary paths induced by head motion can introduce filtered-x mismatch and degrade the stability margin and usable attenuation bandwidth of active headrest noise control. This article proposes a vision-guided secondary-path model updating method for playback-referenced active headrest noise control. A monocular camera provides latency-compensated three-dimensional ear positions, from which ear–loudspeaker distances are estimated to update the internal secondary-path models through an equivalent delay shift and amplitude scaling of nominal impulse responses. The updated models are injected into filtered-x generation and normalised adaptation, while the underlying controller structure remains unchanged. To evaluate the proposed method under controlled dynamic conditions, a synchronised offline replay protocol is adopted, in which the electrical playback reference and binaural error signals are logged under a common hardware clock and replayed for repeatable comparisons. Experiments on a semi-anechoic active headrest platform in the 80–800 Hz band with a 3 dB criterion show that the proposed update enlarges the maximum stable step size by 67%–300% and improves attenuation continuity, yielding a median threshold-bandwidth gain of approximately 10–90 Hz depending on the condition.
Copyright (c) 2026 XuDong Wu; Cong Zhang; JiaXing Luo; ZeXiong Zhang https://creativecommons.org/licenses/by/4.0
MODAL ANALYSIS AND STRUCTURAL OPTIMIZATION OF GEAR MESHING NOISE IN NEW ENERGY VEHICLES
With the rapid development of new energy vehicles, the noise source of its power system has changed significantly, in which the gear mesh noise of the gearbox has a direct constraint on the NVH performance of the whole vehicle. In this paper, a new energy vehicle three-in-one motor in the 7500-9000rpm speed range of the obvious gear whistling problem to carry out research, through the analysis to determine its main noise source for the first gear pair. The study used SolidWorks software to establish a three-dimensional model of the first gear, and imported into ANSYS for finite element modal analysis, and also calculated the gear meshing frequency based on the formula f=n*z/60. The analysis results show that under 8000rpm, the gear meshing frequency is very close to the first-order intrinsic frequency of the structure, which is very easy to trigger structural resonance, resulting in a stepwise increase in the noise sound pressure level. In order to suppress this resonance phenomenon, an economical and direct structural optimization scheme is proposed in this paper: the number of weight-reducing holes in the gear body is reduced from 8 to 4 to enhance the structural stiffness of the spokes. The optimized simulation results show that the first-order modal frequency of the gear is increased to about 3000 Hz, which successfully avoids the excitation frequency under the main working speed, so that the noise source under the common working conditions is transformed into the wind noise and the tire noise, and the gear meshing noise is effectively masked. The study confirms that structural optimization by adjusting the number of weight-saving holes is an effective and economical way to suppress the resonance noise of the gears in new energy vehicles, which improves the dynamic performance while taking into account the lightweight design objective.
Copyright (c) 2026 KangZhe Si https://creativecommons.org/licenses/by/4.0
SIMSCAPE-EQUIVALENT MODELING AND VERIFICATION OF A GAN DEVICE SPICE BEHAVIORAL MODEL FOR PV DC–DC SYSTEM-LEVEL SIMULATION
A Simulink/Simscape-compatible device model is developed for system-level simulation of PV DC–DC power conversion, using a vendor-provided SPICE behavioral subcircuit of the EPC2302 GaN power transistor. After an automatic translation from the SPICE netlist to a Simscape description, semantic and syntactic incompatibilities are analyzed and are found to mainly originate from representing voltage-dependent capacitances as parameterized primitive components, which introduces runtime terminal voltages into parameter evaluation and leads to compilation conflicts. To preserve the device dynamic behavior while complying with Simscape semantics, the voltage-dependent capacitances are reformulated as explicit branch-current relations at the equation level, and the smooth fitting structure of the vendor model is retained to enhance numerical robustness. A datasheet-referenced verification workflow is established to assess consistency in static conduction behavior and dynamic capacitance-related characteristics. The resulting model compiles successfully and runs stably in time-domain simulations, providing a practical foundation for system-level transient analysis and loss-trend evaluation of high-frequency GaN DC–DC converters.
