Search results for: Permanent Analytics Process

Authors: C. Ardil

Abstract:

In this paper, a new MCDMA approach, the permanent analytics process is proposed to assess the immovable valuation criteria and their significance in the placement of the healthcare facility. Five decision factors are considered for the value and selection of immovables. In the multiple factor selection problems, the priority vector of the criteria used to compare several immovables is first determined using the permanent analytics method, a mathematical model for the multiple criteria decisionmaking process. Then, to demonstrate the viability and efficacy of the suggested approach, twenty potential candidate locations were evaluated using the hospital site selection problem's decision criteria. The ranking accuracy of estimation was evaluated using composite programming, which took into account both the permanent analytics process and the weighted multiplicative model. 

Keywords: Hospital Facility Location Selection, Permanent Analytics Process, Multiple Criteria Decision Making (MCDM)

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Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision making, management and planning of healthcare and related activities. However, user resistances, unique position of medical data content and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. Success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose a HA process model with features from rational unified process (RUP) model and agile methodology.

Keywords: Agile methodology, health analytics, unified process model, UML.

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Authors: Khaled Halimi, Hassina Seridi-Bouchelaghem

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The purpose of this paper is to describe how learning analytics approaches based on social semantic web techniques can be applied to enhance the lifelong learning experiences in a connectivist perspective. For this reason, a prototype of a system called SoLearn (Social Learning Environment) that supports this approach. We observed and studied literature related to lifelong learning systems, social semantic web and ontologies, connectivism theory, learning analytics approaches and reviewed implemented systems based on these fields to extract and draw conclusions about necessary features for enhancing the lifelong learning process. The semantic analytics of learning can be used for viewing, studying and analysing the massive data generated by learners, which helps them to understand through recommendations, charts and figures their learning and behaviour, and to detect where they have weaknesses or limitations. This paper emphasises that implementing a learning analytics approach based on social semantic web representations can enhance the learning process. From one hand, the analysis process leverages the meaning expressed by semantics presented in the ontology (relationships between concepts). From the other hand, the analysis process exploits the discovery of new knowledge by means of inferring mechanism of the semantic web.

Keywords: Connectivism, data visualization, informal learning, learning analytics, semantic web, social web.

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Authors: Z. Tasir, S. N. Kew, D. West, Z. Abdullah, D. Toohey

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Research on Learning Analytics is progressively developing in the higher education field by concentrating on the process of students' learning. Therefore, a research project between Malaysian and Australian Universities was initiated in 2015 to look at the use of Learning Analytics to support the development of teaching practice. The focal point of this article is to discuss and share the experiences of Malaysian and Australian universities in the process of developing the collaborative research on Learning Analytics. Three aspects of this will be discussed: 1) Establishing an international research project and team members, 2) cross-cultural understandings, and 3) ways of working in relation to the practicalities of the project. This article is intended to benefit other researchers by highlighting the challenges as well as the strategies used in this project to ensure such collaborative research succeeds.

Keywords: Academic research project, collaborative research, cross-cultural understanding, international research project.

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Authors: Lee P. Leon, Raymond Charles

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This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: Aggregate angularity, asphalt concrete, permanent deformation, rutting prediction.

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Authors: S. Vidhya, S. Sarumathi, N. Shanthi

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Over the past era, there have been a lot of efforts and studies are carried out in growing proficient tools for performing various tasks in big data. Recently big data have gotten a lot of publicity for their good reasons. Due to the large and complex collection of datasets it is difficult to process on traditional data processing applications. This concern turns to be further mandatory for producing various tools in big data. Moreover, the main aim of big data analytics is to utilize the advanced analytic techniques besides very huge, different datasets which contain diverse sizes from terabytes to zettabytes and diverse types such as structured or unstructured and batch or streaming. Big data is useful for data sets where their size or type is away from the capability of traditional relational databases for capturing, managing and processing the data with low-latency. Thus the out coming challenges tend to the occurrence of powerful big data tools. In this survey, a various collection of big data tools are illustrated and also compared with the salient features.

Keywords: Big data, Big data analytics, Business analytics, Data analysis, Data visualization, Data discovery.

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Authors: Linnea Stenliden

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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors within Actor-network theory (ANT). The learning conditions are found to be distinguished by broad complexity, characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: Analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation.

