Flux Coupling Research Articles

A fractional-order discrete memristor neuron model: Nodal and network dynamics

<abstract><p>We discuss the dynamics of a fractional order discrete neuron model with electromagnetic flux coupling. The discussed neuron model is a simple one-dimensional map which is modified by considering flux coupling. We consider a discrete fractional order memristor to mimic the effects of electromagnetic flux on the neuron model. The bifurcation dynamics of the fractional order neuron map show an inverse period-doubling route to chaos as a function of control parameters, namely the fractional order of the map and the flux coupling coefficient. The bifurcation dynamics of the systems are derived both in the time and frequency domains. We present a two-parameter phase diagram using the Lyapunov exponent to categorize the various dynamics present in the system. In addition to the Lyapunov exponent, we use the entropy of the model to distinguish the various dynamics of the systems. To investigate the network behavior of the fractional order neuron map, a lattice array of $ N\times N $ nodes is constructed and external periodic stimuli are applied to the network. The formation of spiral waves in the network and the impact of various parameters, like the fractional order, flux coupling coefficient and the coupling strength on the wave propagation are also considered in our analysis.</p></abstract>

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.

CONSTRUCTION OF ROTOR ANGLE IDENTIFIER IN VECTOR CONTROL SYSTEMS OF DOUBLE FEED MACHINES

In asynchronous electric drives with vector control on the rotor, it is necessary to calculate the value of the sine and cosine of the angle of rotation of the rotor relative to the stator to form control actions. When using angle sensors, complex structural tasks can arise — placement and reliable mounting of the sensor on the shaft and, accordingly, the task of the overall layout of the unit. For high-power machines, the tasks of developing and creating the design of the sensor itself arise. If serial rotor angular position sensors can be used, the task of placing and mounting the sensor is no less difficult. In these cases it is necessary to deduce the second end of a shaft from the case of the engine with contact rings that complicates its design. Therefore, the urgent need to create more reliable electric drives with vector control systems on the rotor is the synthesis of identifiers of the angle of rotation of the rotor.
 Identifiers are known whose calculation algorithms are based on determining the projections of the flow coupling vectors. In the work with the use of coordinate transducers of projections of stator or rotor current vectors and equations of electromagnetic circuits of an asynchronous machine, the synthesis and subsequent analysis of the properties of the rotor position angle identifier in vector control systems of dual power machines is performed. New equations of the identifier of flux couplings are received, its stability is investigated and on conditions of stability types of electric drives in which it is possible to apply the offered identifier are defined. The stability of the vector control system and sufficient identification accuracy when using the proposed equations and functions are confirmed by the method of mathematical modeling of the recommended electric drive systems in different operating modes.

Spiral waves in a hybrid discrete excitable media with electromagnetic flux coupling.

Though there are many neuron models based on differential equations, the complexity in realizing them into digital circuits is still a challenge. Hence, many new discrete neuron models have been recently proposed, which can be easily implemented in digital circuits. We consider the well-known FitzHugh-Nagumo model and derive the discrete version of the model considering the sigmoid type of recovery variable and electromagnetic flux coupling. We show the various time series plots confirming the existence of periodic and chaotic bursting as in differential equation type neuron models. Also, we have used the bifurcation plots, Lyapunov exponents, and frequency bifurcations to investigate the dynamics of the proposed discrete neuron model. Different topologies of networks like single, two, and three layers are considered to analyze the wave propagation phenomenon in the network. We introduce the concept of using energy levels of nodes to study the spiral wave existence and compare them with the spatiotemporal snapshots. Interestingly, the energy plots clearly show that when the energy level of nodes is different and distributed, the occurrence of the spiral waves is identified in the network.

Mixed-Gas Selectivity Based on Pure Gas Permeation Measurements: An Approximate Model.

