bluuebunny/crossref_metadata_2025 huggingface dataset:
The (Vertex) Gutman Index of One Vertex Union of Two Cycles
Authors: Wang Kelun , Guo Haili
Published: January 2022

The Gutman index is a variant of the Wiener index, which related to the degree and the distance. In this paper, we study the vertex Gutman indices of a special kind of graphs, one vertex union of two cycles. And the maximum and minimum of vertex Gutman indices are studied. The results show that the vertex Gutman indices has the maximum at the center and has minimum at some vertices nearest the center.
Modeling Thermal Environment Responses to Terrain and Urbanization of Metropolis
Authors: Tao Sulin , Li Yuhong
Published: January 2022

Thermal environment responses to terrain and urbanization of Beijing, a metropolis of China, were simulated by the Weather Research and Forecasting model (WRF) with the single-layer Urban Canopy model (UCM). Four numerical experiments were designed: (1) the control experiment (Control exp), (2) no-terrain sensitive experiment (No-Terrain exp), (3) no-urban surface sensitive experiment (No-Urban exp), and (4) real land surface sensitive experiment (LU exp). Results indicate that better near-surface air temperature simulations were obtained after using MODIS land surface type product data MCD12Q1. The foehn effect due to northwestern mountains in Beijing were simulated to intensify the high temperature intensity in the plain area. Urban heat island effect existed in this area day and night, and the heat island intensity in the nighttime was obviously greater than that in the daytime. As a result of urbanization, the nighttime temperature had risen by 1.5∼3.5 °C and the expansion range of nighttime high temperature areas was basically consistent with the urban expansion range.
Deterministic and Stochastic Modeling Approaches for Saturation Nonlinearity
Authors: Peng Pai , Huang ChunQing
Published: January 2022

Being different from the most traditional methods of nonlinearity modelling, non-parametric modelling approaches viz. deterministic and stochastic approaches for saturation nonlinearity are proposed in the sense of system impulse response. Based on deterministic approach, the closed-loop system involved saturation nonlinearity can be modelled as the response of the closed-loop system that is subject to impulse stimulation. Alternatively, the closed-loop system involved saturation nonlinearity can be modelled in stochastic manner, in which the impulse response coefficients are estimated by the FCOR algorithm. Moreover, it shows some linear relationship of the impulse response coefficients between different saturation ratios in both the deterministic and stochastic models. This is illustrated by three different numerical examples.
A Detection Model of the Moving Direction in Vertical for UAV to Search Ground Infrared Targets
Authors: Yang Yang , Li Zhijun , Wu Yunqiang , Li Ke , Lu Jie
Published: January 2022

Regarding the relative detection of the moving direction in vertical between the unmanned aerial vehicle (UAV) and the ground target, we have been inspired by the functional advantages of flying insects in nature, such as lightweight, low computational complexity, low power, and the natural characteristics of high adaptability and high reliability in the detection and tracking or escape process of targets. Based on this, with the help of LGMD (lobula giant movement detector) neuron modeling, this paper proposes a detection model of the moving direction in vertical for UAV ground infrared targets based on LGMD neurons modeling (referred to as LGMD-UAVGIT model). In this paper, experiments and tests are mainly carried out on infrared imaging videos taken by UAVs, thus verifying the effectiveness of the new model proposed in the paper for detecting the two typical vertical movement directions of UAVs that are relatively far away from and close to the ground targets.
Prestressed Modal Analysis of Wind Turbine Blade Considering Fluid-solid Coupling
Authors: Li Shanyao , Wang Yingbo , Sun Haipeng , Sun Changle , Zhang Xiaolin , Liu Tingrui
Published: January 2022

Wind turbine blade is a kind of slender elastic body structure, which is prone to vibration and deformation during operation, seriously affecting the smooth operation of wind turbine. Taking the 1.5MW wind turbine blade as the research object, the three-dimensional shell model of the blade is established based on Solidworks, and the composite material layer design of the blade is carried out in ANSYS ACP. The stress and deformation of the blade in the flow field are studied based on the fluid structure coupling method. The first six natural frequencies and modes of the blade are obtained by taking the stress of the structural field as the prestress of the modal analysis. The results show that flapping and shimmy are the main vibration forms of the blade. When resonance occurs, the fluctuation of the blade in the flapping direction is the largest, and the maximum stress appears near the blade root.
Development of Mobile Robot System Based on Nano-scale Micro-surface Measurement
Authors: Ji Zhongwei , Wang Pan , Jia Jiahao , Ding Yan , Zhao Kang , Liu Tingrui
Published: January 2022

