bluuebunny/crossref_metadata_2025_split huggingface dataset:
Principle Study of MoS2 FET at lower Channel Lengths
Authors: Kumar Aruru Sai , Bharath Srinivasulu V. , Ganesh Chokkakula , Jukuru Venkat , Valluru Thanvitha , Vamsi D.P.S.S.S.K 
Published: October 2024

Abstract
This study of a two-dimensional FET (2DFET) works with a channel made of MoS2, MoSe2, and MoTe2 and different dielectric materials. Materials such as molybdenum disulfide (MoS2), molybdenum diselenide (MoSe2), and molybdenum ditelluride (MoTe2) belong to the transition metal dichalcogenide (TMD) family and are known for their fascinating electronic properties. These materials have different band gaps, carrier mobilities, and intrinsic properties that make them ideal candidates for 2D transistor channels. In this study, we investigate the influence of different dielectric materials on the performance of 2D FETs with MoS2, MoSe2, and MoTe2 as channel materials, with a strong focus on high-speed operation. Our study analyzes performance metrics like on-current (Ion), off-current (Ioff), and on-off current ratio which will be more when compared with Si-based FETs.Notably, the choice of dielectric significantly influences these metrics, with high-k dielectrics and HfO2 often surpassing SiO2.
Surface Roughness Prediction using Swarm Fuzzy SVR Technique
Authors: Akash V S , Edwin Raja Dhas J , Anton Savio Lewise K , Jesuthanam C P 
Published: October 2024

Abstract
Surface of a machined component is a significant factor in evaluating the quality. Quality of machined surface plays an important role in predicting the fatigue strength, corrosion resistance and creep life. It is tedious to realize the process parameters behind the surface roughness formation mechanism. Hence development of models, which can predict a wide variety of process parameters to assist the real time factory floor decision making process is challenging. This article addresses the development of particle swarm optimization-based support vector regression model for machining quality prediction. Data set for training and testing the proposed model is obtained from experimental observations supported with regression results with spindle speed, feed rate, depth of cut and vibration as input parameters and surface roughness as output parameter. K-fold cross validation is applied for training and testing the proposed model. Predicted results from swarm-based support vector regression model are validated with fuzzy and support vector regression models. Analysis of Variance is done using the results from signal to noise ratio computations for identifying the influence of controllable factors involved. The analysis from ANOVA indicates that spindle speed and feed rate play significant roles in determining the surface quality of the machined component. Test results reveal that the developed model can be used successfully for machinability data selection.
An examination and characterization study of the aluminum alloy Duralumin (AA2014)
Authors: Sreenivasa Rao M , Nayeem Shaik , Sasi Kiran N V S G , Gowthami K , Krishnaraj J 
Published: October 2024

Abstract
Duralumin, an aluminum alloy with strength and low size, was developed by German metallurgist Alfred Wilms in 1910. It is easy to work with, relatively soft, and ductile under normal circumstances. The alloy can be rolled, forged, and extruded to produce a wide range of products. Compared to aluminum, duralumin has a greater tensile strength, but it is less resistant to oxidation. Compared to pure aluminum, duralumin has a lower electrical conductivity and a higher thermal conductivity than steel. Initially used in stiff airship frames, its composition and heat-treatment procedures were maintained a military secret during the conflict. Duralumin can be cast, created, and manipulated with ease because of its low melting point. After annealing at temperatures ranging from 350 to 380 °C (662 to 716 °F), it is air-cooled. Now that the alloy has changed into a plastic, it is simple to deal with and shape into the appropriate portions. After that, the alloy is heated to 490 to 510°C (914 to 950°F) in order to increase its tensile qualities. After that, the duralumin is toughened by quenching. Three input factors, namely orientations (0,45,90 degrees) of the direction of rolling, strain rates (0.1,0.01,0.001), and temperatures (200,250,300), will be examined in relation to Duralumin AA2014. Yield strength, percentage of elongation, and the final strength of the samples were determined utilizing the Taguchi optimization technique, and plots of various variables were created utilizing Excel sheets in accordance with the positions of the points on the stress-strain plot. Specimen that have been post-tensiled will be SEM-examined and associated with elongation. Tensile lines will be used to analyze the work hardness and flow characteristics. The microstructural characteristics of the alloy will be used to explain the anisotropy in circulation as well as hardened behavior. The microstructures and post tensile will be examined using the optical and scanning microscopes. The X-ray deflection method will be employed to verify the crystal structure present in the cracked surfaces. Lastly, a correlation between the flow, work hardening behavior, and tensile properties of microstructures will be attempted to be established.
Design and Analysis of CVT Cooling System
Authors: Parswajinan C. , Rajesh S. , Vijaya Ramnath B. , Vasundharadevi D. , Harish Shravan V. , Santhosh Krishna N. BA. 
Published: October 2024