Copyright (c) 2026 ZiYu Qin; Tu Hong; Lei Shi https://creativecommons.org/licenses/by/4.0
PERFORMANCE OPTIMIZATION OF TRAJECTORY DEVIATION CORRECTION IN LONG-RANGE BALLISTIC MISSILES: AN ADAPTIVE PID CONTROL APPROACH
Addressing the trajectory deviation problem of long-range ballistic missiles (5000-8000 km range) caused by multiple factors such as aerodynamic disturbance, thrust fluctuation, and gravity field variation during flight, this paper proposes an adaptive PID trajectory correction control method based on a self-tuning parameter strategy. The paper adopts a composite guidance scheme combining inertial and satellite guidance, establishes a three-degree-of-freedom missile flight dynamics model, and designs an improved PID controller incorporating fuzzy parameter tuning, and differential filtering. In simulation experiments on a parabolic-gliding composite trajectory with long-range ballistic missile characteristics, the adaptive PID controller outperforms the traditional PID controller under different flight phases and disturbance conditions, reducing steady-state error by 42.3% and shortening adjustment time by 31.7%. The proposed adaptive PID controller achieves high-precision trajectory tracking during long-range flight, providing theoretical support and simulation validation for control systems in long-range ballistic missile applications.
Copyright (c) 2026 RuoHao Zhang https://creativecommons.org/licenses/by/4.0
PRECISE MEASUREMENT OF SILICON CARBIDE EPITAXIAL LAYER THICKNESS BASED ON INFRARED INTERFERENCE PRINCIPLE AND LEAST SQUARES OPTIMIZATION ALGORITHM
This paper focuses on the precise measurement of epitaxial layer thickness in silicon carbide wafers. An ideal mathematical model based on infrared interference and its solution algorithm were constructed and solved. To construct the ideal mathematical model for epitaxial layer thickness measurement, the study first analyzes the physical principles of reflection and refraction of infrared light at the epitaxial layer-substrate interface. Utilizing Snell's law and trigonometric functions, it derives formulas for calculating optical path difference and phase difference. By establishing the conditions for wave interference maxima and minima, the theoretical formula for calculating epitaxial layer thickness was ultimately derived, successfully establishing a mathematical framework under the idealized assumption of only two reflections. Building upon this ideal model, for the thickness measurement algorithm design task, the study first performed standardized preprocessing on the provided spectral data, including S-G smoothing filtering, effectively reducing noise interference. Subsequently, a peak localization and selection algorithm was applied to precisely identify and jointly utilize the extreme points of all 60 interference fringes. To resolve the integer ambiguity issue for interference order m, a traversal optimization algorithm was designed. By searching for the m value that minimizes the variance of the thickness calculation sequence, the optimal interference order was coherently determined. Finally, the least-squares fitting optimization technique yielded an average epitaxial layer thickness of approximately 11.61 μm. A four-dimensional reliability assessment—encompassing parameter sensitivity, data integrity, theoretical consistency, and computational stability—validated the algorithm's exceptional robustness and reliability within the idealized model framework.
Copyright (c) 2026 Yi Wang https://creativecommons.org/licenses/by/4.0
MULTI-AGENT COORDINATION AND RESOURCE ALLOCATION OPTIMIZATION STRATEGIES FOR SMOKE SCREEN DEPLOYMENT AGAINST DYNAMIC TARGETS
This paper investigates optimal defense strategies for countering single or multiple high-speed incoming missiles by deploying smoke screen decoys through coordinated operations of multiple unmanned aerial vehicles (UAVs) in complex dynamic battlefield environments. The research focuses on the challenging problem of multi-agent cooperative defense and large-scale resource allocation. First, for a three-UAV, single-decoys cooperative countermeasure strategy, a joint optimization model incorporating parameters such as UAV flight direction, velocity, deployment timing, and detonation timing is constructed. A differential evolution algorithm is employed to solve this high-dimensional combinatorial optimization problem. Through iterative differential evolution, optimal parameter configurations for the three UAVs are obtained, achieving effective shielding against missile M1. Subsequently, the scenario is expanded to the most complex five-UAV, three-missile integrated defense problem. This problem involves multiple UAVs, multiple missiles, multiple missile deployments, and resource allocation, constituting a typical large-scale combinatorial optimization problem. This paper innovatively proposes a two-layer hybrid optimization framework combining the Hungarian algorithm and genetic algorithm. The upper layer utilizes the Hungarian algorithm to determine the optimal task allocation between missiles and UAVs, minimizing the initial distance cost to ensure optimal spatial separation. The lower layer, with fixed allocations, employs a genetic algorithm to refine the deployment parameters for each UAV. The final optimized solution successfully achieves comprehensive interference against three missiles, demonstrating the dual-layer model's capability to obtain near-global-optimal multi-objective defense strategies while ensuring real-time feasibility.
