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Manufacturing processes, such as laminations, may introduce uncertainties in the magnetic properties of materials used in electrical machines. This issue, together with magnetization errors, can cause serious deterioration in the performance of the machines. Hence, stochastic material models are required for the study of the influences of the material uncertainties. The purpose of this paper is to present a methodology to study the impact of magnetization pattern uncertainties in permanent magnet electric machines.

The impacts of material uncertainties on the performances of an interior permanent magnet (IPM) machine were analyzed using two different robustness metrics (worst-case analysis and statistical study). In addition, two different robust design formulations were applied to robust multi-objective machine design problems.

The computational analyses show that material uncertainties may result in deviations of the machine performances and cause nominal solutions to become non-robust.

In this paper, the authors present stochastic models for the quantification of uncertainties in both ferromagnetic and permanent magnet materials. A robust multi-objective evolutionary algorithm is demonstrated and successfully applied to the robust design optimization of an IPM machine considering manufacturing errors and operational condition changes.

This paper aims to propose a numerical methodology to reduce the number of computations required to optimally design the rotors of synchronous reluctance machines (SynRMs) with multiple barriers.

Two objectives, average torque and torque ripple, have been simulated for thousands of SynRM models using 2D finite element analysis. Different rotor topologies (i.e. number of flux barriers) were statistically analyzed to find their respective design correlation for high average torque solutions. From this information, optimal geometrical constraints were then found to restrict the design space of multiple-barrier rotors.

Statistical analysis of two considered SynRM case studies demonstrated a design similarity between the different number of flux barriers. Upon setting the optimal geometrical constraints, it was observed that the design space of multiple-barrier rotors reduced by more than 56 per cent for both models.

Using the proposed methodology, optimal geometrical constraints of a multiple-barrier SynRM rotor can be found to restrict its corresponding design space. This approach can handle the curse of dimensionality when the number of geometric parameters increases. Also, it can potentially reduce the number of initial samples required prior to a multi-objective optimization.

This paper aims to propose a data-driven approach to determine the design guidelines for low-frequency electromagnetic devices.

Two different devices, a core-type single-phase transformer and a motor-drive system, are used to show the usefulness and generalizability of the proposed approach. Using a finite element solver, a large database of design possibilities is created by varying design parameters, i.e. the geometrical and control parameters of the systems. Design rules are then extracted by performing a statistical analysis and exploring optimal and sub-optimal designs considering various targets such as efficiency, torque ripple and power factor.

It is demonstrated that the correlation of the design parameters influences the way the data-driven approach must be made. Also, guidelines for defining new design constraints, which can lead to a more efficient optimization routine, are introduced for both case studies.

Using the proposed approach, new design guidelines, which are generally not obtainable by the classical design methods, are introduced. Also, the proposed approach can potentially deal with different parameter–objective correlations, as well as different number of connected systems. This approach is applicable regardless of the device type.

The purpose of this paper is to carry out a numerical study on the dynamic and thermal behavior of a fluid with a constant property and flowing turbulently through a two-dimensional horizontal rectangular channel. The upper surface was put in a constant temperature condition, while the lower one was thermally insulated. Two transverse, solid-type obstacles, having different shapes, i.e. flat rectangular and V-shaped, were inserted into the channel and fixed to the top and bottom walls of the channel, in a periodically staggered manner to force vortices to improve the mixing, and consequently the heat transfer. The flat rectangular obstacle was put in the first position and was placed on the hot top wall of the channel. However, the second V-shaped obstacle was placed on the insulated bottom wall, at an attack angle of 45°; its position was varied to find the optimum configuration for optimal heat transfer.

The fluid is considered Newtonian, incompressible with constant properties. The Reynolds averaged Navier–Stokes equations, along with the standard k-epsilon turbulence model and the energy equation, are used to control the channel flow model. The finite volume method is used to integrate all the equations in two-dimensions; the commercial CFD software FLUENT along with the SIMPLE-algorithm is used for pressure-velocity coupling. Various values of the Reynolds number and obstacle spacing were selected to perform the numerical runs, using air as the working medium.

The channel containing the flat fin and the 45° V-shaped baffle with a large Reynolds number gave higher heat transfer and friction loss than the one with a smaller Reynolds number. Also, short separation distances between obstacles provided higher values of the ratios Nu/Nu₀ and f/f₀ and a larger thermal enhancement factor (TEF) than do larger distances.

This is an original work, as it uses a novel method for the improvement of heat transfer in completely new flow geometry.

The mobile payment system has changed payment patterns and has the potential to improve people’s quality of life and increase the bank’s efficiency. In return, the risks and trust factors inevitably led to increased challenges and become a major concern in the adoption of mobile payment service. Yet, little is known about how risk and trust factors can affect the adoption of mobile payment. Hence, this paper aims to come into contact to solve these issues in the context.