Abstract
Continuously variable transmission (CVT) is a form of automatic gearbox that has the ability to attain infinite gear ratios. They are used in a variety of automobiles, including scooters, Baja vehicles, and ATVs. The engine’s power is transmitted from the primary to the secondary CVT using a belt and pulley system. By adjusting the diameter of the belt over the pulleys, the notion of infinite gear ratios can be achieved. When the vehicle accelerates and during clutch slippage, a large quantity of heat is created in CVT components, resulting in a shorter component service life. As a result, cooling the CVT is required. Depending on the CVT’s speed, the surface temperature can vary from 80°C to 120°C, according to studies. The primary goal of this study is to use a layer of nitrile rubber in the casing to insulate heat from the engine, utilise engine exhaust backpressure to evacuate hot air from a duct on the CVT casing, and use other forced cooling techniques like air cooling through ducts in the CVT casing. A venturi inside a Y-tube design allows hot air to be sucked out of the CVT.
Robust switching control of DC-DC converter under dynamic periodic event-triggered mechanism
Authors: Huang Juan , Fang Jin , Fu Meng 
Published: October 2024

Abstract
The stabilization of a DC-DC converter system with a switching control approach based on a dynamic periodic event-triggered mechanism is addressed in this study. The event-triggered mechanism saves communication resources and improves the control performance. Meanwhile, by considering dynamic variables, the event-triggered condition can be changed depending on the actual situation of the system, which improves the stability and robustness of the system. The comparison and analysis of various triggering strategies show that the switching control method of dynamic periodic event-triggered mechanism can ensure system performance well and effectively reduce the communication burden. Finally, an example of a boost converter is presented, which proves the feasibility of the proposed controller.
Optimization of compensation capacitor detection system of inspection train based on fuzzy genetic algorithm
Authors: Cha Muhan 
Published: October 2024

Abstract
To solve the problem that the existing compensation capacitor detection system has an obvious difference between the received signal peak values of the existing railway line and the high-speed railway, an optimization scheme of the inspection train compensation capacitor detection system is proposed based on a fuzzy genetic algorithm. First, based on electromagnetic field theory, the mathematical model of the inspection train compensation capacitor detection system is established and verified. Then, the fitness function of the genetic algorithm is constructed based on the fuzzy decision. Finally, the system optimization scheme is obtained by evolutionary iteration of the genetic algorithm. The experimental results show that the proposed method can effectively increase the received signal peak value of the detection system, take into account the actual demand of compensating capacitance detection of existing railway lines and high-speed railways, and effectively improve the detection ability of the compensation capacitor inspection train.
A new method for diagnosing insulation failures in battery packs based on BiLSTM networks
Authors: Li Yanming , Duan Liyuan , Zhang Sining , Song Keling 
Published: October 2024

