Transformer Design Research Articles

Optimum Design of Transformers for Offshore Wind Power Generators Considering Their Behavior

This paper presents a structural optimization technique based on precise heat transfer analysis for transformers. Mechanical and thermal stresses during operation are particularly critical in confined environments, such as within wind turbine generators. To optimize the transformer’s structure, the temperature distribution is first calculated using computational fluid dynamics (CFD) based on the finite volume method. Eddy current losses, necessary for thermal analysis, are determined through electromagnetic analysis. These CFD results are then used as input conditions for structural analysis. Finally, structural optimization is performed on critical areas, primarily the radiation fins and panels. All models are analyzed in 3D, and the simulation results are validated through comparison with experimental data. Consequently, the optimized design results were validated against simulations, exhibiting a maximum deviation of 4%. These findings confirm the success of the proposed transformer design optimization.

Topology design of distribution transformers for magnetic coupled energy storage devices

Topology design of distribution transformers for magnetic coupled energy storage devices

Transformative curriculum design for advanced critical thinking and complex problem-solving: theoretical models and practical applications

Transformative curriculum design for advanced critical thinking and complex problem-solving: theoretical models and practical applications

Optimization of Distribution Transformer Design for Harmonic Resilience using a Taguchi-FEM Approach

Optimization of Distribution Transformer Design for Harmonic Resilience using a Taguchi-FEM Approach

The Rise of ChatGPT: Can machines really replace human interaction?

Artificial intelligence (AI) can be characterized as the multidisciplinary approach of computer science and robust dataset that tries to make machines equipped for performing those works that ordinarily require human knowledge. These works include the capacity to learn, adjust, legitimize, comprehend, and understand conceptual ideas as well as the reactivity to complex human credits like consideration, feeling, innovativeness, and so forth. The promising utility of artificial intelligence in medical services has been illustrated with potential advantages in customized medication, drug revelation, and the examination of huge datasets besides the likely applications to further develop conclusions and clinical choices.1 A new debated issue in the digitalized world has been man-made consciousness (artificial intelligence), especially that of ChatGPT. "ChatGPT" is a computer-based intelligence based on huge message datasets in different languages with the capacity to create human-like reactions to message input, created by Open AI (Open AI, L.L.C., San Francisco, CA, USA), ChatGPT derivation is connected with being a chatbot (a program ready to comprehend and produce reactions utilizing a text-based interface) and depends on the generative pre-prepared transformer (GPT) design. 2 ChatGPT can respond to questions and compose various written content, including articles, social media posts, essays, code, and emails. Researchers and the scholar community have gotten blended reactions to this tool regarding its benefits vs its risks. On the other hand, ChatGPT, among different large language models (LLMs), can be helpful in conversational and composing different tasks, helping to build the effectiveness and exactness of the necessary output. This is not a web search tool, reference custodian or even Wikipedia; introducing genuine information isn't planned.3In that capacity, a few teachers and content specialists have proactively found blemishes in the numerical and logical result it delivered. Teachers have additionally found that it will create references and reference records that look genuine, but it does not exist. Furthermore, the utility of artificial intelligence chatbots in the medical field is a fascinating region to test. This relates to the gigantic data and different ideas that medical services understudies are expected to get a handle on. Microsoft likewise declared that ChatGPT would be incorporated into Bing to make a more extravagant inquiry and growth opportunity.4 With the world's biggest innovation organizations contending to coordinate GPT innovation into their apparatuses, new roads of simulated intelligence investigation are not too far off for the field of schooling. While it tends to be useful in numerous ways, there are couple of risks using ChatGPT, for example, expecting that it produces trustworthy outcomes, privileging reproduced knowledge made text over human-made text, offering individual and sensitive data, dismissing the terms of direction, and expanding the mechanized segment. Furthermore, security concerns and the capability of digital assaults with the spread of deception using LLMs ought to likewise be considered. In medical care practice and scholarly composition, real mistakes, moral issues, and the apprehension about abuse including the spread of falsehood ought to be considered.5 Chat GPT and its substitutions can provide teachers and students with equal opportunity to improve their learning, a significant level of creating support, and bearing an innovative thinking. Moreover, with the execution of any new advancement, regardless, its usage conveys numerous risks and the potential for abuse. Deception and predisposition tracked down inside ChatGPT's reactions, combined with occasions of cheating and copyright infringement, have stressed instructive experts. While certain locale and organizations have acted rapidly to boycott ChatGPT, we rather accept, alongside Kranzberg, (1986) that "innovation is neither great nor awful; nor is it impartial" (p. 545).6 As the world discusses the instructive and cultural consequences of ChatGPT and artificial intelligence, what stays clear is that the turn of events and improvement of this kind of innovation indicate that things are not pulling back. Instructors, overseers, and policymakers must proactively look to teach themselves and their understudies on the most proficient method to utilize these devices both ethically and morally. Instructors ought to likewise comprehend the limits of utilizing man-made intelligence apparatuses and that, while each innovation presents both affordances and difficulties, they additionally accompany their own inserted risks.