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: Analytics, Big Data in Education, Hadoop, Learning Analytics.

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Authors: Evisa Mitrou, Nicholas Tsitsianis, Supriya Shinde

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In the age of digitisation and globalisation, businesses have shifted online and are investing in big data analytics (BDA) to respond to changing market conditions and sustain their performance. Our study shifts the focus from the adoption of BDA to the impact of BDA on financial performance. We explore the financial performance of both BDA-vendors (business-to-business) and BDA-clients (business-to-customer). We distinguish between the five BDA-technologies (big-data-as-a-service (BDaaS), descriptive, diagnostic, predictive, and prescriptive analytics) and discuss them individually. Further, we use four perspectives (internal business process, learning and growth, customer, and finance) and discuss the significance of how each of the five BDA-technologies affect the performance measures of these four perspectives. We also present the analysis of employee engagement, average turnover, average net income, and average net assets for BDA-clients and BDA-vendors. Our study also explores the effect of the COVID-19 pandemic on business continuity for both BDA-vendors and BDA-clients.

Keywords: BDA-clients, BDA-vendors, big data analytics, financial performance.

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Authors: Arash Hassanpour Isfahani, Siavash Sadeghi

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Permanent magnet synchronous machines are known as a good candidate for hybrid electric vehicles due to their unique merits. However they have two major drawbacks i.e. high cost and small speed range. In this paper an optimal design of a permanent magnet machine is presented. A reduction of permanent magnet material for a constant torque and an extension in speed and torque ranges are chosen as the optimization aims. For this purpose the analytical model of the permanent magnet synchronous machine is derived and the appropriate design algorithm is devised. The genetic algorithm is then employed to optimize some machine specifications. Finally the finite element method is used to validate the designed machine.

Keywords: Design, Finite Element, Hybrid electric vehicle, Optimization, Permanent magnet synchronous machine.

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Authors: Ramakrishnan Ramanathan, Yanqing Duan, Guangming Cao, Elaine Philpott

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We discuss a theoretical conceptual framework to help understand how the new business analytics technologies have diffused in firms. We draw on three theoretical perspectives for this purpose. They are innovation diffusion theory, IT Business Value and the technology-organization-environment theory. We develop a conceptual framework that helps understand the interlinkages among factors affecting diffusion of business analytics and its impact on performance.

Keywords: Innovation diffusion, IT-Business Value, Technology-Organization-Environment, Business Analytics, Business performance

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Authors: Ayodeji Adesina, Derek Molloy

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Traditional higher-education classrooms allow lecturers to observe students- behaviours and responses to a particular pedagogy during learning in a way that can influence changes to the pedagogical approach. Within current e-learning systems it is difficult to perform continuous analysis of the cohort-s behavioural tendency, making real-time pedagogical decisions difficult. This paper presents a Virtual Learning Process Environment (VLPE) based on the Business Process Management (BPM) conceptual framework. Within the VLPE, course designers can model various education pedagogies in the form of learning process workflows using an intuitive flow diagram interface. These diagrams are used to visually track the learning progresses of a cohort of students. This helps assess the effectiveness of the chosen pedagogy, providing the information required to improve course design. A case scenario of a cohort of students is presented and quantitative statistical analysis of their learning process performance is gathered and displayed in realtime using dashboards.

Keywords: Business process management, cohort analytics, learning processes, virtual learning environment.

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Authors: Tayfun Gundogdu, Guven Komurgoz

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This paper presents design, analysis and comparison of the different rotor type permanent magnet machines. The presented machines are designed as having same geometrical dimensions and same materials for comparison. The main machine parameters of interior and exterior rotor type machines including eddy current effect, torque-speed characteristics and magnetic analysis are investigated using MAXWELL program. With this program, the components of the permanent magnet machines can be calculated with high accuracy. Six types of Permanent machines are compared with respect to their topology, size, magnetic field, air gap flux, voltage, torque, loss and efficiency. The analysis results demonstrate the effectiveness of the proposed machines design methodology. We believe that, this study will be a helpful resource in terms of examination and comparison of the basic structure and magnetic features of the PM (Permanent magnet) machines which have different rotor structure.

Keywords: Motor design, Permanent Magnet, Finite-Elementmethod.