Abstract
Power batteries need to meet the high voltage and large capacity requirements of automobiles, especially under high voltage. Their insulation performance requirements are more stringent. The essay first establishes a mold suitable for insulation failure diagnosis basis the second-order Thevenin equivalent model. Then, the BiLSTM network structure is introduced to construct an insulation failure diagnosis model based on BiLSTM. This model enhances the model’s ability to capture data by bidirectional processing of past and future time series of battery pack insulation data. Finally, the proposed method was validated under different operating conditions. The results showed that the error of the method remained at a low level under both static and dynamic conditions, fully demonstrating the effectiveness of the method in improving prediction accuracy and applicability.
Research on verification method of low frequency electromagnetic field emission intensity detection capability for electric vehicles
Authors: Zhang Yunlei , Fan Yan , Zhang Xu , Zhang Guangyu , Guo Chen 
Published: October 2024

Abstract
Laboratory proficiency testing is one of the important technical methods for evaluating laboratory technical capabilities. Through proficiency testing, the quality and ability of laboratory testing can be evaluated, and the overall level of reference laboratory technical capabilities and differences between laboratories can be assessed, promoting the consistency of laboratory testing results. The testing of electromagnetic field emission intensity of electric vehicles in the frequency range of 150 kHz to 30 MHz is currently conducted entirely in electromagnetic compatibility darkrooms in China. Different suppliers have used different solutions for electromagnetic compatibility darkrooms, resulting in different site characteristics when testing the electromagnetic field emission intensity in the frequency range of 150 kHz to 30 MHz, which affects the test results. This article mainly proposes a verification method to verify the testing ability of electromagnetic field emission intensity in the frequency range of 150 kHz to 30 MHz for electric vehicles.
A capacitance-resistance hybrid fault current limiter based on thyristor
Authors: Fu Minyi , Miao Xiren 
Published: October 2024

Abstract
The converter station based on a half-bridge sub-module has poor tolerance to dc short-circuit faults, which puts forward higher requirements for the detection and breaking performance of dc circuit breakers (DCCBs). To this end, this paper proposes a Capacitance-Resistance hybrid fault current limiter (CRHCL) that can be integrated with DCCBs. The proposed CRHCL realizes the fast switching of the current limiting resistor through the thyristor and the pre-charged capacitor. The working principle and parameter configuration principle of CRHCL are described, and the theory and performance verification are carried out in the single-ended equivalent system simulation. The results show that compared with the traditional scheme of DCCB direct breaking, the proposal has a lower breaking current and breaking voltage, which effectively reduces the demand of DCCB for device number and breaking performance.
Improved load forecasting method based on TCN-BiGRU and attention mechanism
Authors: Chen Qishuo , Jiang Chuanwen , Lei Bohan 
Published: October 2024

Abstract
The accurate anticipation of electricity demand in the short term is crucial for ensuring the safe operation of the power grid and optimizing the power system. However, the existing prediction algorithms often suffer from limited accuracy. To address this issue, this study proposes a novel prediction model called TCN-BiGRU-Attention. This model utilizes TCN to extract features from the original load prediction data, processes the long-term correlations in time series data using GRU, and incorporates attention mechanisms to enhance the utilization of global correlation information. Compared to traditional prediction methods, this prediction model has better accuracy
Electrical-endurance prediction of AC contactor based on transformer
Authors: Liu Yang , Liu Shuxin , Zhang Junhui 
Published: October 2024

Abstract
AC contactors are used frequently in various low-voltage control lines, so electrical life prediction for them can significantly improve the operational reliability of power control systems. To solve the problems of poor prediction accuracy of a single feature in the life of AC contactors, low stability of prediction models, and inability to achieve continuous prediction of long-term series, a Transformer-based life prediction method for AC contactors is proposed. We utilize the LightGBM (Light Gradient Boosting Machine) method and the Spearman correlation coefficient (SCC) method to eliminate the unimportant and weakly correlated feature variables. The experimental results show that the remaining electrical life prediction effect of AC contactor based on the Transformer model has better model stability than other recurrent neural networks, and can more effectively and accurately predict the degradation process of AC contactor.
A transformer winding and core mechanical fault diagnosis approach based on VMD-MFE and GWO-MKELM
Authors: Sun Yuxiao , Zhang Ruizhi , Zhu Yichao , Wang Yizhou , Chen Yichao 
Published: October 2024

