bluuebunny/crossref_metadata_2025_split huggingface dataset:
Model based design of a turbo-compound bottomed to internal combustion engine exhaust gas
Authors: Prospero Federico Di , Battista Davide Di , Cipollone Roberto 
Published: December 2024

Abstract
The transportation sector is living a new era, where the conventional powertrains based on thermal engines are flanked by innovative ones, based on electric and hybrid systems. This revolutionizes the behaviour and the driving habits, as well as the figure of the whole propulsive system, which should integrate different energy sources on board and the energy demand for propulsion, auxiliaries, ancillary components, vehicle needs, etc. But, for heavy-duty vehicles, it is very difficult to abandon in the short and mean term the reciprocating combustion engine technology. Also, for passenger cars and light duty vehicles, the pure electric propulsion seems to put in more evidence limits not only technological. In this panorama, the development of very high efficiency engines is mandatory to fit the emissions targets, both referred to pollutant emission and CO2. In this regard, waste heat recovery into mechanical or electrical energy is one of the most promising options to reduce fuel consumption. It is of particular interest for heavy duty engines, where the operation does not suffer so much the transient phases, and hybrid powertrains, where the energy recovered can be stored in electrical form and used for all the necessities of the vehicles. In this paper, a waste heat recovery system based on an additional turbine placed in the exhaust line of a turbocharged internal combustion engine has been studied. The auxiliary turbine is designed thanks to a model-based approach. The performance map of the turbine has been calculated referring to the thermodynamic conditions of the engine exhaust gases as input parameters. The so-designed component is then integrated with an engine model, and the benefits of a turbo-compound technology bottomed to the engine were assessed. In this way, the potential power recoverable from the turbine is evaluated under design and off-design conditions. The integration with engine model allowed to estimate the side effects related to backpressure increase on the engine exhaust manifold (which leads to an overconsumption or an underrating of the engine torque), as well as the equilibrium change on the turbocharger shaft. Definitively, the final overall engine performances are assessed including the need for a bypass which, in certain engine working conditions, must exclude the recovery.
Model based design and optimization of a shaft cooling for automotive electric motor
Authors: Deriszadeh A. , Di Battista D. , Di Giovine G. , Cipollone R. 
Published: December 2024

Abstract
The on-the-road transportation sector is living a strong transition era, shifting from a technology massively based on internal combustion engines (ICEs) toward electric powertrains. Even though the electrification of vehicles as it is presented today still deserves an in-depth analysis for many reasons not only technological, a share of pure electric vehicles in the future will be present on the market, but reoriented to an urban use where a strong reduction of the harmful pollutants is needed. Within this aim, the improvement of the electric motor reliability, operability, safety, continuity of operation, and peak power delivery as well as the integration of them into the powertrain with the ICE technology is particularly required. Electric motor thermal management influences all the mentioned aspects. Electric motor cooling is usually realized with cooling jackets inside the stator. However, when the specific power (kW/m3) increases (as it is needed for the automotive electric traction), the rotor also requires an intensive cooling introducing some additional complexities. This can be done by cooling the shaft of the rotor via a dedicated inner fluid circulation contributing to keep the electric motor performance closer to the rated conditions.
In this paper, a liquid cooling of the shaft on an electric traction motor has been studied thanks to a Computational Fluid Dynamic (CFD) model and under variable boundary conditions. The cooling can be realized with a double concentric tube in the shaft: the first is fixed, and the second one rotates with the rotor. This concept requires a dedicated mechanical sealing system which ensures fluid sealing. The model has been used to enhance the heat transfer coefficient in order to approach rotor temperature to the one of the cooling fluids. With reference to different operating cooling conditions and designs, the temperatures of the rotor have been predicted also considering different fluids, and geometrical design choices of the cooling double pipe. The proposed design solution reduced the rotor temperature by 30°C compared to a baseline rotor cooling system represented by a simple direct-through cooling passage.
Diagnosis of mechanical faults in high-voltage grid disconnect
Authors: Zhu Kun , Fu Liyou 
Published: December 2024

