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1 – 10 of 38
Open Access
Article
Publication date: 22 November 2023

En-Ze Rui, Guang-Zhi Zeng, Yi-Qing Ni, Zheng-Wei Chen and Shuo Hao

Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural…

Abstract

Purpose

Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.

Design/methodology/approach

A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.

Findings

Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.

Originality/value

In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 34 no. 1
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 12 February 2024

Bahram Jalili, Milad Sadinezhad Fard, Yasir Khan, Payam Jalili and D.D. Ganji

The current analysis produces the fractional sample of non-Newtonian Casson and Williamson boundary layer flow considering the heat flux and the slip velocity. An extended sheet…

Abstract

Purpose

The current analysis produces the fractional sample of non-Newtonian Casson and Williamson boundary layer flow considering the heat flux and the slip velocity. An extended sheet with a nonuniform thickness causes the steady boundary layer flow’s temperature and velocity fields. Our purpose in this research is to use Akbari Ganji method (AGM) to solve equations and compare the accuracy of this method with the spectral collocation method.

Design/methodology/approach

The trial polynomials that will be utilized to carry out the AGM are then used to solve the nonlinear governing system of the PDEs, which has been transformed into a nonlinear collection of linked ODEs.

Findings

The profile of temperature and dimensionless velocity for different parameters were displayed graphically. Also, the effect of two different parameters simultaneously on the temperature is displayed in three dimensions. The results demonstrate that the skin-friction coefficient rises with growing magnetic numbers, whereas the Casson and the local Williamson parameters show reverse manners.

Originality/value

Moreover, the usefulness and precision of the presented approach are pleasing, as can be seen by comparing the results with previous research. Also, the calculated solutions utilizing the provided procedure were physically sufficient and precise.

Details

Multidiscipline Modeling in Materials and Structures, vol. 20 no. 2
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 2 January 2024

Hongjing Dong, Xi Chen, Guangying Yang, Dandan He, Ying Dai and Pengfei He

The purpose of this paper is to obtain a constitutive model of cement-based material in the rheological stage, which owns the different water-cement ratio (w/c) and temperature…

Abstract

Purpose

The purpose of this paper is to obtain a constitutive model of cement-based material in the rheological stage, which owns the different water-cement ratio (w/c) and temperature and have a significant impact on the workability of concrete materials.

Design/methodology/approach

It is introduced a modified Arrhenius equation into the Herschel–Bulkley model, which is widely applied in rheological analysis and constructed an ordinary differential equation (ODE) of w/c from the Navier–Stokes equation. By solving the ODE, an approximate constitutive relation of cement-based materials included w/c and temperature is derived. Compared with the experimental results, the present model is validated.

Findings

The shear stress and shear rate curves with different w/c and temperature are simulated by the present method, and the present model can be applied to analyze the changes of apparent viscosity in cement-based material slurry as the w/c and temperature varying.

Originality/value

This work gives a mathematical model, which can effectively approximate the shear stress–shear rate relation with different w/c and temperature in the rheological stage of cement-based material.

Details

Multidiscipline Modeling in Materials and Structures, vol. 20 no. 1
Type: Research Article
ISSN: 1573-6105

Keywords

Open Access
Article
Publication date: 30 June 2023

Carmel Bond, Gemma Stacey, Greta Westwood and Louisa Long

The purpose of this paper is to evaluate the impact of leadership development programmes, underpinned by Transformational Learning Theory (TLT).

1386

Abstract

Purpose

The purpose of this paper is to evaluate the impact of leadership development programmes, underpinned by Transformational Learning Theory (TLT).

Design/methodology/approach

A corpus-informed analysis was conducted using survey data from 690 participants. Data were collected from participants’ responses to the question “please tell us about the impact of your overall experience”, which culminated in a combined corpus of 75,053 words.

Findings

Findings identified patterns of language clustered around the following frequently used word types, namely, confidence; influence; self-awareness; insight; and impact.

Research limitations/implications

This in-depth qualitative evaluation of participants’ feedback has provided insight into how TLT can be applied to develop future health-care leaders. The extent to which learning has had a transformational impact at the individual level, in relation to their perceived ability to influence, holds promise for the wider impact of this group in relation to policy, practice and the promotion of clinical excellence in the future. However, the latter can only be ascertained by undertaking further realist evaluation and longitudinal study to understand the mechanisms by which transformational learning occurs and is successfully translated to influence in practice.

Originality/value

Previous research has expounded traditional leadership theories to guide the practice of health-care leadership development. The paper goes some way to demonstrate the impact of using the principles of TLT within health-care leadership development programmes. The approach taken by The Florence Nightingale Foundation has the potential to generate confident leaders who may be instrumental in creating positive changes across various clinical environments.