Abstract
In response to the difficulty of accurately diagnosing weak internal faults in transformers using traditional diagnostic methods, this paper proposes a transformer mechanical fault diagnosis approach relying on a combination of variational mode decomposition (VMD) and grey wolf optimization algorithm optimized multiple kernel extreme learning machine (GWO-MKELM). Firstly, VMD obtains the modal components of different orders of the raw vibration signal and uses multi-scale fuzzy entropy (MFE) to compute the entropy value of the optimal modal component. Secondly, to thoroughly apply the diagnostic ability of KELM, a mixed kernel function is constructed using the Gaussian radial kernel function and polynomial kernel function, and a GWO-MKELM diagnostic model is established. Finally, the experimental data proves the effectiveness and superiority of the suggested diagnostic model. This method could supply direction for the formulation of transformer condition maintenance policies.
The influence of traction load on power quality of weak power grid
Authors: Wang Heng , Liu Haijun , Wang Tongxun , Li Yaqiong 
Published: October 2024

Abstract
Due to the characteristics of non-linearity, impact, and asymmetry of the traction load of electrified railway, a large number of harmonic currents and negative sequence currents will be generated after the traction load is connected to the power grid, which will cause the power quality level of adjacent power sources and users to decline, and may seriously affect the power delivery and normal consumption of users. This paper evaluates the power quality problems caused by traction load access through simulation. The limited power of the electric locomotive is put forward in the weak grid area, and the speed of the locomotive is reduced to ensure safe passage through the weak grid area. The simulation results indicate that by appropriately reducing the power output of electric locomotives, we can achieve compliance with national standards for key electrical energy indicators. Additionally, this reduction can mitigate the impact of electrified railways on surrounding users, while maintaining the safe operation of the railways in areas with limited power grid capacity.
Optimal configuration of distributed energy storage based on the identification of voltage-vulnerable nodes
Authors: Wang Zheng , Zhao Shengnan , Wang Luhao , Song Haixia 
Published: October 2024

Abstract
With the rapid growth of distributed photovoltaic power generation and its integration into the grid, the power supply pressure on the grid has significantly intensified, and problems such as voltage exceeding the limit and power backflow are prone to occur. Addressing the issues of voltage surpassing thresholds and power reversal in distribution networks due to distributed photovoltaic systems through strategic placement of distributed energy storage has emerged as a principal research target. To this end, this paper first utilizes the Dempster-Shafer evidence theory to calculate the vulnerability of distribution network nodes based on vulnerability indices, selecting the vulnerable nodes. Subsequently, by analyzing the correlation between power and voltage, the sensitivity of voltage at distribution network nodes is determined. A distributed energy storage voltage regulation planning model is established using relevant constraints of energy storage in the distribution network and line-related conditions. Additionally, the voltage regulation scenarios that consider tap changers and static VAR compensation (SVC) are calculated. Ultimately, the efficacy of the suggested approach is validated through simulation on the IEEE 33-bus system.
Application of sound and vibration recognition technology based on optimized features in underground cable external breakage prevention
Authors: Su Qi , Chen Zhongbin , Li Wei 
Published: October 2024

Abstract
This study focuses on enhancing the accuracy of engineering vehicle identification through the optimization of acoustic characteristics and the use of the UBM-GMM algorithm, aiming to reduce the operation time of the identification process and thereby better prevent underground cable damage. The research compared three types of features: traditional MFCC features, combined feature M1, and optimized feature M2. The results indicated that the optimized feature M2 achieved a recognition accuracy of 94%, with the shortest training and recognition times being 127.017 seconds and 0.86 seconds, respectively. An AUC evaluation of 0.94 demonstrates the model’s strong recognition performance. The study validated the effectiveness of vibration acoustics recognition technology based on optimized acoustic properties in improving the identification rate of engineering vehicles and shortening the recognition time, providing crucial technical support for the timely protection of underground cables.
Performance analysis of hard-switching FSO/RF hybrid link system in foggy weather conditions
Authors: Yang Ruike , Liu Chen 
Published: October 2024

