Electromagnetic analysis and design of electromagnetic devices using permanent magnets

Mesh generation for modelling in magnetics

An automatic procedure is presented for implementing Finite Element magnetic field analysis techniques in the design of electric machines, transformers and related devices. By means of the Boundary Element Method , a mesh is obtained for studying the magnetic field in a given region by the Finite Element Method. In this way , input data can be reduced and more accurate final data acquired on the region considered, while ensuring a big decrease in program run-time (if an FE iterative procedure is used). The advantages of the procedure are illustrated by its application to a transformer. Comparison of the magnetic field values obtained by the proposed procedure and those by the classical Finite Element Method reveals better agreement with measured values in the case of the former and a 20% reduction in program run-time.

The effects of static, dynamic and fatigue behavior on three-dimensional shape optimization of hip prosthesis by finite element method

Oil and gas pipeline failure and leakage can seriously damage people's lives and the ecosystem. The prediction of failure pressure for pipelines with damage is one of the most important and challenging tasks faced by industry, which affects the assessment of pipeline safety. Previous studies widely used industrial models or the finite element (FE) method to predict the failure pressure. However, the industrial models may give limited information, and the FE method has much heavy computation burden. In this work, three machine learning models - artificial neural network (ANN), XGBoost (XGB) and CatBoost (CAT) are developed for forecasting the failure pressure of pipelines with defects. Firstly, the simulation results of the FE method are validated by real failure pressure and compared with the calculation results of industrial models (ASME-B31G and DNV). Then 180 pipeline samples including pipeline attributes and defect sizes collected from real in-line inspection data in a pipeline company and the corresponding FE simulation results of failure pressure of these 180 defective pipelines are used for the training and testing of the machine learning models. The results show that the simulation accuracy of the FE method is higher than the calculation accuracy of the industrial models, and the FE simulation results are suitable to be the outputs of machine learning models. The three machine learning methods all provide satisfactory prediction accuracy in failure pressure. Specifically, CAT is the best machine learning method in this study for its lowest relative error (3.11% on average), mean absolute error (0.53), root mean square error (0.78) and highest coefficient of determination (R2) up to 98% in testing. Moreover, the machine learning models present better performance on average relative errors compared to the industrial models. CAT shows higher accuracy than the industrial models and FE simulation on minimum and average relative errors. Finally, the prediction result of CAT is used to discuss the effect of input features on failure pressure of pipelines, which demonstrates that the importance of features follows the order of pipeline thickness > pipeline outside diameter > defect depth > defect length > defect width. Once the above machine learning methods are used in industry, more and more real data will be collected to train a model and make it more accurate. In this way, these methods will provide an efficient way to evaluate the safety of defective pipelines. In addition, the failure pressure of pipeline could be estimated to help operators figure out a pipeline condition and further prioritize the pipelines for maintenance.

In the tensile strength analysis, the failure criterion and materials stiffness degradation rule were proposed and the X-cor sandwich’s failure modes were also clarified. According to the failure criterion we used the elements with stiffness degradation and their distributions in the finite element model to simulate the types and propagation path of the failure and the failure mechanisms of X-cor sandwich were explained. The finite element analysis indicates during the tension firstly the interfaces between resin regions and Z-pin tips fail and the failure mode is Z-pin pull-out from the face-sheets. The finite element simulated results are in good agreement with the experimental results, the error range is -11.6%~9.7%. The comparison results show the failure criterion and stiffness degradation rule are reasonable and this method can be used to predict the X-cor sandwich’s tensile strength.

Summary form only given. In China, there is a 1000 MW thermal power generator in operation. Large electrical machines are popular in power generation. However, large electrical machines are facing more challenges than small ones due to their features. They have high voltage, high current and high losses, which increase design difficulty in control, insulation and cooling. Moreover, the high torque in large machines will introduce challenges in mechanical designs. It's usually costly to manufacture and maintain the large machines due to their high weight and large volumes. As a result, design of large electrical machines is a complicated process. A review of the general design process of large electrical machines is presented. Firstly, the specifications of the machine should be keep in mind, such as working environment, machine type, electromagnetic performances and so on. Then the topology and parameters of the machine should be selected by optimal design. In addition, stator cooling methods, including air and water cooling, and mechanical supporting of rotor and stator, should be carefully designed respectively.In recent years, large permanent magnet (PM) machines are widely used in wind power, ship propulsion, railway traction, etc. As the capacity of electrical machines increases, there are more and more challenges in design of PM machines. When a PM machine is built and tested, it is often found that the test results do not match predictions well. A set of practical design considerations gained from industrial application experiences are presented, which should be considered during design phase, but often ignored by many machine designers. They are categorized into topology, electromagnetic (EM) performance, loss and efficiency. The causes and effects of some issues are analyzed and some solutions are suggested. They can help machine designers to narrow down the gap between design predictions and test results and build large PM machines with expected performance and high reliability. Superconducting direct-drive generators are new candidates for multi-megawatt class wind generators. Superconducting machines are famous for low weight, small size, and high efficiency. Challenges for large superconducting electrical machines are addressed. In order to find out the suitable topology for multi-megawatt-class direct-drive wind turbine generators, various designs of superconducting machines are compared; advantages and disadvantages are discussed; and a few ways to benefit from their advantages are pointed out. Moreover, characteristics of high and low temperature superconducting materials are concluded. At present, as the current cost of low temperature materials is much lower than high temperature materials. In addition, electromagnetic, mechanical and thermal challenges, including magnet design, excitation system, rotor screen, torque tube, cryogenic cooling system etc., are discussed for superconducting machines.