Abstract
A new mechanical fault diagnosis method for high-voltage isolation switches in power grids is proposed, which often leads to mechanical faults such as bearing jamming and inadequate action, resulting in inaccurate fault signal characteristic values and poor diagnostic results. Based on the characteristic values of vibration signals when mechanical failures occur, we draw a torque angle detection curve and compare it with the curve changes under normal operating conditions to achieve an accurate diagnosis of mechanical failures. The experimental results demonstrate that the mechanical fault diagnosis results of the designed method are consistent with reality, indicating that this method can effectively detect mechanical faults in high-voltage isolation switches in the power grid and has good diagnostic performance.
The separation theorem for mean-field linear quadratic optimal control problem with partial information
Authors: Song Hairong 
Published: December 2024

Abstract
We investigate the separation principle for a class of mean-field stochastic optimal control problems with partial information, where the linear stochastic dynamic system is observed through a linear noisy channel. In our model, the time inconsistency caused by the mean-field terms makes the dynamic programming principle (DPP) inapplicable, which immediately leads to difficulties in deriving the separation principle. Utilizing the optimal filtering equations in several dimensions, we can transform the stochastic optimal control problem with partial information into one with complete details. Subsequently, the Hamilton-Jacobi-Bellman (HJB) equation that can solve the optimal control is obtained with the support of the dynamic programming principle. The separation principle for solving the optimal control of the original problem is derived.
A primary joint frequency regulation strategy for wind-thermal-storage systems considering frequency regulation deadband
Authors: Zhu Zimin , Duan Yu , Zao Weihong , Liu Zhen , Tang Junyi , Guo Jiahao , Ma Xing 
Published: December 2024

Abstract
For the issue of system frequency stability in low-inertia regions, a primary joint frequency regulation strategy for wind-thermal-storage systems considering frequency regulation deadbands is proposed. First, a system frequency response model incorporating wind-storage frequency regulation deadbands is constructed to analyze the dynamic impact of deadband variations on grid frequency. Next, the timing of frequency regulation actions in the wind-storage system is determined by manually setting the frequency regulation deadband. Finally, the effectiveness of the proposed strategy is validated using a large disturbance excitation method.
Synchronization of a nonlinear 4D hyperchaotic system using linear feedback control strategy
Authors: Ding Yanfeng , Cai Guoliang , Shi Wenjun 
Published: December 2024

Abstract
This paper uses a linear feedback control strategy to discuss the synchronization analysis of the nonlinear 4D hyperchaotic system. Targeting four control schemes, namely four, three, two, and one simple linear feedback controller, respectively, the synchronization of this hyperchaotic system was achieved through the Backstepping method. By using some simpler controllers, global asymptotic synchronization has been achieved. Among these four schemes, sufficient conditions for the synchronization of two identical hyperchaotic systems were derived using linear feedback control and the Lyapunov stability theorem. Finally, these results were validated through numerical simulation examples, demonstrating the correctness and effectiveness of the theoretical analysis.
Operation strategy and capacity optimization of wind-solar hydrogen storage system considering the characteristics of electric hydrogen production
Authors: Pu Yu , Song Tao , Cao Bin 
Published: December 2024

Abstract
Wind and solar power for hydrogen production can convert fluctuating renewable energy into high-quality hydrogen, but their intermittency leads to frequent starts and stops of electrolyzers and low integration rates of renewable energy. This study proposes operational strategies and capacity optimization methods for a hybrid hydrogen production system BY using alkaline electrolyzers (AEL) and proton exchange membrane electrolyzers (PEMEL). Compared to conventional approaches, the optimization achieves an increase in hydrogen production and a reduction in power fluctuations, offering insights for enhancing the coordinated operation of wind-solar hydrogen production systems.
High-precision positioning system for composite robots based on visual feedback
Authors: Wen Kangquan , Wu Liming , Wang Chunpeng , Zhang Qiaofen , Zeng Jiaqi , Huang Guanxi 
Published: December 2024

