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Understanding the flow behavior of non-Newtonian fluids from an industrial standpoint is crucial. Many industrial and technical activities, such as the extrusion of polymer sheets, the manufacturing of paper, and the development of photographic films, require non-Newtonian fluids. Heat and mass transport have various manufacturing uses. However, classical heat and mass transfer theories (Fourier and Fick laws) cannot anticipate thermal and solute relaxation time occurrences. The purpose of this investigation is to apply the modified Ohm law to the heat and mass transportation systems, which are established by generalized Fourier and Fick's equations, respectively. A three-dimensional Darcy–Forchheimer flow through a porous medium integrating Hall and ion slip effects is studied for a non-Newtonian fluid known as a "Casson nanofluid" with mixed convection across a stretched surface. To investigate heat transfer augmentation, the modified Buongiorno model for nanofluids is used. It covers practical nanofluid properties as well as the mechanics of random motion and thermo-migration in nanoparticles. These groups of Partial Differential Equations (PDEs) that represent the mathematical model are combined with the proper similarity transformations to create an ordinary differential equations system, which is then resolved using the power of the Lobatto IIIA method. Examples of numerical and graphical data are given to show how various physical constraints affect the variation for velocities, temperatures, mass transfer, dimensionless shear stress, as well as Nusselt and Sherwood numbers. It turns out that lowering the Casson fluid parameters' values reduces the velocity in the spatial coordinates (x, y). A rise in the Hall parameter's values ultimately leads to an improvement in the fluid. This paper sheds light on useful applications including power generation, conservation of energy, friction elimination, and nanofluidics. Nonetheless, the work highlights an important point: by carefully adjusting the Casson parameter, thermophoresis parameter, and Brownian motion parameter, the flow of a Casson fluid, including nanoparticles, may be controlled. [ABSTRACT FROM AUTHOR]

Chitosan, obtained from crustaceans such as crabs and shrimp, has been mainly used in medicine; however, no studies on its use in electronic applications with semiconducting and large storage properties have been reported. Here, we report an n-type semiconducting biomaterial with energy storage properties of 694.4 mJ/m2 consisting of a chitosan nanofiber (ChNF) film with N-type negative resistance. The ChNF generates an alternative-current wave with a frequency of 7.8 MHz at a threshold voltage of 187 MV/m from a direct-current voltage source, with the switching effect of a third-order resistance change. This is due to the Gunn effect, caused by the repeated voltage-induced generation of a strong electric field domain (electric double layer) at the cathode and its disappearance at the anode of the ChNF device. Electron spin resonance spectral analysis showed that conducting electrons of the ChNF were identified as radicals on the aminyl radical, N·H. Paper electronics made from marine products are a great boon to a renewable society. [ABSTRACT FROM AUTHOR]

The injection of the Direct Current (DC) bias component will lead to oversaturation of the transformer core and affect its safe operation. In this paper, the vector magnetic potential A and winding current I are used as the variables solved in the time-step finite element method to simulate the nonlinear transient magnetization characteristics of the transformer under DC bias, and the fixed-point reluctivity is introduced to deal with the nonlinear iterative problem. The field-circuit coupling relationship is established through the electromagnetic induction law, and the two-dimensional time-step finite element model of the transformer core is found. The dynamic J–A hysteresis model is used to deal with the hysteresis effect of iron cores. The fixed-point reluctivity of difference form is introduced to solve the problem of uneven transition and multi-value of magnetization curve with hysteresis in the iterative process. The determination scheme for the equivalent thickness of the core model and the initial iterative value are discussed. A laminated core transformer is made for experiments, and the accuracy and applicability of the model proposed in this paper are verified by comparing the calculation and experimental results. The influence of different voltages and different DC bias components on the electromagnetic characteristics of the transformer is analyzed. [ABSTRACT FROM AUTHOR]

