bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preliminary accident analysis of the loss of vacuum in vacuum vessel for the European DEMO HCPB blanket concept
Authors: Jin Xue Zhou , Raskob Wolfgang 
Published: March 2024

Abstract
Design basis accidents are investigated continuously for the European DEMO reactor accompanying its development. One selected postulated initial event (PIE) is a loss of vacuum (LOVA) in vacuum vessel (VV) with large ingress of air induced by rupture in a VV penetration. It has been investigated for the helium cooled pebble bed (HCPB) blanket concept according to the DEMO baseline 2017. The associated primary heat transfer system (PHTS) and the related systems in the tokamak building, from the VV to the PHTS vault and galleries, are considered for the investigation. The LOVA is postulated to occur at a port seal of the electron cyclotron equatorial port plug on the side of the closure plate with (i) a small leak of 1.0 × 10−3 m2, or (ii) a large break size of 1.0 × 10−2 m2. Air ingress from one port cell into the VV leads to the VV pressurization and the fusion power termination followed by an unmitigated plasma disruption. A loss of off-site power for 32 h is assumed to coincide with the disruption. An in-vessel loss of coolant accident (LOCA) is considered as a consequence if the affected first wall (FW) reaches the defined temperature of 1000 °C. The radioactive inventories in the VV (tritium, W-dust) can mobilize towards the VVPSS, the affected systems in the building and the environment due to pressurization, venting and leak conditions. MELCOR 1.8.6 for fusion is applied for this deterministic safety analysis. The resulting releases of radioactivity to the environment are then provided for dose calculation using the computer systems UFOTRI and COSYMA. Outcomes of this LOVA analysis are critically discussed: the transient evolutions of different cases are compared; hydrogen production is detected in case of aggravating FW failure; the source terms (tritium, W-dust) are transported to the connected systems; and the dose results from the environmental releases are provided.
A new type of resonant magnetic perturbation for controlling edge localized modes
Authors: Yang Xu , Liu Yueqiang , Sun Xuan , Xu Wei , Li Li , He Yuling , Xia Guoliang , Hu Hanqing , Zhou Lina 
Published: March 2024

Abstract
A new type of resonant magnetic perturbation (RMP), generated by helical coils, is proposed for controlling the edge localized mode (ELM) in H-mode tokamak plasmas. The helical coil optimization utilizes the MARS-F code (Liu et al 2000 Phys. Plasmas
7 3681) computed linear resistive fluid response of the plasma to the applied RMP field. The optimal helical coils are found to be located near the outboard mid-plane of the torus, with relatively simple shape but tilted towards the equilibrium magnetic field line pitch. Compared to the window-frame ELM control coils, the optimal helical coils require 2–4 times less current, in order to achieve the same ELM control performance specified by various figures of merit adopted in this work. The results from the present study show a promising path forward in achieving ELM control with RMP fields in tokamak plasmas.
Modeling and Optimization for Cost Optimization Model of Material Distribution System in Power Distribution Network--A Case in Hunan
Authors: Tao X , Zhou W H , Guo X W , Zhan G H , Li Z H , Lin Z G , Liu P F , Zhang F , Shen Z L 
Published: March 2024

Abstract
This paper proposes a method to address several issues in the distribution system of distribution network materials, including non-transparent distribution costs, low punctuality of distribution, and frequent misreporting and misreporting of distribution costs by local warehouses. The method involves constructing a distribution hierarchy for distribution network materials and developing a mathematical model to calculate the costs associated with distribution, loading and unloading, and warehouse finishing. Additionally, a node identification mechanism is established based on the demand for distribution network materials to accurately identify nodes that can be removed from distribution routes. Furthermore, a distribution route optimization algorithm is developed to optimize distribution costs. The effectiveness of the method is then verified through its application to the distribution of distribution materials for the Hunan State Grid Corporation.
Method for minor defect detection in electroluminescent solar cells based on CSR-YOLOv5s
Authors: Chen Weike , Luo Xiao , Liu Liang , Feng Fei , Chen Weiqiang 
Published: March 2024

Abstract
The increasing production of solar cells, resulting from the rapid development of new energy sources, necessitates their inspection during both solar cell production and photovoltaic power plant inspection. Target detection algorithms are widely utilized for defect detection in solar cells. To achieve more accurate detection of minor defects in electroluminescent solar cells, an improved algorithm called CSR-YOLOv5s is proposed in this paper. The CSR-YOLOv5s combines Decoupled Head and CSRBlock with the YOLOv5s baseline model. The CSR-Y OLOv5s demonstrates a 1.1% increase in accuracy and a 2.1% increase in F1-score compared to the YOLOv5s baseline model, resulting in improved accuracy and recall. The algorithm effectively identifies minor defects in electroluminescent solar cells.
Operation State Identification of Commercial & Industrial Users
Authors: Mingxi Wang , Kefu Gao , Lin Ye 
Published: March 2024

