Gap Flux Research Articles

Influence of Aharonov–Bohm flux and dual gaps on electron scattering in graphene quantum dots

Abstract We show how the Aharonov–Bohm flux (AB) ϕ i and the dual gaps (Δ1, Δ2) can affect the electron scattering in graphene quantum dots (GQDs) of radius r 0 in the presence of an electrostatic potential V. After obtaining the solutions of the energy spectrum, we explicitly determine the radial component of the reflected current J r r , the square modulus of the scattering coefficients ∣c m ∣2, and the scattering efficiency Q. Different scattering regimes are identified based on physical parameters such as incident energy E, V, r 0, dual gaps, and ϕ i . In particular, we show that lower values of E are associated with larger amplitudes of Q. Furthermore, it is found that Q exhibits a damped oscillatory behavior with increasing the AB flux. In addition, increasing the external gap Δ1 resulted in higher values of Q. By increasing ϕ i , we show that the oscillations in ∣c m ∣2 disappear for larger values of r 0 and are replaced by prominent peaks at certain values of E and angular momentum m. Finally, we show that J r r displays periodic oscillations of constant amplitude, which are affected by the AB flux.

New Ventilation Cooling for Modular PM Machines Utilizing Flux Gaps and Rotor Ducts

New Ventilation Cooling for Modular PM Machines Utilizing Flux Gaps and Rotor Ducts

Aharonov–Bohm flux and dual gaps effects on energy levels in graphene magnetic quantum dots

We address the question of how the Aharonov–Bohm flux ΦAB can affect the energy levels of graphene magnetic quantum dots (GMQDs) of radius R. To answer this question, we consider GMQDs induced by a magnetic field B and subjected to two different gaps — an internal gap Δ1 and an external gap Δ2. After determining the eigenspinors and ensuring continuity at the boundary of the GMQDs, we formulate an analytical equation describing the corresponding energy levels. Our results show that the energy levels can exhibit either a symmetric or an asymmetric behavior depending on the valleys K(τ=1) and K′(τ=−1) together with the quantum angular momentum m. In addition, we find that ΦAB causes an increase in the band gap width when Δ1 is present inside the GMQDs. This effect is less significant when a gap is present outside, resulting in a longer lifetime of the confined electronic states. Further increases in ΦAB reduce the number of levels between the conduction and valence bands, thereby increasing the band gap. These results demonstrate that the electronic properties of graphene can be tuned by the presence of the AB flux, offering the potential to control the behavior of graphene-based quantum devices.

Diagnosis of Multiple Defects Within Large Hydroelectric Generator Using Stray Flux and Air Gap (Distance and Flux) Measurements

Diagnosis of Multiple Defects Within Large Hydroelectric Generator Using Stray Flux and Air Gap (Distance and Flux) Measurements

Direct observational evidence of strong CO2 uptake in the Southern Ocean.

The Southern Ocean is the primary region for the uptake of anthropogenic carbon dioxide (CO2) and is, therefore, crucial for Earth's climate. However, the Southern Ocean CO2 flux estimates reveal substantial uncertainties and lack direct validation. Using seven independent and directly measured air-sea CO2 flux datasets, we identify a 25% stronger CO2 uptake in the Southern Ocean than shipboard dataset-based flux estimates. Accounting for upper ocean temperature gradients and insufficient temporal resolution of flux products can bridge this flux gap. The gas transfer velocity parameterization is not the main reason for the flux disagreement. The profiling float data-based flux products and biogeochemistry models considerably underestimate the observed CO2 uptake, which may be due to the lack of representation of small-scale high-flux events. Our study suggests that the Southern Ocean may take up more CO2 than previously recognized, and that temperature corrections should be considered, and a higher resolution is needed in data-based bulk flux estimates.

Boosting energy levels in graphene magnetic quantum dots through magnetic flux and inhomogeneous gap

We study the effects of a magnetic flux and an inhomogeneous gap on the energy spectrum of graphene magnetic quantum dots (GMQDs). By considering the Dirac equation in the infinite mass framework, we can analytically obtain eigenspinor expressions. By applying boundary conditions, we obtain an energy spectrum equation in terms of system parameters such as radius, magnetic field, energy, flux, and gap. In the infinite limit, we recover Landau levels for graphene in a magnetic field. We show that the energy spectrum increases significantly in the presence of flux and a gap inside the GMQDs, which prolongs the lifetime of the trapped electron states. We show that higher flux also produces new Landau levels of negative angular momentum. Meanwhile, we find that the gap increases the separation between the electron and hole energy bands. As shown in the radial probability analysis, flux and gap emerge as influential factors in controlling electron mobility, affecting confinement, and prolonging the presence of quasi-bound states.