Virtual synchronous generator (VSG) technology has achieved some results in distributed generation networks and enhanced system stability. For problems that may occur in the system due to ignoring parameter linkages, this paper designs a synergistic controller that establishes the connection between the active frequency and the reactive voltage control loop based on synergy theory. As the output of the synergetic controller, the derived control law u is added to the power frequency control in the form of negative feedback. Two disturbance forms, a step disturbance, and a three-phase short-circuit fault, are set up. The conventional droop control and synergetic droop control results are compared using a MATLAB simulation system. Then, the system parameter variations were studied and analyzed, and the sensitivity of the control system with different values of parameters K1, K2, and K3 in the case of a three-phase short circuit was analyzed, which provides a reference guide for selecting parameters in later control optimization. Finally, the control effectiveness of a multi-machine VSG system was tested. The simulation results show that the proposed method has a pronounced effect on making the system stabilize quickly, which illustrates the effectiveness of this technique. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach—an efficient closed-form approximation iterative fitting algorithm based on laser absorption spectra. Through this closed-form approximation iterative fitting, key parameters such as peak value, spectral line width, and normalized signal area serve as indicators for iteration completion, improving the speed without compromising accuracy. Furthermore, it employs the spectral signal of n cycles as a window for further processing, minimizing external interference. The results show that the proposed method averages 9.75 iterations, while the Levenberg–Marquardt fitting method averages 60.17 iterations. The average iteration time for the proposed method is 588.83 ms, a substantial 81.7% reduction compared to the 3210.5 ms required by the Levenberg–Marquardt fitting. These results decisively demonstrate the efficacy of the proposed method in reducing iteration time and enhancing measurement precision. [ABSTRACT FROM AUTHOR]

Timely and accurate assessment of battlefield strikes can improve the utilization of firepower resources and achieve optimal combat effectiveness. However, due to the complexity and uncertainty of the environment in actual war, it is difficult to obtain accurate target damage information, which can be expressed as uncertain, incomplete, or fuzzy decision information in mathematics. In this paper, the stochastic multi-criteria acceptability analysis method is used to evaluate the damage level of the target under an uncertain environment. We establish a set of characteristic indicators for the target damage effect and use the tracking results of maneuvering targets to determine the degree of target damage. Aiming at the uncertainty of the target data, the upper and lower limit dataset of uncertainty is established, and the membership function of the damage characteristic index is given. Combined with the probability density function, the comprehensive membership function of the damage effect is given, the acceptability index of each damage grade is compared, and the damage effect evaluation with uncertain weight information is given. Based on target vulnerability characteristics and combined with multiple damage elements, a target damage assessment model with multiple damage parameters is established, and the damage results are fitted. We study the relationship between target damage efficiency and various damage parameters. For the optimization strike problem of maximum damage to targets with multiple random incomplete information, a maximum damage optimization model is established using the objective function of maximizing damage probability and the missile firepower coverage area as constraint conditions. Experimental results show that the algorithm used in this paper can effectively solve the damage assessment problem under the condition of random incomplete information. [ABSTRACT FROM AUTHOR]

The variation of temperature modifies the magnetic behavior of ferromagnetic cores which may affect the performance of electrical equipment. Therefore, it is imperative to develop a temperature-dependent hysteresis model to precisely calculate electromagnetic characteristics of electrical equipment. In this paper, a Temporal Convolutional Network (TCN) in combination with the Play operator is developed. The proposed model incorporates the temperature-dependent spontaneous magnetization intensity as the model input to introduce the temperature effect. To enhance the accuracy of model training outcomes, the Bayesian optimization approach for automatically selecting network model parameters is provided. The results show that the proposed model can accurately predict the hysteresis characteristics of materials under varying temperature and frequency conditions. [ABSTRACT FROM AUTHOR]

In magnetically coupled wireless charging systems for electric vehicles, it is common for metal objects to enter the charging system. In this case, the strong magnetic field of wireless charging causes an eddy current effect in the metal object, which generates a large amount of heat. This heat accumulation poses a risk of fire. In this paper, a novel metal object detection system designed for wireless charging of electric vehicles is proposed. The system utilizes the principle that the coil impedance and coupling coefficient change with the presence of metal objects, and a set of composite coils is designed to improve the sensitivity of detection. The detection coil and feedback coil in the composite coil are decoupled by reverse series connection. An LC oscillating circuit based on transformer feedback is used to detect metal objects, and the circuit can make good use of the parameter changes of the composite coil. Finally, an experimental platform for wireless charging metal detection in electric vehicles has been built to validate the proposed system. Through testing, it has been demonstrated that the system can detect the presence of metal objects in a timely and accurate manner. [ABSTRACT FROM AUTHOR]