Abstract
Users’ electricity usage information is helpful to promote performance of load forecasting and demand response. Users’ metering data contains abundant usage information and various approaches have been developed to extract users’ usage information from metering data. Since a user have specific several operation states and the user’s electricity consumption have particular features in each state, user’s operation state identification based approach is developed in this paper. The three phase power with an interval of 15 minutes in a day is utilized as fingerprint of the day. For the abnormal users with anomaly usage, load data should be analysed to get the load fingerprint in each day. Thereafter, the load fingerprint can be clustered with Affinity propagation algorithm. Once the user in suspicious days with much less electricity consumption has similar load fingerprint as that in holiday, the anomaly electricity consumption could be caused by alteration of operation state.
Adversarial Patch Attack Method for Vehicle Target Detection
Authors: Zhang Mingjiang , Bi Junfei , Xie Tao , Zhang Na , Zhao Weihu 
Published: March 2024

Abstract
Due to the susceptibility of intelligent recognition systems to adversarial sample attacks, research on adversarial sample attack methods for target detection is of great significance for improving the safety of vehicle autonomous driving. By studying the transfer-based self-ensemble attack adversarial sample generation algorithm, and based on the trained Faster R-CNN and YOLOX white box target detectors, a cross-model and cross-instance vehicle target detection attack method was designed. Through training, a universal adversarial patch was obtained, which achieved recognition attacks on two types of target detectors and three types of vehicles, resulting in incorrect recognition results being output. Through testing, the average decrease in mAP was about 41.6%, The research results have certain reference significance for the study of autonomous driving safety.
Survey of Research on Face Recognition Methods Based on Depth Learning
Authors: Zhou Xiaobo , Zhu Tian-cai 
Published: March 2024

Abstract
The field of face recognition has recently become a quite popular area of research, which is of great significance to the development of technology. It introduced the definition of face recognition technology and its development process, as well as the technical advantages and application scenarios of the technology. with the development of deep learning, face recognition technology based on deep learning is gradually realized. firstly, the limitations of traditional face recognition technology are pointed out. Then, several popular face recognition methods based on depth learning are analyzed. Finally, this paper introduces the application of deep learning technology in face recognition, summarizes a new deep learning model based on big data, and summarizes and prospects the development of face recognition technology in the future.
Research on Fault Diagnosis of Thermal Power System of Thermal Power Unit under Different Loads
Authors: Deng Liming , Wen Wen , Luo Cuie , Jiang Xin , Peng Liang , Liu Qing 
Published: March 2024

Abstract
Aiming at the problem of difficulty in acquiring fault data under different loads, a domain-adversarial-based fault diagnosis method for convolutional neural networks is established by combining convolutional neural networks with adversarial domain adaptive methods. The method uses convolutional neural networks to extract the fault features of the source and target domain samples, and simultaneously implements joint adjustment of the distributions of the domain-level and class-level features, aligns the feature distributions of the source and target domains by minimizing the difference in the distributions of the two domains through adversarial learning of the domains and aligns the feature distributions of each class of faults by making the distributions of the same kind of features closer through the loss of the central discriminant. With the help of a 600MW supercritical thermal power unit full-working condition simulation system, experiments are carried out under 100%, 90%, 80% and 70% of the rated load, and the results show that the method has effectiveness and superiority in the fault diagnosis of thermal system under different loads.
Fault Diagnosis Method of Inter-Turn Short Circuit of Permanent Magnet Synchronous Motor Based on Third Harmonic
Authors: Wang Hongying 
Published: March 2024

Abstract
In order to realize the effective diagnosis of turn to turn short circuit fault of permanent magnet synchronous motor, a method of turn to turn short circuit fault diagnosis of permanent magnet synchronous motor based on third harmonic is proposed in this paper. Establish the system frequency oscillation analysis model of permanent magnet synchronous motor under the condition of turn to turn short circuit, collect the turn to turn harmonic of permanent magnet synchronous motor, then realize the third harmonic detection of permanent magnet synchronous motor under turn to turn short circuit fault, and detect the inertia of permanent magnet synchronous motor system. Based on the transient energy analysis and fault feature extraction, the turn to turn short circuit fault of permanent magnet synchronous motor is diagnosed. The test results show that this method has high reliability and good detection performance, and can improve the output stability and condition monitoring ability of permanent magnet synchronous motor.
Research on Power Balance Control Method of Electronic Transformer
Authors: Nie Qiong 
Published: March 2024