Absrtact. The system development of the mobile robot mainly includes two parts: one is to build a laser interference system based on piezoelectric ceramic dynamic carrier; The other part is the image processing of the interference fringe pattern collected by the interference system. The laser interference system can be installed on the front-end manipulator of the robot as an integral structure. The shape information of the measured micro-surface can be obtained by processing the interference fringes collected by the image acquisition card on the interference system, so as to achieve the purpose of high-precision surface roughness measurement.
Design of a Small Sweeping Robot Based on STM32
Authors: Zhang Xiaosheng , Zhan Gaopeng , Xu Xin , Fang Kai
Published: January 2022

With the continuous improvement of people’s living standards and the emergence of various intelligent appliances, a household floor sweeping robot is designed in this subject, which can automatically clean the ground in the room. The robot takes STM32F103ZET6 single chip microcomputer as the controller, uses two DC motors and L298N driving chips to drive the robot to walk, and uses ultrasonic sensors to detect indoor obstacles, The infrared sensor is used to detect the indoor edge position, the straight travel control of the robot is realized through the coding disk combined with PID algorithm, and the turning control is realized through differential control and PWM speed regulation. The robot can realize the garbage cleaning in the regular room, and has a certain application prospect.
Research on Multi-modal Medical Image Fusion Based on Multi-Scale Attention Mechanism
Authors: He Baiqing
Published: January 2022

Image fusion technology has been widely used and researched in the fields of medicine, aviation, military and civil. Compared with the traditional image fusion technology, the fusion image technology based on intelligent algorithm generates more realistic, clear and reliable images, and has a lot of detailed information. Deep neural networks have rapidly developed into a research hotspot in medical image analysis, which can automatically extract hidden pathological information from medical image data. Multi-scale and attention mechanism are two important modules in neural networks, which can significantly enhance the features extracted by the network. The problems that need to be solved for medical image fusion based on multi-scale attention mechanism include: how to build a multi-scale module, how to build an attention module, and how to combine multi-scale and attention mechanisms. Construct a deep learning network through a multi-scale attention mechanism, and then adjust the parameters and train the network to achieve multi-modal medical image fusion. In the process of building neural networks, multi-scale and attention mechanisms are incorporated, and multi-scale features of multi-modal medical images are extracted and enhanced for fusion. Through a large number of experiments: (1) The edge strength of the fused image is expected to increase by 10%-20% based on the average value of the existing algorithm; (2) The fused image can achieve high color fidelity and rich detailed information; (3) ) The time required for the fusion algorithm is expected to be reduced by 1%-10% based on the average value of the existing algorithm.
Research on Virtual Campus Roaming System Based on unity 3d Technology
Authors: Luo Hua , Zhou Yiren , Li Yuxuan
Published: January 2022

with the development of virtual simulation technology and network technology, the application of virtual technology in education, games and so on is deepening. Use 3ds Max and unity 3D software to organically combine 3D technology with virtual reality. Taking the hero campus of Nanchang Institute of technology as the design case, this paper aims to develop a multi-user virtual campus roaming system, so that users can truly experience the campus environment anytime and anywhere through the network and roaming equipment, and play a positive role in the information construction of colleges and universities in the future.
Research on Software Defect Prediction and Analysis Based on Machine Learning
Authors: Peng Xuemei
Published: January 2022

The defects of machine learning prediction technology can be more comprehensive and automatic learning model to find the defects in software has become the main method of defect prediction, selection and study of algorithm is the key to improve the accuracy and efficiency of machine learning. Comparing different machine learning defect prediction methods reveals that the algorithms have different advantages in different evaluation indicators, the use of these advantages and combining the stacking ensemble learning method in machine learning is put forward different prediction algorithm of prediction results. As software metrics and again the prediction model of software defect prediction combined machine learning algorithm is based on the experiment with the model of Eclipse, the data sets show the effectiveness of the model.
DOA Estimation of Underwater Acoustic Targets Based on Bayesian Compressed Sensing
Authors: Liu Fei
Published: January 2022

Aiming at the performance degradation or even failure of existing underwater acoustic target direction of arrial (DOA) estimation methods under the conditions of low signal-to-noise ratio and low snapshot, a underwater acoustic target DOA estimation method based on sparse Bayesian compressed sensing theory is studied, and simulation experiments are carried out by MATLAB to verify the feasibility and effectiveness of the proposed method. Simulation results show that compared with CBF , MUSIC and OMP algorithms, the proposed method can improve the estimation accuracy in the case of lower snapshot number, lower number of array elements and smaller array element spacing, and can achieve high resolution DOA estimation in the case of low signal-to-noise ratio and close position of multiple target signals.
Strength Analysis on the Frame of Off-way Wide-body Mining Dump Truck Based on Finite Element Analysis
Authors: Liu Weiwei , Liu Jiang
Published: January 2022