In the present work, a new axisymmetric weak form meshless method is presented for analysis of free vibration of functionally graded material (FGM) cylinders. This method is based on weak form of equilibrium equation and moving least squares (MLS) approximation. Essential boundary conditions are imposed by transformation method. In this method, shape functions that do not satisfy the Kronecker delta condition are corrected, then essential boundary conditions are imposed easily as in the finite element method (FEM). In the present work, the material is assumed to be functionally graded in the radial direction. Variations in the material properties such as Young’s modulus and Poisson’s ratio may be arbitrary functions of the radial coordinate. The FGM cylinder material varies continuously from silicon carbide (SiC) on the inner surface to stainless steel (SUS304) on the outer surface. Free vibration analysis of FGM cylinders with any arbitrary combination of boundary conditions is possible by the proposed model. Natural frequencies obtained from the presented model are in good agreement with results of finite element simulation. Effects of various types of boundary conditions, geometrical parameters, and mechanical properties on the natural frequencies are studied.

Design and operation analysis of electrical machines can be performed by using either full-size or different scale models. This paper deals with the development of electromagnetic field analysis and electrical circuit models of geometrically similar electrical machines based on similarity theory and scale factors. The proposed methodology can be exploited for the design of micro and nano scale electrical machines used in medical and other applications, as it allows the construction of up-scale models more suitable for laboratory measurements.

Electromagnetic ultrasound surface wave generated by combination of double magnets and the snake-shaped coil is widely used in the aluminum plate surface flaw detection. The electromagnetic ultrasonic transducer model is investigated and the theory analysis of electromagnetic ultrasound surface wave and numerical simulation of EMAT physical mechanism are discussed in this paper. Based on ANSYS, the 3-D finite element model of electromagnetic ultrasonic transducer is established, furthermore the relationship between magnet field, Lorentz force and surface wave generated on aluminum plate is concluded by applying electromagnetic structural coupling in this model. The consistency of electromagnetic ultrasonic theory and simulation results provides the theoretic basis for the parameters of electromagnetic ultrasonic transducer and facilitates the structural design and optimization of electro-magnetic ultrasonic transducer surface wave devices.

Real-world groundwater modeling deals with heterogeneous and anisotropic aquifer systems. Numerical models, particularly the finite difference and finite element methods, are extensively used for modeling such a complex aquifer system. The finite difference method is an age-old straightforward approach, whereas the finite element method is more idealistic, relatively new, and has emerged as a popular approach. The unique advantages with the finite element method are (i) an irregular-shaped domain can be discretized into elements with a matching boundary, (ii) a node can be connected with the neighboring nodes in any direction. Thus, the finite element analysis allows water/solute to flow more freely toward the surrounding nodes along nodal links. On the other hand, the mathematical formulation of the finite element technique follows a set of rules step by step. Conventionally, this idealistic approach uses shape functions and integration techniques to develop element matrices, which, in turn, are assembled to form the global matrix. This conventional global matrix was found to be inconsistent with the basic partial differential equation representing the mass balance in a nodal domain as a control volume. As a result, the matrix solution, particularly for nonlinear problems (e.g., vadose zone flow, density dependent flow, and so forth) becomes unstable and computationally burdensome. To overcome the limitations of the conventional finite element method for real-world groundwater modeling, a new approach, called the direct-formulation finite element (DFFE) method, has been developed. In this approach, a two-dimensional model domain is discretized into triangular elements. Element matrices are formed directly based on flow principles and material properties of elements without using shape functions and integration process. The DFFE method is robust. The global matrix is consistent, and the solution is stable and efficient. The results obtained from this approach were found in a good agreement with that obtained from analytical and other widely used models.

The magnetic gear system works with magnetic forces obtained with the help of permanent magnets and has a structure that can be an alternative to classical gear systems. In order to transmit torque between the input and output shaft, unlike conventional gears, there is a transmission without mechanical contact in the magnetic gear system. Therefore, friction is eliminated. Elimination of friction means that magnetic gear systems operate at much higher efficiency compared to conventional gearbox systems. Since the movement and torque transmission in magnetic gear systems occur without contact, it never requires lubrication and problems arising from lubrication do not occur. In conventional mechanical gearbox systems, the conversion rate is determined by the number of teeth used. Similarly in magnetic gear systems, the number of permanent magnets used determines the conversion rate. In this study, a magnetic gear system with a coaxial structure was designed and its electromagnetic analysis was made with the finite element method. Axial torque values at certain speeds in the input shaft and output shaft were obtained as a result of finite element analysis depending on time.

