Hasil untuk "Electrical engineering. Electronics. Nuclear engineering"

Karina Kohl, Luigi Carro

Software Engineering (SE) faces simultaneous pressure from AI automation (reducing code production costs) and hardware-energy constraints (amplifying failure costs). We position that SE must redefine itself around human discernment-intent articulation, architectural control, and verification-rather than code construction. This shift introduces accountability collapse as a central risk and requires fundamental changes to research priorities, educational curricula, and industrial practices. We argue that Software Engineering, as traditionally defined around code construction and process management, is no longer sufficient. Instead, the discipline must be redefined around intent articulation, architectural control, and systematic verification. This redefinition shifts Software Engineering from a production-oriented field to one centered on human judgment under automation, with profound implications for research, practice, and education.

Yiming Zhang, Yuxi Liu, Sailing He

ABSTRACT A compact leaky‐wave antenna (LWA) with innovative phase‐shift asymmetric coupling for continuous beam scanning is presented. The antenna utilises a slow‐wave half‐mode substrate integrated waveguide with spoof surface plasmon polaritons (SW‐HMSIW‐SSPP) transmission line structure to achieve ultra‐compact dimensions in both longitudinal and lateral directions. The radiation characteristic is achieved using sinusoidal modulation on the SSPP structure. To enable continuous beam scanning through broadside, a novel and simple phase‐shift asymmetric coupling method is developed by placing sinusoidally modulated patches with π/2 phase shift on the metallised blind via‐hole arrays. This approach effectively suppresses the open stopband (OSB) and enables continuous beam scanning from backward to forward directions without radiation degradation at broadside. A prototype of the proposed LWA is fabricated and characterised. The measured results demonstrate that the antenna with 12 unit‐cells operates over a wide frequency range from 14.3 to 20.5 GHz with continuous beam scanning from −40° to +30°, while maintaining an ultra‐compact aperture of only 6.67 λ0 × 0.27 λ0.

Daiki Mayumi, Hiroki Matsuda, Tetsuya Yokota et al.

This study presents the construction of the first digital twin utilizing non-identifiable television viewing history data. As the media landscape continues to evolve, understanding viewer behavior has become increasingly crucial. By simulating viewing behaviors based on real-time data, our approach enables the virtual reproduction of viewer preferences and behavior patterns, facilitating optimized advertising, content production, and marketing strategies. We propose a method for classifying user viewing tendencies using large-scale, non-identifiable data and develop a simulator based on these classifications. A detailed analysis of the data led to the extraction of tailored features for television viewing and the development of a highly accurate classification model. The weekday and weekend models achieved F1 scores of approximately 0.95, demonstrating their strong predictive capabilities. This study provides valuable insights into digital twin construction for television viewing and opens new avenues for data-driven media strategies.

Chuanzhe Wang, Jie Lv, Mengyi Yang et al.

Cardiovascular diseases (CVD) are the leading global threat to human health. The clinical application of vascular stents improved the survival rates and quality of life for patients with cardiovascular diseases. However, despite the benefits stents bring to patients, there are still notable complications such as thrombosis and in-stent restenosis (ISR). Surface modification techniques represent an effective strategy to enhance the clinical efficacy of vascular stents and reduce complications. This paper reviews the development strategies of vascular stents based on surface functional coating technologies aimed at addressing the limitations in clinical application, including the inhibition of intimal hyperplasia, promotion of re-endothelialization. These strategies have improved endothelial repair and inhibited vascular remodeling, thereby promoting vascular healing post-stent implantation. However, the pathological microenvironment of target vessels and the lipid plaques are key pathological factors in the development of atherosclerosis (AS) and impaired vascular repair after percutaneous coronary intervention (PCI). Therefore, restoring normal physiological environment and removing the plaques are also treatment focuses after PCI for promoting vascular repair. Unfortunately, research in this area is limited. This paper reviews the advancements in vascular stents based on surface engineering technologies over the past decade, providing guidance for the development of stents.

Ashis Kumar Mandal, Md Nadim, Chanchal K. Roy et al.