Unlocking the secrets of color psychology for transformative interior design through SEHT

Colour psychology transcends visual appeal, delving into the profound connection between hues and human emotions. For budding interior decorators, this understanding is not merely an artistic endeavour but a tool to craft spaces that align with the occupants' emotional and spiritual needs. Subconscious Energy Healing Therapy (SEHT) offers a transformative lens for understanding the deeper resonance of colours, going beyond traditional aesthetics to unlock their emotional and energetic impact. SEHT is rooted in the idea that colours carry vibrational energies capable of influencing the subconscious mind. By leveraging this knowledge, interior decorators can create environments that foster positivity, balance, and healing. For instance, soft blues can evoke tranquillity, making them ideal for bedrooms, while vibrant yellows can stimulate creativity and energy in workspaces. Similarly, calming greens can restore a sense of harmony in living areas, while warm earthy tones can ground and comfort. The SEHT approach empowers designers to curate interiors that resonate with the energies and intentions of the occupants. By aligning colour choices with the principles of emotional well-being, decorators can create spaces that not only look stunning but also nurture the soul. This method bridges the gap between design and well-being, turning interiors into sanctuaries of healing and inspiration. Incorporating SEHT into interior design transforms it from a visual craft to an intuitive science. It allows designers to infuse their creations with purpose, crafting spaces that heal, energize, and connect on a subconscious level, fostering harmony within both the environment and its inhabitants. This topic explores the interplay of colour psychology and Subconscious Energy Healing Therapy (SEHT) for budding interior decorators. It emphasizes how colours not only transform spaces aesthetically but also influence emotional well-being and subconscious energy. Through the SEHT approach, this topic delves into understanding the deeper psychological impacts of hues, guiding designers to create spaces that heal, inspire, and rejuvenate both body and mind.

A mixed-method concurrent transformative study of metadiscourse markers employed by L2 speakers: does proficiency level matter?

The current study explored and compared the employment of interactive and interactional metadiscourse markers (MDMs) by the International English Language Testing System (IELTS) speaking test takers at beginner, intermediate, and advanced levels. To conduct this discourse analysis research, a mixed-methods approach with concurrent transformative design was employed. In the quantitative phase, the frequency of MDMs was calculated and compared, while in the qualitative phase, the variety of MDMs was analyzed. The data comprised a total of 36 YouTube videos on the test takers’ performance in part 3 of the IELTS speaking test at different band scores. The IELTS speaking band scores were converted into Common European Framework Reference (CEFR) levels using a converting scale, and the videos were transcribed to be analyzed. The results showed a level-by-level increasing trend in MDM use from beginner to advanced level. Moreover, the highly proficient L2 speakers used a wider range and a larger variety of MDMs in their discussions. The comparison between interactional and interactive MDMs also revealed that L2 speakers, at all proficiency levels, use the former considerably more than the latter. The findings of this study have significant pedagogical implications for language assessment, teaching, and learning, which are discussed in the discussion section in detail.

An Optical Transformation Design Method of Sky Screen Sensor Based on Lens Convergence

An Optical Transformation Design Method of Sky Screen Sensor Based on Lens Convergence

Design of rupture-proof transformers equipped with on-load tap-changer in the event of internal arc failures

Design of rupture-proof transformers equipped with on-load tap-changer in the event of internal arc failures

Design of a neural transformer for Spanish to Mexican Sign Language automatic translation/interpretation

ABSTRACT This paper uses a multi-head neural transformer to present the text-to-text translation/interpretation of Sign Language (SL) in the context of glosses (written SL). A Spanish to Mexican Sign Language (MSL) gloss dataset was built based on simple and compound sentences and the corresponding interpretation in MSL gloss. The interpretation process was achieved by implementing state-of-the-art tools in the natural language processing (NLP) field called neural transformers. We tried different architectures, varying the number of encoder-decoder layers and hyperparameters. The best of our models achieved 0.68 BLEU in the training phase and 0.33 in the validation phase. MSL glosses are crucial as they rule the grammatical order in which MSL has to be executed. All these quantitative and qualitative results confirm the potential applicability of neural transformers to create effective automatic translators for the Spanish language to MSL, with similar effectiveness shown by other automatic translators for other more likely languages.

