Hasil untuk "Electrical engineering. Electronics. Nuclear engineering"

C. R. Teeneti, T. Truscott, D. Beal et al.

Autonomous underwater vehicles (AUVs) are increasingly used for undersea exploration. The endurance of AUVs is limited by the onboard energy storage among which the battery systems dominate. Various underwater recharging methods are employed to increase the AUV range and autonomy. Currently, contact-based underwater recharging utilizes the wet-mate connector technology that requires a high-precision AUV docking, and is prone to electrical safety issues. To overcome these limitations, underwater wireless recharging techniques for AUVs have been explored in recent years. Wireless charging offers a safe and reliable method for autonomous power transfer between a charging station and a vehicle. This article reviews the state-of-the-art inductive wireless power transfer (IWPT) solutions for underwater applications and discusses the engineering challenges of the IWPT system design. Underwater environmental factors, such as seawater conductivity, temperature, pressure, water currents, and biofouling phenomenon, impose constraints on IWPT systems. A comprehensive review of AUV energy storage systems, docking methods, IWPT system control methods, and compensation networks is presented in this article. Based on the main operational and constructional principles, the AUV IWPT systems are categorized as loosely coupled transformers and resonant IWPT systems. Each of the categories is illustrated through their main design principles and implementations reported in the literature so far. Technical challenges, such as integration of IWPT system into an AUV hull, interoperability, alignment and retention issues, docking station sinking and stability, the design of pressure-tolerant charging electronics, data transfer, and the battery operation in the underwater environment are discussed in this article too. The article is concluded with the best practice overview of designing an IWPT system for AUVs.

Jiahong Xiang, Wenxiao He, Xihua Wang et al.

The Rust programming language presents a steep learning curve and significant coding challenges, making the automation of issue resolution essential for its broader adoption. Recently, LLM-powered code agents have shown remarkable success in resolving complex software engineering tasks, yet their application to Rust has been limited by the absence of a large-scale, repository-level benchmark. To bridge this gap, we introduce Rust-SWE-bench, a benchmark comprising 500 real-world, repository-level software engineering tasks from 34 diverse and popular Rust repositories. We then perform a comprehensive study on Rust-SWE-bench with four representative agents and four state-of-the-art LLMs to establish a foundational understanding of their capabilities and limitations in the Rust ecosystem. Our extensive study reveals that while ReAct-style agents are promising, i.e., resolving up to 21.2% of issues, they are limited by two primary challenges: comprehending repository-wide code structure and complying with Rust's strict type and trait semantics. We also find that issue reproduction is rather critical for task resolution. Inspired by these findings, we propose RUSTFORGER, a novel agentic approach that integrates an automated test environment setup with a Rust metaprogramming-driven dynamic tracing strategy to facilitate reliable issue reproduction and dynamic analysis. The evaluation shows that RUSTFORGER using Claude-Sonnet-3.7 significantly outperforms all baselines, resolving 28.6% of tasks on Rust-SWE-bench, i.e., a 34.9% improvement over the strongest baseline, and, in aggregate, uniquely solves 46 tasks that no other agent could solve across all adopted advanced LLMs.

Emir Poskovic, Fausto Franchini, Elisa Fracchia et al.

Axial flux offer a promising and reliable solution for various applications. The use of soft magnetic composite (SMC) materials allows to resolve some of the challenges associated with these motors. Two axial flux motors with identical designs are devolved, with the only variation being in the preparation of the SMC stators. The effect of magnetization during the stator manufacturing process has been assessed. Various tests are conducted in order to compare the performance of the magnetized and non-magnetized stators. Distinct differences have been noted, showing some advantages for the prototype with aligned SMC material. These results are further explained through microstructural analyses.