The frame is an important component for the off-way wide-body mining dump truck. The carrying capacity of the truck is greatly affected by the strength of the frame. The finite element analysis was used to simulate the strength of the frame under the work condition of full load and lifting. The maximum stress of the frame is 214MPa under the full load condition, and the maximum stress of the frame is 459MPa under lifting condition. The upper surface of the frame near the rear axle is the more dangerous section for the frame under the two working conditions. The stiffness of the front leaf spring has very impact to the maximum stress of the frame for both full load condition and lifting condition, but has some impact to the maximum stress near the support of the front leaf spring.
High-Frequency Vibration Control of Rotating Beam Based on Trailing-edge Flap
Authors: Wang Jian , Li Shanyao , Sun Changle , Liu Tingrui
Published: January 2022

Abstract This study is to investigate an active control method, based on trailing-edge flap, in high-frequency vibration control of rotating blade beam. The structure is modeled as composite blade beam with circumferentially asymmetric stiffness configuration, which is based on analysis of the elastic flap-wise/twist displacements and incorporates the angle control of trailing-edge flap driven by a stepping motor. Aerodynamic expressions are based on a novel quasi-steady model suitable for trailing-edge flap. Based on a strip theory, the multi-body dynamic aeroelastic system is analyzed and solved. The active control is realized by Hœ algorithm using linear matrix inequality (LMI) design. This study is to investigate time-domain stability analysis and robust control method, realize displacement response analysis and robust performance analysis, and input signal display of trailing-edge flap angle. The optimization mechanism of LMI is to optimize uncertain robust performance parameters based on the selection of robust control parameters, so that the controlled displacement and control input are kept within reasonable ranges. The reliability and robustness of H» control algorithm based on LMI are verified by comparisons of the results of high-frequency vibration control using different robust performance parameters.
Research on Position Sensorless Vector Control of Synchronous Reluctance Motor Based on High Frequency Injection Method
Authors: Li Dengke , Liu Yukun
Published: January 2022

In order to achieve the high-performance control position sensorless vector control of synchronous reluctance motor (SynRM), this paper investigated its running-up performance and capability at zero or low speed range. The contribution of this paper mainly includes two parts. Firstly, it takes cross-saturation effect into consideration, Secondly, the paper improves the control stiffness and reliability under low-speed sensorless operation condition by adopting the pulsating sinusoidal high frequency voltage injection snesorless method. By injecting high-frequency voltage excitation signal, the rotor position is estimated from the high-frequency response current. The simulation results verified the feasibility of the control algorithm, and fulfilled the running-up of the SynRM at zero speed, the capability of stability is evaluated via simulation results.
Digital Twin-Based Reconfiguration Time Point Prediction Method for Reconfigurable Manufacturing Systems
Authors: Liu Zhihao , Wang Taiyong , Zhou Yiren , Zhao Wei , Zheng Mingliang , Ke Zhisheng , Zhao Xiaomeng
Published: January 2022

In the operation cycle of reconfigurable manufacturing system, the system needs to be continuously reconstructed to adapt to the changes of market demand. Aiming at the problem of when to reconstruct the reconfigurable manufacturing system, combined with digital twinning, a prediction method of reconfiguration time point of reconfigurable manufacturing system is proposed. Firstly, the factors affecting the processing capability and function of reconfigurable manufacturing system are analyzed quantitatively, the optimization objective is to minimize the part completion time and reconfiguration cost, and the multi-objective cuckoo algorithm is used to solve it; Then, the digital twin model of reconfigurable machine tool and reconfigurable production line is constructed, so that the state of reconfigurable manufacturing system can be truly mapped in virtual space, and the simulation and prediction framework of reconfigurable manufacturing system is constructed; Secondly, the initial scheme configuration is generated according to the production demand, the set threshold is optimized and simulated, and the simulation sample data is analyzed to obtain the appropriate reconstruction time; Finally, an engineering example is given to verify the feasibility and effectiveness of the method.
An Improved Dark Channel Prior Method for Dusty Image Restoration
Authors: Zhang Ya , Yang Weimin
Published: January 2022

For the images which were obtained in a dusty environment, because of the tiny particles suspended in the atmosphere absorb and scatter the light, there is serious haze in the images. The haze can directly cause colour changes and the loss of image details. As a result, a lot of efficient features in the dusty image were concealed or weakened by the haze, which created difficulties to obtain a natural and clear restored image, and has brought serious impact for aerospace, automatic driving and traffic monitoring in the dusty environment. An improved restoration method based on dark channel prior theory and gradient domain guided filtering was proposed to remove the haze and restore the dusty image. According to the characteristics of the dusty images, a specific guided image was adopted to make gradient domain guided filtering for the dark channel image firstly, so that the transmittance image can be better refined than that in the dark channel prior method, and then the image can be restored according to the image degradation model. Experiments show that the visual effect of the restored image is natural and clear, and can retain most effective features, which lays a foundation for computer vision-based target monitoring and recognition in the dusty environment.
Research on University Computer Teaching Based on Data Mining Learning Model
Authors: Xu Guibing
Published: January 2022