Details

Leadership in Health Services, vol. 37 no. 5
Type: Research Article
ISSN: 1751-1879

Keywords

Article
Publication date: 5 January 2024

Kevin Leung and Vincent Cho

Based on self-determination theory (SDT), this study aims to determine the motivation factors of reviewers writing long reviews in the anime industry.

Abstract

Purpose

Based on self-determination theory (SDT), this study aims to determine the motivation factors of reviewers writing long reviews in the anime industry.

Design/methodology/approach

This study analyzes 171,188 online review data collected from an online anime community (MyAnimeList.net).

Findings

The findings show that intensity of emotions, experience in writing reviews and helpful votes in past reviews are the most important factors and positively influence review length. The overall rating of the anime moderates the effects of some motivation factors. Moreover, reviewers commenting on their favorite or nonfavorite anime also have varied motivation factors. Furthermore, this study has addressed the p-value problem due to the large sample size.

Research limitations/implications

This study provides a comprehensive and theoretical understanding of reviewers' motivation for writing long reviews.

Practical implications

Online communities can incorporate the insights from this study into website design and motivate reviewers to write long reviews.

Originality/value

Many past studies have investigated what reviews are more helpful. Review length is the most important factor of review helpfulness and positively affects it. However, few studies have examined the determinants of review length. This study attempts to address this issue.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 15 January 2024

F.D. Ayegbusi and A.S. Idowu

The purpose of this study is to investigate the effects of entropy generation of some embedded thermophysical properties on heat and mass transfer of pulsatile flow of…

Abstract

Purpose

The purpose of this study is to investigate the effects of entropy generation of some embedded thermophysical properties on heat and mass transfer of pulsatile flow of non-Newtonian nanofluid flows between two porous parallel plates in the presence of Lorentz force are taken into account in this research.

Design/methodology/approach

The governing partial differential equations (PDEs) were nondimensionalized using suitable nondimensional quantities to transform the PDEs into a system of coupled nonlinear PDEs. The resulting equations are solved using the spectral relaxation method due to the effectiveness and accuracy of the method. The obtained velocity and temperature profiles are used to compute the entropy generation rate and Bejan number. The influence of various flow parameters on the velocity, temperature, entropy generation rate and Bejan number are discussed graphically.

Findings

The results indicate that the energy losses can be minimized in the system by choosing appropriate values for pertinent parameters; when thermal conductivity is increasing, this leads to the depreciation of entropy generation, and while this increment in thermal conductivity appreciates the Bejan number, the Eckert number on entropy generation and Bejan number, the graph shows that each time of increase in Eckert will lead to rising of entropy generation while this increase shows a reduction in Bejan number. To shed more light, these results were further demonstrated graphically. The current research was very well supported by prior literature works.

Originality/value

All results are presented graphically, and the results in this article are anticipated to be helpful in the area of engineering.

Details

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

Keywords

Open Access
Article
Publication date: 15 September 2023

Marissa Condon

The paper proposes an efficient and insightful approach for solving neutral delay differential equations (NDDE) with high-frequency inputs. This paper aims to overcome the need to…

Abstract

Purpose

The paper proposes an efficient and insightful approach for solving neutral delay differential equations (NDDE) with high-frequency inputs. This paper aims to overcome the need to use a very small time step when high frequencies are present. High-frequency signals abound in communication circuits when modulated signals are involved.

Design/methodology/approach

The method involves an asymptotic expansion of the solution and each term in the expansion can be determined either from NDDE without oscillatory inputs or recursive equations. Such an approach leads to an efficient algorithm with a performance that improves as the input frequency increases.

Findings

An example shall indicate the salient features of the method. Its improved performance shall be shown when the input frequency increases. The example is chosen as it is similar to that in literature concerned with partial element equivalent circuit (PEEC) circuits (Bellen et al., 1999). Its structure shall also be shown to enable insights into the behaviour of the system governed by the differential equation.

Originality/value

The method is novel in its application to NDDE as arises in engineering applications such as those involving PEEC circuits. In addition, the focus of the method is on a technique suitable for high-frequency signals.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 43 no. 1
Type: Research Article
ISSN: 0332-1649

Keywords

Open Access
Article
Publication date: 13 February 2024

Viktoriya Zipper-Weber and Andrea Mandik

The negative cultural bias vis-à-vis international business and cross-cultural management has been duly acknowledged, necessitating recommendations towards investigating its…

Abstract

Purpose

The negative cultural bias vis-à-vis international business and cross-cultural management has been duly acknowledged, necessitating recommendations towards investigating its positive effects. Methodologically, quantitative research clearly predominates, and there have been calls for alternative approaches. Thus, this conceptual paper addresses the research gap (methodological and thematic) by investigating if multicultural teams can be an essential part of the global workforce and whether positive effects exist regarding dynamic capabilities, learning and knowledge transfer.

