Hasil untuk "Electrical engineering. Electronics. Nuclear engineering"

Sumit Goenka, V. Sant, S. Sant

Christoph Balada, Max Bondorf, Sheraz Ahmed et al.

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. However, significant changes, such as the transition to renewable energy (photovoltaic, wind turbines, etc.) and an increasing number of energy consumers with complex load profiles (electric vehicles, home battery systems, etc.), pose new challenges for the electricity grid. At the same time, these challenges are usually too complex to be solved with traditional approaches. In this gap, where traditional approaches are reaching their limits, Machine Learning has become a popular tool to bridge this shortcoming through data-driven approaches. To enable novel ML implementations is we propose FiN-2 dataset, the first large-scale real-world broadband powerline communications (PLC) dataset. FiN-2 was collected during real practical use in a part of the German low-voltage grid that supplies energy to over 4.4 million people and shows well over two billion data points collected by more than 5100 sensors. In addition, we present different use cases in asset management, grid state visualization, forecasting, predictive maintenance, and novelty detection to highlight the benefits of these types of data. For these applications, we particularly highlight the use of novel machine learning architectures to extract rich information from real-world data that cannot be captured using traditional approaches. By publishing the first large-scale real-world dataset, we also aim to shed light on the previously largely unrecognized potential of PLC data and emphasize machine-learning-based research in low-voltage distribution networks by presenting a variety of different use cases.

Sheng Ren, Rui Cao, Wenxue Tan et al.

The single image super-resolution based on deep learning has achieved extraordinary performance. However, due to inevitable environmental or technological limitations, some images not only have low resolution but also low brightness. The existing super-resolution methods for restoring images through low-light input may encounter issues such as low brightness and many missing details. In this paper, we propose a semantic-aware guided low-light image super-resolution method. Initially, we present a semantic perception guided super-resolution framework that utilizes the rich semantic prior knowledge of the semantic network module. Through the semantic-aware guidance module, reference semantic features and target image features are fused in a quantitative attention manner, guiding low-light image features to maintain semantic consistency during the reconstruction process. Second, we design a self-calibrated light adjustment module to constrain the convergence consistency of each illumination estimation block by self-calibrated block, improving the stability and robustness of output brightness enhancement features. Third, we design a lightweight super resolution module based on spatial and channel reconstruction convolution, which uses the attention module to further enhances the super-resolution reconstruction capability. Our proposed model surpasses methods such as RDN, RCAN, and NLSN in both qualitative and quantitative analysis of low-light image super-resolution reconstruction. The experiment proves the efficiency and effectiveness of our method.

Jingbo Li, Yile Fang, Zhuhao Wu et al.

Islet transplantation is a promising strategy for diabetes mellitus treatment as it can recapitulate endogenous insulin secretion and provide long-term glycemic control. Islet models constructed in biomaterial scaffolds that reproduce biological characteristics of native islets is a feasible option to circumvent the dilemma of donor shortage and the requirement of chronic immunosuppression. Herein, we developed bioinspired artificial microcapsule-based islet models with microvessels for glycemic control using microfluidic electrospray strategy. Microfluidic electrospray can generate uniform hydrogel microcapsules with core-shell structure for encapsulating islet cells. The cell-laden microcapsules enabled the efficient transportation of nutrient, oxygen, and insulin; as well as the incorporation with microvessels for prompting glucose responsiveness and molecular exchange. We demonstrated by in vivo experiments that the blood glucose, food intake, and body weight of diabetic mouse models were alleviated, and the glucose tolerance was promoted after the engraftment of islet microcapsules. We further demonstrated the improved functionality of transplanted islet model in insulin secretion, immune escape, and microcirculation using standard histological and molecular analysis. These results indicated that the microcapsules with microvessels are promising artificial islet models and are valuable for treating diabetes.

Jinhui Cheng, Zhaoliang Guan, Jiangduo Fu et al.