A comprehensive research model that reflects the customer satisfaction and loyalty to the adoption of mobile payment services is developed and empirically tested using exploratory and confirmatory factor analysis and structural equation modeling.

Findings reveal that the perceived risk has a significant negative impact on perceived trust and customer satisfaction. Perceived trust is the most important variable in building customer satisfaction, and customer satisfaction is the reasonable predictor of customer loyalty. In addition, gender differences moderate the adoption of the mobile payment service.

The results of the study hold several implications for scholars in the field of technology adoption on financial transactions and offer valuable managerial insights to design their mobile payment adoption strategies to pursue greater acceptance and diffusion of this new payment system.

The design of electromagnetic systems for a variety of applications such as induction heating, electrical machines, actuators and transformers requires the solution of a multi-physics problem often involving thermal, structural and mechanical coupling to the electromagnetic system. This results in a complex analysis system embedded within an optimization process. The appearance of high-performance computing systems over the past few years has made coupled simulations feasible for the design engineer. When coupled with surrogate modelling techniques, it is possible to significantly reduce the wall clock time for generating a complete design while including the impact of the multi-physics performance on the device.

An architecture is proposed for linking multiple singe physics analysis tools through the material models and a controller which schedules the execution of the various software tools. The combination of tools is implemented on a series of computational nodes operating in parallel and creating a “super node” cluster within a collection of interconnected processors.

The proposed architecture and job scheduling system can allow a parallel exploration of the design space for a device.

The originality of the work derives from the organization of the parallel computing system into a series of “super nodes” and the creation of a materials database suitable for multi-physics interactions.

The aim of this study was to compare the defined indicators of tuberculosis (TB) control program in the intervention and control prisons, after implementation of the national clinical protocol for TB and HIV management in Iranian prisons, suggesting active health service provision in all steps of service provision.

This was quasi-experimental study conducted among inmates of two prisons in Iran. Great Tehran prison was purposively chosen as the intervention prison and Karaj prison was purposively chosen as control prison as well. Intervention and control prisons were compared in terms of the TB indicators within three periods (before intervention, during implementation and follow-up period) from October 2013 to June 2014.

Number of inmates with TB symptoms who underwent TB workup was four times more in intervention prison compared to control prison (9.3 vs 2.5 cases out of 1,000 inmates per month in the case prison compared to the control prison). Such difference was also significant in the intervention prison, comparing before and during the intervention period. The patient finding in case prison increased significantly after the intervention (223.6 vs 81.8 cases out of 100,000 inmates per year). The number of TB cases who received HIV testing increased from 50 to 100%.

Active health service provision has significantly improved indicators in the intervention prison. The authors recommend implementation of this guideline in all prisons of Iran. Integration of other diseases with high burden among prisoners is also recommended in the active health services provision.

Acoustic noise is a crucial performance index in the design of electrical machines. Due to the challenges associated with modelling a complete motor, the stator is often used to estimate the sound power in the prototyping stage. While this approach greatly reduces lengthy simulations, the actual sound power of the motor may not be known. But, from the acoustic noise standpoint, not much is known about the correlation between the stator and complete motor. This paper, therefore, aims to use the sound pressure levels of the stator and the full motor to investigate the existence of correlations in the interior permanent magnet synchronous motor.

A multiphysics simulation framework is proposed to evaluate the sound pressure levels of multiple motor geometries in a given design space. Then, a statistical analysis is performed on the calculated sound pressure levels of each geometry over a selected speed range to compare the correlation strength between the stator and the full model.

It was established that the stator and the complete motor model are moderately correlated. As such, a reliance on the stator sound power for design and optimization routines could yield inaccurate results.

The main contribution involves the use of statistical tools to study the relationship between sound pressure levels associated with the stator geometry and the complete electric motor by increasing the motor sample size to capture subtle acoustic correlation trends in the design space of the interior permanent magnet synchronous motor.

The purpose of this study is to investigate the factors that affect students’ behavioral intentions to use virtual classrooms at Princess Sumaya University for Technology (PSUT) in Jordan.

A quantitative research approach was adopted, an online survey method was used and the data were collected among students at PSUT in Jordan. A total of 511 responses were usable for analysis. A structural equation modeling partial least squares technique was used to examine the hypothesized model.

The findings reveal that the proposed factors have direct and indirect relationships with behavioral intentions to use virtual classrooms. They show that students’ satisfaction has a direct influence on behavioral intention, while other variables such as instructor characteristics, virtual classroom quality, perceived self-efficacy, perceived organizational support, perceived ease of use and perceived usefulness have an indirect effect on behavioral intentions to use virtual classrooms.

The study was conducted at PSUT in Jordan, which could limit the generalizability of the findings. Furthermore, the present study measured students’ behavioral intentions to use virtual classrooms and future research should consider the actual use of virtual classrooms.