Under the background of the development of big data, the research of learning analysis technology has shifted from theoretical fields to practical application fields such as teaching big data analysis and learning behavior prediction. However, it is worth noting that the wide application of big data technology has led to a large increase in text data, and how to quickly obtain accurate information has become a decisive factor in improving students’ learning ability. Therefore, this article combines the current status of computer teaching in colleges and universities to construct a data mining learning model to evaluate the effects of current college computer teaching methods. On this basis, it helps computer teachers to choose the most reasonable teaching style and teaching methods, and guide students to better master computer skills in order to achieve the best computer teaching effect.
Hybrid MMC Redundancy Configuration Calculation Method Based on Heuristic Algorithm
Authors: Lu Xiaojian , Zeng Zi’an , Lv Xichao , Luo Xusong , Zhang Gongliao , Fan Youping
Published: January 2022

Most of the existing redundant configuration methods of modular level converters (MMC) only consider the reliability of the MMC, and rarely consider the utilization of insulated gate bipolar transistors (IGBT). A heuristic algorithm-based calculation method for hybrid MMC redundancy configuration is proposed in order to better meet the engineering practicality. Firstly, the topology of the hybrid MMC is introduced, and the correlation between submodules is introduced into the calculation of its reliability. Secondly, the index of IGBT utilization is proposed to judge the economic advantage. The effects of correlation and service life on the reliability of the hybrid MMC and the IGBT utilization are analyzed. Then, heuristic factors are constructed with reliability and IGBT utilization, and the optimal redundancy configuration scheme of hybrid MMC is obtained by heuristic algorithm. Finally, based on the parameters of Kunliulong multi-terminal hybrid DC transmission project, the calculation is verified in Matlab and compared with the results of the difference method to illustrate the feasibility and superiority of the proposed redundancy configuration calculation method.
The CEEMD-LSTM-ARIMA Model and Its Application in Time Series Prediction
Authors: Sun Chen , Nong Yingxiong , Chen Zhibin , Liang Dong , Lu Ying , Qin Yishuang
Published: January 2022

Research shows that there are some data sets with strong timing in reality. After certain processing, they can predict the changes of transactions in the future to some extent and play a positive role in guiding production. However, they often have the characteristics of overall trend variability and seasonal fluctuation, and are also affected by many random factors. Therefore, the data show strong non stationarity. In this paper, a CEEMD-LSTM-ARIMA combined model is proposed. This method reconstructs variables by decomposing time series data, and adopts appropriate methods to deal with variables with different characteristics. In this paper, CEEMD-LSTM-ARIMA combined model is used to predict cigarette data. The experimental results show that the proposed combined model has faster convergence speed and higher accuracy than LSTM and ARIMA, and has more advantages in time series data prediction.
Phase-Variable Modeling and Comparative Study between a PMa-CPA and a CPA Alternator by Simulation Analysis
Authors: Tsai Ming-Fa , Tseng Chung-Shi , Bai Shu-Yui
Published: January 2022

This paper presents the phase-variable modeling of a permanent magnet-assisted claw-pole alternator in PSIM simulation software tool with the performance compared with a claw-pole alternator model, which is a special case of the permanent magnet-assisted claw-pole alternator model with the rotor permanent-magnet flux constant setting equal to zero. The constructed model can be simulated as a real alternator directly connected to a diode-bridge rectifier or switch-mode rectifier circuit for the integrated power application system simulation analysis. The proposed model contains two features, one of which is that the stator and rotor windings are circuit-based. The other one feature is that the mechanical torque input is based on a mathematical function. In this model, the rotor position-dependent variable inductor is replaced by a separate voltage source according to the voltage source absorption theorem. The simulation shows that the proposed model has faster torque step response and higher power efficiency than the claw-pole alternator model. The proposed model can be employed to the application of the control design and simulation study of voltage regulation in automobiles. The simulation results with 15-V command and the load sudden change verify the correction of the proposed model.
The Optimization Simulation Analysis of Heavy NC Machine Tool Bed
Authors: Luo Bing , Zhao Xin
Published: January 2022

In order to reduce the high manufacturing cost of heavy numerical control (NC) machine tool bed, the paper first introduced the stiffness and strength calculation method of constant cross-section and constant span beam, and deduced the theoretical optimization model with the minimum cross-section area of the bed as the optimization objective. Using the interior point method completed the optimization analysis of the machine bed. Then, the ISIGHT software was used to realize the integration of design software and analysis software, and the optimization simulation analysis of the machine bed was completed under the same interface. Finally, the calculation accuracy of the theoretical model is verified by comparing the optimization results of the theoretical model and the simulation model. The weight can be reduced by more than 10% on the basis of ensuring the stiffness and strength of the machine bed. The method lays a theoretical foundation for the manufacture of the machine bed.
Analytical Modeling for Magnetic Field Calculation of SPMSM Based on Equivalent Magnetic Network Method
Authors: Wang Jin , Zhang Jialin , Yu Zhanyang , Du Jianmin , Li Yan
Published: January 2022