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Authors: Wuttigrai Ngamsirijit

Abstract:

Talent management in today’s modern organizations has become data-driven due to a demand for objective human resource decision making and development of analytics technologies. HR managers have been faced with some obstacles in exploiting data and information to obtain their effective talent management decisions. These include process-based data and records; insufficient human capital-related measures and metrics; lack of capabilities in data modeling in strategic manners; and, time consuming to add up numbers and make decisions. This paper proposes a framework of talent management through integration of talent value chain and human capital analytics approaches. It encompasses key data, measures, and metrics regarding strategic talent management decisions along the organizational and talent value chain. Moreover, specific predictive and prescriptive models incorporating these data and information are recommended to help managers in understanding the state of talent, gaps in managing talent and the organization, and the ways to develop optimized talent strategies.    

Keywords: Decision making, human capital analytics, talent management, talent value chain.

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Authors: Andi Pawawoi, Syafii

Abstract:

Instantaneous electromagnetic torque of simple reflectance generator can be positive at a time and negative at other time. It is utilized to design a permanent magnet reluctance generator specifically. Generator is designed by combining two simple reluctance generators, consists of two rotors mounted on the same shaft, two output-windings and a field source of the permanent magnet. By this design, the electromagnetic torque on both rotor will be eliminated each other, so the input torque generator can be smaller. Rotor is expected only to regulate the flux flow to both output windings alternately, until the magnetic energy is converted into electrical energy, such as occurs in the transformer energy conversion. ​​The prototype trials have been made to test this design. The test result show that the new design of permanent magnets reluctance generator able to convert energy from permanent magnets into electrical energy, this is proven by the existence 167% power output compared to the shaft input power.

Keywords: Energy, Magnet permanent, Reluctance generator.

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Authors: Jeong-Min Jo, Young-Jae Han, Chang-Young Lee

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Attracting ferromagnetic forces between magnet and reaction rail provide the supporting force in Electromagnetic Suspension. Miniature maglev using permanent magnets and electromagnets is based on the idea to generate the nominal magnetic force by permanent magnets and superimpose the variable magnetic field required for stabilization by currents flowing through control windings in electromagnets. Permanent magnets with a high energy density have lower power losses with regard to supporting force and magnet weight. So the advantage of the maglev using electromagnets and permanent magnets is partially reduced by the power required to feed the remaining onboard supply system so that the overall onboard power is diminished as compared to that of the electromagnet. In this paper we proposed the how to design and control the miniature maglev and confirmed the feasibility of the levitation system using electromagnets and permanent magnets through the manufacturing the miniature maglev

Keywords: Magnetic Levitation system, Maglev, Permanent Magnets, Hybrid Magnet.

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Authors: N. Yogal, C. Lehrmann

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The use of permanent magnets (PM) is increasing in permanent magnet synchronous machines (PMSM) to fulfill the requirements of high efficiency machines in modern industry. PMSM are widely used in industrial applications, wind power plants and the automotive industry. Since PMSM are used in different environmental conditions, the long-term effect of NdFeB-based magnets at high temperatures and their corrosion behavior have to be studied due to the irreversible loss of magnetic properties. In this paper, the effect of magnetic properties due to corrosion and increasing temperature in a climatic chamber has been presented. The magnetic moment and magnetic field of the magnets were studied experimentally.

Keywords: Permanent magnets (PM), NdFeB, corrosion behavior, temperature effect, permanent magnet synchronous machine (PMSM).

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Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Moses Noel Dogonyaro

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This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.

Keywords: Data Analytics, Security, Privacy, Bootstrapping, and Fully Homomorphic Encryption Scheme.

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Authors: Ye Wang, Ickjai Lee

Abstract:

Due to the widespread of mobile sensing, there is a strong need to handle trails of moving objects, and trajectories. This paper proposes three visual analytics approaches for higher order information of trajectory datasets based on the higher order Voronoi diagram data structure. Proposed approaches reveal geometrical, topological, and directional information. Experimental resultsdemonstrate the applicability and usefulness of proposed three approaches.

Keywords: Visual Analytics, Higher Order Information, Trajectory Datasets, Spatio-temporal data.

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Authors: Yusuf Yasa, Erkan Mese

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This paper investigates the thermal issue of permanent magnet synchronous generator which is frequently used in direct drive gearless small-scale wind turbine applications. Permanent Magnet Synchronous Generator (PMSG) is designed with 2.5 kW continuous and 6 kW peak power. Then considering generator geometry, mechanical design of wind turbine is performed. Thermal analysis and optimization is carried out considering all wind turbine components to reach realistic results. This issue is extremely important in research and development (R&D) process for wind turbine applications.

