Magnetic Flux Coupling Research Articles

Two-Stage DC Fault Current Limiter Combining Hybrid Magnetic Materials and Active Flux Coupling Coils

Two-Stage DC Fault Current Limiter Combining Hybrid Magnetic Materials and Active Flux Coupling Coils

Hyperchaos of neuron under local active discrete memristor simulating electromagnetic radiation.

Memristor enables the coupling of magnetic flux to membrane voltage and is widely used to investigate the response characteristics of neurons to electromagnetic radiation. In this paper, a local active discrete memristor is constructed and used to study the effect of electromagnetic radiation on the dynamics of neurons. The research results demonstrate that increasing electromagnetic radiation intensity could induce hyperchaotic attractors. Furthermore, this neuron model generates hyperchaotic and three points coexistence attractors with the introduction of the memristor. A digital circuit is designed to implement the model and evaluate the randomness of its output sequence. Neuronal models exhibit a rich dynamic behavior with electrical radiation stimulation, which can provide new directions for exploring the production mechanisms of certain neurological diseases.

Dynamics and network behavior of a four-dimensional discrete neuron model with magnetic flux coupling

Dynamics and network behavior of a four-dimensional discrete neuron model with magnetic flux coupling

Electromagnetic analysis and detent force minimization of a linear vernier motor

This paper proposes a new dual-sided linear permanent magnet vernier motor (LPMVM). The advantages of high thrust density, low thrust ripple, positive force elimination and structural stability are introduced in detail. The double-sided structure and toroidal winding proved the novelty of the machine tool, which is suitable for high definition digital control machine tools. Firstly, the basic structure and working principle of the engine are introduced. Through theoretical analysis, the expressions of electromagnetic thrust and detent force are derived. Thirdly, basic characteristics of permanent magnetic magnet flux coupling, backless electromotive force, detent force and electromagnetic drive are analyzed by using a a simplified three-phase model with symmetric boundary in 3-D finite element analysis. Finally, the thrust density and the detent force of the designed motor are calculated and analyzed. The results show that the designed motor is superior to the linear permanent magnet synchronous motor.

Correlated insulating states in carbon nanotubes controlled by magnetic field

Recent experiments have shown that nearly metallic nanotubes remain insulating throughout magnetic field sweeps, in which the magnetic flux through the nanotube is expected to pass through a critical point where the single-particle band gap closes in one valley. Here, the authors investigate correlated insulating states of zigzag carbon nanotubes, which emerge from the interplay of electron-electron interactions, magnetic flux, strain, and spin-orbit coupling. They find that the gap for charged excitations generically remains open near the critical flux value, and predict a novel mirror symmetry breaking phase that may arise in the experimentally relevant regime of spin-orbit coupling.

Quantum Hall response of SU(3) fermions

We discuss the quantum Hall response of SU(3) fermions in two-dimensional lattices, when artificial magnetic flux and color-orbit coupling are present. We analyze the Hall conductance tensor in the charge-charge, color-charge, charge-color, and color-color sectors. When charge and color are conserved, we directly relate the Hall conductances to corresponding Chern numbers describing topological color insulators. We establish the bulk-edge correspondence for Hall conductances in toroidal (without edges) and cylindrical (with edges) geometries. When color is not conserved or when edge states are not robust to disorder or SU(3)-symmetric interactions, we show that the color Hall conductances are not quantized, but the corresponding Chern numbers, which are a bulk property, can still be used to label the topological insulating phases. Depending on the robustness of edge states to disorder and interactions, we identify the topological phases to be strong, intermediate, or weak. We envision applications to $\mathrm{SU}(N)$ ultracold fermions such as $^{173}\mathrm{Yb}$ and $^{87}\mathrm{Sr}$.

Emerging Spiral Waves and Coexisting Attractors in Memductance-Based Tabu Learning Neurons

Understanding neuron function may aid in determining the complex collective behavior of brain systems. To delineate the collective behavior of the neural network, we consider modified tabu learning neurons (MTLN) with magnetic flux. Primarily, we explore the rest points and stability of the isolated MTLN, as well as its dynamical characteristics using maximal Lyapunov exponents. Surprisingly, we discover that for a given set of parameter values with distinct initial conditions, the periodic and the chaotic attractors may coexist. In addition, experimental analysis is carried out using a microcontroller-based implementation technique to support the observed complex behavior of the MTLN. We demonstrate that the observed numerical results are in good agreement with the experimental verification. Eventually, the collective behaviors of the considered MTLN are investigated by extending them to the network of the lattice array. We discover that when the magnetic flux coupling coefficient is varied in the presence of an external stimulus, the transition from spiral waves to traveling plane waves occurs. Finally, we manifest the formation of spiral waves in the absence of an external stimulus in contrast to previous observations.

