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The purpose of this study is to reduce the cogging torque in axial flux permanent magnet (AFPM) machine using optimal magnet shape.

This study analyzes different magnet shapes for AFPM machine performance enhancement. Three-dimensional (3D) finite element analysis is performed to see the effects of pole shaping on the cogging torque of the AFPM machine.

The magnetic pole shape has a significant effect on cogging torque and overall efficiency. The conventional model has the highest torque whereas the conventional skewing affected cogging torque positively and significantly reduced the cogging torque. The combination of skewing the pole along with face curving is more effective and decreases the cogging torque from 3.88 Nm to 1.5 Nm.

Rare-earth magnets are the most expensive and important part of AFPM machines. Shape and volume optimization of rare-earth magnets is crucial for the performance of AFPM machines. The research aims to analyze the different permanent magnet designs for performance improvement of the AFPM machine. Conventional flat top trapezoidal, curved-top and skewed-magnet shapes are analyzed and the performance of the AFPM machine is compared with different magnet shapes. Curved-top shape and skewed magnet significantly reduce the cogging torque. Furthermore, a combination of curved-top shape and skew magnet shape is proposed to reduce the cogging torque further and improve the AFPM machine’s overall performance. Newly proposed magnet profile gives skewed curve magnet shapes which reduce the cogging torque further. 3D finite element analysis has been used to analyze the single-sided AFPM with all four different magnet shapes. The research focuses on single-sided AFPM machines, but the results are also valid for double-sided AFPM machines and can be extended to other topologies of AFPM machines.

When solving the cogging torque of complex electromagnetic structures, such as consequent pole hybrid excitation synchronous (CPHES) machine, traditional methods have a huge computational complexity. The notable feature of CPHES machine is the symmetric range of field-strengthening and field-weakening, but this type of machine is destined to be equipped with a complex electromagnetic structure. The purpose of this paper is to propose a hybrid analysis method to quickly and accurately solve the cogging torque of complex 3D electromagnetic structure, which is applicable to CPHES machine with different magnetic pole shapings.

In this paper, a hybrid method for calculating the cogging torque of CPHES machine is proposed, which considers three commonly used pole shapings. Firstly, through magnetic field analysis, the complex 3D finite element analysis (FEA) is simplified to 2D field computing. Secondly, the discretization method is used to obtain the distribution of permeance and permeance differential along the circumference of the air-gap, taking into account the effect of slots. Finally, the cogging torque of the whole motor is obtained by using the idea of modular calculation and the symmetry of the rotor structure.

This method is applicable to different pole shapings. The experimental results show that the proposed method is consistent with 3D FEA and experimental measured results, and the average calculation time is reduced from 8 h to 4 min.

This paper proposes a new concept for calculating cogging torque, which is a hybrid calculation of dimension reduction and discretization modules. Based on magnetic field analysis, the 3D problem is simplified into a 2D issue, reducing computational complexity. Based on the symmetry of the machine structure, a modeling method for discretized analytical models is proposed to calculate the cogging torque of the machine.

This study aims to obtain the minimum torque ripple at the maximum average torque for Flux-switching permanent magnet (FSPM) machines.

This paper is about torque performance optimization of the FSPM machines. To achieve that, finite element analysis and genetic algorithm (GA) are used. Five different designs are simulated, optimized and compared on their air gap flux density, back electromotive force, cogging torque, average torque, torque density and torque ripple.

After the thousands of iterations, its proved that all proposed shaping techniques have potential for reducing torque ripple and cogging torque, with slightly reduced average torque. The best design is the joint stator and rotor shaping, Design V, which results in the lowest torque ripple and cogging torque. The techniques should be applicable to FSPMs with other stator slot/rotor pole number combinations.

In this paper, rotor pole shaping by notching, chamfering and generic shaping, stator tooth shaping and joint shaping techniques are investigated for 12 s/10p FSPM machines. Rotor and stator flanks are optimized separately and jointly, by using finite element analysis and GA for optimization to achieve maximum average torque and minimum torque ripple. Five different design is implemented and compared, respectively.

This study aims to apply machine learning (ML) to identify new financial elements managers might use for earnings management (EM), assessing their impact on the Standard Jones Model and modified Jones model for EM detection and examining managerial motives for using these components.