Copyright (c) 2025 TianJian Zhong https://creativecommons.org/licenses/by/4.0
INTELLIGENT IDENTIFICATION AND DECISION SUPPORT SYSTEM FOR TBM CONSTRUCTION RISK SYNERGISTICALLY DRIVEN BY KNOWLEDGE GRAPHS AND LARGE LANGUAGE MODELS
Tunnel Boring Machines (TBMs) are widely used in subway and tunnel projects due to their efficiency and safety. However, the complexity and high uncertainty of the construction environment lead to lag and limitations in traditional risk identification methods. Addressing the urgent need for intelligent management, this study combines the advantages of Knowledge Graphs (KG) in structured knowledge representation and Large Language Models (LLMs) in natural language understanding to construct a synergistically driven intelligent risk identification and decision support system for TBM construction.First, the study employs ontology modeling to build a risk knowledge graph covering risk factors, risk-causing mechanisms, and consequences, achieving entity-relation extraction through multi-source heterogeneous data mining. Second, the Large Language Model is adapted and fine-tuned by constructing an engineering corpus and injecting domain knowledge. Finally, a synergistic mechanism is designed to realize intelligent risk identification and decision-making.The innovations of this study include: (1) Proposing a "Knowledge Retrieval - Semantic Understanding - Logical Reasoning" three-layer architecture, effectively fusing explicit knowledge with reasoning capabilities; (2) Developing a multi-modal risk feature fusion identification model, improving identification accuracy and real-time performance; and (3) Building an intelligent recommendation engine for risk response plans, supporting multi-scenario simulation. Experimental and engineering application results indicate that the system significantly improves the precision and recall of risk identification, effectively enhancing the risk management level of TBM construction.
Copyright (c) 2026 YongKun Li; Yin Bo https://creativecommons.org/licenses/by/4.0
IDENTIFICATION OF A CRITICAL INITIAL TEMPERATURE WINDOW FOR PEMFC COLD START UNDER LINEAR 25 S LOADING BASED ON A ONE-DIMENSIONAL MULTIPHASE MODEL
The low-temperature cold-start capability of proton exchange membrane fuel cells (PEMFCs) is strongly influenced by the initial temperature and the water-thermal coupling behavior within the stack. In this study, a one-dimensional multiphase cold-start model was developed based on a lumped-parameter approach. A 5 kW stack consisting of 30 single cells was investigated under a unified linear 25 s loading strategy, in which the current density was linearly increased from 0 to 0.5 A·cm -2 and then maintained constant. The cold-start evolution characteristics were systematically analyzed over an initial temperature range from -4 °C to -20 °C. The simulation results reveal the existence of a distinct critical initial temperature interval (approximately -12 °C to -14 °C) under the prescribed loading protocol, with the upper and lower bounds corresponding to two fundamentally different evolutionary pathways. When the initial temperature exceeds the lower bound of this interval, the stack establishes a stable positive thermo-electrical coupling feedback, enabling voltage recovery and sustained operation. In contrast, when the initial temperature falls below this interval, the system progressively enters an irreversible degradation trajectory and ultimately becomes unstable. Further analysis indicates that the decisive factor governing cold-start success is not the overall heat generation level, but whether the edge cells can surpass the freezing point and complete ice melting within a critical time window. These findings provide a theoretical basis for cold-start boundary identification and strategy optimization.