Saygun Guler, Emre Aslanger, Murat Kaya Yapici

Spurred by the global pandemic, research in health monitoring has pivoted towards the development of smart garments, enabling long-term tracking of individuals’ cardiovascular health by continuously monitoring the electrocardiogram (ECG) and detecting any abnormality in the signal morphology. Many types of dry electrodes have been proposed as alternatives to gold standard Ag/AgCl wet electrodes, and they have been integrated into clothes capable of acquiring only a limited number of the different ECG traces. This limitation severely diminishes the diagnostic utility of the collected ECG data and obstructs the garment’s potential for clinical-level evaluation. Here, we demonstrate a special ECG upper armband with a glove component which houses graphene-textile electrodes, where a fully mobile, exploring electrode located at the index finger enables the user to strategically position the electrode on-demand to desired body areas and measure the different ECG traces that are bipolar limb and unipolar chest leads. Based on measurements with and without employing the well-known Wilson Central Terminal (WCT) arrangement, the correlation ratio of unipolar ECG chest leads acquired with the graphene textile-based armband and Ag/AgCl electrodes both in “WCT-less” configuration reach up to %99.65; and up to %99.54 when Ag/AgCl electrodes are utilized “with WCT” while the graphene-based armband in “WCT-less” configuration. To the authors’ best knowledge, this study reports the first multilead on-demand “touch-and-measure” ECG recording from a fully wearable textile garment. Moreover, owing to the human-centered armband design, we achieved a more than three-fold reduction in electrode count from 10 in clinical ECG practice down to 3.

R.A. Pitts, A. Loarte, T. Wauters et al.

To mitigate the impact of technical delays, provide a more rationalized approach to the safety demonstration and move forward as rapidly as possible to a reactor relevant materials choice, the ITER Organization embarked in 2023 on a significant re-baselining exercise. Central to this strategy is the elimination of beryllium (Be) first wall (FW) armour in favour of tungsten (W), placing plasma-wall interaction (PWI) centre stage of this new proposal. The switch to W comes with a modified Research Plan in which a first “Start of Research Operation” (SRO) campaign will use an inertially cooled, temporary FW, allowing experience to be gained with disruption mitigation without risking damage to the complex water-cooled panels to be installed for later DT operation. Conservative assessments of the W wall source, coupled with integrated modelling of W pedestal and core transport, demonstrate that the elimination of Be presents only a low risk to the achievement of the principal ITER Q = 10 DT burning plasma target. Primarily to reduce oxygen contamination in the limiter start-up phase, known to be a potential issue for current ramp-up on W surfaces, a conventional diborane-based glow discharge boronization system is included in the re-baseline. First-of-a-kind modelling of the boronization glow is used to provide the physics specification for this system. Erosion simulations accounting for the 3D wall geometry provide estimates both of the lifetime of boron (B) wall coatings and the subsequent B migration to remote areas, providing support to a simple evaluation which concludes that boronization, if it were to be used frequently, would dominate fuel retention in an all-W ITER. Boundary plasma (SOLPS-ITER) and integrated core–edge (JINTRAC) simulations, including W erosion and transport, clearly indicate the tendency for a self-regulating W sputter source in limiter configurations and highlight the importance of on-axis electron cyclotron power deposition to prevent W core accumulation in the early current ramp phase. These predicted trends are found experimentally in dedicated W limiter start-up experiments on the EAST tokamak. The SOLPS-ITER runs are used to formulate W source boundary conditions for 1.5D DINA code scenario design simulations which demonstrate that flattop durations of ∼100 s should be possible in hydrogen L-modes at nominal field and current (Ip = 15 MA, BT = 5.3 T) which are one of the principal SRO targets. Runaway electrons (RE) are considered to be a key threat to the integrity of the final, actively cooled FW panels. New simulations of RE deposition and subsequent thermal transport in W under conservative assumptions for the impact energy and spatial distribution, conclude that there is a strong argument to increase the W armour thickness in key FW areas to improve margins against cooling channel interface damage in the early DT operation phases when new RE seeds will be experienced for the first time.