The role of intellectual stimulation on students creativity improvement in higher education: A systematic literature review

In Higher Education, intellectual stimulation as a key aspect of transformational leadership, plays a vital role in fostering creativity and critical thinking among students. Several efforts have been made to improve students’ creativity in teaching and learning. Intellectual stimulation in Higher Education plays a significant role in fostering keen interest for learning and preparing students for future challenges. It creates a dynamic educational experience that benefits both the educators and students. However, there are still many institutions that have not optimized their students’ capacity development. For this reason, intellectual stimulation is considered as a strategic means for the improvement of creativity in education. All over the world, educational institutions encourage transformative teaching and learning skills design so as to implement a shift from the traditional pedagogy and be more creative with their teaching activities. Nevertheless, teaching and learning accomplishments in Higher Education are often faced with the challenge of resistance to change which slows down the improvement of students’ creativity improvement. This study comprises a systematic literature review using PRISMA approach to track related researches on the role of intellectual for the improvement of creativity in teaching and learning in Higher Education. The study defines the concept of intellectual stimulation and creativity in teaching and learning. The significance of intellectual stimulation in Higher Education is to enhance teaching strategies, influence policies and guide future research by providing a clear and impactful contribution through the promotion of active learning, encouraging student feedback on their thinking processes, directing funding towards innovative teaching methods and technologies that enhance intellectual stimulation in order to build supportive learning environments and finally, policy makers can use findings on intellectual stimulation to advocate for curricula that emphasizes problem solving, creativity and real world application .Results obtained indicate that intellectual stimulation plays a crucial role in improving students’ creativity. Findings from the study can be linked to potential policy changes for enhancing educational practices and improving education policies serving as advocates for inquiry-based learning and critical thinking skills. The potential contribution of this review study will prompt educators to encourage questioning, introduce diverse learning activities such as group projects and case studies, critical thinking exercises, foster a growth mindset in students, connect to real world issues.

Research on Wireless Charging System Based on Photovoltaic Power Supply

Given the popularity of mobile devices and rapid advances in wireless technology, it is impossible to overlook how important charging methods should be as convenient and environmentally sustainable. This paper investigates the PV power supply integration in their wireless charging systems, which aligns well with developing an environmentally safe and renewable alternative for recharging that would alleviate pressure on conventional harvesting of electricity, while also improving ecological conservation and reducing carbon emissions following earlier interests. Firstly, based on the PV battery model modeling methods and fully considering light intensity conditions at various temperatures throughout a year-long experimental validation of the electrical output characteristics of these PV panels. Second, it adapts and optimizes DC-DC converters to the output of PV panels for higher energy conversion efficiency by stabilizing energy outputs due to weathering issues. Additional area for research includes the choice and tuning of Maximum Power Point Tracking (MPPT) algorithms that will enable this system to follow maximum power point under diverse weather and light conditions in order to maximize energy harvesting. Moreover, the paper also performs an in-depth study of coupling transformer design and optimization of main circuit parameters for better energy transmission efficiency and System stability. The feasibility and effectiveness of the PV-powered wireless charging systems are validated by simulation verification as well as experimental testing in this paper.

Assessment of Non-Linear Modeling of Ladle Furnace Transformer Using Finite Element Analysis

This paper assesses a non-linear model of a three-phase Ladle Furnace Transformer, on slow front transients under no-load conditions. The model is designed to maintain accuracy and reduce complexity in estimating equivalent circuit parameters using three methods: analytical calculations, finite element analysis, and test measurement. The results reveal that analytical and finite element methods show discrepancies lower than 1%. Tests measurement, on the other hand, shows discrepancies higher than 5%, when compared to ones obtained from analytical and finite elements methods. Such discrepancy is particularly high in the estimation of leakage inductances and capacitances, and it is attributed mainly to differences between the transformer design and its actual assembly. Additionally, there are inherent inaccuracies in test procedures and instrumentation errors. The proposed model does not require difficult-to-obtain parameters and incorporates the non-linearity of magnetizing inductance, contributing to more accurate simulations. This simplified model is suitable for analyzing slow front transients and can be integrated into future studies addressing vacuum circuit breaker switching in electric arc furnace power systems, contributing to performance improvements in industrial applications. Additionally, the methodology for parameter determination can be applied to conventional power transformers, highlighting its versatility.