Effects of Time Delay on Bifurcation and Synchronization of Flux-Coupled and Chemically Coupled Neurons

Based on the chemical synaptic coupling neuron model, the differences and types of synchronization under inhibitory and excitatory conditions are discussed.According to the effect of magnetic flux coupling on neuron discharge, the discharge states, bifurcation types and synchronization of ML neuron models with delay, magnetic flux coupling and chemical coupling are discussed.It is found that ML neuronal systems with magnetic flux coupling and chemical coupling can produce rich inverse periodic bifurcation or incremental periodic bifurcation behaviors under different parameters.The introduction of time delay, although it can increase the periodicity of the system, will also break the system synchronization. Conversely, appropriate coupling strength can increase synchronization.

Suppressing spiral waves in a lattice array of coupled neurons using delayed asymmetric synapse coupling

Abstract The coupling between neuronal oscillator plays a significant role in their network performance. When the coupling is asymmetric in an electrical synapse connection, the entire dynamical behaviour of the neuron model changes. Such asymmetric synapse coupling on neuron models exposed to magnetic flux induction will display more complex behaviours. Hence, we propose a coupled neuron model considering flux coupling with asymmetric electrical synapse. The various dynamical properties of the coupled neuron model are explored by considering the coupling coefficients and flux coupling constant as the control parameters. The coexistence of at least chaotic with chaotic or chaotic with periodic or periodic with periodic firing patterns are identified in the new model for different values of coupling strengths. Such coexisting firing patters are also seen for discrete values of the flux coupling coefficient. The investigation is expanded further to the network performance of such coupled neurons considering the coupling coefficient as the parameter of discussion. A simple applied plane wave is disturbed and rotating spiral waves are formed in the network for different values of the coupling strength. We have shown that by introducing magnetic flux coupling into the neuron model, we could suppress the spiral waves in the network. As an alternative by considering a coupled neuron model without flux coupling and with delayed asymmetric electrical synapse coupling, we showed that the spiral waves are completely suppressed effectively for selected values of delay. Using delayed coupling comparatively more effective than flux coupling for supressing spiral waves in the network.

Analysis of cogging torque in dual-stage magnetically geared devices considering magnetic flux coupling

The dual-stage magnetically geared machine (DSMGM) has a high gear ratio. The first stage is a Vernier machine (VM), and the second stage is a coaxial magnetic gear (CMG). These two components share a common rotor (CR), and they are partially flux coupled. Two DSMGMs with different PM arrangements are fabricated and tested. The DSMGM-I with gear ratio 34 can work smoothly, while the DSMGM-II with gear ratio 14.875 is hard to be started up. The purpose of this paper is to reveal the failure of the DSMGM-II. Due to the magnetic flux coupling, there is a recessive CMG in DSMGM structure. The recessive CMG in DSMGM-II prototype is activated and results in high cogging torque and high torque ripple. The thickness of CR yoke controls the portion of flux penetrating through stator. When the thickness of CR yoke is large enough, the cogging torque of the DSMGM-II can be improved. Moreover, another effective method to improve the cogging torque is designing a flux barrier to magnetically decouple the VM and CMG components. For direct-drive robotic application, a DSMGM with Halbach-PM-array is presented. It has a high gear ratio, high torque capability and low cogging torque.

A Novel 2-DOF Lorentz Force Actuator for the Modular Magnetic Suspension Platform.

The modular magnetic suspension platform depends on multi degree of freedom of Lorentz force actuators for large bearing capacity, high precision positioning and structure miniaturization. To achieve the integration of vertical driving force and horizontal driving force, a novel 2- (two degrees-of-freedom) DOF Lorentz force actuator is developed by designing the pose of the windings and permanent magnets (PMs). The structure and the working principle are introduced. The electromagnetic force mathematical model is established by the equivalent magnetic circuit method to analyze the coupling of magnetic flux. The distribution characteristics of magnetic flux density are analyzed by the finite-element method (FEM). It is found that the coupling of the magnetic flux and the large magnetic field gradient severely reduce the uniformity of the air-gap magnetic field. The electromagnetic force characteristic is investigated by FEM and measurement experiments. The difference between FEM and experiment results is within 10%. The reasons of driving force fluctuation are explained based on the distribution of air-gap magnetic field. The actuator performance are compared under the sliding mode control algorithm and PID control algorithm and the positioning accuracy is 20 μm and 15 μm respectively. Compared with the similar configuration, the motion range and force coefficient of the Lorentz force actuator in this paper are larger. It has a certain guiding significance on the structure design of the multi degree of freed Lorentz force actuator.