Weronika Zubrzycka-Singh

The X-ray imaging systems dedicated for X-ray spectroscopy, based on a semiconductor strip sensors have been recently an important research topic. The most important research objective is working towards improvement of the spectroscopic and position resolution features [1]–[3]. In spectroscopic applications the short strip silicon detectors are widely used due to their relatively small capacitance and leakage current. Using strip pitch below 75 μm enables achievement of high spatial resolution. In this work, the analysis and design of the read-out electronics for the short silicon strip detectors are presented. The Charge Sensitive Amplifier (CSA) is optimized for the detector capacitance of about 1.5 pF, and the shaping amplifier default peaking time is about 1 μs (controlled by the sets of switches). To achieve the lowest possible noise level, the sources of noise in a radiation imaging system both internal (related to the frontend electronics itself), as well as external, were considered [4]. We target the noise level below 40 el. rms, considering low power consumption (a few mW) and limited channel area. To increase the speed of incoming hits processing, the continuoustime resistive CSA feedback together with a digital feedback reset are included. The prototype integrated circuit comprises of 8 charge processing channels, biasing circuits, reset and base-line restoration logic, and a calibration circuit.

Xingang Guo, Yaxin Li, Xiangyi Kong et al.

Modern engineering, spanning electrical, mechanical, aerospace, civil, and computer disciplines, stands as a cornerstone of human civilization and the foundation of our society. However, engineering design poses a fundamentally different challenge for large language models (LLMs) compared with traditional textbook-style problem solving or factual question answering. Although existing benchmarks have driven progress in areas such as language understanding, code synthesis, and scientific problem solving, real-world engineering design demands the synthesis of domain knowledge, navigation of complex trade-offs, and management of the tedious processes that consume much of practicing engineers' time. Despite these shared challenges across engineering disciplines, no benchmark currently captures the unique demands of engineering design work. In this work, we introduce EngDesign, an Engineering Design benchmark that evaluates LLMs' abilities to perform practical design tasks across nine engineering domains. Unlike existing benchmarks that focus on factual recall or question answering, EngDesign uniquely emphasizes LLMs' ability to synthesize domain knowledge, reason under constraints, and generate functional, objective-oriented engineering designs. Each task in EngDesign represents a real-world engineering design problem, accompanied by a detailed task description specifying design goals, constraints, and performance requirements. EngDesign pioneers a simulation-based evaluation paradigm that moves beyond textbook knowledge to assess genuine engineering design capabilities and shifts evaluation from static answer checking to dynamic, simulation-driven functional verification, marking a crucial step toward realizing the vision of engineering Artificial General Intelligence (AGI).

Muhammad Tayyab Khan, Zane Yong, Lequn Chen et al.

Engineering drawings are fundamental to manufacturing communication, serving as the primary medium for conveying design intent, tolerances, and production details. However, interpreting complex multi-view drawings with dense annotations remains challenging using manual methods, generic optical character recognition (OCR) systems, or traditional deep learning approaches, due to varied layouts, orientations, and mixed symbolic-textual content. To address these challenges, this paper proposes a three-stage hybrid framework for the automated interpretation of 2D multi-view engineering drawings using modern detection and vision language models (VLMs). In the first stage, YOLOv11-det performs layout segmentation to localize key regions such as views, title blocks, and notes. The second stage uses YOLOv11-obb for orientation-aware, fine-grained detection of annotations, including measures, GD&T symbols, and surface roughness indicators. The third stage employs two Donut-based, OCR-free VLMs for semantic content parsing: the Alphabetical VLM extracts textual and categorical information from title blocks and notes, while the Numerical VLM interprets quantitative data such as measures, GD&T frames, and surface roughness. Two specialized datasets were developed to ensure robustness and generalization: 1,000 drawings for layout detection and 1,406 for annotation-level training. The Alphabetical VLM achieved an overall F1 score of 0.672, while the Numerical VLM reached 0.963, demonstrating strong performance in textual and quantitative interpretation, respectively. The unified JSON output enables seamless integration with CAD and manufacturing databases, providing a scalable solution for intelligent engineering drawing analysis.

Muhammad Tayyab Khan, Zane Yong, Lequn Chen et al.