Semi‐flooded cooling for high torque density modular permanent magnet machines

AbstractThe authors investigate a semi‐flooded cooling technology for modular permanent magnet machines using flux gaps (FGs) in alternate stator teeth for extra cooling channels. The investigated machine is separated into stationary and rotational components by a polyether ether ketone sleeve. Liquid is directed into the stationary component to achieve a significant temperature reduction, at the same time, avoiding the liquid leakage into the rotating component that will cause an increase in friction losses. The FGs in the modular machine increase the contact area between coolant and machine components, resulting in better cooling efficiency. Furthermore, the FGs contribute to reduced pressure loss by minimising system flow resistance. The influence of the FG width on improving machine cooling efficiency, lowering machine temperature, and reducing pressure losses is delved. Additionally, the investigation considers the impact of inlet and outlet areas to reveal the influences stemming from fluid expansions and contractions in these regions. Computational fluid dynamics (CFD) modelling is employed to simulate the cooling performances of the investigated machines. In addition, the flow network analysis has also been employed to help understand the fluid behaviour within machines. A series of tests have been carried out to validate the CFD modelling.

MICRO-EDD OF INCONEL 800 USING ELECTROMAGNETIC FIELD

Micro-electro-discharge drilling ([Formula: see text]EDD) is a type of non-traditional machining process used for drilling micro-holes of desired dimensions with a high aspect ratio. But, there are no such research works that could have explained the desired accurate circular shape of micro-holes. The need for a more advanced hybrid machining process to improve the overall efficiency in terms of mainly desired circular shape and radial overcut is evolved. In this research work, an electromagnetic field force-assisted micro-EDM process has been carried out on Inconel 800 with a copper tool of 450[Formula: see text][Formula: see text]m. Experimental results showed that measured metal removal rate and tool wear rate decreased for ascending values of magnetic flux density, peak current and gap voltage, whereas circularity increases linearly with an increase in magnetic flux density and also the effects of magnetic field on circularity of micro-holes on Inconel 800 are more predominant than other parameters.

Analysis of the Outer Layer Performance of Fire Protective Clothing

In the present study, an attempt has been made to analyse the protection performance of fire-protective clothing. Various exposures to the same fabric in different configurations result in different protection performances. Box-Behnken experiment design was used to optimize the process parameters such as pick density (P), heat flux (Q), and air gap (D). Through surface methodology response, the relationship among the process parameters such as pick density (P), heat flux (Q), and air gap (D) was established. The experimental multi-parametric equation for calculating the radiant protection time (RT) and flame protection time (FT) was acquired. The fabric used was developed with 2/40 Ne Nomex IIIA yarns. The pick density (P) ranged from 40 to 64 picks per inch, heat flux (Q) ranged from 0.5 to 1.5 cal/cm2/sec, and air gap (D) ranged from 0 to 25 mm. To experimentally determine the level of protection, Stoll criteria were used. The experimental and predicted protection time values show a high correlation coefficient value (R2 = 0.985 for radiant and 0.978 for flame). The maximum improvement in protection was obtained at a high level of air gap (25 mm), low level of heat flux (0.5 cal/cm2/sec) and low level of pick density (40 picks per inch). Obtained results, calculations and equations will help researchers explore the empirical equation of the Box-Behnken model and other surface response curves. The values of protection time, in the specified range of the process parameters, by a single calculation could be possible to obtain.