In order to quickly calculate electromagnetic parameters and reduce total harmonics distortions (THD) of air-gap flux density for surface-mounted permanent magnet synchronous motor (SPMSM), the equivalent magnetic network method (EMNM) is used. Compared with traditional magnetic circuit method, the calculation result is more accurate and the calculation speed is faster than finite element method FEM). The EMNM considering the stator groove shape and core saturation is established by piecewide fitting of annular equivalence and magnetic ring curve formulas of the groove fan. The accuracy of EMNM is verified by FEM.
Round Traffic Sign Detection Algorithm
Authors: Huang Yinrong , Wang Bing , Yuan Xiemin
Published: January 2022

Traffic signs are an important part of autonomous driving and intelligent transportation. It provides instructions for pedestrians and vehicles and is critical to road traffic safety. However, existing detection algorithms cannot achieve real-time high-precision detection. Therefore, this paper proposes an algorithm that combines traditional methods with deep learning to detect circular traffic signs. Based on the HSV color space, the red and blue channel images are separated, and the candidate regions of the original image are extracted using the Hough transform. The shallow convolutional neural network (CNN) classifier rejects not traffic signs and classifies traffic signs. Experiments show that the algorithm is real and effective. On the CPU platform, the average accuracy rate is 96.2%, and the detection speed reaches 0.3 s / frame. Under the condition of ensuring the average accuracy rate, the detection speed is greatly reduced. The algorithm achieves the fastest speed, which makes real-time high-precision detection possible. The algorithm is more suitable for vehicle embedded systems.
A Region Preference-based Optimization Algorithm for Satellite Mission Planning Problem
Authors: Xiong Minghui , Xiong Wei
Published: January 2022

For the earth observation satellite mission planning problem, objectives such as observed target quantity, observation profit, energy consumption, image quality should be considered simultaneously, which is a many-objective optimization problem. Classical optimization-based mission planning algorithms obtain a set of non-dominated solutions in the entire search space, while only a single satisfy final plan is desired by decision maker. In this paper, a five-objective optimization model for satellite mission planning problem is constructed, then a region preference-based evolutionary algorithm, HMOEA-T, is applied to obtain the desired solutions. The decision makers describe the preference on each objective in target region form, then the algorithm guides a more detailed search within the preference region rather than the entire Pareto front. Comparative studies with preference-based methods (T-NSGA-III) and classical methods (NSGA-III) are conducted. We have exemplified the proposed method manage to obtain the solutions satisfying the mission planning preference and achieve better performance in convergence and diversity.
Research on the Selection of Path Planning Algorithm: A Case Study in Leeds
Authors: Yan Pang
Published: January 2022

Path planning algorithms are the core of path planning technology, and different path planning algorithms have different performances in terms of search efficiency and planning efficiency in different application areas. The traditional path planning algorithm selection mainly relies on personal knowledge and experience and takes a qualitative analysis method. With the variety of path planning algorithms and the increase of environmental complexity, the limitations of this empirical method are more and more obvious, and it is difficult to meet the actual needs of path planning and achieve the ideal path planning effect. The selection of path planning algorithms is an evaluation problem involving multiple factors and requires comprehensive algorithm selection and analysis. This paper addresses the problems of the selection method of the path planning algorithm, applies uncertainty theory and multi-attribute decision theory, constructs an evaluation system for path planning algorithm selection, proposes a multi-criteria EV-VIKOR decision model and decision method for path planning algorithm selection, and combines the results show the effectiveness of the decision-making method proposed in this paper.
Research on Rope Stripping Device of Elevator Speed Governor
Authors: Feng Shuangchang , Chen Jie , Liang Yanchun , Fang Kun
Published: January 2022

The elevator speed governor needs to be inspected regularly. According to the requirements, the maintenance unit of the inspected elevator shall verify the action speed of the speed governor every two years (within the service life of 15 years) or every year (over the service life of 15 years). When checking the speed governor, it is necessary to separate the steel wire rope from the speed limiting wheel, drive the speed limiting wheel to rotate through an external device, and then observe whether it is effective. In the existing means, when it is necessary to separate the steel wire rope from the speed governor, two forceps are usually used to clamp the steel wire rope respectively, and the two forceps are respectively placed on the surface of the elevator machine room. When the steel wire rope between the two forceps is long, the steel wire rope is separated from the speed governor wheel. However, this rope removal method is cumbersome and easy to pinch hands, and the pliers will also deform the steel wire rope in the clamping part. In order to solve the above problems, this paper studies a rope stripping device of elevator governor, which is convenient, fast, safe and reliable.
Design of cable laying condition monitoring system
Authors: Shen Shengwei
Published: January 2022