Abstract
Composite robots, which integrate robotic arms with Automated Guided Vehicles (AGVs), offer flexibility but face challenges due to insufficient navigation precision. To address this issue, this paper proposes a high-precision positioning system for composite robots based on visual feedback. First, the system constructs an environment map and performs path planning through LiDAR to realize preliminary navigation. Due to the limited localization accuracy of LiDAR, the system introduces a visual feedback mechanism after the robot arrives at the target point, acquires the position information of markers in real-time through the camera, and precisely adjusts the end-effector so that it actually achieves the absolute positioning accuracy of the robotic arm. This method is equal to the end positioning accuracy of the robotic arm after compensation when the absolute positioning accuracy of the robotic arm is 0.2mm. This system holds significant potential in industrial automation, particularly in scenarios requiring high-precision operations, and provides critical support for enhancing production efficiency and product quality.
Design of an FPGA-accelerated real-time gaze estimation system
Authors: Wu Jinjun , Han Peng 
Published: December 2024

Abstract
Real-time gaze estimation has extensive applications in various fields, such as smart classrooms, advertising analysis, and smart homes. With the continuous maturation of neural network technology, gaze estimation under large models can achieve excellent accuracy and speed, but it requires high-computing processors, which results in overly large devices, thereby limiting the application scope of gaze estimation. Deploying a real-time gaze estimation system onto edge devices, albeit with a slight compromise in accuracy to ensure real-time performance, significantly enhances the practical value of estimation. This paper deeply integrates gaze estimation algorithms with FPGA by leveraging block-wise convolution and fusing single convolutions to address the limited on-chip memory of FPGA, thereby improving the parallelism of model inference. As a result, we achieved 32 frames per second on the ZYNQ7035 processor with an average power consumption of 6.4 watts.
Pulse eddy current testing of corrosion defects in pipelines with insulation layer based on U-shaped sensors
Authors: Cao Aisong 
Published: December 2024

Abstract
In response to the insufficient detection ability of CUI in pipelines, based on U-shaped sensors, combined with the wide spectrum and non-contact characteristics of pulse eddy current detection technology, the area and depth of corrosion defects on the outer wall of pipelines can be effectively detected without removing the insulation. Simulation and experimental research are conducted on the outer wall defects of carbon steel test tubes with insulation layers. The simulation results show that the excitation magnetic field generated by the U-shaped sensor can effectively penetrate the inner wall of the pipeline, and the two signal-receiving coils of the U-shaped sensor will generate significant characteristic signals when passing through defects. The detection voltage position curve is obtained by applying the voltage distribution analysis method, and the characteristic signal length is the defect length. The experimental results show that when the detection sensor passes through and leaves the defect, the detection voltage distribution curve will generate a significant voltage drop characteristic signal, and the distance between the measurement points is consistent with the length of the defect. The experimental results are highly consistent with the simulation results.
A multi time scale flexible operation and consumption method for new energy generation considering load elasticity
Authors: Huang He , Yu Aihua , Song Jin , Zhang Nan 
Published: December 2024

Abstract
The proportion of new energy in the power system continues to increase, but the intermittent and fluctuating characteristics also bring serious challenges to the stable operation of the power grid. In order to more effectively utilize new energy generation, this paper proposes a multi time scale flexible scheduling strategy that combines load elasticity, aiming to optimize the consumption of new energy and the operation of the power grid. This method analyzes the influencing factors of load elasticity, establishes a load elasticity model, and combines predictive and real-time data of new energy generation to develop a flexible operation strategy at multiple time scales. By optimizing scheduling and real-time control, while ensuring the stable operation of the power grid, we propose a strategy aimed at achieving efficient utilization of new energy generation. After experimental verification, this strategy is not only effective, but also demonstrates good adaptability in practical applications.
The combustion biased dual cross-limited control strategy for industrial boiler furnaces
Authors: Liu Bao , Pan Yulong , Wang Zaiying 
Published: December 2024