Investigation of Torque Improvement of Modular Stator Surface-mounted Permanent Magnet Machines with Flux Gaps

Investigation of Torque Improvement of Modular Stator Surface-mounted Permanent Magnet Machines with Flux Gaps

Interactive mechanism between connexin43 and Cd-induced autophagic flux blockage and gap junctional intercellular communication dysfunction in rat hepatocytes

Cadmium (Cd) is a significant environmental contaminant known for its potential hepatotoxic effects. However, the precise mechanisms underlying Cd-induced hepatotoxicity have yet to be fully understood. Therefore, the purpose of this study was to investigate the dynamic role of connexin 43 (Cx43) in response to Cd exposure, particularly its impact on gap junctional intercellular communication (GJIC) and autophagy in hepatocytes. To establish an in vitro model of Cd-induced hepatocyte injury, the Buffalo rat liver 3A cell line (BRL3A) was utilized.In order to elucidate the mechanism by which Cx43 influences Cd-induced hepatocyte toxic injury, inhibitors of Cx43 (Dynasore) and P-Cx43 (Ro318220) were employed in the model. The findings revealed that inhibiting Cx43 and its phosphorylation further compromised GJIC function, exacerbating the impairment, while also intensifying the blockage of autophagic flux. To gain further insight into the role of Cx43, siRNA was utilized to knock down Cx43 expression, yielding similar results. The down-regulation of Cx43 expression was found to worsen the morphological damage induced by cadmium exposure, diminish the cell proliferation capacity of BRL3A cells, and exacerbate the disruption of GJIC and autophagic flow caused by Cd.These findings suggest that Cx43 may serve as a potential therapeutic target for the treatment of liver damage resulting from Cd exposure. By targeting Cx43, it may be possible to mitigate the adverse effects of Cd on hepatocytes.

Torque Generation Mechanism of Dual-Permanent-Magnet-Excited Vernier Machine by Air-Gap Field Modulation Theory

The dual-permanent-magnet-excited vernier (DPMEV) machine has attracted increasing interest for its high torque density. However, it is difficult to analyze due to the complex structure. In this article, the torque generation mechanism of DPMEV machines is analyzed from the perspective of magnetic field modulation. First, based on air-gap field modulation theory, the stator and rotor modulation factor models as well as armature and permanent magnet magnetomotive force (MMF) models are established, respectively. Considering the bidirectional field modulation effect of the DPMEV machine, the modulation process of MMF is derived. Then, by analyzing the modulated armature and permanent magnetic field, the torque generation mechanism is investigated. In addition, a machine with stator flux gap structure is proposed and the reasons for its torque increase are explained. Finally, a prototype of DPMEV machine is manufactured and tested to verify the effectiveness of the analytical results.

Eddy Covariance CO2 Flux Gap Filling for Long Data Gaps: A Novel Framework Based on Machine Learning and Time Series Decomposition

Continuous long-term eddy covariance (EC) measurements of CO2 fluxes (NEE) in a variety of terrestrial ecosystems are critical for investigating the impacts of climate change on ecosystem carbon cycling. However, due to a number of issues, approximately 30–60% of annual flux data obtained at EC flux sites around the world are reported as gaps. Given that the annual total NEE is mostly determined by variations in the NEE data with time scales longer than one day, we propose a novel framework to perform gap filling in NEE data based on machine learning (ML) and time series decomposition (TSD). The novel framework combines the advantages of ML models in predicting NEE with meteorological and environmental inputs and TSD methods in extracting the dominant varying trends in NEE time series. Using the NEE data from 25 AmeriFlux sites, the performance of the proposed framework is evaluated under four different artificial scenarios with gap lengths ranging in length from one hour to two months. The combined approach incorporating random forest and moving average (MA-RF) is observed to exhibit better performance than other approaches at filling NEE gaps in scenarios with different gap lengths. For the scenario with a gap length of seven days, the MA-RF improves the R2 by 34% and reduces the root mean square error (RMSE) by 55%, respectively, compared to a traditional RF-based model. The improved performance of MA-RF is most likely due to the reduction in data variability and complexity of the variations in the extracted low-frequency NEE data. Our results indicate that the proposed MA-RF framework can provide improved gap filling for NEE time series. Such improved continuous NEE data can enhance the accuracy of estimations regarding the ecosystem carbon budget.