Using eXtreme gradient boosting on 23,310 the US firm-year observations from 2012 to2021, the study pinpoints nine financial variables potentially used for earnings manipulation, not covered by traditional accruals models.

Cost of goods sold and earnings before interest, taxes, depreciation and amortization are identified as the most significant for EM, with relative importances of 40.2% and 11.5%, respectively.

The study’s scope, limited to a specific data set and timeframe, and the exclusion of some financial variables may impact the findings’ broader applicability.

The results are crucial for researchers, practitioners, regulators and investors, offering strategies for detecting and addressing EM.

Insights from the study advocate for greater financial transparency and integrity in businesses.

By incorporating ML in EM detection and spotlighting overlooked financial variables, the research brings fresh perspectives and opens new avenues for further exploration in the field.

The purpose of this study is to present a novel extended hybrid analytical method (HAM) that leverages a two-dimensional (2-D) coupling between the semi-analytical Maxwell–Fourier analysis and the finite element method (FEM) in Cartesian coordinates.

The proposed model is applied to flat permanent-magnet linear electrical machines with rotor-dual. The magnetic field solution across the entire machine is established by coupling an exact analytical model (AM), designed for regions with relative magnetic permeability equal to unity, with a FEM in ferromagnetic regions. The coupling between AM and FEM occurs bidirectionally (x, y) along the edges separating teeth regions and their adjacent regions through applied boundary conditions.

The developed HAM yields accurate results concerning the magnetic flux density distribution, cogging force and induced voltage under various operating conditions, including magnetic or geometric parameters. A comparison with hybrid finite-difference and hybrid reluctance network methods demonstrates very satisfactory agreement with 2-D FEM.

The original contribution of this paper lies in establishing a direct coupling between the semi-analytical Maxwell–Fourier analysis and the FEM, particularly at the interface between adjacent regions with differing magnetic parameters.

The purpose of this paper is to introduce an aid for teaching transverse flux permanent magnet machines (TFPMs) with emphasis on their torque production.

The Lorentz force law is applied to fictitious current loops emulating the permanent magnets (PMs) mounted on the rotor according to different arrangements; the air gap flux density is created by the armature current.

Implemented in a master lecture on special AC machines, the proposed approach has revealed a renewed interest in electromagnetic fundamentals for pedagogical purposes. It makes simple the explanation of the principle of operation of a class of AC machines reputed by the complexity of their magnetic circuits. The latter incorporates axially stacked decoupled sub-circuits, one per phase generating alternating magnetic fields. More specifically, there is common air gap, shared by the machine phases, in which a rotating magnetic field is created by the superposition of the PM contribution and the armature one.

Accounting for the complexity of the magnetic circuits and the three-dimensional (3D) flux paths characterizing TFPMs, a 3D finite element analysis (FEA) is required for the validation of the analytical predictions. Nevertheless, such a 3D FEA validation is far from being obvious to be carried on within a master lecture.

While the basis of Lorentz forces resulting from fictitious current loops emulating PMs has been considered in some referenced papers, its simple and pedagogical application to assess the torque production of several TFPM concepts represents the added value of the present paper.

This paper explores if the firm’s strategic orientation can be associated with differences in cost behavior activity.

Using Compustat data from 1979 to 2012, the archival study examines if there are differences between differentiation and cost leadership strategies on the firm’s cost stickiness.

The main finding provides evidence that firms pursuing a differentiation strategy exhibit greater cost stickiness, on average, as compared to firms pursuing a cost leadership strategy. This relationship is moderated by the optimistic or pessimistic expectations of managers for future sales.

This paper contributes to the literature on cost management by explaining how strategic positioning affects firms’ cost behavior using the framework of asymmetric cost behavior. The study encompasses both product and period costs and documents the impact on earnings.

This paper aims to investigate the features of single phase shaded pole stator with squirrel–cage rotor or permanent magnet rotor, that leads to an investigation of these topoloties as induction motor or synchronous motor. The comparative analysis is realised for the following three topologies: single phase shaded pole induction motor (SPIM) with squirrel–cage rotor, the second topology (single phase synchronous motor) has the same stator configuration but with permanent magnet rotor and the third investigated topology is similar to the second one, where the stator poles instead of iron steel are made of soft composite material.

