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Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

Confronting the unveiled sophisticated structural and physical characteristics of permanent magnets, notably the samarium–cobalt (Sm-Co) alloy, This work aims to introduce a simulation scheme that can link physics-based micromagnetics on the nanostructures and magnetostatic homogenization on the mesoscale polycrystalline structures.

The simulation scheme is arranged in a multiscale fashion. The magnetization behaviors on the nanostructures examined with various orientations are surrogated as the micromagnetic-informed hysterons. The hysteresis behavior of the mesoscale polycrystalline structures with micromagnetic-informed hysterons is then evaluated by computational magnetostatic homogenization.

The micromagnetic-informed hysterons can emulate the magnetization reversal of the parameterized Sm-Co nanostructures as the local hysteresis behavior on the mesostructures. The simulation results of the mesoscale polycrystal demonstrate that the demagnetization process starts from the grain with the largest orientation angle (a) and then propagates to the surrounding grains.

The presented scheme depicts the demand for integrating data-driven methods, as the parameters of the surrogate hysteron intrinsically depend on the nanostructure and its orientation. Further hysteron parameters that help the surrogate hysteron emulate the micromagnetic-simulated magnetization reversal should be examined.

This work provides a novel multiscale scheme for simulating the polycrystalline permanent magnets’ hysteresis while recapitulating the nanoscale mechanisms, such as the nucleation of domains, and domain wall migration and pinning. This scheme can be further extended to simulate the part-level hysteresis considering the mesoscale features.

Wafer bonding is a key process for 3 D advanced packaging of integrated circuits. It requires very high accuracy for the wafer alignment. To solve the problems of large movement stroke, position calibration error and low production efficiency in optical alignment, this paper aims to propose a new wafer magnetic alignment technology (MAT) which is based on tunnel magneto resistance effect. MAT can realize micro distance alignment and reduces the design and manufacturing difficulty of wafer bonding equipment.

The current methods and existing problems of wafer optical alignment are introduced, and the mechanism and realization process of wafer magnetic alignment are proposed. Micro magnetic column (MMC) marks are designed on the wafer by the semiconductor manufacturing process. The mathematical model of the space magnetic field of the MMC is established, and the magnetic field distribution of the MMC alignment is numerically simulated and visualized. The relationship between the alignment accuracy and the MMC diameter, MMC remanence, MMC thickness and sensor measurement height was studied.

The simulation analysis shows that the overlapping double MMCs can align the wafer with accuracy within 1 µm and can control the bonding distance within the micrometer range to improve the alignment efficiency.

Magnetic alignment technology provides a new idea for wafer bonding alignment, which is expected to improve the accuracy and efficiency of wafer bonding.

This paper aims to propose an energetic model parameter calculation method for predicting the materials’ symmetrical static hysteresis loop and asymmetrical minor loop to improve the accuracy of electromagnetic analysis of equipment.

For predicting the symmetrical static hysteresis loop, this paper deduces the functional relationship between magnetic flux density and energetic model parameters based on the materials’ magnetization mechanism. It realizes the efficient and accurate symmetrical static hysteresis loop prediction under different magnetizations. For predicting the asymmetrical minor loop, a new algorithm is proposed that updates the energetic model parameters of the asymmetrical minor loop to consider the return-point memory effect.

The comparison of simulation and experimental results verifies that the proposed parameters calculation method has high accuracy and strong universality.

The proposed parameter calculation method improves the existing parameter calculation method’s problem of relying on too much experimental data and inaccuracy. Consequently, the presented work facilitates the application of the finite element electromagnetic field analysis method coupling the hysteresis model.

This study aims to present a unique hybrid metaheuristic approach to solving the nonlinear analysis of hall currents and electric double layer (EDL) effects in multiphase wavy flow by merging the firefly algorithm (FA) and the water cycle algorithm (WCA).

Nonlinear Hall currents and EDL effects in multiphase wavy flow are originally described by partial differential equations, which are then translated into an ordinary differential equation model. The hybrid FA-WCA technique is used to take on the optimization challenge and find the best possible design weights for artificial neural networks. The fitness function is efficiently optimized by this hybrid approach, allowing the optimal design weights to be determined.

The proposed strategy is shown to be effective by taking into account multiple variables to arrive at a single answer. The numerical results obtained from the proposed method exhibit good agreement with the reference solution within finite intervals, showcasing the accuracy of the approach used in this study. Furthermore, a comparison is made between the presented results and the reference numerical solutions of the Hall Currents and electroosmotic effects in multiphase wavy flow problem.

This comparative analysis includes various performance indices, providing a statistical assessment of the precision, efficiency and reliability of the proposed approach. Moreover, to the best of the authors’ knowledge, this is a new work which has not been explored in existing literature and will add new directions to the field of fluid flows to predict most accurate results.

This study addresses the production optimization of a cellular manufacturing system (CMS) in magnetic production enterprises. Magnetic products and raw materials are more critical to transport than general products because the attraction or repulsion between magnetic poles can easily cause traffic jams. This study needs to address a method to promote the scheduling efficiency of the problem.