Disorder effects in the Kitaev-Heisenberg model

We study the interplay of disorder and Heisenberg interactions in the Kitaev model on a honeycomb lattice. The effect of disorder on the transition between Kitaev spin liquid and magnetic ordered states as well as the stability of magnetic ordering is investigated. Using Lanczos exact diagonalization we discuss the consequences of two types of disorder: (i) random-coupling disorder and (ii) singular-coupling disorder. They exhibit qualitatively similar effects in the pure Kitaev-Heisenberg model without long-range interactions. The range of spin-liquid phases is reduced and the transition to magnetic ordered phases becomes more crossoverlike. Furthermore, the long-range zigzag and stripy orderings in the clean system are replaced by their three domains with different ordering direction. Especially in the crossover range the coexistence of magnetically ordered and Kitaev spin-liquid domains is possible. With increasing the disorder strength the area of domains becomes smaller and the system goes into a spin-glass state. However, the disorder effect is different in magnetically ordered phases caused by long-range interactions. The stability of such magnetic ordering is diminished by singular-coupling disorder and, accordingly, the range of the spin-liquid regime is extended. This mechanism may be relevant to materials like $\ensuremath{\alpha}\text{\ensuremath{-}}{\mathrm{RuCl}}_{3}$ and ${\mathrm{H}}_{3}{\mathrm{LiIr}}_{2}{\mathrm{O}}_{6}$ where the zigzag ground state is stabilized by weak long-range interactions. We also find that the flux gap closes at a critical disorder strength and vortices appears in the flux arrangement. Interestingly, the vortices tend to form kinds of commensurate ordering.

Coupled Electromagnetic–Thermal Modelling of Dynamic Performance for Modular SPM Machines

This paper presents coupled electromagnetic (EM)–thermal modelling of the steady-state dynamic performances, such as torque speed curve and the efficiency map, for surface-mounted permanent magnet machines. One important feature of such a model is that it considers the demagnetization caused by magnet temperature rise at different rotor speeds. EM-only simulations, which often assume that the machines operate under constant temperature, have been widely used in the literature. However, the interaction between EM and thermal performances could lead to very different dynamic performance prediction. This is because the material properties, e.g., magnet remanence, coercivity, and copper resistivity are temperature-dependent. The temperature rise within electrical machines reduces torque/power density, PM eddy current losses, and iron losses but increases copper loss. Therefore, the coupled EM–thermal modelling is essential to determine accurate temperature variation and to obtain accurate EM performances of electrical machines. In this paper, the coupled EM–thermal modelling is implemented for both modular and non-modular machines to reveal the advantages of the modular machine under different operating conditions. The results show that the modular machine generally has better dynamic performance than the non-modular machine because the introduced flux gaps in alternate stator teeth can boost both EM and thermal performance.

Three-dimensional Global Simulations of Type-II Planet–Disk Interaction with a Magnetized Disk Wind. I. Magnetic Flux Concentration and Gap Properties

Giant planets embedded in protoplanetary disks (PPDs) can create annulus density gaps around their orbits in the type-II regime, potentially responsible for the ubiquity of annular substructures observed in PPDs. Although a substantial amount of works studying type-II planetary migration and gap properties have been published, they have almost exclusively all been conducted under the viscous accretion disk framework. However, recent studies have established magnetized disk winds as the primary mechanism driving disk accretion and evolution, which can coexist with turbulence from the magnetorotational instability (MRI) in the outer PPDs. We conduct a series of 3D global nonideal magnetohydrodynamic (MHD) simulations of type-II planet–disk interactions applicable to the outer PPDs. Our simulations properly resolve the MRI turbulence and accommodate the MHD disk wind. We found that the planet triggers the poloidal magnetic flux concentration around its orbit. The concentrated magnetic flux strongly enhances angular momentum removal in the gap, which is along the inclined poloidal field through a strong outflow emanating from the disk surface outward to the planet gap. The resulting planet-induced gap shape is more similar to an inviscid disk, while being much deeper, which can be understood from a simple inhomogeneous wind torque prescription. The corotation region is characterized by a fast trans-sonic accretion flow that is asymmetric in azimuth about the planet and lacking the horseshoe turns, and the meridional flow is weakened. The torque acting on the planet generally drives inward migration, though the migration rate can be affected by the presence of neighboring gaps through stochastic, planet-free magnetic flux concentration.