This paper designs a cable laying condition monitoring system. The system uses endoscope to monitor the defects in the pipeline, and uses tension sensor to monitor the traction in the process of cable laying. Through the test and test data analysis, the tension measurement range of the system is 0-10T and the measurement accuracy is 0.01T. The video system can clearly observe the defects in the cable duct. Therefore, the monitoring system designed in this paper can monitor the cable laying state and avoid the damage to the cable caused by pipeline defects and excessive tension.
A modified PSO Algorithm based on Cloud Theory for optimizing the Fuzzy PID controller
Authors: LI Xiang , Chen Jianjun
Published: January 2022

To obtain a more efficient intelligent controller, this paper presents a modified cloud theory-based particle swarm optimization (CTPSO) algorithm to improve fuzzy PID controller. Cloud evolution and mutation methods based on cloud theory are introduced to tune inertia weight of particle swarm optimization algorithm (PSO), which can improve the optimization accuracy and speed of PSO. The comparative experiments indicate that CTPSO performs better than PSO and other optimization algorithm recently proposed by other researchers. The CTPSO is used to set the initial PID control parameters and optimize control rules of fuzzy PID controller. According to an engineering case of the 180°C-die heater’s temperature control, the novel optimized fuzzy PID controller can suppress the oscillation and overshoot significantly. It also owns smaller adjustment time, static error and better comprehensive performance compared with the initial controller.
Simulation and analysis of temperature characteristics of a dual-coil magnetorheological brake
Authors: Huang Yuming , Wu Jie
Published: January 2022

In this paper, the temperature characteristics of a dual-coil magnetorheological (MR) brake have been studied by theoretical analysis and finite element simulation. Firstly, the mathematical model of the temperature field of the MR brake is established based on the analysis of the heat source. Then, the temperature field simulation analysis under steady-state and transient operation has been conducted. From the simulation, the maximum slip power of MR brake under steady-state conditions is obtained. Under slip operation, the temperature in MR fluid working gaps of the dual-coil MR brake rises rapidly. The research results can provide a reference for the research of heat dissipation technology of MR brakes.
Reinforcement learning control method of torque stability of three-phase permanent magnet synchronous motor
Authors: Tian Mengqi , Wang Ke , Lv Hongyu , Shi Wubin
Published: January 2022

Regarding the control strategy of the permanent magnet synchronous motor, the field-oriented control based on the PI controller have the instability of the output torque. In order to stabilize the output torque of the permanent magnet synchronous motor, this paper adopts reinforcement learning to improve traditional PI controller. Finally, in the MATLAB/Simulink simulation environment, a new control method based on reinforcement learning is established. The simulation results show that the reinforcement learning control method used in this paper can improve the stability of the output torque.
Prediction of Vehicle Braking Deceleration Based on BP Neural Network
Authors: Zhang Shen , Li Da , Du Feng , Wang Tao , Liu Yunpeng
Published: January 2022

Abstract:This paper first introduces the BP neural network, upgrades and optimizes the neural network according to the actual demand, and then establishes the prediction model of vehicle braking deceleration according to the relevant parameters affecting vehicle deceleration. According to the vehicle relative distance, vehicle relative speed, front vehicle acceleration, collision time and lateral distance, the vehicle deceleration is predicted and analyzed. After data verification, the vehicle braking deceleration prediction model is more accurate for vehicle deceleration prediction, and the established prediction model is effective.
Research on system simulation based on fuzzy self-tuning
Authors: Xu Gang
Published: January 2022

This paper introduces the principle of fuzzy control. On this basis, a fuzzy self-tuning PID controller is designed to the requirements of SRD system. The fuzzy self-tuning PID controller is introduced into the switched reluctance motor speed regulation system, the switched reluctance motor speed regulation system based on fuzzy self-tuning PID is simulated and compared with the conventional PID switched reluctance motor speed regulation system. The comparison results show that the application of fuzzy self-tuning PID controller in the switched reluctance motor speed regulation system can make the speed regulation system obtain good dynamic Static performance.
Remaining Useful Life for Aircraft Engine Forecasting Based on Data-driven
Authors: Niu Wei , Huang Wei , Wang Hao , Cheng Juan , Wang Sen
Published: January 2022