Preface

XIV International Conference on Recent Advances in Structural Dynamics (RASD) The RASD conference series was initiated by the late Professor Maurice Petyt of the Institute of Sound and Vibration Research (ISVR), Southampton, in 1980 “to review the advances which have been made in the theory and practice of structural dynamics … leading to a valuable exchange of ideas and form the basis for new developments”. Following a successful and hugely enjoyable sojourn in Lyon, 2019, and a delay due to the Covid 19 pandemic, the fourteenth conference returned in July 2024 to its inaugural venue, with the same aim. Just over 100 talks were presented during three days, including the following inspirational keynote addresses: Mahmoud Hussein Metadamping and metaharvesting: Vibration engineering at the intrinsic material level Guglielmo Aglietti Vibration testing of spacecraft structure - Virtual Testing & Multi DoF Shakers Jason Zheng Jiang Generative design for dynamic performance transformation The drinks and canape reception at Solent Sky aircraft museum was a highlight for attendees from all engineering backgrounds. List of Organising committee is available in this Pdf.

A Modified Area Product-Based Design for High-Frequency Planar Transformer Including Temperature Rise

A Modified Area Product-Based Design for High-Frequency Planar Transformer Including Temperature Rise

An intelligent transformer enabled medium voltage AC network for loss minimization and node voltage improvement

Abstract The research work presented here discusses about design and integration of intelligent transformer (IT) to the 15 kV/0.4 kV overloaded distribution feeder in Wolaita Sodo Town. The feeder contains 113 distribution transformers with different capacities ranging from 50 kVA to 1250 kVA. The proposed intelligent transformer is a three-stage modular type using phase shift multicarrier modulations for MMC front end converter. Its middle stage is dual active bridge having input series output parallel (DAB-ISOP) configuration using a phase shift modulation. The smart transformer’s back end uses an MMC inverter using interleaved phase shift modulation. The distribution feeder is modeled in MATLAB/Simulink and the designed intelligent transformer is allocated to it using voltage stability index (VSI). The peak load data, feeder data and transformer data of the distribution system under study are obtained from the utility office. The existing distribution feeder’s performance was evaluated by using backward-forward sweep load flow simulation for peak loading condition. The line flows and voltage profile at all nodes were observed and candidate nodes for enhancement were identified. Placement of modular intelligent transformer by using voltage stability index (VSI) was conducted to improve the voltage profiles, minimize reactive power flows and losses. Based on the simulation results for base case scenario, total power loss of 936.5 kW is obtained. The minimum node voltage of 0.81PU and maximum reactive power flow of 10.9MVAr were observed for the base case simulation. Placement of intelligent transformer at weak node 67 and node 111 improves the node voltages to have a minimum value 0.965 PU and maximum value of 1.05PU. The total power loss is reduced to 511.5 kW (54.5% improvement) after integration of intelligent transformer

XR for Transformable and Interactive Design

This article aims to show the applicability and evaluation of a teaching-learning method based on user experience (UX) design and extended reality (XR) in architectural studios. In the summer of 2023, the XR Assisted: Transformable and Interactive Design studio utilized the UX+XR teaching-learning method. During the studio, the emphasis was on designing a transformable and interactive architectural installation, with the UX as a center and XR, artificial intelligence, and inmotics as design and visualization tools. In the UX+XR method, the users were the students, and each student designed transformable architecture by applying UX strategies to their specific urban installation users. The UX+XR method had four phases. Each phase incorporated a cross-strategy UX+XR during the design process stages. Using UX+XR, the participants designed an architectural installation where the concepts of transformability, ephemerality, interactivity, flexibility, adaptability, versatility, and playfulness were present. Based on testing the six architectural installations designed during the studio using the UX+XR method, our data showed that XR enhanced the designer’s perception, constituted a new means of expression on an accurate scale, and is a highly immersive and interactive resource for communicating ideas and reinforcing visualization, simulation, stimulation, and interaction. XR is a powerful tool that, as used in the designed method, allows an elevated level of visual communication, understanding of spatial dimensions, and an effective multi-user collaborative strategy for evaluating the designed proposals.