The investigation in this work starts with a performance analysis of single-phase SPIM. Afterwards for the same stator topology the squirrel rotor is replaced with a two-pole permanent magnet rotor and the same performance analysis is realised for this topology. Finally, the second topology is improved bay replacing the iron steel stator poles with stator poles made of soft magnetic composite material and performance analysis is realised for this third type of topology as well. The performance analysis of all topologies is realised by implementation of finite element method and finite element analysis.

The presented data and diagrams from the realized investigation show that single phase synchronous motor with shaded pole stator has an improved characteristics in comparison with the initial single-phase SPIM. Finally, the third topology realized on the bases of the single-phase synchronous motor has the best performance characteristics due to the implementation of soft magnetic material in the realization of the stator poles. The proposed methodology for structural and performance improvement of a single-phase SPIM topology opens the possibility for additive manufacturing application and significant cost reduction.

The focus was put on exploration the possibilities of the single-phase shaded pole stator topology for application in low-power and low-cost single phase self-starting motors. By simple replacement of the squirrel–cage rotor, in the reference AKO-16 motor, with one-piece ferrite permanent magnet rotor, the self-starting single phase synchronous motor was derived. In the next step, owing to simplify the SPPM motor production process and manufacturing, the stator poles instead of iron steel lamination were made of soft composite material Somaloy®. It opens the possibility for additive manufacturing application and significant cost reduction.

This study aims to expand antecedent roles on social entrepreneurial behavioural intention by integrating both the Three Pillars of Institutions and the Mair Noboa model. The literature lacks in investigating both institutional- and individual-level antecedents to determine social entrepreneurial behavioural intention. This proposed integrated model was developed in which the Mair Noboa's model antecedents mediates the positive relationship between the antecedents of Three Pillars of Institutions and social entrepreneurial intention.

This study uses quantitative research methodologies to answer the research question of the extent that institutional-level antecedents in turn influence individual antecedents and thus determine social entrepreneurial intention. To explore this, a Web-based survey distributed across Bangladesh (n = 412). The confirmation of hypotheses involved using covariance-based structural equation modelling (SEM) for data analysis. The resulting measurement and structural models successfully met all criteria for reliability, model fit, convergent validity and discriminant validity. The hypotheses were subsequently assessed by examining both direct relationships and mediating effects.

The findings demonstrated a significant relationship between the antecedents of the Three Pillars of Institutions and the Mair Noboa model. The results suggest that the Mair Noboa model antecedents can mediate the relationship between the Three Pillars of Institutions and social entrepreneurial intention.

This paper advances the existing knowledge of social entrepreneurial intention, through the novel lens of combined institutional and individual antecedents. This paper fills an important knowledge gap by exploring both institutional- and individual-level antecedents to determine social entrepreneurial intention. This study findings yield fresh theoretical and practical insights into how institutional and individual antecedents jointly influence social entrepreneurial intention.

President Trump's tenure was accompanied by a series of protectionist measures that intended to reinvigorate US-based production and make manufacturing supply chains more “local”. Amidst these increasing institutional pressures to localise, and the business uncertainty that ensued, this study investigates the extent to which manufacturers reconfigured their supply bases.

Bloomberg's Supply Chain Function (SPLC) is used to manually extract data about the direct suppliers of 30 of the largest American manufacturers in terms of market capitalisation. Overall, the raw data comprise 20,100 quantified buyer–supplier relationships that span seven years (2014–2020). The supply base dimensions of spatial complexity, spend concentration and buyer dependence are operationalised by applying appropriate aggregation functions on the raw data. The final dataset is a firm-year panel that is analysed using a random effect (RE) modelling approach and the conditional means of the three dimensions are plotted over time.

Over the studied timeframe, American manufacturers progressively reduced the spatial complexity of their supply bases and concentrated their purchase spend to fewer suppliers. Contrary to the aims of governmental policies, American manufacturers increased their dependence on foreign suppliers and reduced their dependence on local ones.

The research provides insights into the dynamics of manufacturing supply chains as they adapt to shifting institutional demands.