NUMERICAL-FIELD ANALYSIS OF THE CHARACTERISTICS OF A THREE-PHASE MAGNETIC FIELD INDUCTOR FOR THE TREATMENT OF VARIOUS SUBSTANCES WITH CURRENT STABILIZATION

Introduction. A three-phase magnetic field inductor (MFI) similar to the asynchronous motor stator, which provides processing of various substances, is considered. This is done by means of oblong ferromagnetic elements moving with a rotating magnetic field and located in its cylindrical working chamber. Problem. The aim of the work is to develop the theory and conduct practical calculations of the parameters and characteristics of the MFI that connect the electromagnetic quantities and their phase relationships in the mode of its load. Methodology. The studies are carried out on the basis of numerical calculations of the magnetic field in the MFI taking into account the ferromagnetic elements in its working chamber. The calculation model of the chamber is represented by a homogeneous anisotropic magnetic medium for which the method of determining different magnetic permeabilities by its longitudinal and transverse axes is given. In order to obtain the characteristics of the presented MFI, the method of determining the electromagnetic parameters and phase relationships of the quantities accompanying its operation has been developed. Results. The theory and results of numerical-field analysis of electromagnetic quantities, their phase relationships and corresponding characteristics of three-phase MFI are presented. Calculations of characteristics are made for the inductor load mode depending on the phase shift of the magnetomotive force of the stator winding relative to the longitudinal axis of the chamber and while ensuring the constant value of the current of this winding. The characteristics include magnetic flux coupling, EMF and stator winding voltage, phase shifts between them and current, electromagnetic moment, input and output power, electrical and magnetic loss power, power factor and efficiency. Practical value. The technique of numerical-field calculations of electromagnetic quantities and their phase relationships is developed, and also the set of characteristics which should promote designing and perfection of inductors of the considered type is received. The presented technique is universal as it allows to display their cores practically of any shape.

Performance of DC SQUID Second-Order Axial Gradiometer Response to Radio Frequency Interference

A low-Tc dc SQUID placed in a superconducting and magnetic shield is insensitive to magnetic interference, but not completely immune to the effects of radio frequency interference (RFI). Here, we investigated the effect of two orthogonal RF fields on the second-order axial gradiometer's transfer characteristics and noise characteristics. RF field induced phase shift of the V – $\Phi$ curve. The modulated spikes of RF field on the V – $\Phi$ curve and noise spectrum became significant with the RF field increasing. The white noise of the system increased to 12.5 $fT/\sqrt{\text{Hz}}$ with +10 dB axial RF field, nearly one and a half times of 8.5 $fT/\sqrt{\text{Hz}}$ without RFI. The working point jumping occurred under the radial RF field of +5 and +10 dB, and the white noise increased to 17.2 and 165.8 $fT\sqrt{\text{Hz}}$ , respectively. The reason of work point drift related to the magnetic flux coupling between the SQUID and pickup coil needs further studies.

A New Type of DC Superconducting Fault Current Limiter

A new type of Superconducting Fault Current Limiter (SFCL) for dc applications is proposed. This SFCL consists of a current transmission/limiting coil, an iron-core, and a set of superconductor rings. The superconductor rings are placed between the current transmission/limiting coil and the iron-core. For application, the current transmission/limiting coil is connected in series to a dc transmission line. During normal power transmission, magnetic flux coupling between the current transmission/limiting coil and the iron-core is prevented by the magnetic shielding of the superconductor rings, and the current transmission coil has low impedance. Because of shielding effect of the superconductor rings iron-core has high permeability at the beginning of short circuit, current-limiting coil can effectively limit fault current rise. When the fault current reaches a certain level, the superconductor rings will quench and the shielding effect is greatly reduced. The current-limiting coil strengthens the coupling with the iron core, increases the inductance, and will suppress the further increase of the fault current. A laboratory proof-of-concept prototype was made to demonstrate the feasibility of the idea. Experiments have been carried out with the prototype. In this paper, we will introduce the detailed information of the principle, the prototype, and the experimental results. In addition, a design of the new type of dc SFCL is installed in a ±160 kV high-voltage direct current system.