Inevitable process variations (PVT) brought by both the magnetic tunneling junction (MTJ) and MOSFET based on the complementary metal-oxide semiconductor (CMOS) technology become a major obstacle for the mass production of spin transfer torque magnetic random access memory (STT-MRAM). The detriment of the process variations leads to a serious degradation in the fundamental yield with the shrinkage of the technology nodes. However, the conventional data-cell-variation-tolerant (DCVT) sense scheme cannot get the target read yield due to the limited sense margin (SM). To resolve this problem, a DCVT triple sampling non-destructive self-reference sensing scheme (TSNS) is proposed in the paper, which doubles the SM, with lower power consumption and better SM compared with the conventional DCVT sense scheme. Monte Carlo simulation with industry-compatible 65-nm model parameters results show that the proposed sensing scheme shows over 2.5 times higher SM and less power consumption compared to the previous self-reference circuit. The proposed sensing scheme can get the target read yield with lower power consumption. [ABSTRACT FROM AUTHOR]

Installing a three-phase saturated core fault current limiter (TSFCL) is an effective method to limit the increasing short-circuit current in high-voltage alternating current (HVAC) systems. However, the traditional TSFCL uses silicon steels as its working material for the iron core, resulting in poor current-limiting effects, requiring a large DC excitation current, and having a slow response speed. Nanocrystalline alloys have advantages such as a lower saturation point, higher permeability in the unsaturated zone, and a steep B–H curve, making them highly suitable for TSFCL's applications. However, their poor capability which withstands fault hindered their large-scale commercialization. Therefore, this paper proposes a novel hybrid magnetic material based on TSFCL (HMTFCL), where the materials of the working limbs are replaced by nanocrystalline alloys. Compared to TSFCL, the DC excitation current of HMTFCL decreases by 60.5%. And, the HMTFCL reduces the peak short-circuit current by 23%. Last, the magnetic flux intensity inside the working limb of HMTFCL is reduced to zero more quickly. [ABSTRACT FROM AUTHOR]

After the service provider temporarily selects the required edge nodes based on social and storage capabilities, application execution causes the edge nodes to cache part of the application data. Therefore, offloading part of the application computing tasks to the selected edge nodes can effectively improve application execution performance. However, in cases where the resources of user's IoT devices are insufficient, tasks can be further offloaded to traditional edge servers or even to the cloud to maximize application execution efficiency. In this paper, the entire uninstall utility is modeled as a weighted sum of task completion time and energy consumption. Under the premise of considering users' preferences for completion time and energy consumption, a game-based uninstallation algorithm is proposed. The algorithm performs uninstallation by optimizing the uninstallation decision. Based on user preferences, the total system overhead is relatively small. The subsequent simulation experiments show that the algorithm can reduce system overhead on the basis of satisfying user preferences and has relatively good adaptability. [ABSTRACT FROM AUTHOR]

In this paper, two improved ultra-wideband (UWB) balanced power amplifiers based on the flip-chip system-in-package technique and electronic design automation (EDA) are proposed. The conventional approach to system-on-chip (SoC) involves integrating all sub-circuit designs into a single manufacturing process. However, in radio frequency circuits, adopting the SoC approach necessitates intricate matching designs, leading to an increase in development costs. In this study, two types of SiGe unit power amplifiers attempted to achieve a flat S21 response using simpler matching for input/output. The cascode architecture was adopted as the main structure for the first type of unit power amplifier (type I). Subsequently, the design of the second type unit power amplifier was built upon the foundation of the first type, with the only difference being the implementation of two parallel cascode structures (type II), and the primary goal is to enhance both gain and output power compared to the first type. In addition, for this second type unit power amplifier, in conjunction with a quadrature hybrid coupler, the optimal impedance matching value was selected to maintain the flatness of gain across the entire UWB range. Furthermore, the poor performance of S11,22 of these two types of unit power amplifiers was improved by using quadrature hybrid couplers using the WIPD process combined with EDA simulation. Therefore, using flip-chip packaging technology can effectively reduce the increased wafer fabrication costs caused by complex matching designs in active circuits. This improved system has the potential to offer a new practical application for UWB power amplifier design. [ABSTRACT FROM AUTHOR]

