Explore the vast range of titles available.

An overview of transmission/reflection-based methods for the electromagnetic characterisation of materials is presented. The paper initially describes the most popular approaches for the characterisation of bulk materials in terms of dielectric permittivity and magnetic permeability. Subsequently, the limitations and the methods aimed at removing the ambiguities deriving from the application of the classical Nicolson–Ross–Weir direct inversion are discussed. The second part of the paper is focused on the characterisation of partially conductive thin sheets in terms of surface impedance via waveguide setups. All the presented measurement techniques are applicable to conventional transmission reflection devices such as coaxial cables or waveguides.

In this paper, size-dependent dynamic stability of axially loaded functionally graded (FG) composite truncated conical microshells with magnetostrictive facesheets surrounded by nonlinear viscoelastic foundations including a two-parameter Winkler–Pasternak medium augmented via a Kelvin–Voigt viscoelastic approach is analyzed considering nonlinear cubic stiffness. To this purpose, von Karman-type kinematic nonlinearity along with modified couple stress theory of elasticity was applied to third-order shear deformation conical shell theory in the presence of magnetic permeability tensor and magnetic fluxes. The numerical technique of generalized differential quadrature (GDQ) was used for the solution of microstructural-dependent dynamic stability responses of FG composite truncated conical microshells. It was seen that moving from prebuckling to postbuckling domain somehow increased the significance of couple stress type of size dependency on frequency. In addition, within both prebuckling and postbuckling regimes, an increase of material gradient index decreased the importance of couple stress type of size dependency on the frequency of an axially loaded FG composite truncated conical microshell. Furthermore, it was revealed that by applying a positive magnetic field to an axially loaded truncated conical microshell with magnetostrictive facesheets, its frequency at a specific axial load value was increased in prebuckling domain and decreased in postbuckling domain. However, this pattern was reversed by applying a negative magnetic field.

The paper proposes a 3D extension of the linear tensor model of magnetic permeability for axially anisotropic materials. In the proposed model, all phases of a magnetization process are considered: linear magnetization, magnetization rotation, and magnetic saturation. The model of the magnetization rotation process is based on the analyses of both anisotropic energy and magnetostatic energy, which directly connect the proposed description with physical phenomena occurring during a magnetization process. The proposed model was validated on the base of previously presented experimental characteristics. The presented extension of the tensor description of magnetic permeability enables the modelling of inductive devices with cores made of anisotropic magnetic materials and the modelling of magnetic cores subjected to mechanical stresses. It is especially suitable for finite element modelling of the devices working in a magnetic saturation state, such as fluxgate sensors.

The orientation of the induced eddy currents is an important parameter for eddy currents testing probes used in Non-destructive Testing (NDT). In general, the eddy currents distribution is chosen to promote path changes when a defect is present, being preferentially set perpendicular to the target defects orientation. This usually requires complex geometry excitation coils and the consequent production difficulties. A new approach on the design of eddy currents testing probes is here presented, employing high magnetic permeability pattern substrates to shape the eddy currents distribution. This simulated and experimentally validated approach shift’s the excitation coils production complexity to the magnetic substrate, whose production can be easily tackled with additive manufacturing technologies.

Grinding thermal damages, commonly called grinding burns occur when the grinding energy generates too much heat. Grinding burns modify the local hardness and can be a source of internal stress. Grinding burns will shorten the fatigue life of steel components and lead to severe failures. A typical way to detect grinding burns is the so-called nital etching method. This chemical technique is efficient but polluting. Methods based on the magnetization mechanisms are the alternative studied in this work. For this, two sets of structural steel specimens (18NiCr5-4 and X38Cr-Mo16-Tr) were metallurgically treated to induce increasing grinding burn levels. Hardness and surface stress pre-characterizations provided the study with mechanical data. Then, multiple magnetic responses (magnetic incremental permeability, magnetic Barkhausen noise, magnetic needle probe, etc.) were measured to establish the correlations between the magnetization mechanisms, the mechanical properties, and the grinding burn level. Owing to the experimental conditions and ratios between standard deviation and average values, mechanisms linked to the domain wall motions appear to be the most reliable. Coercivity obtained from the Barkhausen noise, or magnetic incremental permeability measurements, was revealed as the most correlated indicator (especially when the very strongly burned specimens were removed from the tested specimens list). Grinding burns, surface stress, and hardness were found to be weakly correlated. Thus, microstructural properties (dislocations, etc.) are suspected to be preponderant in the correlation with the magnetization mechanisms.