Keywords: Direct drive, gearless wind turbine, permanent magnet synchronous generator (PMSG), small-scale wind turbine, thermal management.

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Authors: M. Barański

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This article presents a new vibration diagnostic method designed to (PM) machines with permanent magnets. Those devices are commonly used in small wind and water systems or vehicles drives. The author’s method is very innovative and unique. Specific structural properties of PM machines are used in this method - electromotive force (EMF) generated due to vibrations. There was analysed number of publications which describe vibration diagnostic methods and tests of electrical PM machines and there was no method found to determine the technical condition of such machine basing on their own signals. In this article will be discussed: the method genesis, the similarity of machines with permanent magnet to vibration sensor and simulation and laboratory tests results. The method of determination the technical condition of electrical machine with permanent magnets basing on its own signals is the subject of patent application and it is the main thesis of author’s doctoral dissertation.

Keywords: Electrical vehicle, generator, permanent magnet, traction drive, vibrations.

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Authors: Malika.D Kedir-Talha, Mohamed Mehenni

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In order to be able to automatically differentiate between two modes of permanent flow of a liquid simulating blood, it was imperative to put together a data bank. Thus, the acquisition of the various amplitude spectra of the Doppler signal of this liquid in laminar flow and other spectra in turbulent flow enabled us to establish an automatic difference between the two modes. According to the number of parameters and their nature, a comparative study allowed us to choose the best classifier.

Keywords: Doppler spectrum, flow mode, pattern recognition, permanent flow.

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Authors: Petter Eklund, Jonathan Sjölund, Sandra Eriksson, Mats Leijon

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The spoke type rotor can be used to obtain magnetic flux concentration in permanent magnet machines. This allows the air gap magnetic flux density to exceed the remanent flux density of the permanent magnets but gives problems with leakage fluxes in the magnetic circuit. The end leakage flux of one spoke type permanent magnet rotor design is studied through measurements and finite element simulations. The measurements are performed in the end regions of a 12 kW prototype generator for a vertical axis wind turbine. The simulations are made using three dimensional finite elements to calculate the magnetic field distribution in the end regions of the machine. Also two dimensional finite element simulations are performed and the impact of the two dimensional approximation is studied. It is found that the magnetic leakage flux in the end regions of the machine is equal to about 20% of the flux in the permanent magnets. The overestimation of the performance by the two dimensional approximation is quantified and a curve-fitted expression for its behavior is suggested.

Keywords: End effects, end leakage flux, permanent magnet machine, spoke type rotor.

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Authors: K. Allaw, J. Adjizian Gerard, M. Chehayeb, A. Raad, W. Fahs, A. Badran, A. Fakherdin, H. Madi, N. Badaro Saliba

Abstract:

Population estimation using Geographic Information System (GIS) and remote sensing faces many obstacles such as the determination of permanent residents. A permanent resident is an individual who stays and works during all four seasons in his village. So, all those who move towards other cities or villages are excluded from this category. The aim of this study is to identify the factors affecting the percentage of permanent residents in a village and to determine the attributed weight to each factor. To do so, six factors have been chosen (slope, precipitation, temperature, number of services, time to Central Business District (CBD) and the proximity to conflict zones) and each one of those factors has been evaluated using one of the following data: the contour lines map of 50 m, the precipitation map, four temperature maps and data collected through surveys. The weighting procedure has been done using decision tree method. As a result of this procedure, temperature (50.8%) and percentage of precipitation (46.5%) are the most influencing factors.

Keywords: Remote sensing and GIS, permanent residence, decision tree, Lebanon.

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Authors: Abdolamir Nekoubin

Abstract:

The line start permanent magnet motor (LSPMM) combines a permanent magnet rotor for a better motor efficiency during synchronous running with an induction motor squirrel cage rotor to permit the motor starting by direct coupling to power source. In this paper effect of the rotor structure on a line start synchronous permanent magnet motor (LSPMM) is analyzed. LSPMM motor with three different structures for rotor is designed by using RMxprt software; efficiency and line current of LSPMM motor for different structures in full-load condition have been presented. The results indicate that with correct choosing of rotor structure, maximum efficiency can be found.