Abstract
Free space optical communication is vital for modern high-speed communication, yet it encounters considerable obstacles in foggy weather conditions. This study utilizes a combination of the Malaga model for turbulence-induced errors and a stochastic model for the fog to derive formulations that estimate both the likelihood of signal loss and the mean bit error rate in the integrated channel of the FSO link. Moreover, by employing a threshold hard-switched FSO/RF hybrid link system, our evaluation focuses on determining the outage probability and the average bit error rate for the composite link system. By analyzing the performance metrics of both the sole FSO link and the combined FSO/RF link, it is clear that the hybrid system shows a marked improvement in reducing the chances of signal interruption, which highlights the enhanced reliability offered by the integration of FSO/RF links in maintaining consistent communication system operations.
Design of pulse width modulation circuit based on PWM modulation
Authors: Du Wenhe , Chai Ruili , Chen Shuoyu , Wang Lei 
Published: October 2024

Abstract
The key to the modulation technology of the switching power supply is to control the on-off of the power switch and realize the real-time adjustment of the duty cycle with the system through the control signal. In order to improve the realization accuracy of the control signal, a generation method different from the traditional pulse width modulation signal is proposed. The two edge signals are processed by the RS trigger to generate the pulse width modulation signal. The circuit is designed and simulated in SMIC 0.18 μm CMOS process. In the full feedback current range, the duty cycle of the pulse width modulation signal decreases linearly, which can effectively improve the conversion efficiency of the power supply.
Multi-wave impedance modeling and transient characterization of lightning strikes on long-span transmission towers
Authors: Zhang Junfeng , Wang Chaoqun , Liu Chunlin , Jin Miao , Bao Hua , Zhu Bo , Zou Demu 
Published: October 2024

Abstract
With the increase in crossing distance, the height of long-span transmission towers suitable for UHV transmission lines is also increasing. The ultra-high height and ultra-long span increase the probability of long-span sections being struck by lightning. Therefore, the lightning strike long-span transmission tower model and its transient characteristics analysis are particularly important for lightning protection. In this paper, considering the concrete structure of the main material members of the long-span transmission tower, a multi-wave impedance modeling method for the tower is proposed. Firstly, the tower is divided into three parts: nominal height, upper tower body, and cross arm. The wave impedance of each part is calculated using finite element simulation, empirical formula, and parallel multi-conductor equivalent impedance theory. Then, the simulation verifies the electromagnetic transient characteristics of the multi-wave impedance model of the long-span transmission tower. Based on the ATP-EMPT simulation software, the segmented Hara model is constructed with the proposed multi-wave impedance refinement model, and the simulation results are consistent, which verifies the validity of the model. Finally, the lightning transient characteristics of long-span transmission towers under different conditions are simulated and analyzed, which provides guidance for its lightning protection design.
Research on an optimal load of sliding electrical contact based on the SSA-LS_SVM model
Authors: Chi Yixuan , Cao Mingyuan 
Published: October 2024

Abstract
During the operation of the pantograph-catenary system, the contact current, wear amount, and friction coefficient will affect the determination of the optimal pressure load. A self-made testing machine simulates the actual operation of the pantograph catenary, and the relationship between various factors and pressure load under different working conditions is analyzed. The least squares support vector machine model is optimized by the sparrow algorithm to establish the SSA-LS_SVM prediction model with the optimal load as the output. The Pareto solution set is obtained by multi-objective optimization of the optimal load with a multi-objective genetic algorithm. The weight of the three variables is obtained by the entropy weight method, and the multi-objective optimization problem is transformed into a single-objective optimization problem to determine the optimal pressure load.