Abstract
Aiming at the problem of poor output stability and power gain of the power electronic transformer of the microgrid energy storage system, a power balance control method for the power electronic transformer of the microgrid energy storage system based on parallel modular multi-level commutation control is proposed. The reactive power outer loop parameter fusion method is used to sample the power dynamic load parameters and information fusion processing for the transformers in the system. According to the static limit active power adjustment of the fuzzy parameter factors on the output voltage side of the DC port, the steady-state gain of the power electronic transformer of the microgrid energy storage system is calculated. The static current limiting adjustment method is used to construct the feedback compensation model of the power electronic transformer of the microgrid energy storage system. In the active power control loop, the optimal design of the power electronic transformer power balance control of the microgrid energy storage system is realized through transient stable power adjustment. The test results show that using this method to perform power balance control on the power electronic transformer of the microgrid energy storage system has high output stability and good active power balance, which improves the robustness and adaptability of the transformer balance control.
Automatic identification of transformer excitation inrush based on second-order Taylor coefficient
Authors: Guo Xirong 
Published: March 2024

Abstract
In order to solve the time-consuming problem of the existing automatic identification methods of transformer inrush current, an automatic identification method of transformer inrush current based on second-order Taylor coefficient was designed. Ignore the leakage resistance and winding resistance of transformer winding, get the second harmonic characteristic quantity, assume the transformer variable ratio value is fixed, identify the transformer winding parameters, introduce the decay coefficient to describe the characteristic of excitation inrush current gradually decaying with time, construct the excitation inrush current Taylor expansion phase model, and set the automatic identification mode based on the second order Taylor coefficient. Experimental results: The designed transformer excitation inrush current automatic identification method and the other two transformer excitation inrush current automatic identification method of the elapsed time were: 55.32ms, 71.52ms, 71.04ms, indicating that after the integration of the second-order Taylor coefficient, the designed transformer excitation inrush current automatic identification method better performance.
Assessment of hemostatic ability of biomaterial based on chitosan and Eclipta prostrata L. extract
Authors: Linh Nguyen Ngoc , Manh Vu Quoc , Chau Giang La , Chinh Nguyen Thuy , Dung Hoang Tran , Thuy Duong Tran Thi , Hoang Thai , Trung Vu Quoc 
Published: March 2024

Abstract
The biomaterials based on chitosan and Eclipta prostrata L. extract have been prepared by microemulsion method and solution method (with and without sodium tripolyphosphate (STPP) as a cross-linking agent). The main component in Eclipta prostrata L. extract is flavonoid groups. The structure of the chitosan/extract biomaterials was studied by infrared spectroscopy. The chitosan/extract biomaterial using STPP cross-linker appeared an absorption band at 1152 cm−1 attributed to the vibrations of C–O–P bonds, which proved that chitosan has crosslinked with STPP. The morphology of the biomaterials was investigated by the dynamic light scattering technique and field emission scanning electron microscopy. The obtained results showed that the particle size of the chitosan/extract biomaterials prepared by microemulsion method and solution method with STPP ranged from 68.06 nm to 1484 nm, with an average particle size of 304.9–1019 nm. The microemulsion method produced biomaterials with much smaller average particle size than the solution method using cross-linkers. The hemostatic ability of the biomaterials was better than that of the control sample based on the time of blood clotting formation and glomerular aggregation ability. The sample with the ratio of E. prostrata L. extract: chitosan of 1:30 had the lowest hemostasis time (6 min 46 s) and its glomerular aggregation rate after 5 min was 13.05%. This indicated that the biomaterials based on chitosan and E. prostrata L. extract are promising for application in biomedicine as hemostatic materials.
Optimization of methane yield from co-digestion of alkalipretreated groundnut shells and duck waste using response surface methodology
Authors: Olatunji K O , Madyira D M 
Published: March 2024

Abstract
Anaerobic co-digestion of lignocellulose feedstock with livestock waste can assist in overcoming the challenges of digesting lignocellulose and balancing the nutrient contents of the process. This study investigated the optimum conditions for methane yield production from anaerobic co-digestion of alkali-pretreated groundnut shells and duck waste using Response Surface Methodology (RSM). A central composite design of the RSM model with three input variables of retention time, temperature, and substrate mixing ratio was used to set up the anaerobic digestion process. Individual and interactive influence of the three process parameters were examined. The result showed that all three process parameters considered are significant and determine the methane yield. The developed RSM model predicted a daily methane yield of 53.33 mL CH4/g VSadded for optimal conditions of 11 days, 26 °C temperature, and 50: 50 mixing ratio, which is not the same as the optimum methane yield observed from the experiment (54.26 mL CH4/g VSadded) and at different process conditions. Cumulative methane yields of 666.72 and 666.66 mL CH4/g VSadded were predicted and observed, respectively, which shows a very close range. The RSM coefficient of determination (R2) value of 0.8251 (82.51%) was observed, indicating a close fit between the predicted and observed yields. Analysis of variance (ANOVA) p < 0.0001 indicates that the developed model could be helpful in anaerobic co-digestion of lignocellulose materials and livestock waste. This study can be replicated at the industrial scale.
Residual Stress Prediction during TIG and MIG Welding Process of Steel - A Review
Authors: Lawal S L , Afolalu S A 
Published: March 2024