This work provides a comprehensive overview of advanced integration-inspired memory process design, focusing on the integration methods of 2D, 2.5D, and 3D. The integration of compute and memory blocks has demonstrated encouraging outcomes in enhancing memory access latency and energy efficiency for data-centric operations. The challenges and future prospects for PIM design include addressing trade-offs in the integration process, thermal management in highly integrated 3D designs, developing design automation tools for 3D designs, and identifying practical application scenarios for PIM to maximize its benefits. The use of through-silicon vias (TSVs) technology enables the efficient design of 3D structures with improved bandwidth density, while hybrid bonding technology shows advantages in achieving higher interconnect density and data transmission bandwidth. Monolithic integration represents a distinctive solution for high-density module integration, whereby custom circuit layers are stacked vertically in a single chip. This approach represents an efficient alternative to traditional 2D integration technologies. These advances in integration technology provide a roadmap for the future of PIM design and its application in real-world scenarios. In conclusion, the continuous development and integration of different technologies in PIM design has the potential to significantly enhance performance, energy efficiency, and integration density for data-centric tasks.

T. Bibik, I. Ostapenko, D. Feshchenko

Physical security systems in today's conditions play a key role in maintaining nuclear security and ensuring the normal functioning of facilities in the nuclear power industry. Given the possible lack of electrical power caused by missile strikes in wartime, the enemy or criminals can take advantage of the vulnerability of the physical protection system, the means of which will be de-energized, which can lead to unacceptable radiation consequences [1] as a result of successfully executed illegal actions (sabotage, theft, etc.) ). Therefore, in accordance with the legislation, a number of requirements are put forward to the power supplies of the complex of engineering and technical means of the physical security system, the fulfillment of which in the process of designing, construction or operation of the physical security system is aimed at preventing the failure of power supplies or minimizing the probability of failures in the reliable power supply of the equipment of the physical security n system protection An important stage of ensuring the uninterrupted functioning of the physical security system in conditions of long-term emergency power outages is the selection of a generator set. In this work, the object of research is the security of critical infrastructure objects in conditions of long-term power outages, and the subject of research is the power supply system of the complex of engineering and technical means of the physical security system. The paper analyzes the existing regulatory and legal documentation regarding physical security and provides the method of selecting a generator set, as well as the option of integrating the set into the scheme of power supplies of the complex of engineering and technical means. The main method of the process of selecting the specified equipment is the comparison and analysis of the parameters specified by the manufacturer with the parameters and characteristics that will meet the requirements of the current regulatory and legal documentation and the needs of the training center in supplying electricity to this or that equipment. The method presented in the paper is universal in application and can be scaled to other critical infrastructure facilities, where it is necessary to provide power supplies with a power reserve in conditions of long-term emergency shutdowns of industrial power sources.

Nina Bencheva, N. Kostadinov

Teaching digital electronics, microprocessor systems, embedded systems and other similar courses requires teachers to constantly adapt their teaching methods in order to improve the learning results. Courses in the field of digital systems are present in every curriculum of specialties such as electronics, information technologies, computer engineering and even mechanical engineering. Therefore, these courses shall be taught effectively, so that students can apply the knowledge learned to solve their practical engineering problems. In the introduction of this paper an analyses of different learning styles and delivery methods as well as their applications in the context of the pandemic is presented. For the purposes of the study, the training in three courses Digital electronics, Microprocessor systems and Digital systems design learned by students of several specialties in the Faculty of Electrical Engineering, Electronics and Automation at University of Ruse is considered. A comparative analysis of student performance results during online learning and traditional learning was performed. A survey conducted among students on their satisfaction from the online teaching in two of these courses during the pandemic is presented. The results of the survey were analysed and some conclusions were drawn.

Dr. Santosh Parakh, Dr. Yuvraj Nalwade

Abstract: This study gives an empirical perspective regarding engineering students towards sports and physical education, cultural activities and stress management. This research examines various motives for participation and non-participation in various activities. College students involved in lot of stress due to academic work, competition, daily hassles, parental expectations etc. Total sample of 270 respondents who were pursuing Bachelor of Engineering was selected. The students chosen for the study were from departments of Electronics and Telecommunication (E&TC), Computer Science (CSE), Mechanical Engineering (ME), Information Technology (IT) and Electrical Engineering (EE). Chi-square testing was used to taste the stated hypothesis in Research Methodology. This research concludes that students perusing engineering are actively involved in various activities because they are aware of benefit of active participation in sports, physical education and cultural events. At the same time they are also aware about stress management and what are most important causing factors of stress. Result of Hypothesis testing proves that Stress Management is directly proportional to EducationalPerformance & Parental Expectation. Sports activities found significant impact on Physical Fitness whereas participation in cultural events if directly related to Stress Management. Keywords: Stress Management, Physical Education, Cultural Events wellbeing, Sports Events, Mental health.