Demagnetization Analysis of Modular SPM Machine Based on Coupled Electromagnetic-Thermal Modelling

This paper investigates magnet demagnetization characteristics of the modular permanent magnet machine. The influence of flux gaps on magnet flux density, losses distribution, torque and demagnetization are analyzed for different operating conditions. The magnet demagnetizations caused by three sources, such as the PM field, the armature field, and the magnet temperature rise, are individually investigated using the frozen permeability method. Furthermore, coupled electromagnetic (EM)-thermal modelling is also adopted in this paper to fully reveal the advantages of the modular machine in improving machine EM performances. This is essential due to the temperature-dependent properties of the machines, such as the magnet remanence, coercivity, and copper resistivity. For comparison propose, the EM performances with a particular focus on the demagnetization withstand capability for both the modular and non-modular machines are investigated based on the EM-thermal coupling. It is found that, compared to the non-modular machine, the modular machine can achieve higher torque, higher efficiency, and better demagnetization withstand capability.

Comparison of Two Sinusoidal Magnetization Modes of Bonded Magnetic Rings

This paper compares the application of two different sinusoidal magnetization methods of a bonded magnetic ring in a permanent magnet motor. Sinusoidal magnetization of a bonded magnetic ring can be realized by eccentric pole cutting or magnetization with eccentric fixture. Firstly, the parametric optimization of the two methods is carried out by finite−element simulation software, with the goal of minimizing the total harmonic distortion (THD) of Air−gap flux density. Then, when the THD of Air−gap flux density is roughly the same, the cogging torque, output torque, back−EMF, magnet dosage, and other parameters of the two magnets in the application of permanent magnet motor are compared. The results show that the performance of the two methods is similar, and the two methods have their own advantages. Finally, an eccentric bonded magnetic ring and eccentric magnetizing fixture are made, respectively, for experimental comparison. The experimental results are consistent with the simulation results. This paper can provide some reference value for the selection of sinusoidal magnetization mode of a bonded magnetic ring.

Evaluation of gap-filling methods for CH4 flux data based on eddy covariance method in the Lake Taihu, China

Eddy covariance method has become a key technique to measure CH4 flux continuously in lakes. A large number of CH4 flux data was missing due to variable reasons. In order to reconstruct a complete time series of CH4 flux, it is necessary to find an appropriate gap-filling method to insert the CH4 flux data gap. Based on the routine meteorological data and CH4 flux data measured at Bifenggang site in the eastern part of the Taihu eddy flux network during 2014 to 2017, we analyzed the control factors of CH4 flux at the half-hour scale and daily scale. With those data, we tested that whether nonlinear regression method and two machine learning methods, random forest algorithm and error back propagation algorithm, could fill the CH4 flux gap at the half-hour scale and daily scale. The results showed that CH4 flux at the half-hour scale was mainly influenced by sediment temperature, friction velocity, air temperature, relative humidity, latent heat flux and water temperature at 20 cm in the growing season, and was mainly affected by relative humidity, latent heat flux, wind speed, sensible heat flux and sediment temperature in non-growing season. The CH4 flux at the daily scale was mainly affected by latent heat flux and relative humidity. Random forest model was the best in CH4 flux data gap filling at both time scales. The random forest model with the input variables of day of year, solar elevation angle, sediment temperature, friction velocity, air temperature, water temperature at 20 cm, relative humidity, air pressure, and wind speed was more suitable for filling the CH4 flux data gap at the half-hour scale. The random forest model with the input variables of day of year, sediment temperature, friction velocity, air temperature, water temperature at 20 cm, relative humidity, air pressure, wind speed, and downward shortwave radiation was more suitable for filling CH4 flux data gap at the day scale. The interpolation models could fill the data gap better at daily scale than that at the half-hour scale.

A novel approach for modeling MRR in EDM process using utilized discharge energy

The discharge energy generated during the EDM operation characterizes the productivity of the process. The present research attempts to model the material removal process of EDM by obtaining the actual discharge energy during the spark occurrence. The model incorporates the actual discharge conditions by analyzing the real-time V–I waveforms acquired during the EDM operation to determine the discharge power. The model also establishes that discharge power density is a function of applied heat flux and discharge gap. The model verification is conducted by performing a series of experiments on Titanium grade-5 alloy using a full factorial L18 design. The current study implements tool lift time compensation to achieve accurate MRR from the experimental outcomes. The specific energy obtained using the current approach shows better stability compared to previous literature. The parametric studies show gap voltage to be the most significant parameter in influencing the MRR. The main effects plot show the influence of different process parameters on MRR. Additionally, the surface morphology of workpiece and tool surface through SEM and EDS analysis shows the presence of different anomalies and confirms surface alloying. The predicted outcomes of the model show a maximum deviation of 13.05% from the practical evidence.