Abstract
The combustion process in boilers is a crucial aspect of industrial boiler operation, and the quality of this process is closely related to the industrial boiler’s operational efficiency and pollutant emissions. This paper focuses on furnace combustion control within the industrial boiler control system and proposes an improved variable bias control method to address the issues associated with over-oxygen and oxygen-deficient combustion, which are prevalent in current double-closed-loop cascade proportional control technologies. First, the working principle of the variable bias double cross-limit combustion process is analyzed, and the variable bias cross-limit combustion control system is designed. Second, by introducing a bias variable, the paper addresses the problem that fixed bias parameters in the double cross-limit control system cannot accommodate the variable loading and rapid response requirements. Finally, the range of bias coefficients is estimated using the trial-and-error method. Experimental results demonstrate that the variable bias double cross-limit control strategy resolves the issues of oxygen deficiency and over-oxygen combustion, along with the slow response speed of conventional combustion control modes, enhances fuel heat utilization efficiency, and reduces pollutant and harmful gas emissions.
The application and optimization of scene reduction algorithm in integrated prediction of wind and photovoltaic energy
Authors: Zhang Tao , Yang Ligang , Zhu Ruijin , Yuan Chao 
Published: December 2024

Abstract
Wind power and photovoltaic energy, as the most representative clean energy sources, have experienced rapid development. However, they are highly dependent on meteorological conditions and have poor predictability, posing a significant challenge for the integrated forecasting of wind power and photovoltaic energy. This paper investigates a scenario reduction algorithm based on Latin hypercube sampling and probability distribution to optimize the integrated forecasting of wind power and photovoltaic energy. By generating a large number of wind power and photovoltaic scenarios and utilizing Euclidean distance and probability distribution calculations, the scenarios are streamlined. The algorithm is implemented in MATLAB, and the effectiveness and superiority of the algorithm are demonstrated through detailed experiments and plots.
A method for calculating the allowable crack size of the main pipeline for a certain PWR
Authors: Chen Zhangxing , Zhang Xuesheng , Zhou Zhou 
Published: December 2024

Abstract
To determine the allowable crack size of the main coolant pipeline, the FEM method was first utilized to perform the stress distribution analysis on the main coolant pipeline under conditions such as pressure tests, normal operation conditions, plus safe shutdown earthquake load. The maximum stress intensity at the weld of the main coolant pipeline was obtained by using theoretical formulas. Subsequently, the NRC ring-shaped crack pipe analysis method based on plastic fracture theory was performed to calculate the critical size of semi-elliptical cracks on the inner surface of the pipe under different conditions. Finally, based on the stress intensity calculation results and fatigue crack propagation, the amount of expansion of standard postulated semi-elliptical cracks on the inner surface of the pipe over a 40-year lifetime was calculated. The results show that within the 40-year lifetime, the size of the postulated initial crack plus expansion is far smaller than the corresponding critical crack size. It can be considered that the postulated initial crack will not lead to fatigue failure of the pipe, and thus, the initial crack size used in fatigue crack expansion calculations can be considered as the allowable crack size for the pipe. In this paper, the cold leg of the main coolant pipeline in a certain nuclear power plant was studied.
Research on hull curved plate surface flattening method based on Dijkstra search and compass intersection solving
Authors: Liu Yuqi , Zhai Yayu , Wang Yinghua 
Published: December 2024