An approximate model based on friction-coefficient formalism is developed to predict the mixed-gas permeability and selectivity of polymeric membranes. More specifically, the model is a modification of Kedem’s approach to flux coupling. The crucial assumption of the developed model is the division of the inverse local permeability of the mixture component into two terms: the inverse local permeability of the corresponding pure gas and the term proportional to the friction between penetrants. Analytical expressions for permeability and selectivity of polymeric membranes in mixed-gas conditions were obtained within the model. The input parameters for the model are ideal selectivity and solubility coefficients for pure gases. Calculations have shown that, depending on the input parameters and the value of the membrane Peclét number (the measure of coupling), there can be both a reduction and an enhancement of selectivity compared to the ideal selectivity. The deviation between real and ideal selectivity increases at higher Peclét numbers; in the limit of large Peclét numbers, the mixed-gas selectivity tends to the value of the ideal solubility selectivity. The model has been validated using literature data on mixed-gas separation of n-butane/methane and propylene/propane through polymeric membranes.

Role of IL-33 receptor (ST2) deletion in diaphragm contractile and mitochondrial function in the Sugen5416/hypoxia model of pulmonary hypertension

Pulmonary arterial hypertension (PAH) is a progressive disease of the pulmonary vasculature that leads to right ventricular failure. Skeletal muscle maladaptations limit physical activity and may contribute to disease progression. The role of alarmin/inflammatory signaling in PAH respiratory muscle dysfunction is unknown. We hypothesized that diaphragm mitochondrial and contractile functions are impaired in SU5416/hypoxia-induced pulmonary hypertension due to increased systemic IL-33 signaling. We induced pulmonary hypertension in adult C57Bl/6 J (WT) and ST2 (IL1RL1) gene ablated mice by SU5416/hypoxia (SuHx). We measured diaphragm fiber mitochondrial respiration, inflammatory markers, and contractile function ex vivo. SuHx reduced coupled and uncoupled permeabilized myofiber respiration by ∼40 %. During coupled respiration with complex I substrates, ST2−/− attenuated SuHx inhibition of mitochondrial respiration (genotype × treatment interaction F[1,67] = 3.3, p = 0.07, η2 = 0.04). Flux control ratio and coupling efficiency were not affected by SuHx or genotype. A higher substrate control ratio for succinate was observed in SuHx fibers and attenuated in ST2-/- fibers (F[1,67] = 5.3, p < 0.05, η2 = 0.07). Diaphragm TNFα, but not IL-33 or NFkB, was increased in SuHx vs. DMSO in both genotypes (F[1,43] = 4.7, p < 0.05, η2 = 0.1). Diaphragm force-frequency relationships were right-shifted in SuHx vs. WT (F[3,440] = 8.4, p < 0.05, η2 = 0.0025). There was no effect of ST2−/− on the force-frequency relationship. Force decay during a fatigue protocol at 100 Hz, but not at 40 Hz, was attenuated by SuHx vs. DMSO in both genotypes (F[1,41] = 5.6, p < 0.05, η2 = 0.11). SuHx mice exhibit a modest compensation in diaphragm contractility and mitochondrial dysfunction during coupled respiration; the latter partially regulated through ST2 signaling.

Engineering Li/Na selectivity in 12-Crown-4–functionalized polymer membranes

Lithium is widely used in contemporary energy applications, but its isolation from natural reserves is plagued by time-consuming and costly processes. While polymer membranes could, in principle, circumvent these challenges by efficiently extracting lithium from aqueous solutions, they usually exhibit poor ion-specific selectivity. Toward this end, we have incorporated host-guest interactions into a tunable polynorbornene network by copolymerizing 1) 12-crown-4 ligands to impart ion selectivity, 2) poly(ethylene oxide) side chains to control water content, and 3) a crosslinker to form robust solids at room temperature. Single salt transport measurements indicate these materials exhibit unprecedented reverse permeability selectivity (∼2.3) for LiCl over NaCl-the highest documented to date for a dense, water-swollen polymer. As demonstrated by molecular dynamics simulations, this behavior originates from the ability of 12-crown-4 to bind Na+ ions more strongly than Li+ in an aqueous environment, which reduces Na+ mobility (relative to Li+) and offsets the increase in Na+ solubility due to binding with crown ethers. Under mixed salt conditions, 12-crown-4 functionalized membranes showed identical solubility selectivity relative to single salt conditions; however, the permeability and diffusivity selectivity of LiCl over NaCl decreased, presumably due to flux coupling. These results reveal insights for designing advanced membranes with solute-specific selectivity by utilizing host-guest interactions.