Accurate extraction of key information from 2D engineering drawings is crucial for high-precision manufacturing. Manual extraction is slow and labor-intensive, while traditional Optical Character Recognition (OCR) techniques often struggle with complex layouts and overlapping symbols, resulting in unstructured outputs. To address these challenges, this paper proposes a novel hybrid deep learning framework for structured information extraction by integrating an Oriented Bounding Box (OBB) detection model with a transformer-based document parsing model (Donut). An in-house annotated dataset is used to train YOLOv11 for detecting nine key categories: Geometric Dimensioning and Tolerancing (GD&T), General Tolerances, Measures, Materials, Notes, Radii, Surface Roughness, Threads, and Title Blocks. Detected OBBs are cropped into images and labeled to fine-tune Donut for structured JSON output. Fine-tuning strategies include a single model trained across all categories and category-specific models. Results show that the single model consistently outperforms category-specific ones across all evaluation metrics, achieving higher precision (94.77% for GD&T), recall (100% for most categories), and F1 score (97.3%), while reducing hallucinations (5.23%). The proposed framework improves accuracy, reduces manual effort, and supports scalable deployment in precision-driven industries.

Thiago Barradas, Aline Paes, Vânia de Oliveira Neves

The effective execution of tests for REST APIs remains a considerable challenge for development teams, driven by the inherent complexity of distributed systems, the multitude of possible scenarios, and the limited time available for test design. Exhaustive testing of all input combinations is impractical, often resulting in undetected failures, high manual effort, and limited test coverage. To address these issues, we introduce RestTSLLM, an approach that uses Test Specification Language (TSL) in conjunction with Large Language Models (LLMs) to automate the generation of test cases for REST APIs. The approach targets two core challenges: the creation of test scenarios and the definition of appropriate input data. The proposed solution integrates prompt engineering techniques with an automated pipeline to evaluate various LLMs on their ability to generate tests from OpenAPI specifications. The evaluation focused on metrics such as success rate, test coverage, and mutation score, enabling a systematic comparison of model performance. The results indicate that the best-performing LLMs - Claude 3.5 Sonnet (Anthropic), Deepseek R1 (Deepseek), Qwen 2.5 32b (Alibaba), and Sabia 3 (Maritaca) - consistently produced robust and contextually coherent REST API tests. Among them, Claude 3.5 Sonnet outperformed all other models across every metric, emerging in this study as the most suitable model for this task. These findings highlight the potential of LLMs to automate the generation of tests based on API specifications.

A. Gillespie, Cuikun Lin, Ian Jones et al.

Ongoing research in new nuclear mechanisms hold the potential for beneficial developments in nuclear power cycle designs. Recent reports investigated the possibility of lattice dynamics to influence nuclear processes in metals. Results from Steinetz et al., at the NASA Glenn Research Center indicated that it may be feasible to initiate deuterium deuterium fusion reactions that are enhanced using electron screening to reduce the deuterium deuterium fusion barrier. This article presents tritium production results from both simulations and experiments targeting specific nuclear processes in an effort to identify the source of higher energy neutrons observed in those results. We explore two pathways of tritium generation in TiD2 through this fusion cycle. Tritium production from TiD2 in the University of Missouri Research Reactor, where the neutron spectrum was approximately 90 percent thermal, was within 25 percent of the predicted amount from simulations, and well explained by known nuclear reactions without invoking screening enhanced recoil-induced fusion. Tritium production from TiD2 in the cyclotron vault at MURR, where the neutron spectrum was completely energetic with almost no thermal neutrons, was a factor of 2.9 to 5.1 times higher than predicted from simulations using known nuclear reactions. This indicates the likelihood of an additional mechanism, such as collision-induced fusion in the solid state, increasing the credibility in the results from Steinetz et al.

