Search results

1 – 10 of over 7000
Article
Publication date: 14 March 2024

Mustafa Altınel and Uğur Yalçın

This paper aims to examine the uniform diffracted fields from a perfectly magnetic conductive (PMC) surface with the extended theory of boundary diffraction wave (BDW) approach.

Abstract

Purpose

This paper aims to examine the uniform diffracted fields from a perfectly magnetic conductive (PMC) surface with the extended theory of boundary diffraction wave (BDW) approach.

Design/methodology/approach

Miyamoto and Wolf’s symbolic expression of the vector potential was used in the extended theory of BDW integral. This vector potential is applied to the problem, and the nonuniform field expression found was made uniform. Here, the expression is made uniform, using the detour parameter with the help of the asymptotic correlation of the Fresnel function. The BDW theory for the PMC surface extended the diffracted fields, and the uniform diffracted fields were calculated.

Findings

The field expressions obtained were interpreted with the graphs numerically for different aperture radii and observation distances. It has been shown that the BDW is continuous behind the diffracting aperture. There does not exist any discontinuity at the geometrically light-to-shadow transition boundary, as is required by the theory.

Originality/value

The results were graphically compared with diffracted fields for other surfaces. As far as we know, the uniform diffracted fields from the circular aperture on a PMC surface were calculated for the first time with the extended theory of the BDW approach.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 20 March 2024

Ziming Zhou, Fengnian Zhao and David Hung

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine…

Abstract

Purpose

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.

Design/methodology/approach

To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.

Findings

The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.

Originality/value

The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 13 February 2024

Ionut Nica

This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we…

Abstract

Purpose

This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.

Design/methodology/approach

The analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.

Findings

The results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.

Originality/value

This study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 12 February 2024

Lutz Bornmann and Klaus Wohlrabe

Differences in annual publication counts may reflect the dynamic of scientific progress. Declining annual numbers of publications may be interpreted as missing progress in…

Abstract

Purpose

Differences in annual publication counts may reflect the dynamic of scientific progress. Declining annual numbers of publications may be interpreted as missing progress in field-specific knowledge.

Design/methodology/approach

In this paper, we present empirical results on dynamics of progress in economic fields (defined by Journal of Economic Literature (JEL), codes) based on a methodological approach introduced by Bornmann and Haunschild (2022). We focused on publications that have been published between 2012 and 2021 and identified those fields in economics with the highest dynamics (largest rates of change in paper counts).

Findings

We found that the field with the largest paper output across the years is “Economic Development”. The results reveal that the field-specific rates of changes are mostly similar. However, the two fields “Production and Organizations” and “Health” show point estimators which are clearly higher than the estimators for the other fields. We investigated the publications in “Production and Organizations” and “Health” in more detail.

Originality/value

Understanding how a discipline evolves over time is interesting both from a historical and a recent perspective. This study presents results on the dynamics in economic fields using a new methodological approach.

Details

Journal of Documentation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0022-0418

Keywords

Article
Publication date: 9 January 2024

Juelin Leng, Quan Xu, Tiantian Liu, Yang Yang and Peng Zheng

The purpose of this paper is to present an automatic approach for mesh sizing field generation of complicated  computer-aided design (CAD) models.

Abstract

Purpose

The purpose of this paper is to present an automatic approach for mesh sizing field generation of complicated  computer-aided design (CAD) models.

Design/methodology/approach

In this paper, the authors present an automatic approach for mesh sizing field generation. First, a source point extraction algorithm is applied to capture curvature and proximity features of CAD models. Second, according to the distribution of feature source points, an octree background mesh is constructed for storing element size value. Third, mesh size value on each node of background mesh is calculated by interpolating the local feature size of the nearby source points, and then, an initial mesh sizing field is obtained. Finally, a theoretically guaranteed smoothing algorithm is developed to restrict the gradient of the mesh sizing field.