Guozheng Zhang, Shuo Wang, Chen Li et al.

A modular multilevel converter (MMC) can generate different common-mode voltage (CMV) values due to the high-frequency changing of the switching state under various modulation strategies. The high-frequency dv/dt will produce common-mode current in the equivalent common-mode loop to the ground, which will affect the insulation and shorten the life of the equipment. To eliminate the effect of common-mode voltage on MMC operation, a common-mode voltage elimination strategy (0CMV-SVPWM) is proposed for five-level MMC space vector pulse width modulation (SVPWM) by using the vector that does not generate common-mode voltage as the reference vector in this paper. The proposed strategy is studied and analyzed by the rapid prototype development experimental system based on RT-LAB to verify the feasibility and effectiveness of the proposed strategy.

Johannes L. Otto, Lukas M. Sauer, Malte Brink et al.

Nickel-based filler metals are frequently used in high temperature vacuum diffusion brazing for austenitic stainless-steel joints when components are subjected to high static or dynamic loads, corrosive environments and elevated temperatures. Due to melting point depressing metalloids such as silicon and boron, hard and brittle intermetallic phases are formed during the brazing process depending on the diffusion mechanisms. These brittle phases significantly affect mechanical and corrosive properties of the compounds. To quantify the influences of their amount, morphology and distribution, deep learning image segmentation was applied to segment these phases of the athermal solidification zone and the diffusion zone. Subsequently, characteristic microstructure parameters were calculated from these. The parameters of six different brazed joint variations were compared with their experimental characterization of mechanical and corrosive properties so that several correlations could be identified. Finally, a layer-by-layer removal of a brazed joint was performed using a focused ion beam, and a 3D model was reconstructed from the generated images to gain a mechanism-based understanding beyond the previous 2D investigations.

D.Z. Fu, T.J. Yang, Y.J. Pan et al.

In China’s goal of reaching carbon neutrality by 2060, the blending-biofuel-based heating technique is being used to reduce CO2 and air-pollutant emissions in existing district heating systems in northern China. This brings a series of new system components, complex interactions, and multiple-polymorphic uncertainties to the heating systems, making it difficult for the heating-system manager to improve the traditional fuel management mode while considering the demands of society, economy, policy, environment, and system operation. To address this issue, this study proposes an inexact multi-recourse hybrid-fuel management model for a biofuel-penetrated district heating system (BDHS). The model minimizes the total heating cost by optimizing the biofuel blending ratio, coal and biofuel deficit-recourse pattern among different heating sources, and selecting the optimal CO2 reduction mode under uncertainties. An application of the model to a BDHS case in Dalian City shows that the 5% biofuel blending ratio is suitable for both main heating sources and that the 0 deficit of high-quality coal can be up to [2.48, 2.69] × 103 tonne with the “cold-degree” changing from “mild” to “cold”. The results also indicate that the proposed model can ensure biofuels and high-quality coal are not overused or misused, but instead consumed responsibly. Additionally, most of the CO2 produced in the pulverized coal boiler is traded, while most of the CO2 sourced from the circulating fluid bed boiler is treated by the chemical absorption equipment. Finally, the model reveals that a high system cost (up to [84.73, 96.83] × 106 CNY) and low CO2 emission (down to [66.13, 78.07] × 103 tonne) can be obtained at a high thermalization coefficient through the tradeoff analysis.

XIONG Zhongmin, ZENG Qi, LU Peng, WANG Zhenhua, ZHENG Zongsheng

Logical reasoning is the ability to perceive patterns and connections between visual elements. Endowing computers with human-like reasoning ability is a critical area of research；state-of-the-art deep neural networks have achieved superhuman performance in image processing and other fields.However，the concept of logical reasoning through images requires further research.To address the problems of insufficient feature extraction and generalization of Multi-scale Relation Network（MRNet），an improved logical reasoning method，called Residual Attention Multi-scale Relation Network（ResAMRNet），is proposed. In the backbone network，shallow features are integrated into the deep network training process by utilizing residual structures and combining jump and long jump. This reduces the loss of feature information and improves the feature extraction capability of the model. In the reasoning module，the channel attention mechanism and residuals are combined to detect the relationship features between each image line.It can differentiate the significance of each feature channel，learn the attention weight adaptively，and extract key features.In this study，a Double-pooled Efficient Channel Attention（DECA） mechanism is proposed to combine global maximum pooling to further obtain feature information regarding objects and to improve generalization.Experimental results on representative logical reasoning datasets，Relational and Analogical Visual rEasoNing（RAVEN） and Improved RAVEN（I-RAVEN），show that the accuracy of the proposed method using these datasets is higher by 8.3 and 18.1 percentage points，respectively，than that of MRNet. Therefore，it demonstrates strong logical reasoning capabilities.