Copyright (c) 2026 YueWen Zeng; Lei Shi https://creativecommons.org/licenses/by/4.0
SOME PROPERTIES OF HYPERBOLIC TRIGONOMETRIC FUNCTIONS
This paper investigates some fundamental properties of hyperbolic trigonometric functions on the hyperbolic number plane. Hyperbolic numbers form a commutative ring with zero divisors, generated by two real numbers via the Cartesian basis. Within this algebraic framework, this paper systematically establish the system of hyperbolic trigonometric functions. By fully leveraging the decomposition properties of hyperbolic numbers and their associated trigonometric functions, this work effectively overcomes the mathematical difficulties arising from the presence of zero divisors in the hyperbolic number ring. On this basis, this paper for the first time in the context of a hyperbolic number ring containing zero divisors, systematically derived and rigorously proved the addition theorems for the hyperbolic sine, cosine, tangent, and cotangent functions. On this basis, we have successfully derived and rigorously proved the addition theorems for the hyperbolic sine, cosine, tangent, and cotangent functions, establishing a complete system of angle addition formulas and laying a solid foundation for the theory of hyperbolic functions. The addition theorems established in this research will provide an important theoretical foundation for the further development of hyperbolic analysis in function theory, while simultaneously injecting new research momentum into the further study of the properties and expansions of hyperbolic trigonometric series. These theoretical achievements are expected to play significant roles in the study of hyperbolic differential equations, geometric analysis, and related physical problems.
Copyright (c) 2025 HaoLin Fu https://creativecommons.org/licenses/by/4.0
DYNAMIC MODELING AND ANALYSIS OF IN-WHEEL SUSPENDED ELECTRIC WHEEL SYSTEM
The introduction of in-wheel motors increases the unsprung mass of electric vehicles, exacerbates vibrations when the vehicle is subjected to road excitation, and affects ride comfort and stability. The in-wheel suspended electric wheel has become an important technical means to improve the above-mentioned problems of in-wheel motors. This paper conducts a vertical dynamic characteristic analysis of two electric wheel configurations. A 1/4 vehicle model was established based on the Matlab/Simulink platform, and the vibration response characteristics of the two electric wheels under different road excitations were obtained. Experimental tests were performed on the vibration characteristics of the two electric wheels using a swept-sine road excitation. The experimental results were in good agreement with the simulation results, verifying the reliability and accuracy of the simulation model.
Copyright (c) 2025 Peng Zhang; Lei Jiang; ShangQing Liu; ShengShuo Yan; JingXin Bai; Ping Zhang https://creativecommons.org/licenses/by/4.0
INORGANIC COMPOSITE STONE-LIKE CAST-IN-PLACE TECHNOLOGY AND ENGINEERING APPLICATION PERFORMANCE EVALUATION FOR URBAN RENEWAL
To address the demand for green, adaptable building materials in urban renewal’s existing building renovation and public space transformation, and solve traditional stone-like materials’ defects (long construction period, poor adaptability, low solid waste utilization), this study optimizes inorganic composite stone-like cast-in-place technology and evaluates its performance. Industrial solid wastes (steel slag, recycled construction aggregates) serve as main raw materials; composite cementitious systems and functional admixtures are developed, with key process parameters determined via orthogonal experiments. Results show that at 72% solid waste replacement rate, 0.28 water-binder ratio, 0.4% retarder content and 20–25℃ pouring temperature, the material’s 28-day compressive/flexural strength reaches 105/9.8 MPa, setting time 4–6 h, meeting on-site construction requirements. It exhibits excellent durability, with 8.2% strength loss after 50 freeze-thaw cycles and grade-4+ stain resistance. Engineering verification confirms 40% higher construction efficiency, 35% lower cost and 1.2 t/100 m2 carbon emission reduction versus traditional dry-hanging. This scheme offers green, efficient technical support for urban renewal, with significant engineering and environmental value.