Research in software engineering is essential for improving development practices, leading to reliable and secure software. Leveraging the principles of quantum physics, quantum computing has emerged as a new computational paradigm that offers significant advantages over classical computing. As quantum computing progresses rapidly, its potential applications across various fields are becoming apparent. In software engineering, many tasks involve complex computations where quantum computers can greatly speed up the development process, leading to faster and more efficient solutions. With the growing use of quantum-based applications in different fields, quantum software engineering (QSE) has emerged as a discipline focused on designing, developing, and optimizing quantum software for diverse applications. This paper aims to review the role of quantum computing in software engineering research and the latest developments in QSE. To our knowledge, this is the first comprehensive review on this topic. We begin by introducing quantum computing, exploring its fundamental concepts, and discussing its potential applications in software engineering. We also examine various QSE techniques that expedite software development. Finally, we discuss the opportunities and challenges in quantum-driven software engineering and QSE. Our study reveals that quantum machine learning (QML) and quantum optimization have substantial potential to address classical software engineering tasks, though this area is still limited. Current QSE tools and techniques lack robustness and maturity, indicating a need for more focus. One of the main challenges is that quantum computing has yet to reach its full potential.

Tim Wittenborg, Ildar Baimuratov, Ludvig Knöös Franzén et al.

The aerospace industry operates at the frontier of technological innovation while maintaining high standards regarding safety and reliability. In this environment, with an enormous potential for re-use and adaptation of existing solutions and methods, Knowledge-Based Engineering (KBE) has been applied for decades. The objective of this study is to identify and examine state-of-the-art knowledge management practices in the field of aerospace engineering. Our contributions include: 1) A SWARM-SLR of over 1,000 articles with qualitative analysis of 164 selected articles, supported by two aerospace engineering domain expert surveys. 2) A knowledge graph of over 700 knowledge-based aerospace engineering processes, software, and data, formalized in the interoperable Web Ontology Language (OWL) and mapped to Wikidata entries where possible. The knowledge graph is represented on the Open Research Knowledge Graph (ORKG), and an aerospace Wikibase, for reuse and continuation of structuring aerospace engineering knowledge exchange. 3) Our resulting intermediate and final artifacts of the knowledge synthesis, available as a Zenodo dataset. This review sets a precedent for structured, semantic-based approaches to managing aerospace engineering knowledge. By advancing these principles, research, and industry can achieve more efficient design processes, enhanced collaboration, and a stronger commitment to sustainable aviation.

Nasir U. Eisty, Jeffrey C. Carver, Johanna Cohoon et al.

In the evolving landscape of scientific and scholarly research, effective collaboration between Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) is pivotal for advancing innovation and ensuring the integrity of computational methodologies. This paper presents ten strategic guidelines aimed at fostering productive partnerships between these two distinct yet complementary communities. The guidelines emphasize the importance of recognizing and respecting the cultural and operational differences between RSEs and SERs, proactively initiating and nurturing collaborations, and engaging within each other's professional environments. They advocate for identifying shared challenges, maintaining openness to emerging problems, ensuring mutual benefits, and serving as advocates for one another. Additionally, the guidelines highlight the necessity of vigilance in monitoring collaboration dynamics, securing institutional support, and defining clear, shared objectives. By adhering to these principles, RSEs and SERs can build synergistic relationships that enhance the quality and impact of research outcomes.

Oz Levy, Ilya Dikman, Natan Levy et al.

This paper explores how generative AI can help automate and improve key steps in systems engineering. It examines AI's ability to analyze system requirements based on INCOSE's "good requirement" criteria, identifying well-formed and poorly written requirements. The AI does not just classify requirements but also explains why some do not meet the standards. By comparing AI assessments with those of experienced engineers, the study evaluates the accuracy and reliability of AI in identifying quality issues. Additionally, it explores AI's ability to classify functional and non-functional requirements and generate test specifications based on these classifications. Through both quantitative and qualitative analysis, the research aims to assess AI's potential to streamline engineering processes and improve learning outcomes. It also highlights the challenges and limitations of AI, ensuring its safe and ethical use in professional and academic settings.

Lekshmi Murali Rani

The study of behavioral and social dimensions of software engineering (SE) tasks characterizes behavioral software engineering (BSE);however, the increasing significance of human-AI collaboration (HAIC) brings new directions in BSE by presenting new challenges and opportunities. This PhD research focuses on decision-making (DM) for SE tasks and collaboration within human-AI teams, aiming to promote responsible software engineering through a cognitive partnership between humans and AI. The goal of the research is to identify the challenges and nuances in HAIC from a cognitive perspective, design and optimize collaboration/partnership (human-AI team) that enhance collective intelligence and promote better, responsible DM in SE through human-centered approaches. The research addresses HAIC and its impact on individual, team, and organizational level aspects of BSE.