Xiaoling Wei, Yongbao Feng, Xiaoxia Han et al.

At present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by active and passive noise reduction methods. However, whether it is active noise reduction or passive noise reduction, they all focus on how to suppress the transmission of sound waves and cannot solve the problems of flow leakage, obvious temperature rise, and noise excitation from the root cause. Therefore, it is necessary to determine the location of the primary and secondary excitation sound sources of FIV, the identification of true and false sounds, and the characteristic relationship between flow and noise. This provides a theoretical basis and engineering application direction for the mechanism of noise reduction of FIV. The numerical calculation part of the acoustics in this paper is solved by the hybrid method, and the flow field is discretely calculated by the large eddy simulation (LES) module in the Fluent software. When the calculated flow field is stable, the velocity field of one impeller rotation period is selected to be output as the iterative value of the sound field and imported into ACTRAN for Fourier transform. Then, the sound field calculation is carried out, and the result of the spatial and temporal variation of the sound field is finally obtained. Through experiments, it was found that when the load of the gear pump is 8 MPa, the volumetric efficiency of the optimized circular-arc helical gear pump of the sliding bearing was improved by about 4%. When the rotation speed is 2100°r/min, the arc helical gear pump reduced the surface temperature rise by 2.5°C. This verified that the optimized performance of the sliding bearing in the arc helical gear pump is significantly improved. Through the theoretical model of the temperature rise of the sliding bearing, the phenomenon that the surface temperature of the prototype gear pump was not significantly increased with the loading in the low pressure region is explained.

Shijia Liu, Ayse Ay, Qiaochu Luo et al.

The integration of non-enzymatic glucose sensing entities into device designs compatible with industrial production is crucial for the broad take-up of non-invasive glucose sensors. Copper and its oxides have proven to be promising candidates for electrochemical glucose sensing. They can be fabricated in situ enabling integration with standard copper metallisation schemes for example in printed circuit boards (PCBs). Here, copper oxide electrodes are prepared on flexible polyimide substrates through direct annealing of patterned electrode structures. Both annealing temperature and duration are tuned to optimise the sensor surface for optimum glucose detection. A combination of microscopy and spectroscopy techniques is used to follow changes to the surface morphology and chemistry under the varying annealing conditions. The observed physico-chemical electrode characteristics are directly compared with electrochemical testing of the sensing performance, including chronoamperommetry and interference experiments. A clear influence of both aspects on the sensing behaviour is observed and an anneal at 250 °C for 8 h is identified as the best compromise between sensor performance and low interference from competing analytes.

Yurii Borodenko, S. Arhun, A. Hnatov et al.

According to the COVID-19 pandemic, educational institutions around the world were forced to urgently switch to distance learning. A particularly difficult situation has arisen in higher educational institutions when teaching special technical disciplines, where practical and laboratory exercises, which were conducted in laboratories and special classes before the COVID-19 pandemic, play an important role. Therefore, the paper presents a method for conducting practical and laboratory classes during on-line training on the example of the Department of Automotive Electronics of the Kharkiv National Automobile and Highway University (Ukraine). It is shown that the use of information technologies makes it possible to largely compensate for the lack of full-time classes. For special (subject) disciplines, the perception of information is achieved by using films demonstrating methods for the implementation of subject tasks. The main task of the teacher when conducting practical exercises in the conditions of distance learning is the competent selection of the source video material and its optimal fragmentation. In this regard, a classification of educational video content is proposed, and examples of its use by teachers during online classes are considered. The results of this work are intended to help educators improve the level of engineering education during distance learning.