Copyright (c) 2025 LianDi Zhao; XianWei Wang https://creativecommons.org/licenses/by/4.0
HYBRID-CONTROLLED IPOS LLC CONVERTER FOR FUEL CELL APPLICATIONS
Fuel-cell power conditioning systems require DC–DC converters to achieve high efficiency, wide-range voltage regulation, and reliable operation under significant input and load variations. To address these requirements, this paper investigates an IPOS-type secondary LLC resonant DC–DC converter and proposes a hybrid control strategy combining pulse-frequency modulation (PFM) and phase-shift modulation (PSM). In the proposed scheme, PFM is employed as the primary control method to realize wide-range voltage regulation, while a frequency-clamping with phase-shift compensation mechanism is introduced to maintain effective power control and dynamic performance when the switching frequency reaches its practical upper limit. The effectiveness of the proposed topology and control strategy is validated through MATLAB/Simulink simulations and experimental studies on a laboratory prototype. Experimental results demonstrate a peak conversion efficiency of 96.6% under rated conditions, with efficiency remaining above 96% near the rated load range. In addition, the maximum output voltage deviation between two IPOS phases is limited to 1.9% under full-load operation, and fast, stable input-current tracking is achieved under step reference changes from 20 A to 80 A without noticeable overshoot. These results confirm that the proposed converter and hybrid control strategy are well suited for high-efficiency, wide-range fuel-cell energy conversion applications.
Copyright (c) 2026 JueXiao Chen; EnYong Li; Lei Shi; ZhongYao Jiang https://creativecommons.org/licenses/by/4.0
CURRENT STATUS OF NEAR-SURFACE OZONE POLLUTION RESEARCH IN CHINA
In recent years, with the effective control of fine particulate matter (PM2.5) pollution in China, the problem of near-surface ozone (O3) pollution has become increasingly prominent, becoming one of the important factors restricting the continuous improvement and attainment of ambient air quality standards. This article systematically reviews the latest progress in research on near-surface ozone pollution in China. Studies show that since the 13th Five-Year Plan, the overall O3 concentration in China has shown a trend of first rising and then plateauing, exhibiting significant regional differences and seasonal high incidence in key urban clusters such as the Beijing-Tianjin-Hebei region and the Yangtze River Delta. In terms of formation mechanism, the nonlinear relationship between ozone formation and its precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), has always been the core of research: most urban central areas are in VOCs control zones, while regional background areas and some suburban areas are mostly NOx control zones or transition zones, and their control sensitivity dynamically evolves with the progress of pollution reduction . Meteorological conditions, especially extreme high temperatures and strong solar radiation, have a significant promoting effect on ozone formation and accumulation, and the "heat wave-ozone" compound pollution is gradually becoming a new prominent problem. In terms of prevention and control strategies, the synergistic control of ozone and PM2.5 has risen to an important strategic direction. It is urgent to implement differentiated NOx and VOCs emission reduction measures based on precise sensitivity analysis, and to strengthen regional joint prevention and control mechanisms. Future research should focus on the synergistic governance of compound pollution, refined source spectrum analysis and efficient control of VOCs, the microscopic processes of ozone formation, and the systematic upgrading of forecasting and early warning technologies.
Copyright (c) 2025 Xin Lin https://creativecommons.org/licenses/by/4.0
FEAST: FEATURE ENGINEERING AND STACKING FRAMEWORK FOR COMPLEX SYSTEM PREDICTION
The challenge of capturing high-dimensional interactions and ensuring stable predictions in complex engineering systems, characterized by rapidly growing heterogeneous data, limits traditional models. To address this, we introduce FEAST (Feature Engineering and Advanced Stacking Framework), whose core innovation lies in its integrated approach: (1) Hierarchical feature optimization using K-Means++ clustering and adaptive correlation to significantly reduce redundancy and enhance feature discrimination; (2) An advanced stacked ensemble leveraging diverse base learners (MLR, XGBoost, LightGBM, CatBoost, GBDT) fused via Shapley-weighted combination and a regularized (Elastic Net) meta-learner to robustly capture complex patterns; (3) An efficient Monte Carlo Dropout-based uncertainty quantification module providing reliable confidence intervals for risk-aware decisions. Comprehensive experiments demonstrate FEAST's superiority: it achieves 12.7% higher prediction accuracy (p<0.01), 41% lower cross-validation error variability, and a 92.3% confidence interval coverage rate, significantly outperforming baseline models in complex engineering prediction tasks.