Field coupling benefits signal exchange between Colpitts systems

Some evidences have confirmed that field coupling is much effective to realize signal propagation between neurons, and the biological function of synapse connection has also been modulated when field coupling is activated. These theoretical prediction and confirmation are approached on neuron model with electromagnetic induction and magnetic flux coupling is used to describe the effect of field coupling. Neuron is treated as a smart signal processor and neuronal activities can be reproduced in electric circuit by setting appropriate parameters. When time-varying current flows along the inductorium, magnetic flux across the coil is changed and induced electromotive force of the inductor is triggered. Indeed, exchange of magnetic flux between inductoriums (induction coils) can trigger modulation on magnetic field. Therefore, two nonlinear circuits can be connected to reach possible consensus of outputs by using this kind of field coupling. In this paper, two identical Colpitts oscillators are coupled by transformer which is introduced from partial inductance equivalent circuit (PEEC), and the potential differences between circuit nodes are analysed to find synchronization approach under field coupling. An unit matrix is used to derive the Master Stability Functions of the coupled systems, and the synchronization manifold of the system describes the effect of the parasitic elements on dynamical behaviour. It is also found that both of the gain of the oscillators and the coupling coefficient of transformer are important bifurcation parameters for synchronization manifold of the system. Similar investigation is as well practiced on printed circuit board (PCB) and the synchronization approach is confirmed under field coupling. This kind of field coupling provides another effective way to synchronization modulation via continuous exchange of field energy in the coupling device.

Field coupling-induced pattern formation in two-layer neuronal network

The exchange of charged ions across membrane can generate fluctuation of membrane potential and also complex effect of electromagnetic induction. Diversity in excitability of neurons induces different modes selection and dynamical responses to external stimuli. Based on a neuron model with electromagnetic induction, which is described by magnetic flux and memristor, a two-layer network is proposed to discuss the pattern control and wave propagation in the network. In each layer, gap junction coupling is applied to connect the neurons, while field coupling is considered between two layers of the network. The field coupling is approached by using coupling of magnetic flux, which is associated with distribution of electromagnetic field. It is found that appropriate intensity of field coupling can enhance wave propagation from one layer to another one, and beautiful spatial patterns are formed. The developed target wave in the second layer shows some difference from target wave triggered in the first layer of the network when two layers are considered by different excitabilities. The potential mechanism could be pacemaker-like driving from the first layer will be encoded by the second layer.

Performance of Inductive Coupled Power Transfer Versus the Coil Shape - Investigation using Finite Element Analysis

The objective of this paper is to investigate the impact of the spiral coil shape of inductive coupled power transfer on its performance. The coil shapes evaluated are: circular, square and pentagon spiral shapes. The coils are modelled in Ansoft Maxwell software. Simulations are carried out to determine the mutual inductance, coupling coefficient and magnetic flux density. The performance in term of magnetic flux density, mutual inductance and coupling coefficient of the three coils shapes are compared. Of the three shapes, the pentagon is shown to have the best performance in term of its mutual inductance, coupling coefficient and magnetic flux density.

Collective response, synapse coupling and field coupling in neuronal network

Based on an improved neuron model with electromagnetic induction, the collective responses of chain neuronal network are detected. Besides the gap junction coupling between adjacent neurons, magnetic flux coupling is used to describe the effect of field coupling among all neurons. A statistical factor of synchronization is calculated to find the pattern stability dependence on the coupling intensity of junction coupling and field coupling. Bifurcation analysis and wave propagation are presented. It is found that signal propagation can be suppressed by field coupling on the network driven by external stimulus with diversity. Otherwise, network synchronization can be enhanced when external current stimulus are imposed on neurons of the network uniformly.

Electron transport through a linear tri-quantum-dot molecule Aharonov-Bohm interference

Using the non-equilibrium Keldysh Green's function technique, electron transport properties through a two-terminal linear tri-quantum-dot molecule Aharonov-Bohm (A-B) interference are investigated. The conductance as a function of electron energy is numerically calculated. The influence of magnetic flux and interdot coupling strength on the conductance is researched. Fano resonances emerge in the conductance spectrum, and two bound states in the continuum form simultaneously when the interdot couplings take appropriate values. A conductance dip is observed and evolves into an antiresonance band with increasing magnetic flux. The system can be designed as a quantum switch by adjusting the intramolecular couplings.

Phase synchronization between two neurons induced by coupling of electromagnetic field

Based on an improved neuron model with electromagnetic induction being considered, the phase synchronization approaching is investigated on a four-variable Hindmarsh–Rose neuron model by describing the electromagnetic induction with magnetic flux. The effect of time-varying electromagnetic field is described by magnetic flux and the coupling of electromagnetic field is also described by exchange of magnetic flux. It is found that magnetic flux coupling between neurons can induce perfect phase synchronization, the Lyapunov exponent spectrum and local Lyapunov dimension are calculated by using wolf scheme to detect phase synchronization of chaotic time series for membrane potentials. These results confirmed that neurons exposed to external electromagnetic field can induce phase synchronization and appropriate behaviors can be selected. It could give new mechanism explanation for phase synchronization by applying field coupling between neurons.