Preface International Scientific Conference “FarEastCon” took place on October 2-4, 2018 in Vladivostok, Russian Federation. The conference was organized by 10 universities - Far Eastern Federal University (FEFU, Vladivostok), North-Eastern Federal University (Yakutsk), Amur State University of Humanities and Pedagogy (Komsomolsk-on-Amur), Far Eastern State Transport University (Khabarovsk), Komsomolsk-on-Amur State Technical University (Komsomolsk-on-Amur), Amur State University (Blagoveshchensk), Vladivostok State University of Economics and Service (Vladivostok), Research Institute of Building Physics and Fencing Constructions of the Academy of Construction and Architecture (Moscow), Economic Research Institute of Far Eastern Branch of the Russian Academy of Sciences (Khabarovsk), Pacific National University (Khabarovsk). The conference was carried out under financial support of the Far Eastern Federal University, the Russian Foundation for Basic Research as well as at informational support of the Institute of Electrical and Electronics Engineers (Russian (Far Eastern) Subsection of IEEE). The conference participants submitted papers reflecting recent advances in the field of materials engineering and technologies for production and processing in the different areas of modern manufacturing. The international program committee has selected totally 310 papers for publishing in the “IOP Conference Series: Materials Science and Engineering (MSE)” (IOP Publishing Ltd.) Organizing committee would like to express our sincere appreciation to everybody who has contributed to the conference. Heartfelt thanks are due to authors, reviewers, participants and to all the team of organizers for their support and enthusiasm which granted success to the conference. Conference Char, Denis B. Solovev.

P. Bhowmik, K. Suh

Young Baik Kim, Felipe P Vista, K. Chong

Abstract The analog-based Ex-core Neutron Flux Monitoring System (ENFMS) in Korean Nuclear Power Plants (NPPs) has been performing its intended functions successfully for a long time. On the other hand, the primary concern with the extended use of analog systems is the aging effect, such as mechanical failures, environmental degradation, and obsolescence. The transition to a digital-based Man-Machine Interface Systems (MMIS) in Korea and other countries has been accelerating, but some systems are still analog-based IC systems, such as the ENFMS in APR1400 NPPs. Digitalized ENFMS can become a reality using computers and microprocessors owing to the progress in digital electronics and information technology. This paper presents the result of the first phase of the research on the digitalization of the ENFMS signal processing electronics for NPPs operated or produced in Korea. It has two main parts: (1) review engineering bases of ex-core neutron flux monitoring system, including nuclear engineering, instrumentation techniques, and analog and digital signal processing techniques, and (2) analysis of analog signal processing electronics of ENFMS for OPR1000 and APR1400 power plants. They are prerequisite to the second phase of the research which is the detailed implementation of the digitalization.

USMAN, A., CHOUDHRY, M. A.

Static Transfer Switch (STS) is required for high-speed transfer of essential load to the alternate power source when the main source fails due to power disturbance (PD). A fast and accurate PD detection method is required to ensure transfer time recommended by Computer Business Equipment Manufacturers Association (CBEMA) and IEEE Std. 446. This study encompasses the machine learning technique to reduce detection time for the disturbance on the preferred source. The 10 sample frames of acquired voltage signal were first differentiated and then distinctive features, i.e., Mean Absolute Deviation (MAD) and Energy (E) were extracted from the resultant frames. The features were fed to the Linear Support Vector Machine (L-SVM) classifier to detect the occurrence of PD events. The proposed approach achieved 100% accuracy for PD detection and detection time was significantly reduced. The system is robust in terms of unbalanced and marginal PDs. The system was validated using both simulated and real voltage signals. The proposed algorithm is easy to implement on an embedded system. Hence, detection time according to STS requirements can be achieved under various power system conditions.

Soumik Sen, Liqi Zhang, Xianyong Feng et al.

The Austin SuperMOS is an intelligent 7.2kV/60A SiC power switch integrated with a gate driver and an isolated auxiliary power supply. Design considerations for the auxiliary power supply in a 5kV Austin SuperMOS based full bridge power electronic building block (PEBB), in terms of electrical performance and insulation against high voltages, are presented in this paper. In the presented auxiliary power supply, an LLC resonant converter along with 4 individual floated voltage sources including high frequency and high-voltage isolation transformers are developed. The design of individual floating sources is based on circuit and FEM simulations as well as necessary engineering calculation. Partial discharge measurements are also conducted to validate the proposed high voltage transformer design. Electrical measurements performed on the fabricated full bridge PEBB reveal stable and proper operation of the system.