Copyright (c) 2026 WanJun Cai; JiangYi Le; Rui Gu; Hang Zhao; SiYu Tang https://creativecommons.org/licenses/by/4.0
OPTIMIZATION OF URBAN SOLID WASTE COLLECTION ROUTES AND MULTI-VEHICLE COLLABORATIVE DISPATCH DECISION-MAKING
Addressing the core demands of enhancing transportation efficiency and controlling costs in urban solid waste management, this study constructs a multi-objective optimization model for waste collection routes and multi-vehicle coordination scheduling based on multi-dimensional constraints. During the fundamental route planning phase, a mathematical model minimizing total travel distance is established for single-type waste collection points, alongside an improved genetic algorithm incorporating a Markov chain adaptive mechanism. This algorithm employs a hybrid coding scheme for primary and auxiliary chromosomes, dynamically adjusts crossover and mutation operators, and incorporates local optimization strategies like embedded neighborhood search. It successfully achieves efficient task allocation, with experimental results yielding a total travel distance of 1,144.5 kilometers. During the complex multi-vehicle coordination phase, the model was extended to a joint transportation scenario involving four specialized waste collection vehicle types, comprehensively considering constraints such as vehicle payload, volume, unit transportation cost, and maximum daily driving time. An improved multi-objective genetic algorithm was employed for solution, achieving Pareto-optimal scheduling of multi-source waste streams through segmented sequence encoding and feasibility correction mechanisms. Results demonstrate the model's ability to clearly characterize operational efficiency and cost structures across vehicle categories, with food waste collection and transportation accounting for the highest cost proportion at 38.3%.
Multi-vehicle collaborative optimization
Copyright (c) 2026 ZhiYang Chen; ChangYuan Chen; BiRui Yang https://creativecommons.org/licenses/by/4.0
RESEARCH ON DUAL PLC SIMULATION TECHNOLOGY BASED ON MODBUS TCP COMMUNICATION
With the rapid development of industrial automation technology, efficient communication between PLCs has become the key to realizing complex control systems. Based on the MODBUS TCP protocol, this paper studies the simulation method of dual PLC communication, aiming to improve the reliability and real-time performance of industrial control networks. By constructing a dual PLC communication simulation platform based on MODBUS TCP, the data frame structure and communication mechanism of the protocol are analyzed. The logic design and communication configuration of the PLC program are implemented using TIA Portal software, and the simulation platform adopts S7-PLCSIM Advanced. The experimental results show that the simulation system can stably realize data exchange between dual PLCs, providing a reference for multi-PLC collaborative control in industrial fields. This research provides theoretical support and practical basis for the application of MODBUS TCP in industrial automation.
Copyright (c) 2026 Hong Chen https://creativecommons.org/licenses/by/4.0
PRE-SYNCHRONIZATION CONTROL BASED ON VSG PARAMETER COOPERATIVE ADAPTATION
Virtual synchronous generator (VSG) emulate synchronous generators to provide inertia and damping support for distributed power integration. However, conventional VSG control employs fixed parameters that hinder dynamic adaptation to system changes, often resulting in grid connection impact currents and voltage harmonics. To overcome these limitations, this study proposes a pre-synchronization strategy based on coordinated adaptive control of VSG parameters. A VSG mathematical model is established to analyze parameter influences on system output characteristics. A coordinated adaptive control method incorporating rotational inertia and damping coefficients is then developed, which demonstrates faster suppression of excessive changes and deviations in output response compared to conventional strategies. Furthermore, a pre-synchronization mechanism is integrated to achieve smooth grid synchronization while significantly reducing inrush currents and voltage harmonics before and after connection. Simulation results via PSCAD validate the feasibility and effectiveness of the proposed control strategy.
Copyright (c) 2026 YuLin Yuan https://creativecommons.org/licenses/by/4.0