Findings

To achieve high performance, the proposed approach has been implemented in multithreaded parallel using OpenMP. Numerical results demonstrate that the proposed approach is remarkably efficient to construct reasonable mesh sizing field for complicated CAD models and applicable for generating geometrically adaptive triangle/tetrahedral meshes. Moreover, since the mesh sizing field is defined on an octree background mesh, high-efficiency query of local size value could be achieved in the following mesh generation procedure.

Originality/value

How to determine a reasonable mesh size for complicated CAD models is often a bottleneck of mesh generation. For the complicated models with thousands or even ten thousands of geometric entities, it is time-consuming to construct an appropriate mesh sizing field for generating high-quality mesh. A parallel algorithm of mesh sizing field generation with low computational complexity is presented in this paper, and its usability and efficiency have been verified.

Details

Engineering Computations, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 9 January 2024

Caecilia Drujon d’Astros, Camille Gaudy and Marianne Strauch

This paper aims to explore the role of the researcher’s emotions in ethnographic practice in accounting research. This paper focuses on shame as an emotion that lingers on…

Abstract

Purpose

This paper aims to explore the role of the researcher’s emotions in ethnographic practice in accounting research. This paper focuses on shame as an emotion that lingers on, despite the efforts to work through those emotions.

Design/methodology/approach

The authors conducted a collective autoethnography to make sense of the fieldwork and after-fieldwork emotions and their consequences. This autoethnography began with the three authors discovering their shared feeling of shame.

Findings

Building on Hochschild’s theory (1979, 1983) on emotional labor, the authors demonstrate how shame emerged as a central and lingering emotion of the ethnographies beyond an emotional labor process. The authors show how a double shame appeared toward the field participants and the academic accounting community, affecting the writing and the work.

Originality/value

The authors demonstrate that the perception of the research community’s rules of feelings gives rise to emotions that ultimately change the work. The authors show how collective autoethnography can help accounting research to acknowledge and give room to emotions.

Details

Qualitative Research in Accounting & Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1176-6093

Keywords

Article
Publication date: 17 January 2024

Beyza Aksoy, Ayhan Akpınar and Çağatay Ünüsan

This study aims to present a bibliometric overview of the academic research on export performance (EP) in the business and management areas.

106

Abstract

Purpose

This study aims to present a bibliometric overview of the academic research on export performance (EP) in the business and management areas.

Design/methodology/approach

A bibliometric overview of 1,463 papers from 1968 to 2021, including performance analysis, science mapping analysis and graphical mapping, was conducted using the Scopus database. SciMAT software was used for thematic analysis and conceptual evolution mapping of the EP domain, and VOSviewer software was used for graphical visualization.

Findings

This study shows that EP research experienced spectacular growth, especially between 1998 and 2003, and the interest in this field continues to increase. Also, the USA and the UK appear to be the absolute leaders in EP research, with the best indicators of productivity and influence in all dimensions analyzed. The findings from the analysis through SciMAT indicate that “capabilities” and “R&D” are the main Motor themes that have contributed the most to the EP literature, whereas “global value chain” and “start-up” are emerging themes as new areas of interest.

Research limitations/implications

This study develops a baseline for representing certain and exhaustive insights in the EP field and specifies trends over a period. Using a single database and excluding book chapters/conference papers are limitations of this study.

Originality/value

EP is a research field that has gained wide acceptance in the academic community and international marketing literature. To the best of the authors’ knowledge, no bibliometric overview has analyzed the EP literature. This study presents the first systematic quantitative analysis of academic research on EP in the business and management areas.