Max Neuwinger, Dirk Riehle

The design of effective programming languages, libraries, frameworks, tools, and platforms for data engineering strongly depends on their ease and correctness of use. Anyone who ignores that it is humans who use these tools risks building tools that are useless, or worse, harmful. To ensure our data engineering tools are based on solid foundations, we performed a systematic review of common programming mistakes in data engineering. We focus on programming beginners (students) by analyzing both the limited literature specific to data engineering mistakes and general programming mistakes in languages commonly used in data engineering (Python, SQL, Java). Through analysis of 21 publications spanning from 2003 to 2024, we synthesized these complementary sources into a comprehensive classification that captures both general programming challenges and domain-specific data engineering mistakes. This classification provides an empirical foundation for future tool development and educational strategies. We believe our systematic categorization will help researchers, practitioners, and educators better understand and address the challenges faced by novice data engineers.

Adrian Bajraktari, Michelle Binder, Andreas Vogelsang

Modern science is relying on software more than ever. The behavior and outcomes of this software shape the scientific and public discourse on important topics like climate change, economic growth, or the spread of infections. Most researchers creating software for scientific purposes are not trained in Software Engineering. As a consequence, research software is often developed ad hoc without following stringent processes. With this paper, we want to characterize research software as a new application domain that needs attention from the Requirements Engineering community. We conducted an exploratory study based on 8 interviews with 12 researchers who develop software. We describe how researchers elicit, document, and analyze requirements for research software and what processes they follow. From this, we derive specific challenges and describe a vision of Requirements Engineering for research software.

Michela Prunella, Roberto Maria Scardigno, Domenico Buongiorno et al.

Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted feature extraction, selection, and validation, counted on a combined approach of parameterized image processing algorithms and explicated human knowledge. The outstanding performance of deep learning (DL) for vision systems, in automatically discovering a feature representation suitable for the corresponding task, has exponentially increased the number of scientific articles and commercial products aiming at industrial quality assessment. In such a context, this article reviews more than 220 relevant articles from the related literature published until February 2023, covering the recent consolidation and advances in the field of fully-automatic DL-based surface defects inspection systems, deployed in various industrial applications. The analyzed papers have been classified according to a bi-dimensional taxonomy, that considers both the specific defect recognition task and the employed learning paradigm. The dependency on large and high-quality labeled datasets and the different neural architectures employed to achieve an overall perception of both well-visible and subtle defects, through the supervision of fine or/and coarse data annotations have been assessed. The results of our analysis highlight a growing research interest in defect representation power enrichment, especially by transferring pre-trained layers to an optimized network and by explaining the network decisions to suggest trustworthy retention or rejection of the products being evaluated.

X.B. Ye, B.C. Pan

Since tungsten (W) was considered as the most promising plasma facing materials (PFMs) in fusion reactors, there has been extensive research on the physical performance of W-PFMs. It is found that under the extreme conditions in a fusion reactor, W-PFMs should be in a nonequilibrium state of high electronic temperature and low ionic temperature. This leads to the possibility of non-thermal phase transitions, where the crystal structure of the tungsten material may change from body-centered cubic (bcc) phase to hexagonal close-packed (hcp) phase or face-centered cubic (fcc) phase. Consequently, it is necessary to investigate the relevant physical properties of hcp-W and fcc-W under the electron-excited state. In this work, the fundamental physical properties, including atomic structures, electronic structures, elastic constants, and vacancy formation energies, of bcc-W, hcp-W and fcc-W, were theoretically calculated at various electronic temperatures. The mechanical stability of these three phases was also systematically analyzed under varying electronic temperatures. The results of this research are expected to provide a certain guidance in the optimization of W-PFMs in future fusion reactors.

Jan Heine, Herbert Palm

The increasing pressure within VUCA (volatility, uncertainty, complexity and ambiguity) driven environments causes traditional, plan-driven Systems Engineering approaches to no longer suffice. Agility is then changing from a "nice-to-have" to a "must-have" capability for successful system developing organisations. The current state of the art, however, does not provide clear answers on how to map this need in terms of processes, methods, tools and competencies (PMTC) and how to successfully manage the transition within established industries. In this paper, we propose an agile Systems Engineering (SE) Framework for the automotive industry to meet the new agility demand. In addition to the methodological background, we present results of a pilot project in the chassis development department of a German automotive manufacturer and demonstrate the effectiveness of the newly proposed framework. By adopting the described agile SE Framework, companies can foster innovation and collaboration based on a learning, continuous improvement and self-reinforcing base.