As for the low forecasting precision problem about time series in avionics complex system, a time series combined forecasting model of complex systems was established based on GM (grey model is referred to as GM). However, using the traditional GM(1, 1) model to predict complex system failures might result in huge forecasting errors. To solve the drawbacks of the traditional GM(1, 1) model, this work developed the traditional GM(1, 1) model (abbreviated as DGM(1, 1)), which can predict non-geometric sequences more correctly. To reduce such mistakes, a PS-DGM (1, 1) forecast model was created by combining DGM(1, 1) with the particle-swarm optimization process. The DGM(1, 1) model was utilized to generate the forecasting sequence, and then the particle-swarm optimization approach was employed to further alter them, resulting in the degradation trend prediction of avionics complex system characteristic parameters. The experimental results show that the PS-DGM(1, 1) model’s validity was confirmed by tracking and forecasting avionics equipment experiment data in a real-world setting, and that the suggested model achieves higher precision than the old one.
Impact of plant-based meat alternatives on cattle inventories and greenhouse gas emissions
Authors: Lusk Jayson L. , Blaustein-Rejto Dan , Shah Saloni , Tonsor Glynn T.
Published: January 2022

New plant-based meat alternatives that aim to mimic the taste and texture of beef could have significant economic, environmental, and animal welfare impacts if they replace animal-based meats and reduce livestock production. Whether plant-based meat alternatives can achieve these ends depends on the extent to which consumers are willing to substitute for plant-based meat alternatives, the structure of the meat industry, and the inter-linkages of the livestock industry with the other parts of the economy. We construct and calibrate an economic model to estimate how a reduction in plant-based meat prices, or increases in demand for plant-based meat, in the United States affect cattle production. For every 10% reduction in price or increase in demand for plant-based meat alternatives, we estimate U.S. cattle production falls approximately 0.15%, U.S. cattle producers’ economic welfare falls by $300 million/year, and U.S. consumer welfare rises by $513 million/year. Increases in U.S. demand for plant-based meat alter trade patterns, leading to a reduction of beef imports and an increase in beef exports, a phenomenon that further reduces global greenhouse gas emissions and land use given the relative efficiency of U.S. beef production. For every 10% reduction in the price of plant-based meat alternatives, we estimate that the global reduction in emissions is equivalent to 0.41% of U.S. emissions from beef production and 1.4 % when including carbon sequestration from reforestation of abandoned cropland and pasture and reduced land-use change emissions.1 Even substantial reductions in prices of plant-based meat alternatives are unlikely to have substantive impacts on the U.S. cattle population and emissions, suggesting the need to also pursue alternative mitigation strategies, such as innovations to reduce the methane emissions per head.
Life-cycle impacts from different decarbonization pathways for the European car fleet
Authors: Dirnaichner Alois , Rottoli Marianna , Sacchi Romain , Rauner Sebastian , Cox Brian , Mutel Christopher , Bauer Christian , Luderer Gunnar
Published: January 2022

For light-duty vehicles (LDVs), alternative powertrains and liquid fuels based on renewable electricity are competing options considered by policymakers and stakeholders for achieving necessary CO2 emission reductions in the transport sector. While the urgency of climate change and the need to reach mitigation targets are well understood, system-wide implications along other sustainability dimensions need further exploration. We integrate a detailed transport system model into an integrated assessment framework and couple it with prospective life cycle impact analysis. This allows to assess different technological pathways of the European LDV fleet until 2050 for a comprehensive set of environmental and resource depletion indicators. Results indicate that greenhouse gas emissions drop significantly in all mitigation scenarios. However, impacts increase in several non-climate change impact categories even with fully renewable electricity supply. Additional impacts arise from the production of battery and fuel-cell components, and from a significant rise in electricity demand, most prominently for synthetic fuels. We consequently find that changes in mobility life-styles and in the relevant industrial processes are paramount to reduce environmental impacts from a climate-friendly LDV fleet across all categories.
Analytical study regarding topological optimisation of an internal combustion engine cylinder block
Authors: Gaidur M , Pascal I , Rakosi E , Ulian T , Talif S , Manolache Gh
Published: January 2022

The continuous rush for development has led the world of automotive engineering to progress that seemed unimaginable just a few years ago. This research paper examined the impact of a topological optimisation of an internal combustion engine block. Starting with the initial conditions, a constraint and load case scenario was established, after which a FEA simulation was conducted to set the reference values. In the last part of the research paper, test results are head-to-head compared to determine and quantify the improvements. This study aims to reduce the volume of the optimised part and increase its overall rigidity. The topology optimisation process represents a good solution for “what if” scenarios. By varying optimisation constraints, the designers can quickly check if the mass reduction of the analysed part is worth the changes.
Numerical investigation of a pressure wave supercharger
Authors: Costiuc I , Costiuc L
Published: January 2022