Details

Journal of Business & Industrial Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 14 November 2023

Hajar Pouran Manjily, Mahmood Alborzi, Turaj Behrouz and Seyed Mohammad Seyed- Hosseini

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with…

Abstract

Purpose

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

Design/methodology/approach

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

Findings

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

Originality/value

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

Details

Journal of Science and Technology Policy Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 19 December 2023

Isabella Sulis, Barbara Barbieri, Luisa Salaris, Gabriella Melis and Mariano Porcu

This paper aims to assess gender bias in Italian university student mobility controlling for the field of study. It uses data from the Italian National Student Archive (Anagrafe…

Abstract

Purpose

This paper aims to assess gender bias in Italian university student mobility controlling for the field of study. It uses data from the Italian National Student Archive (Anagrafe Nazionale degli Studenti – ANS) for the cohort of freshmen enrolled in the 2017 academic year. The macro-regional comparison unfolds across the following areas: North and Centre, Southern Italy and main Islands (Sicily and Sardinia).

Design/methodology/approach

The analysis is firstly carried out at the national level, and secondly, it focusses on macro-geographical areas. University mobility choices are thus investigated from a gender perspective, conditioning upon other theoretically relevant characteristics collected for the prospective first-year university student population enrolled in 2017. The authors analyse data in a regression setting (logit models) within the multilevel framework, which considers students at level 1 and the field of study at level 2. Gender differences in the propensity to be a mover – conditional upon the choice of the field of study – were captured by introducing random intercepts to account for clustering of students in fields of study and random slopes to allow the gender effect to differ among them.

Findings

Findings show that university student mobility in Italy leads evidence of gender bias. This has been detected using a multilevel random slope approach that allowed the authors to jointly estimate a slope parameter for gender within each field of study. Moreover, using a regression setting allowed the authors to control for heterogeneity in geographical, educational and socio-demographic characteristics across students. In line with previous empirical findings, the authors' data highlight the presence of a relevant mobility flow of university students from the South toward the North-Centre of Italy and lower mobility of female students compared to male students from the South and Islands.

Originality/value

To the best of the authors' knowledge, there are no studies in Italy, which investigate if families' investment in higher education in terms of selection of no-local universities are affected by gender bias and if geographical differences in this behaviour between macro-areas are in place. Thus, investigating students' choices in tertiary education allows the authors to shed light on the presence of gender bias in families' education strategies addressed to increase the endowment of students' assets for future job opportunities.

Details

International Journal of Manpower, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-7720

Keywords

Article
Publication date: 22 March 2024

Shahin Alipour Bonab, Alireza Sadeghi and Mohammad Yazdani-Asrami

The ionization of the air surrounding the phase conductor in high-voltage transmission lines results in a phenomenon known as the Corona effect. To avoid this, Corona rings are…

Abstract

Purpose

The ionization of the air surrounding the phase conductor in high-voltage transmission lines results in a phenomenon known as the Corona effect. To avoid this, Corona rings are used to dampen the electric field imposed on the insulator. The purpose of this study is to present a fast and intelligent surrogate model for determination of the electric field imposed on the surface of a 120 kV composite insulator, in presence of the Corona ring.

Design/methodology/approach

Usually, the structural design parameters of the Corona ring are selected through an optimization procedure combined with some numerical simulations such as finite element method (FEM). These methods are slow and computationally expensive and thus, extremely reducing the speed of optimization problems. In this paper, a novel surrogate model was proposed that could calculate the maximum electric field imposed on a ceramic insulator in a 120 kV line. The surrogate model was created based on the different scenarios of height, radius and inner radius of the Corona ring, as the inputs of the model, while the maximum electric field on the body of the insulator was considered as the output.

Findings

The proposed model was based on artificial intelligence techniques that have high accuracy and low computational time. Three methods were used here to develop the AI-based surrogate model, namely, Cascade forward neural network (CFNN), support vector regression and K-nearest neighbors regression. The results indicated that the CFNN has the highest accuracy among these methods with 99.81% R-squared and only 0.045468 root mean squared error while the testing time is less than 10 ms.

Originality/value

To the best of the authors’ knowledge, for the first time, a surrogate method is proposed for the prediction of the maximum electric field imposed on the high voltage insulators in the presence Corona ring which is faster than any conventional finite element method.

Details

World Journal of Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1708-5284

Keywords

1 – 10 of over 7000