Keywords: Permanent magnets, LSPMM motor, rotor.

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Authors: P. Pistelok

Abstract:

The article presents the concept of an electromagnetic circuit generator with permanent magnets mounted on the surface rotor core designed for single phase work. Computation field-circuit model was shown. The spectrum of time course of voltages in the idle work was presented. The cross section with graphically presentation of magnetic induction in particular parts of electromagnetic circuits was presented. Distribution of magnetic induction at the rated load point for each phase was shown. The time course of voltages and currents for each phases for rated power were displayed. An analysis of laboratory results and measurement of load characteristics of the generator was discussed. The work deals with three electromagnetic circuits of generators with permanent magnet where output voltage characteristics versus rated power were expressed.

Keywords: Permanent magnet generator, permanent magnets, vibration, course of torque, single phase work, asymmetrical three phase work.

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Authors: Hadi Aghazadeh, Seyed Ebrahim Afjei, Alireza Siadatan

Abstract:

In this paper, a proper approach is taken to assess a set of the most effective rotor design parameters for an external-rotor permanent magnet assisted synchronous reluctance motor (PMaSynRM) and therefore to tackle the design complexity of the rotor structure. There are different advantages for introducing permanent magnets into the rotor flux barriers, some of which are to saturate the rotor iron ribs, to increase the motor torque density and to improve the power factor. Moreover, the d-axis and q-axis inductances are of great importance to simultaneously achieve maximum developed torque and low torque ripple. Therefore, sensitivity analysis of the rotor geometry of an 8-pole external-rotor permanent magnet assisted synchronous reluctance motor is performed. Several magnetically accurate finite element analyses (FEA) are conducted to characterize the electromagnetic performance of the motor. The analyses validate torque and power factor equations for the proposed external-rotor motor. Based upon the obtained results and due to an additional term, permanent magnet torque, added to the reluctance torque, the electromagnetic torque of the PMaSynRM increases.

Keywords: Permanent magnet assisted synchronous reluctance motor, flux barrier, flux carrier, electromagnetic torque, and power factor.

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Authors: O. J. G. Somsen, G. P. M. Wagemakers

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Magnetic signature detection provides sensitive detection of metal objects, especially in the natural environment. Our group is developing a tabletop setup for magnetic signatures of various small and model objects. A particular issue is the separation of permanent and induced magnetization. While the latter depends only on the composition and shape of the object, the former also depends on the magnetization history. With common deperming techniques, a significant permanent signature may still remain, which confuses measurements of the induced component. We investigate a basic technique of separating the two. Measurements were done by moving the object along an aluminum rail while the three field components are recorded by a detector attached near the center. This is done first with the rail parallel to the Earth magnetic field and then with anti-parallel orientation. The reversal changes the sign of the induced- but not the permanent magnetization so that the two can be separated. Our preliminary results on a small iron block show excellent reproducibility. A considerable permanent magnetization was indeed present, resulting in a complex asymmetric signature. After separation, a much more symmetric induced signature was obtained that can be studied in detail and compared with theoretical calculations.

Keywords: Magnetic signature, data analysis, magnetization, deperming techniques.

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Authors: Airoldi G., Bumby J. R., Dominy C., G.L. Ingram, Lim C. H., Mahkamov K., N. L. Brown, A. Mebarki, M. Shanel

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Axial Flux Permanent Magnet (AFPM) Machines require effective cooling due to their high power density. The detrimental effects of overheating such as degradation of the insulation materials, magnets demagnetization, and increase of Joule losses are well known. This paper describes the CFD simulations performed on a test rig model of an air cooled Axial Flux Permanent Magnet (AFPM) generator built at Durham University to identify the temperatures and heat transfer coefficient on the stator. The Reynolds Averaged Navier-Stokes and the Energy equations are solved and the flow pattern and heat transfer developing inside the machine are described. The Nusselt number on the stator surfaces has been found. The dependency of the heat transfer on the flow field is described temperature field obtained. Tests on an experimental are undergoing in order to validate the CFD results.

Keywords: Axial flux permanent magnet machines, thermal modeling, CFD.

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Authors: R. Clancy, M. Ahern, D. O’Sullivan, K. Bruton

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The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Keywords: Analytics, digitization, industry 4.0, manufacturing.

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