Comprehensive Assessment of Ferroresonance and its Effects in Selected Distribution Substations in Nasarawa State, Nigeria

Ferroresonance in distribution networks generates harmful harmonics, excessive heating, and potential transformer failures, yet limited research focuses on its impact in Nigerian low-voltage systems. This study examines ferroresonance susceptibility in low-voltage distribution transformers, with an emphasis on core saturation, harmonic distortion, and grading capacitance effects under varied operational conditions across substations in Lafia, Akwanga, and Keffi. By analyzing transformer responses from 50V to 500V and harmonic profiles in Delta (1.12Ω) and Star-Grounded (1.53Ω) configurations, the research highlights transformer design's critical role in ferroresonance resilience. Findings reveal that increasing grading capacitance from 90 pF to 1550 pF substantially elevated peak voltages from 0.420kV to 2.400kV (Lafia), 2.450kV (Akwanga), and 2.540kV (Keffi), and currents from 28A, 26A and 27A to 103A, 118A, and 130A, respectively. Voltage THD similarly rose from 6.5%, 6.3% and 6.7% to 35.5%, 38.2%, and 36.0%, respective; with current THD climbing from 7.8% 7.5% and 7.9% to 40.2%, 44.1%, and 42.3% respectively, indicating varying ferroresonance susceptibility across the substations. Delta configurations show lower ferroresonance risk compared to Star-Grounded types, underscoring optimal winding configuration and capacitance management as key resilience factors. Recommendations include targeted harmonic filtering and precise capacitance management to stabilize transformer operation. Future research should consider broader transformer model diversity, adaptive control systems, and machine learning techniques for enhanced ferroresonance risk assessments.

Bridging Physics-Informed and Data-Driven Materials Designs to Catalyze Deep Decarbonization

Electrifying and decarbonizing key industrial sectors, including chemical and materials industries, as well as transportation and aviation, is a pressing mission of our time. Industrial players and governments worldwide have set ambitious targets to reduce carbon emissions, which need to be decreased to net-zero around mid-century in order to address global warming and climate change. For such deep decarbonization, it is crucial to develop unprecedented materials, such as electrocatalysts that can efficiently and steadily produce green chemicals and fuels at scale and generate renewable electricity on demand. In this talk, I will introduce how a joint computational–experimental approach can be established to accelerate catalyst materials design using first-principles atomistic simulations, synchrotron X-ray spectroscopies, and physics-inspired machine learning. I will highlight how mechanistically elucidating and quantitatively controlling the electronic structure of transition metal compounds can effectively alter their chemical bondings, modulate key reaction barriers toward dissolution and electrocatalysis, and thus influence their durability and reactivity, respectively, offering physics-driven guiding principles for optimizing their catalytic performance. Moreover, I will demonstrate how combining machine learning with materials physics can accelerate the discovery of multicomponent oxides—a new class of materials with too-complicated atomic orderings for an exhaustive investigation—through the development of machine-learning models that accurately predict ordering-dependent materials properties by capturing intrinsic symmetries. To conclude, I will discuss new opportunities for further resolving fundamental knowledge gaps between the structural, reaction, and compositional complexities of electrocatalyst surfaces to fully unlock transformative materials design for catalyzing sustainability and decarbonization.

Study on the Electric Field Distribution Characteristics of 66 kV Dry-Type Transformer Based on Functional Graded Material (FGM) Treatment

Functional graded materials (FGMs) have been successfully applied for improving the insulation performance of insulators, yet there is currently no relevant literature on their application in dry-type transformers. Therefore, it is meaningful to study the feasibility of using FGMs to improve the insulation performance of dry-type transformers through research on electric field distribution. This paper sets FGMs in the dry-type transformer spacer only or both the spacer and winding end to change the relative permittivity values in the corresponding areas. By comparing the electric field distribution characteristics on the inner and outer surfaces of the high-voltage coil and the lower surface of the spacer of the dry-type transformer under each control method with the case without setting FGMs, the study found that when FGMs were only set on the spacer, the control methods set in this paper could not improve the electric field distribution of the transformer. When FGMs are employed at the spacers and end windings, two modulation strategies can mitigate the electric field intensity on the outer surface of the high-voltage windings. Specifically, a continuous increase in relative permittivity can reduce the electric field intensity by 34.02%, while an initial decrease followed by an increase can result in a reduction of 13.58%. This paper provides theoretical guidance for insulation design of transformers with high voltage levels of 66 kV and above, especially as transformers with high voltage levels face greater challenges in regulating surface electric fields.