The findings of this study offer significant and useful information to policymakers, instructors, developers and students regarding the use of virtual classrooms in universities. Based on students’ needs and readiness, the findings identify which factors to consider when developing an e-learning system to enhance learning and teaching performance.

This study extends existing knowledge by developing a conceptual model to identify the key factors of virtual classroom adoption in higher education institutions in Arab countries. This study contributes to the literature in the context of e-learning by validating an extended technology acceptance model from an Arab countries perspective and considering the differences in culture, learning style and physical environment compared to developed countries.

This study aims to explore the relationships among destination brand equity, brand authenticity and revisit intention. The mediating role of tourist satisfaction and the moderating role of destination familiarity in these relationships are also investigated.

Based on the stimulus–organism–response theory, a structural equation model was constructed to test the relationships among the study variables. The original data was obtained using a questionnaire survey method from domestic tourists who have traveled to Guilin in China.

The findings revealed that brand equity and brand authenticity not only positively and directly affect revisit intention but also have an indirect influence on revisit intention through the mediating role of tourist satisfaction. Destination familiarity positively moderates the direct influence of brand equity on revisit intention. Furthermore, brand authenticity significantly and positively affects brand equity.

The findings of this study provide a certain enlightenment for brand marketing and tourist destination management.

This study reveals the impact path of brand equity and brand authenticity on revisit intention, compensating for the lack of attention on impact mechanism among them. This study proves the impact of brand authenticity on destination brand equity. This compensates for the deficiencies that ignore possible antecedents affecting destination brand equity and the impact of brand authenticity on brand equity in the context of tourism destination. This study also confirms the specific dimensions of brand equity and brand authenticity in the context of Chinese tourism destinations in response to the current controversy.

旅游目的地品牌资产、品牌真实性与重游意愿: 游客满意度的中介作用与目的地熟悉度的调节作用

摘要

本研究致力于探究旅游目的地品牌资产、品牌真实性与重游意愿之间的关系。本文也研究了游客满意度在这些关系中所起的中介作用以及目的地熟悉度的调节作用。

本文以刺激-机体-反应理论为基础, 通过构建结构方程模型来对变量之间的关系进行检验。原始数据是通过问卷调查法从曾在桂林旅游的国内游客中获得。

目的地品牌资产和品牌真实性在直接正向影响重游意愿的同时, 还通过游客满意度的中介作用来间接影响重游意愿。目的地熟悉度在品牌资产对重游意愿的直接影响中起着正向调节作用。此外, 目的地品牌真实性对品牌资产起着显著正向影响。

本研究揭示了目的地品牌资产与品牌真实性对重游意愿的影响路径, 弥补了对其中影响机制关注不足的缺陷。本研究证实了旅游目的地背景下品牌真实性对品牌资产的具体影响, 弥补了现有文献较少关注影响目的地品牌资产的可能前因以及旅游目的地背景下品牌真实性对品牌资产具体影响的不足。此外, 本研究以中国旅游目的地为研究背景, 证实了品牌资产与品牌真实性的具体维度, 回应了当前的争议。

本研究结论对旅游目的地品牌营销与管理提供一定的启示。

Valor de marca de destino turístico, autenticidad de marca y voluntad de volver a visitar：El papel mediador de la satisfacción del turista y el papel moderador de la familiaridad con el destino

Resumen

este estudio tiene como objetivo explorar las relaciones entre el valor de la marca de destino, la autenticidad de la marca y la intención de volver a visitar. También se investiga el papel mediador de la satisfacción del turista y el papel moderador de la familiaridad con el destino en estas relaciones.

con base en la teoría Estímulo-Organismo-Respuesta, se construye un modelo de ecuación estructural para probar las relaciones entre las variables de investigación. Los datos originales se obtienen mediante el método de encuesta por cuestionario de turistas nacionales que han viajado a Guilin en China.

los hallazgos revelaron que el valor y la autenticidad de la marca no solo afectan positiva y directamente la intención de volver a visitar, sino que también tienen una influencia indirecta en la intención de volver a visitar a través del papel mediador de la satisfacción del turista. La familiaridad con el destino modera positivamente la influencia directa del valor de la marca en la intención de volver a visitar. Además, la autenticidad de la marca afecta de manera significativa y positiva al valor de la marca.

este documento revela el camino del impacto del valor de marca y la autenticidad de la marca en la intención de volver a visitar, compensando la falta de atención al mecanismo de impacto entre ellos. Este trabajo demuestra el efecto de la autenticidad de la marca en el valor de la marca del destino, que compensa las deficiencias que ignoran los posibles antecedentes que afectan el valor de la marca del destino y el impacto de la autenticidad de la marca en el valor de la marca en el contexto del destino turístico. Este estudio también confirma las dimensiones específicas del valor de marca y la autenticidad de la marca en el contexto del destino turístico chino, respondiendo a la controversia actual.

los hallazgos de este documento proporcionan cierta iluminación para el marketing de marca y la gestión de destinos turísticos.