Inverse analysis is a method for determining material parameters by minimizing the difference between experimental and the finite element (FE) simulated results, such as the load-stroke curve and barreling shape of a deformed specimen using an optimum design technique. In this study, ring compression tests were conducted to predict the flow stress of materials and interfacial friction conditions. Cylinder compression tests were conducted under the same process conditions to estimate the validity of the data obtained from the ring compression tests. By comparing the experimental results with the FE simulated results, it was confirmed that flow stress and the interfacial friction condition obtained from the ring compression tests, as well as their inverse analysis, are quite reasonable. The validity of both the flow stress function and the interfacial friction condition using the above procedures was verified by the experiments.

This study was aimed to investigate the machining stability of a horizontal milling machine with hybrid guideway systems by finite element method. To this purpose, we first created finite element model of the milling machine with the introduction of the contact stiffness defined at the sliding and rolling interfaces, respectively. Also, the motorized built-in spindle model was created and implemented in the whole machine model. Results of finite element simulations reveal that linear guides with different preloads greatly affect the dynamic responses and machining stability of the horizontal milling machine. The critical cutting depth predicted at the vibration mode associated with the machine tool structure is about 10 mm and 25 mm in the X and Y direction, respectively, while the cutting depth predicted at the vibration mode associated with the spindle structure is about 6.0 mm. Also, the machining stability can be increased when the preload of linear roller guides of the feeding mechanism is changed from lower to higher amount.

IntroductionIn recent years, SMPMSM is quietly famous compared with other conventional motors in industrial applications due to higher efficiency, higher reliability, low cost, and smooth torque [1]–[3]. In general, several objective optimizations need to be consider, which required an optimization technique for an electrical motor. This paper deals with an optimal design of a surface-mounted permanent magnet synchronous machine (SMPMSM) with an exact analytical subdomain model by using a genetic algorithm method. To analyze the characteristic of permanent magnet (PM) motors, the classical optimization method, such as the finite element method (FEM), is intensively used. However, FEM has several time problems that require a longer computational time to evaluate the performance of PM motors. This problem can be overcome by using a genetic algorithm (GA) method combined with a subdomain model (SD), which developed an improved performance of SMPMSM, for instance, total harmonic distortion (THDv) and phase back-EMF. In this design, a three-phase 12-slot/8-pole PM motor is established with an exact SD model with radial magnetization patterns. Then, the GA ensemble with SD model to search the optimality of SMPMSM machine design. In the final analysis, the optimal new design of SMPMSM demonstrated by comparing with the initial design that is investigated by FEM. The result of induced back-EMF, and magnetic flux density of optimal design is compared with the initial design to show the advantages of GA optimization method.Analytical Model, Genetic Algorithm and Parameter of optimizationThe purpose of this analysis is to investigate the optimization design of a three-phase 12-slot/8-pole SMPMSM with a radial magnetization pattern. This optimization problem has been solved by obtains the minimum THDv as a fitness function. In order to process the optimization design of SMPMSM, several parameters need to be optimized i.e magnet pole-pitch, αp and slot-opening angle, boa. The roulette method is used to select the objective function of optimization with 50 maximum generations per iteration. The cross and mutation probability need to be set which requires linear and uniform recombination which is 0.89 and 0.025 respectively. The parameters of 12-slot/8-pole SMPM motor as follows: radius of the rotor, Rr = 23mm, the radius of PM surface Rm = 26mm, the inner radius of the stator Rsb = 42.5mm, axial length, la = 50mm, air-gap length, lg = 1mm, remanence of the magnet, Br, 1.12T, relative coil permeability, µr = 1.05 with the number of pole pairs, Np is 8 and number of stator slots, Ns is 12.The result, Discussion and ConclusionThe phase back electromotive force has a significant relationship with flux-linkage because phase back electromotive force is derived from the rate of change of flux-linkage. In Fig. 1. show the waveform of phase back electromotive force against rotor position of initial and optimal design in radial magnetization patterns. The initial design of phase back electromotive force waveform shows more trapezoidal compare with the optimal design which has a sinusoidal waveform. The comparison of total harmonic distortion between the initial and optimal design of SMPMSM are demonstrated in Fig. 2 below. The result from Fig.2. shows the highest total harmonic distortion of 12-slot/8-pole motor is an initial design which is 11.34% compared with the optimal design where 1.3%. The magnitude of harmonic in phase back electromotive force |En| of initial design shows 22.24 V compare to optimal design which is 17.4 V. This shows a good agreement that the optimal motor design gives lowest total harmonic distortion compare with the initial design. The optimizes of SMPMSM motor with the following parameters are given in Table 1. **

An electromagnet and a float are needed to be designed for a magnetic suspension system. In this paper an optimized design of an electromagnet is being carried out based on minimum flux leakage and maximum amount of force that can be imparted on the float. This paper also compares different designs to find out advantages and disadvantages of these designs. Design starts from a simple and naive design of electromagnet and then gradually improved until a satisfactory design is obtained. Different shapes of floats were also considered for an optimum design of float. Electromagnetic analysis is carried with commercial FEM (Finite Element Method) software to calculate different parameters of design. Later the result from the FEM software is verified by analytical calculation.