Effect of magnetic induction on the synchronizability of coupled neuron network.

Master stability functions (MSFs) are significant tools to identify the synchronizability of nonlinear dynamical systems. For a network of coupled oscillators to be synchronized, the corresponding MSF should be negative. The study of MSF will normally be discussed considering the coupling factor as a control variable. In our study, we considered various neuron models with electromagnetic flux induction and investigated the MSF's zero-crossing points for various values of the flux coupling coefficient. Our numerical analysis has shown that in all the neuron models we considered, flux coupling has increased the synchronization of the coupled neuron by increasing the number of zero-crossing points of MSFs or by achieving a zero-crossing point for a lesser value of a coupling parameter.

Heat and electric flux coupling of closed-loop thermoelectric generator

Thermoelectric generator (TEG) has been proved as a promising technology for directly converting heat into electricity based on Seebeck effect. On the contrary, this electricity can trigger a solid-state cooling based on conventional Peltier effect. However, these two effects induce a coupling between heat and electric flux, especially for the quantitative relationship still remaining a mystery. Here, we show experimental evidence and theoretical calculation for the coupling by monitoring transient response of fluid temperature and output power. The experimental maximum heat flow in open circuit is 1162 W at cold fluid flow rate V̇c = 0.3 m3/h and fluid temperature difference ΔTf = 70 °C, enhanced by 13% owing to heat compensation from intrinsic coupling in closed-loop circuit. Meanwhile, the measured maximum output power of TEG is 18.2 W, and subsequently decreases to 15.4 W due to the objective existence of coupling. This double-edged sword in coupling vigorously inspires the potential applications in heat-dissipation situation such as spacecraft, electronic components, photovoltaic, refrigerator and etc. Present findings open a novel avenue for manipulating heat-electricity conversion in practical engineering.

Noise induced suppression of spiral waves in a hybrid FitzHugh-Nagumo neuron with discontinuous resetting.

A modified FitzHugh-Nagumo neuron model with sigmoid function-based recovery variable is considered with electromagnetic flux coupling. The dynamical properties of the proposed neuron model are investigated, and as the excitation current becomes larger, the number of fixed points decreases to one. The bifurcation plots are investigated to show the chaotic and periodic regimes for various values of excitation current and parameters. A N×N network of the neuron model is constructed to study the wave propagation and wave re-entry phenomena. Investigations are conducted to show that for larger flux coupling values, the spiral waves are suppressed, but for such values of the flux coupling, the individual nodes are driven into periodic regimes. By introducing Gaussian noise as an additional current term, we showed that when noise is introduced for the entire simulation time, the dynamics of the nodes are largely altered while the noise exposure for 200-time units will not alter the dynamics of the nodes completely.

A review on metal additive manufacturing: modeling and application of numerical simulation for heat and mass transfer and microstructure evolution

Metal additive manufacturing technology has been widely used in prototyping, parts manufacturing and repairing. Metal additive manufacturing is a multi-scale and multi-physical coupling process with complex physical phenomena of heat and mass transfer and microstructure evolution. It is hard to directly observe the dynamic behavior and microstructure evolution of molten pool during additive manufacturing. Therefore, numerical simulation of additive manufacturing process is significant since it can efficiently and pertinently predict and analyze the physical phenomena in the process of metal additive manufacturing, and provide a reference for technological parameters selection. In this review, the research progress of numerical simulation of metal additive manufacturing is discussed. Various aspects of numerical simulation models are reviewed, including: (1) Introduction of basic control method and physical description of numerical simulation models; (2) Comparison of various heat and mass transfer models based on different physical assumptions (heat conduction model; heat flux coupling model; discrete powder particle heat flux coupling model); (3) Applications of various microstructure evolution models [phase field (PF), cellular automata (CA), and Monte Carlo (MC)]. Finally, the development trend of numerical simulation of metal additive manufacturing, including the thermal-flow-solid coupling model and deep learning for numerical model, is analyzed.