K. Proskuryakov, A. Anikeev, R. M. Ismail

In this paper, the existing results of this study have been carried out at NRU MPEI to create digital technologies for constructing the acoustic field of primary circuit equipment designed to manage the life cycle of nuclear power plants (NPPs) with VVER and develop their digital twins. The purpose of this paper is to study the influence of non-design dynamic loads on equipment and the causes of which are currently unknown and not provided for by regulatory documentation. The research methodology is based on using digital modeling of the acoustic field to predict its dependence on operating conditions, and also on the verification of the forecast at an operating NPP. The obtained results have been tested to the creation of methods and algorithms for calculating the acoustic field of VVER, which have no analogues in nuclear and thermal power engineering. The adequacy of the acoustic field of the VVER primary circuit to a group of simultaneously functioning Helmholtz resonators has been proved.

S. A. Aljasar, Y. Xu, Mohammad R. Qasaimeh

In this paper, first time Silicon carbide (SiC) nanoparticles have been laser fabricated, characterized and introduced into the flexible Kapton substrate for thermal heater application. The primary attention is devoted to emerging thermal sensor applications for the nuclear industry, bringing a boon or a security purpose. The fabricated structures were characterized through the scan electron microscopy (SEM), ultra violet microscope (UV) used for absorbance and electrochemical oxidation and reduction in terms of stability of sillion carbide nanoparticles. Combining the excellent electrical properties of Silicon carbide and high temperature tolerance of polyimide, we demonstrated for the first time a flexible SiC sensor. A quick and simple approach is used to fast fabricate the thermal heater prototype. This facile method for synthesizing SiC nanoparticles provides a new idea for high-value thermal heater application for nuclear sensor.

K. Proskuryakov, E. Afshar, A. Anikeev et al.

The method of calculating frequencies of the acoustic standing waves (ASW) in digital acoustic models of steam generator (DAMSG) is similar to that used for the digital acoustical model for nuclear reactors (DAMNR). DAMSG is regarded as an auto oscillatory system that consists of a distinctive group of dissipative non-linear systems that are able to perform oscillations of un-damped nature with parameters independent of primary conditions and determined only by the system characteristics. The verification results of the DAMSG of VVER-440 are showed. An approach has been developed to determine the ASW frequencies generated in the SG. An anomalous boost in the power of pressure fluctuations in the reactor nominal operation mode indicates the presence of acoustical resonances in the bandwidth of the main circulation pump (MCP) rotation frequency which gives rise to the practical significance of the developed new models of the SG. Using DAMSG is able to optimize designs and can help in minimizing unwanted cyclic loads. This is a crucial for maintaining long-term operation in maneuverable modes of all small reactors.

S. A. Aljasar, Artyom G. Naymushin, Y. Xu

A new type of low-enriched uranium fuel (LUE) is intended to allow high-performance nuclear investigation and experimental reactors which use highly-enriched uranium fuel (HEU) to be transitioned to low-enriched uranium. The University of Tomsk Research Reactor (IRT-T) has successfully completed analysis and construction simulations for transformation to LEU, and HEU, which is utilized as a nuclear fuel source, is being demonstrated further in this research. Nuclear nonproliferation approaches are demonstrated in reactor issues due to uncertainties. Experimenters propose the conversion of HEU reactors to LEU in order to adulterate HEU iterative reactors. In this investigation, Points of development, problems encountered, and views are all covered in depth.

Anton G. Zubkov, D. A. Oleksyuk, Evgeniy A. Vertikov et al.

The paper presents an analysis of the influence of the axial non-uniform of power distribution on the magnitude of the critical heat flux (CHF) in the fuel assemblies (FA) of water-cooled nuclear. A numerical study of the influence of various shape factors on the distribution of the CHF value is carried out for various regime parameters of the coolant and the shapes of the axial power distribution. The method of optimization of empirical coefficients in correlation for the shape factor of the axial profile of power distribution is presented. The cumulative effect of such factors as axial non-uniform of power distribution and heat transfer grid-intensifiers on the value of CHF is considered.

S. A. Aljasar, Artyom G. Naymushin, Y. Xu

Perspectives on minimal optimization of risk management claims as an advent research area. It is necessary to minimize emergency risks and improve system reliability in the nuclear industries. Accordingly, research-based development is concerned with risk-related problems, such as handling safety and hazardous conditions. The present study combines experimental estimation and simulation of the research reactor type (IRT) using parameters commonly used in hydraulic tests. Data were taken from an 8tube IRT-3M hydraulic simulation with 8 IRT-3M fuel pooling tubes. ANSYS was used to develop a simulation of hydraulic fuel assembly tubes. Furthermore, experimental results were used to verify the ANSYS codes, and coolant speeds within the gaps in the fuel assembly were calculated.