Design/methodology/approach

The underlying ethnographic research design enabled exploring within the embedded single case study from an emic perspective, including qualitative observation and semi-structured expert interviews, and provided detailed insights into the company’s multicultural work environment.

Findings

The results reveal that applying a qualitative design allowed the needed exploration and show that multicultural, geographically dispersed teams are positively experienced and considered necessary in today’s globalised world. They are likely to increase in the future. Moreover, dynamic capabilities (multicultural competencies) are indispensable for multicultural teamwork. Regarding learning opportunities, different viewpoints for discussion and the ability to reflect on these offer valuable insights. In line with theory, multiculturality is considered a “two-edged sword”, providing simultaneous benefits and challenges. Contrary to the theory, even highly important information transfers can occur virtually, although occasional physical contact is essential for trust building.

Originality/value

The multinational family business offers a unique example of a positive relationship between multiculturalism and organisational excellence and demonstrates how the application of a qualitative methodology can support theory building by delivering a revised model of dynamic capabilities in multicultural environments with geographical dispersion.

Article
Publication date: 13 February 2024

Anastasia Romanova

The paper aims to provide an overview of the state-of-the-art of the event industry in the context of digitalization to understand how digital technologies change the event…

Abstract

Purpose

The paper aims to provide an overview of the state-of-the-art of the event industry in the context of digitalization to understand how digital technologies change the event industry and what research topics are the most promising for further exploration.

Design/methodology/approach

A bibliometric analysis of the existing body of knowledge on the topic was conducted and the results were visualized using CiteSpace 5.8.R3. A total of 1999 articles and proceeding papers from the Web of Science Core Collection published between 2007 and 2022 were selected for our analysis. Based on the articles and proceeding papers in the Web of Science Core Collection database, we selected a set of publications for our analysis. The data were obtained through specific keywords related to our research topic. The method involves a process of three main stages: data collection, data processing and the bibliometric analysis.

Findings

Co-citation analysis indicated that issues of crowd management and tracking human mobility during mass events are important for the event industry and that technologies such as the Internet of Things, special-purpose mobile applications and systems make it easier for an event organizer to handle the issues. The findings demonstrated a weak scientific collaboration between countries in the topic studied and shift of research hotspots to study of satisfaction, motivation and behavioral patterns of events attendees. Based on this analysis, three directions for future research were revealed.

Research limitations/implications

The results should be interpreted in light of our sample, because the analysis was conducted within our sample which has boundaries. We collected data from all categories in the Web of Science Core Collection database, but we considered only articles and proceeding papers as opposed to all possible types of scientific publications and other databases. In the study, we focused on detecting the state-of-the-art of the event industry in the context of digitalization overall. More specific topics that could be analyzed remain, for example, the dependency of digital technologies from the event type, etc.

Practical implications

This study reflects the state-of-the-art of the event industry in the context of digitalization. It provides researchers with key developmental trends in the event industry, which assists them in more deeply understanding the evolution of research hotspots in the field during last 15 years and defining future research agenda. The paper presents an overview of digital technologies used in various types of events and describes the issues and results related to the implementing digital technologies. The results obtained were extremely important, as they can be used by event managers and organizers to enhance customers’ experience during the events.

Originality/value

This study reflects the state-of-the-art of the event industry in the context of digitalization. This is the first attempt to make an overall analysis of scientific papers published in the Web of Science Core Collection on the topic studied without excluding any categories. The search procedure is transparent, and the results can be reproduced in other search fields using the same approach. Based on this analysis, three directions for future research were revealed including technological aspects of online event-based social networks, issues of crowd management and security at mass events and issues of attendees’ acceptance of novel digital technologies.

Details

EuroMed Journal of Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1450-2194

Keywords

Article
Publication date: 4 January 2024

Zicheng Zhang

Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent…

Abstract

Purpose

Advanced big data analysis and machine learning methods are concurrently used to unleash the value of the data generated by government hotline and help devise intelligent applications including automated process management, standard construction and more accurate dispatched orders to build high-quality government service platforms as more widely data-driven methods are in the process.

Design/methodology/approach

In this study, based on the influence of the record specifications of texts related to work orders generated by the government hotline, machine learning tools are implemented and compared to optimize classify dispatching tasks by performing exploratory studies on the hotline work order text, including linguistics analysis of text feature processing, new word discovery, text clustering and text classification.

Findings

The complexity of the content of the work order is reduced by applying more standardized writing specifications based on combining text grammar numerical features. So, order dispatch success prediction accuracy rate reaches 89.6 per cent after running the LSTM model.

Originality/value

The proposed method can help improve the current dispatching processes run by the government hotline, better guide staff to standardize the writing format of work orders, improve the accuracy of order dispatching and provide innovative support to the current mechanism.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

1 – 10 of 38