SIMULATION OF MOBILE ROBOT CLAMPING MAGNETS BY CIRCLE-FIELD METHOD

Abstract There are a list of complicated tasks need to be solved to increase the working productivity and decrease working cost in modern shipbuilding and ship repair. Good results in solving those problems are shown whether automation with varied robots implementation. The mobile robots able to move and perform given technological operations on different-spaced ferromagnetic surfaces are equipped with own control systems, movers and clamping devices. Usually, reliability and safety of such robots are in direct dependence on designers’ adequate representation of their behavior that is described by mathematical description of separate parts or the robot in the whole to correct control problem solving. The article amply considers the process of the climbing mobile robot clamping electromagnet simulation model building using the improved circle-field method on the example of BR-65/30 clamping electromagnet. The model is built on the basis of interpolated dependences of flux coupling and electromagnetic force on the magnetomotive force and the value of the air gap obtained by numerical calculations of the magnetic field. The dynamic properties of the electromagnet are investigated and a family of its traction characteristics is obtained by the developed model, which can be used for automatic control of the robot clamping device. References 25, figures 5, tables 3.

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.

Multiscale modeling of the effects of temperature, radiation flux, and sink strength on point-defect and solute redistribution in dilute Fe-based alloys

In this work, we investigate the radiation-induced segregation (RIS) resulting from the coupling between the atomic and point defect (PD) fluxes towards the structural defects of the microstructure. This flux coupling depends on the migration mechanisms of PDs and atoms, including thermal diffusion mechanisms and forced atomic relocations (FAR) occurring in displacement cascades. We derive an analytic model of the PD and solute RIS profiles accounting for PD production and mutual recombination, the FAR mechanism, and the overall sink strength of the microstructure controlling the elimination of PDs at structural defects. From this model, we present a parametric investigation of diffusion and RIS properties in dilute Fe-$B$ ($B$ = P, Mn, Cr, Si, Ni, and Cu) binary alloys, in the form of quantitative temperature/radiation flux/sink strength maps. As in previous works, we distinguish three kinetic domains for the diffusion and RIS properties: the recombination domain, the sink domain, and the thermal domain. Both our analytical approach and numerical applications demonstrate that the diffusion and RIS behaviors of PDs and solute atoms largely differ from one kinetic domain to another. Moreover, at high radiation flux, low temperature, and large sink strength, FARs tend to destroy the solute RIS profiles and therefore reduce the overall amount of RIS by forcing the mixing of solute and host atoms, especially close to PD sinks. Finally, we provide quantitative criteria to emulate in-reactor RIS behaviors by ion irradiation.

No need to detune transmitters in 32-channel receiver arrays at 7 T.

Ultrahigh field magnetic resonance imaging facilitates high spatiotemporal resolution that benefits from increasing the number of receiver elements. Because high‐density receiver arrays have a relatively small element size compared with the transmitter, a side effect is that such setups cause low flux coupling between the transmitter and receiver. Moreover, when transmitters are designed in a multitransmit configuration, their relative size is much smaller than the sample, reducing coupling to the sample and thereby potentially also the coupling to the receivers. Transmitters are traditionally detuned during reception. In this study, we investigate, for a 32‐channel receiver head array at 7 T, if transmitter detuning of a quadrature birdcage or of an eight‐channel transmit coil can be omitted without substantially sacrificing signal‐to‐noise ratio (SNR). The transmit elements are operated once with and once without detuning and, in the latter, the received signals are either merged with the array or excluded for image reconstruction. For each of the three measurements, SNR and 1/g‐factor maps are investigated. The tuning of the quadrature and eight‐channel transmit coils during signal reception introduced a 10.1% and 6.5% penalty in SNR, respectively, relative to the SNR received with detuned transmitters. When also incorporating the signal of the transmit coils, the SNR was regained to 98.5% or 101.4% for the quadrature and eight‐channel coil, respectively, relative to the detuned transmitters, while the 1/g‐factor maps improved slightly. For the 32‐channel receive coil used the SNR penalty can become negligible when omitting detuning of the transmit coils. This not only simplifies transmit coil designs, potentially increasing their efficiency, but also enables the transmitters to be used as receivers in parallel to the receiver array, thus increasing parallel imaging performance.