Abstract
The change of the surface curvature during the line heating forming process of ship outer plates changes the spatial position of frame lines on the surface, which makes it challenging to locate the position of frame lines during the digital plate-forming inspection. It is necessary to establish the mapping between the frame line data of complex surface shape and the corresponding data in the two-dimensional flattening state with the help of surface flattening algorithms, so as to obtain the spatial position of the frame line data of outer plates in the actual forming state. A Dijkstra-compass intersection-solving algorithm is proposed to achieve surface flattening of ship outer plates. Firstly, the point cloud data of the outer plate shape surface is interpolated and fitted by NURBS to obtain the surface data of the outer plate. Then, the Dijkstra search algorithm is used to find the geodesic, and the frame line curvature is calculated according to the triangular similarity law. Finally, the geodesic line and the middle frame line are expanded, and the surface flattening data is obtained by further expanding the mesh points. This method is used to flatten the cylindrical and circular table surfaces, and the flattening error is less than 3mm compared with theoretical values. The test results show that the proposed method can effectively flatten the three-dimensional surface of the ship’s outer plates, and the deployment accuracy meets the actual use requirements.
Optimized design of measurement wiring for multi-beam bathymetric system based on geometric modeling
Authors: Wan Ziying , Li Jiaying , Wei Lai 
Published: December 2024

Abstract
In this paper, by establishing a mathematical model of the coverage width of the multi-beam bathymetric system and the overlap rate between adjacent strips, and combining it with a computer language program, several unknown quantities, such as the coverage width of the multi-beam bathymetric strips, the opening angle of the multi-beam transducer, and the overlap rate with the previous line of measurement, were accurately calculated. In addition, the study extended the model with optimization and in-depth analysis to determine the shortest measurement length of the multi-beam survey vessel. Finally, the validity and accuracy of the model in actual measurements are verified by testing the model. The model improves the working efficiency and measurement accuracy of the bathymetric system and provides an important theoretical basis for future marine scientific research.
Spread spectrum encode watermark algorithm in document images
Authors: Xu Jianing , Xu Xin , Zhu Xiaoqiang 
Published: December 2024

Abstract
This paper introduces a document image watermarking algorithm based on spread spectrum coding patterns. The algorithm firstly encodes the watermark information to be hidden using spread spectrum coding patterns to generate watermark code blocks. These watermark codes are characterized by their robustness against tampering, difficulty to forge, and ease of recognition. The watermark information is then embedded by fine-tuning the corresponding pixels in the B channel, achieving the imperceptibility of the watermark. During the decoding process, the document images are subjected to obtain the linear characteristics, and the Hough transform is used to correct the document image. Experimental results show that this method has strong robustness against most noise attacks and can handle certain scenarios of rotation and occlusion, making it suitable for fields such as copyright protection. Patterns
A hybrid graph-spatial spectral transformer framework for hyperspectral image analysis
Authors: Butt Imtiaz Ahmed , Bo Li , Qutab Irfan , Butt Riaz Ahmad , Fatima Unaiza , Arif Muhammad Ammaz 
Published: December 2024

Abstract
Hyperspectral Image Classification (HSIC) is proving challenging because of the data’s huge dimensionality and the intricate link between spectral and spatial information. This study introduces a new approach called the Hybrid Graph-Spatial Spectral Transformer, which aims to address these issues. This approach combines the benefits of graph-based algorithms with spatial-spectral transformers. Regarding this matter, it regards HSI characteristics as a graph structure, where each node represents a single pixel and edges denote spectral similarity. This enables complete integration of the two dimensions. The sophisticated attention mechanism in this model enables the acquisition of comprehensive spatial-spectral representations, hence improving the accuracy of class differentiation. Furthermore, the model excels at capturing extensive connections between different spectral bands, allowing for a more profound understanding of the complex relationships within hyperspectral imaging (HSI) data. The capacity to flexibly modify attention weights across various spectral resolutions enhances its flexibility and accuracy. Empirical findings using established hyperspectral imaging (HSI) datasets consistently demonstrate that this model consistently surpasses current state-of-the-art methods, leading to a substantial increase in classification accuracy.