Erdinç Keskin, Sami Arsoy

In geotechnical engineering, the void ratio stands out as a critical parameter that is closely related to several essential soil properties, including permeability, compressibility, settlement and bearing capacity. Accurate and rapid determination of this key parameter is therefore essential. Traditional methods involve assessing the properties of soil samples taken from the field using simple laboratory techniques. However, determining the void ratio requires the determination of parameters such as soil water content and specific gravity. Whilst these parameters can be determined using straightforward methods, their determination in civil engineering typically takes place over an extended period. Consequently, there is a tendency to explore alternative methods for delineating specific physical properties of soils. While some methods provide direct results, such as nuclear methods, others provide results indirectly through correlations using techniques such as drilling. Due to technological advances and the increased importance of time as a critical economic parameter, there is an increasing demand for fast and reliable methods. Accordingly, Time Domain Reflectometry (TDR), which is widely used in electrical engineering, has begun to find application in civil engineering. In this study, research is carried out to determine the void ratio, a key parameter in soil mechanics, using the TDR method. Experiments were therefore carried out on samples prepared in the laboratory with different void ratios, and the void ratios of the soils were then determined using the TDR method. The results of this study suggest that the TDR method could serve as an alternative approach for determining the void ratio of soils.

Vinicius Negri Machado, Fernando Ortiz Martinz, Wilson Komatsu et al.

The modeling process of a component or system consists of several steps, which are rarely entirely covered in undergraduate courses. Moreover, theoretical and laboratory lectures focus on different stages on modeling, and are commonly taught at different periods, which may negatively affect the learning process. Thus, this paper proposes a set of lectures that mixes theory and experiments, taught in an experimental laboratory, and which address all steps of modeling process. The case study is a single-phase transformer, where from a conceptual (electromagnetic) model, physical (electrical) models are developed up to a model capable of representing more complex phenomena such as inrush currents and magnetizing inductance saturation. Increasingly detailed theoretical modeling, using simulation tools and experimental measurements, guides the student in this process. It is shown that models can be improved at the expense of deeper understanding of the involved phenomena, and of more complex theoretical and experimental strategies to validate them. Moreover, this paper demonstrates that modeling complexity is only necessary up to a point which explains adequately the experimental results. Finally, the paper presents the perception of the students on the lectures, indicating that this teaching methodology can be adequate for other courses on system modeling.

Guangjie Chen, Zhaoyun Zhang

With the rapid growth in the number of EVs, a huge number of EVs are connected to the power grid for charging, which places a great amount of pressure on the stable operation of the power grid. This paper focuses on the development of V2G applications, based on the current research status of V2G technology. Firstly, the standards on V2G applications and some pilot projects involving more representative V2G systems are introduced. Comparing V2G applications with ordered charging and unordered charging, the social and economic benefits of V2G applications are highlighted. Analysis of the social benefits of V2G applications concerns three points: the grid demand response, personalized charging, and the coordination of renewable energy sources. And analysis of the economic benefits of V2G applications is divided into three parties: the grid, the aggregator, and individuals. From the perspective of innovative EVs expanding the application scenarios through V2G technology, V2G applications for commercial EVs, emergency power applications, and vehicle-to-vehicle energy trading are introduced. The current challenges related to V2G applications are presented: users’ willingness to participate in V2G applications, battery loss, charging and discharging tariffs, privacy and security, and power loss. Finally, some research recommendations for the development of V2G applications are given and the current state of research in regard to those recommendations is presented.

Dewi Suriani, Fathiah Fathiah, Muhammad Ikhsan

Inverter material is one of the essential materials in power electronics courses. An inverter is an electronic device that converts direct current (DC) into alternating current (AC). This concept is the foundation of electronics. Because the power electronics course is a practicum course, a practicum module is required as an intermediary teaching medium; this practical module discusses 3-phase inverter material, which uses the pulse width modulation (PWM) and sinusoidal pulse width modulation inverter (SPWM) switching methods. Through Tinkercad software, the circuit is assembled, and the output wave results from the two methods used are seen in designing the 3-phase inverter practical module using the Research and Development method. This research uses media and material validation sheet instruments to determine the feasibility of the 3-phase inverter practicum module. The research results showed that the percentage of media experts was 94%, material experts were 81%, and language experts were 84%. Hence, the 3-phase inverter practicum module is very suitable for use and can make it easier for students to understand inverters. Thus, developing a 3-phase inverter practicum module can effectively increase students' understanding of inverter material and interest in learning. It can also be an alternative for lecturers in teaching.