The paper aims at a numerical investigation of the evolution of velocity, pressure and temperature field along the wave rotor channels for a pressure wave supercharger. Since in literature most of the studies are made considering the working fluid as incompressible and inviscid in a 2D field, the present study is using the compressible and viscous terms in unsteady Navier-Stokes equations for fluid in 3D field. The geometry was drawn in CAD software using measurements made on a real model of the CX-93 pressure wave supercharger. The simulation was conducted using a CFD code for unsteady 3D k-e, k-co model approach to reproduce data such as pressures, temperature and mass flows which are usually measured in real engine pressure wave supercharging. The computational domain for uRANS was modeled as a moving rotational domain with adaptive meshing. Results such as velocity, pressure and temperature field in the rotor channels were obtained for exhaust gas inlet pressure of 0.28 MPa and 1465 K temperature at different rotational speeds. The air inlet state considered was: 0,098 MPa and 293 K. Supercharging by means of a pressure wave supercharger, in order to improve the performance of an internal combustion engine, appears to be a promising solution since the exhaust gas generates a benefice boost of intake air with significant advantages when compared to the conventional turbocharging. The numerical modelling of the complex phenomena occurring within the narrow channels might be a useful tool for improving the pressure exchange between the working fluids, either by modifying the input parameters or by optimizing the geometry of the rotor, ports or pockets.
Numerical evaluation of vehicles aerodynamics in platoon using CFD simulation
Authors: Scurtu I L , Gheres M I
Published: January 2022

Due to increased traffic and new technologies developed to improve road safety, a new vehicle driving technique is being studied. The vehicles’ platooning driving method has as objective to minimize the aerodynamic drag and therefore the fuel consumption. The aim of this study is to evaluate the distance between platoon traveling vehicles and to propose an optimal travel distance. The CFD evaluation is performed for two categories of vehicles at a given velocity and distance between them for two cases: in the first simulation scenario, a tractor-trailer is represented, followed by a SUV positioned at a given distance from the rear of the vehicle combination; in the second simulation, two tractor-trailers at the same boundary condition as for the first case are simulated. The vehicles models are made by using a CAD modelling environment, respecting the overall dimensions of an existing vehicle. The numerical evaluation of a distance between vehicle models is performed using the CFD method based on the Navier-Stokes equations averaging. The last part of the paper presents the interpretation of CDF simulation results, establishing the recommended travel distance between vehicles and conclusions of this study.
Overview on globally applied used engine oil recycling technologies
Authors: Ratiu S A , Tirian G O , Mihon N L , Armioni M D
Published: January 2022

Due to the growing importance of environmental issues in modern society, the global economy has been compelled to refocus further towards eco-friendly, low-pollution technologies based on waste recycling. Furthermore, these technologies not only offer economic value to products at the end of their life cycle, but they have the ability to address the issue of inadequate waste storage in landfills. At the same time, given the growing trends in the number of vehicles, the demand for lubricants is also increasing, which involves the generation of larger and larger amounts of used engine oil. Being included in the category of hazardous waste, it requires management based on sustainable principles, and recycling is recommended as a preferred method of treatment, as it still has a high economic value. This article aims to present some of the technologies that have been effectively implemented on a global scale for the recycling of used engine oil, as well as a series of advantages that these processes present, both ecologically and from an economic perspective.
The influence of the air filter location on the intake system temperature in the case of engines for drifting
Authors: Birtok Baneasa C , Budiul Berghian A , Ratiu S A
Published: January 2022

This paper presents a comparative study regarding the influence of the air filter location on the intake system temperature in the case of engines for drifting. The heat flow dispersion map at the engine compartment was determined for four different cases. The measurements were performed with a thermographic camera in the area of the air filter and intake manifold. The results obtained after the test contribute to the efficiency of the thermal management of the engine by reducing the temperature of the intake air.
The analysis of kinematic parameters of the vehicle occupants on impact with a rigid barrier
Authors: Nedelescu C , Chiru A , Vrabie P , Trusca D
Published: January 2022

This paper studies the kinematic parameters of the vehicle occupants in case of a frontal impact between a vehicle and a concrete barrier. The main objective is to determine the head and thorax acceleration of vehicle occupants during the impact with a rigid barrier. To achieve the scope of the study a frontal damping system was used.
Considerations on reducing fuel consumption and emissions by optimizing traffic control in congested urban areas
Authors: Vilcan Adrian , Martin Ivana , Nicolae Viorel , Istrate Mihaela
Published: January 2022

The balance between city development, as, for example, an increasing number of working places and emissions control, is a challenge in our days in the urban environment. All new developments in the urban area, either commercial, office or residential, will generate a specific demand for mobility. This new demand will put supplementary pressure on the urban transport system in the influence area. Therefore, approaching it from a macro to micro dimension using transport models would be a benefit for both, as optimizing the traffic control in main junctions in the area of the development will reduce the traffic congestion and delays. The paper deals with effects on reducing fuel consumption and emissions as an effect of optimization of traffic control in main junctions in the areas of new developments.