The change in the parameters values of different physical nondestructive testing methods (surface acoustic waves, magnetic structuroscopy, and electrochemical potential) was studied depending on the hydrogen concentration in carbon steel in the range of 0.4–8.5 ppm. The most sensitive are the coercive force values, which changed by more than 25%. The values of the residual magnetic induction and the electrochemical potential of the metal surface changed by 23 and 20%, respectively, making them also applicable for assessing the hydrogen content in this steel. Other investigated parameters showed lower efficiency and their change were: for the magnetic hysteresis loop area of about 10%, and the maximum magnetic permeability and the relative change of the surface acoustic wave propagation velocity—approximately 2%.

The paper presents the results of the author's research on effectively determining the initial conditions for the time-stepping model of a high-speed inverter-driven induction machine. The classical time-harmonic and multi-harmonic models based on the multidimensional effective magnetic permeability were used and compared as a preconditioner for the time-stepping model to speed up the steady-state solution. The carried-out simulation experiment proved that using both approaches radically accelerates computations. Furthermore, it has been shown that the multi-harmonic model is much more effective for problems with strong harmonic effects.

This paper presents a novel finite element method (FEM) of optimization for driving frequency in magneto-mechanical systems using contactless magnetoelastic torque sensors. The optimization technique is based on the generalization of the axial and shear stress dependence of the magnetic permeability tensor. This generalization creates a new possibility for the determination of the torque dependence of a permeability tensor based on measurements of the axial stress on the magnetization curve. Such a possibility of quantitative description of torque dependence of a magnetic permeability tensor has never before been presented. Results from the FEM-based modeling method were validated against a real magnetoelastic torque sensor. The sensitivity characteristics of the model and the real sensor show a maximum using a driving current of similar frequency. Consequently, the proposed method demonstrates the novel possibility of optimizing magnetoelastic sensors for automotive and industrial applications.

For the study, we used four kerosene-based ferrofluid samples containing magnetite nanoparticles stabilized with oleic acid. Starting from the initial sample (A0), the other three samples were obtained by dilution with kerosene. The complex magnetic permeability measurements were performed in the microwave region (0.5–6) GHz, for different H values of the polarizing magnetic field, between (0–115) kA/m. These measurements revealed the ferromagnetic resonance phenomenon for each sample, allowing the determination of the anisotropy field (HA) and the effective anisotropy constant (Keff) of nanoparticles, depending on the volume fraction of particles (φ). At the same time, the measurements allowed the determination of the specific magnetic loss power (pm), effective heating rate (HReff), intrinsic loss power (ILP), and specific absorption rate (SAR) as functions of the frequency (f) and magnetic field (H), of all investigated samples, using newly proposed equations for their calculation. For the first time, this study evaluates the maximum limit of the applied polarizing magnetic field (Hmax ≈ 80 kA/m) and the minimum limit volume fraction of nanoparticles (φmin ≈ 3.5%) at which microwave heating of the ferrofluid remains efficient. At the same time, the results obtained show that the temperature increase of the ferrofluid samples, upon interaction with a microwave field, can be controlled by varying both H and φ, pointing to possible applications in magnetic hyperthermia.

Magnetorheological and electrorheological fluids manifest a change in rheological behavior when subjected to a magnetic or electric field, respectively, such that they require electrical and magnetic characterization. In this paper, a simple and accurate mathematical model based on a small number of parameters provides the relative magnetic permeability of magnetorheological fluids as a function of the applied magnetic field. Furthermore, for the testing and magnetic characterization of magnetorheological fluids, a new metering equipment setup is implemented. Starting with the achieved experimental data, the mathematical relation μr=f(B) is represented by means of a radial basis function neural network, with neurons having a Gaussian activation function; by means of post-training pruning procedures, the trained neural network is applied using the proposed data. Therefore, the obtained mathematical relation μr=f(B) is in good agreement with the experimental data, with an approximate error of 8%.