Shin Morishima, Hiroki Matsutani

A computing cluster that interconnects multiple compute nodes is used to accelerate distributed reinforcement learning that uses DQN (Deep Q-Network). In distributed reinforcement learning, actor nodes acquire experiences by interacting with a given environment and a learner node optimizes the DQN model. When distributed reinforcement learning is used in practical applications such as robotics, we can assume that actor nodes are located in edge side while the learner node is located in cloud side. In this case, the long-haul communication between them imposes significant communication overheads. However, most prior works simply assume that actors and learner are located closely, and do not take the overheads into account. In this paper, we focus on the practical environment where the actors and learner are located remotely, and they interact via a buffer node that collects information from multiple actor nodes. We implement a prototype system in which the buffer and learner nodes are connected via a 25GbE (Gigabit Ethernet) switch and a 10km optical fiber cable. Although a replay memory functionality is closely associated with the learner side, in this paper we propose to combine the replay memory into the buffer node. In our experiments using the prototype system, the proposed approach is compared with an existing approach in terms of the training efficiency (i.e., training loss) and the transfer efficiency over the long-haul communication (i.e., average priority of transferred experiences). As a result, the training loss of the proposed approach is reduced to 26% of the existing approach, and the average priority is 3.92 times higher than the existing approach after the training loss is converged. These results demonstrate that the proposed approach can improve the training/communication efficiency compared with the existing approach in a practical system that imposes long-haul communication between the actors and learner.

Tengpeng Chen, Fangyan Liu, Hongxuan Luo et al.

The Gaussian noise distribution is typically used in dynamic state estimation (DSE) but it is not always true in practice because of abnormal system inputs, impulsive noise and measurement outliers. In this paper, a new robust DSE approach based on a new robust Lp norm based estimator and the cubature Kalman filter (CKF) is developed for power systems with non-Gaussian noise statistics. The Lp norm based estimator is derived from the Lp norm formula and the quadratic formula in order to alleviate the impacts from bad data and outliers. The proposed Lp-CKF DSE approach exhibits good accuracy because a new estimation error covariance is obtained by using the influence function. The robustness of the proposed Lp-CKF DSE approach is verified by performing simulations on a generator in the IEEE 39-bus system.

Ming Li, Jike Zhong, Tianle Chen et al.

Recent studies on large language models (LLMs) and large multimodal models (LMMs) have demonstrated promising skills in various domains including science and mathematics. However, their capability in more challenging and real-world related scenarios like engineering has not been systematically studied. To bridge this gap, we propose EEE-Bench, a multimodal benchmark aimed at assessing LMMs' capabilities in solving practical engineering tasks, using electrical and electronics engineering (EEE) as the testbed. Our benchmark consists of 2860 carefully curated problems spanning 10 essential subdomains such as analog circuits, control systems, etc. Compared to benchmarks in other domains, engineering problems are intrinsically 1) more visually complex and versatile and 2) less deterministic in solutions. Successful solutions to these problems often demand more-than-usual rigorous integration of visual and textual information as models need to understand intricate images like abstract circuits and system diagrams while taking professional instructions, making them excellent candidates for LMM evaluations. Alongside EEE-Bench, we provide extensive quantitative evaluations and fine-grained analysis of 17 widely-used open and closed-sourced LLMs and LMMs. Our results demonstrate notable deficiencies of current foundation models in EEE, with an average performance ranging from 19.48% to 46.78%. Finally, we reveal and explore a critical shortcoming in LMMs which we term laziness: the tendency to take shortcuts by relying on the text while overlooking the visual context when reasoning for technical image problems. In summary, we believe EEE-Bench not only reveals some noteworthy limitations of LMMs but also provides a valuable resource for advancing research on their application in practical engineering tasks, driving future improvements in their capability to handle complex, real-world scenarios.