Circular charge and spin currents in a spatially varying Rashba ring in presence of Aharonov-Bohm flux

We investigate magnetic response in a single-channel mesoscopic ring, subjected to Aharonov- Bohm (AB) flux, in presence of spatially varying Rashba spin-orbit (SO) coupling. Simulating the ring system in a tight-binding framework we calculate both charge and spin currents and discuss the interplay between AB flux and SO coupling on these currents. Some anomalous patterns are exhibited following the energy spectrum. Our analysis can be utilized to study the magnetic response in similar kind of spatially varying SO coupled systems and helps us to probe fascinating operations.

Performance improvement of DFIG‐based wind farms using NARMA‐L2 controlled bridge‐type flux coupling non‐superconducting fault current limiter

Doubly-fed induction generators (DFIGs) have drawn prominent interest in the field of wind power generation, but they are vulnerable to grid faults. Grid codes mandate DFIGs to employ a sort of fault ride-through (FRT) technique during faults. Fault current limiters (FCLs) always help to augment the FRT capability of DFIGs and a non-linear controller boosts their performances. In this study, a non-linear auto-regressive moving average-L2 (NARMA-L2) controller-based bridge-type flux coupling non-superconducting FCL (BFC-NSFCL) is proposed to enhance the FRT capability of the wind farm. The authors analysed the performance of the proposed NARMA-L2-based BFC-NSFCL (NL2-BFC-NSFCL) against that of the conventionally used series dynamic braking resistor (SDBR), bridge-type FCL (BFCL), and proportional–integral (PI) controller-based BFC-NSFCL (PI-BFC-NSFCL). They tested the performance of the NL2-BFC-NSFCL through multiple temporary and permanent fault scenarios and carried out the mathematical and graphical analysis in MATLAB/Simulink platform. They found that the proposed NL2-BFC-NSFCL's performance surpasses the performances of the SDBR, the BFCL, and the PI-BFC-NSFCL. Moreover, the NL2-BFC-NSFCL has faster system recovery capability after the occurrence of any fault than other competitors.

Flux Coupling and the Objective Functions' Length in EFMs.

Structural analysis of constraint-based metabolic network models attempts to find the network’s properties by searching for subsets of suitable modes or Elementary Flux Modes (EFMs). One useful approach is based on Linear Program (LP) techniques, which introduce an objective function to convert the stoichiometric and thermodynamic constraints into a linear program (LP), using additional constraints to generate different nontrivial modes. This work introduces FLFS-FC (Fixed Length Function Sampling with Flux Coupling), a new approach to increase the efficiency of generation of large sets of different EFMs for the network. FLFS-FC is based on the importance of the length of the objective functions used in the associated LP problem and the imposition of additional negative constraints. Our proposal overrides some of the known drawbacks associated with the EFM extraction, such as the appearance of unfeasible problems or multiple repeated solutions arising from different LP problems.

Wind Speed, Surface Flux, and Intraseasonal Convection Coupling From CYGNSS Data

AbstractThis study analyzes wind speed and surface latent heat flux anomalies from the Cyclone Global Navigation Satellite System (CYGNSS), aiming to understand the physical mechanisms regulating intraseasonal convection, particularly associated with the Madden‐Julian oscillation (MJO). An advantage of CYGNSS compared to other space‐based data sets is that its surface wind speed retrievals have reduced attenuation by precipitation, thus providing improved information about the importance of wind‐induced surface fluxes for the maintenance of convection. Consistent with previous studies from buoys, CYGNSS shows that enhanced MJO precipitation is associated with enhanced wind speeds, and that associated surface heat flux anomalies have a magnitude about 7–12% of precipitation anomalies. Thus, latent heat flux anomalies are an important maintenance mechanism for MJO convection through the column moist static energy budget. A composite analysis during boreal summer over the eastern north Pacific also supports the idea that wind‐induced surface flux is important for MJO maintenance there.

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.