Abstract
In this study, a forensic review of residual stress predictions and its impact on welded joints especially the steel pipes during the Tungsten inert gas welding and metal inert gas welding processes were reviewed. It was established that in the case of MIG welding, the effect of residual stress can be reduced after treatment. In the case of TIG welding process, increase in current will lead to deformation and residual stresses. Estimating the residual stress is a challenging task. It is common to predict residual stress using a notch stress intensity factor, a numerical simulation approach coupled with a thermal-mechanical finite element model. Thus, adequate design in welding parameters will help in the optimization of the process to achieve a safe and reliable welded joint during TIG and MIG welding process.
The Impact of Stand-Alone Systems in Nigeria’s Energy Distribution Sector and Present-Day Challenges Faced
Authors: Stephanie Nwangwu , Amanesi Abubakar John , Faith Ademola Omolola 
Published: March 2024

Abstract
The electricity situation in Nigeria has become alarming, with the population increasing over the years, the supply of electricity has failed to reach the demand. With over 223 million residents in the country, 95 million people lack an adequate supply of electricity. 91% of the supply is allocated to the urban areas while 30% at most reaches the rural economy due to constraints in the electrical grid. This has caused overdependence on other sources of generation such as diesel generators, and other means of generation. Using these other sources of generation has contributed to the nation’s carbon footprint and global warming. This paper aims to study the impact of stand-alone microgrids and how they could curb the electricity deficit in Nigeria, there is also a brief background on renewable energy as it forms the foundation of microgrids. This paper concludes that though microgrids could mitigate global warming and curb the country’s electricity deficit, factors such as security and management are preventing the successful implementation of these means.
Experimental investigation of the impact of GMAW welding parameters on the mechanical properties of AISI 316L/ER 316L using quaternary shielding gas
Authors: Khrais Samir , Al Hmoud Hadeel , Abdel Al Ahmad , Darabseh Tariq 
Published: March 2024

Abstract
In this study, the parameters of Metal Inert Gas (MIG) and Metal Active Gas (MAG) were investigated of AISI 316L/ER 316L. A quaternary shielding gas mixture consisting of Argon (Ar), Helium (He), Carbon Dioxide (CO2), and Nitrogen (N2) was chosen. The Taguchi orthogonal array (OA-L9) methodology was employed to explore optimal welding settings, including arc current (120A, 160A, 200A), wire feed rate (3, 3.5, 4 m min−1), and shielding gas combination (G1, G2, G3). The findings highlighted the importance of shielding gas in influencing the ultimate tensile strength (UTS), elongation percentage (EL%), and material toughness of welding joints. Notably, the highest UTS (515.77 MPa), EL% (20.85%), and material toughness (133J) were achieved by the specific group gas combination shown as G1. It is recommended to configure welding parameters to an arc current of 160A, a wire feed rate of 4 m min−1, and the G1 gas combination. Welded specimens using a G1 gas mixture showcased the best UTS and EL%. Additionally, it was found that the fusion zone (FZ) and heat-affected zone (HAZ) hardness are most profoundly influenced by the choice of gas combination (G2), resulting in the best hardness values of 253.79 HV and 239.68 HV, respectively. The optimal parameters for achieving the desired material hardness were precisely identified as (120A, 3 m min−1, G2). These insights offer a pathway to enhance welding performance and, in turn, elevate the quality and efficiency of industrial applications.
Study on operational temperature of magneto-rheological fluid and design dimensions of magneto-rheological damper for optimization
Authors: Kumar Kariganaur Ashok , Kumar Hemantha , Arun M 
Published: March 2024

Abstract
This study aims to restrict the upper limit for flow gap and effective length in magnetorheological (MR) damper for optimal performance. Initially, the sedimentation study of in-house MR fluid (25%) shows that an 8% reduction in the sedimentation ratio with the addition of additive and nonlinear Herschel-Bulkley (HB) model fit reflects a 32.5% decrease in average yield stress with increasing currents when the parallel plate gap is increased from 1 mm to 2 mm. Owing to this decrease in yield stress, further study is extended to fabricate two MR dampers with limit values (LV) of flow gap and effective length with a common magnetic outer cylinder. Testing results of MR dampers revealed a 72% reduction in damping force at 0.8 A current when the LV’s is increased from LV-1 to LV-2. Selecting LV-1 over LV-2 as the upper limit for any design optimization will give the MR damper optimal performance. At higher input parameters, amplitude has a 135% greater impact on damping force than frequency and current. It is also demonstrated that saturation magnetization depends on the applied magnetic field and input loading parameters. Finally, gravimetric analysis shows that the effectiveness of the MR fluid and magnetic particle starts to decline after 322 °C and 400 °C.