A. Alam

CHIEF EDITOR Prof. Dr. AHM Zahirul Alam, IIUM, Malaysia EXECUTIVE EDITOR Assoc. Prof. Dr. Muhammad Mahbubur Rashid, IIUM, Malaysia EDITORIAL BOARD MEMBERS Prof. Dr. Sheroz KhanOnaizah College of Engineering and Information TechnologySaudi ArabProf. Dr. AHM Asadul HuqDepartment of Electrical and Electronic EngineeringDhaka University, BangladeshProf. Dr. Pran Kanai ShahaDepartment of Electrical and Electronic EngineeringBangladesh University of Engineering and Technology, BangladeshAssoc. Prof. Dr. SMA MotakabberFaculty of EngineeringInternational Islamic University Malaysia, MalaysiaProf. Dr. ABM Harun Ur RashidDepartment of Electrical and Electronic EngineeringBangladesh University of Engineering and Technology, BangladeshProf. Dr. Joarder KamruzzamanEngineering and Information TechnologyFederal University, AustraliaDr. Md Arafatur RahmanReader in Cyber SecurityUniversity of Wolverhampton, UK Aims & Scope of Asian Journal of Electrical and Electronic Engineering The Asian Journal of Electrical and Electronic Engineering (AJoEEE), published biannually (March and September), is a peer-reviewed open-access journal of the AlamBiblio Press. The Asian Journal of Electrical and Electronic Engineering (AJoEEE) publishes original research findings as regular papers, review papers (by invitation). The Journal provides a platform for Engineers, Researchers, Academicians, and Practitioners who are highly motivated to contribute to the Electrical and Electronics Engineering disciplines. It also welcomes contributions that address the developing world's specific challenges and address science and technology issues from a multidisciplinary perspective. Referees' Network All papers submitted to AJoEEE Journal will be subjected to a rigorous reviewing process through a worldwide network of specialised and competent referees. Each accepted paper should have at least two positive referees' assessments. Submission of a Manuscript A manuscript should be submitted online to the Asian Journal of Electrical and Electronic Engineering (AJoEEE) website https://alambiblio.com/ojs/index.php/ajoeee. Further correspondence on the status of the paper could be done through the journal website.

P. E. Korneev, A. Ignatyev

Relevance Practical training of highly qualified engineering personnel in the field of industrial automation is one of the key factors in the technological development of the material production sectors of our economy. The laboratory base in higher educational institutions should be equipped with modern stands with equipment that corresponds to the technological level of real equipment of industrial enterprises. The article discusses the issues of designing and constructing a mobile multifunctional training and research laboratory stand for industrial automation based on a programmable relay of domestic production PR200, provides functional and structural diagrams of the laboratory stand, provides a complete list of electrical components used to create the stand. The economic assessment of the manufacture of a laboratory stand gives grounds to conclude that it is economically feasible to produce such stands by the staff of departments of industrial automation. The article also shows the experience of introducing this laboratory stand into the educational process of bachelor's degree preparation in the direction of 15.03.04 «Automation of technological processes and productions». The laboratory stand based on the PR200 is a universal, multifunctional, mobile stand designed to implement multi-level tasks of industrial automation, which can also be used as a visual aid when conducting career guidance and exhibition events in extracurricular premises. The project to create a laboratory stand based on the PR200 can be scaled up in other higher educational institutions of our country without spending time on preparatory and research parts. Aim of research To develop a mobile multifunctional training and research laboratory stand for industrial automation based on Russian-made equipment that is actually used by industrial enterprises and to introduce this laboratory stand into the educational process of training specialists in the field of industrial automation. Research methods Computer-aided design and computer-aided modeling of electrical circuits were used to develop the laboratory stand. Results The developed laboratory stand was produced and introduced into the educational process at the Department of automated production technologies of the Yegoryevsk Institute of Technology (branch) of Moscow State University of Technology «STANKIN» during laboratory and practical classes in the disciplines: «Mechanics and Control», «Electrical Engineering and Electronics», «Automation and Control Tools». In addition, graduate students at the stand conduct full-scale modeling of automation systems as part of research and preparation of the final qualification work.