To address this problem, this study formulated a mixed-integer linear programming (MILP) model to describe the problem and proposed an auction and negotiation-based approach with a local search to solve it. Auction- and negotiation-based approaches can obtain feasible and high-quality solutions. A local search operator was proposed to optimize the feasible solutions using an improved conjunctive graph model.

Verification tests were performed on a series of numerical examples. The results demonstrated that the proposed auction and negotiation-based approach with a local search operator is better than existing solution methods for the problem identified. Statistical analysis of the experiment results using the Statistical Package for the Social Sciences (SPSS) software demonstrated that the proposed approach is efficient, stable and suitable for solving large-scale numerical instances.

An improved auction and negotiation-based approach was proposed; The conjunctive graph model was also improved to describe the problem of CMS with traffic jam constraint and build the local search operator; The authors’ proposed approach can get better solution than the existing algorithms by testing benchmark instances and real-world instances from enterprises.

The noise measurement on magnetoresistive (MR) sensors is generally conducted by techniques including single-channel data sampling and fast Fourier transform (FFT) analysis as well as two-channel cross-correlation. The single-channel method is easy to implement and is widely used in the noise measurement on MR sensors, whereas the two-channel method can only eliminate part of the system noise. This study aims to address two key issues affecting measurement accuracy: calibration of the measurement system and the elimination of system noise.

The system is calibrated by using a low-noise metal film resistor in that the system noise is eliminated through power spectrum subtraction. Noise measurement and analysis are conducted for both thermal noise and detectivity of magnetic tunnel junction (MTJ) sensor.

The thermal noise measurement error is less than 2%. The detectivity of the MTJ sensor reaches 27 pT/Hz^1/2 at 2 kHz.

This study provides a more practical solution for noise measurement and system calibration on MR sensors with a bias voltage and magnetic field.

The purpose of this paper is to verify results related to losses in the core of a brushless DC prototype motor, obtained using its computer FE models, by experimental tests on manufactured machines. The paper focuses on the comparison of losses in the core of a machine with a classical stator core made of an iron–silicon material (Fe–Si) and a new one made of a modern METGLAS material.

Computer models of the prototype motors were created using FEM. The designed machines were manufactured, and experimental tests were performed. To achieve high frequencies in rotating magnetic fields, motors with a stator to rotor pole ratio of 9/12 were built. Twin rotor approach was applied, as two identical rotors were built along the two geometrically identical stators made of different core materials.

Experimental studies have shown the superiority of the METGLAS material over the classical Fe–Si material. Material parameters were measured directly on the prepared cores as library data used in the simulation may be incorrect due to technological processes during core production, which was also verified. Problems related to twin rotor approach have been identified. Solution to the problem has been suggested. Necessity of 3D FEM modelling was identified.

The main source of originality is that METGLAS material used in the prototype machines was developed and manufactured by the authors themselves. Original approach to core parameter evaluation based on simplified methodology has been suggested. Another original part is a simplified methodology applied to loss measurement during no-load test.

The paper aims to expand the scope of application of the lattice Boltzmann method (LBM), especially in the field of aircraft engineering. The traditional LBM is usually applied to incompressible flows at a low Reynolds number, which is not sufficient to satisfy the needs of aircraft engineering. Devoted to tackling the defect, the paper proposes a developed LBM combining the subgrid model and the multiple relaxation time (MRT) approach. A multilayer adaptive Cartesian grid method to improve the computing efficiency of the traditional LBM is also employed.

The subgrid model and the multilayer adaptive Cartesian grid are introduced into MRT-LBM for simulations of incompressible flows at a high Reynolds number. Validated by several typical flow simulations, the numerical methods in this paper can efficiently study the flows under high Reynolds numbers.

Some numerical simulations for the lid-driven flow of cavity, flow around iced GLC305, LB606b and ONERA-M6 are completed. The paper presents the investigation results, indicating that the methods are accurate and effective for the separated flow after icing.

LBM is developed with the addition of the subgrid model and the MRT method. A numerical strategy is proposed using a multilayer adaptive Cartesian grid method and its treatment of boundary conditions. The paper refers to innovative algorithm developments and applications to the aircraft engineering, especially for iced wing simulations with flow separations.

The purpose of this paper is to reveal the effect of microstructure on the corrosion behavior of CoCrNi alloy in 3.5 Wt.% NaCl solution.

The as-cast CoCrNi alloy was prepared by arc melting, and the cold-rolled and annealed alloys were prepared by processing the as-cast alloy.

The experimental results showed that a protective passivation film was formed on the surfaces of these CoCrNi MEA, and the stability and compactness of alloys increased in the sequence of cold-rolled, as-cast and annealed CoCrNi alloys. The annealed CoCrNi alloys had the best pitting resistance.

This study proposes the effect of the microstructure of CoCrNi alloy on corrosion resistance.