In this paper, a fault feature extraction method based on the combination of computational order tracking (COT) and variational mode decomposition (VMD) is proposed to solve the problem of fault feature extraction in a gearbox under variable speed conditions. First, a speed estimation method based on a forward-backward greedy algorithm and Fourier fitting is proposed to solve the speed estimation problem under variable speed conditions. Then, a feature extraction method based on COT, VMD, and fast kurtometry is proposed. COT is used to calculate the order. After the signal is decomposed by VMD, a fast kurtogram is used to filter the modal components with obvious fault features so as to extract fault features. Finally, combined with the analysis of actual equipment examples, the experimental results show that steady-state filtering can effectively filter the background noise and improve the signal-to-noise ratio. The rotation speed estimated by the forward–backward greedy algorithm and Fourier fitting is very close to the actual speed, which verifies that the method proposed in this paper can effectively solve the problem of fault feature extraction of a gearbox under variable speed conditions. [ABSTRACT FROM AUTHOR]

Pyrotechnic device is the key initiating component of weapon system, and its function reliability will directly affect the triggering of detonation and actuation mechanism. In order to enhance the survival ability of pyrotechnic device in intricate electromagnetic interference environment, it is necessary to carry out in-depth research on the electromagnetic protection technique of pyrotechnic device. In this paper, a new electromagnetic protection circuit based on vertical punch through PN junction device is proposed, which monolithically integrates the circuit with polysilicon semiconductor bridge on a single chip. The Electro-static Discharge (ESD) test was carried out according to the method specified by standard electrostatic standard 500 pF/500 Ω/25 kV, and the ESD capability of the proposed new chip was not less than 25 kV. Compared with the electromagnetic protection circuit by transient voltage suppressor diode based on lateral punch through junction device structure, the new chip increases the effective junction area of PN junction, reduces the current density, and increases the current conduction ability and electrostatic roughness of the diode. The new chip has a larger diode effective junction capacitance, which not only improves the ESD capability but also improves the RF protection capability at the same time. [ABSTRACT FROM AUTHOR]

The dependence of residual stresses on differential permeability, determining the so called Magnetic Stress Calibration (MASC) curve, results in the Universal MASC curve after normalizing the stress and permeability axes with the yield stress and the maximum differential permeability of the steel under test, respectively. The motivation of this paper is to illustrate the ability of obtaining the MASC curve of an unknown steel just by measuring its yield stress and maximum differential permeability. The calculated MASC curve of an unknown type of steel, obtained by multiplying the stress and permeability axes of the Universal MASC curve with the yield stress and maximum differential permeability obtained by the stress-strain curve under simultaneous measurement of the permeability, was compared with the actual MASC curve of the same unknown type of steel determined by the classical method, with an agreement better than ±5%. The conclusion is that the actual MASC curve of an unknown type of steel can be determined just by a stress-strain measurement, with simultaneous determination of the maximum amplitude of the differential permeability. [ABSTRACT FROM AUTHOR]

Wireless Power Transfer (WPT) technology has been developing rapidly in recent years. Electric Vehicles (EVs), as an emerging mode of transport, also benefit from the WPT technology. Various EV manufacturers have different coupling structures, which can lead to incompatibility problems between the coils. Meanwhile, due to the human parking, misalignment between the transmitting and receiving coils may occur. To solve these problems, this paper proposes a reconfigurable bipolar coil structure with both interoperability and misalignment tolerance. A 200-W experimental prototype is built, which can achieve 84.33% and 84.76% system transmission efficiency with vertical and horizontal bipolar coils. The effectiveness of the proposed reconfigurable bipolar coil is finally verified by comparing the computational and experimental results. [ABSTRACT FROM AUTHOR]

In this paper, a pole-changing (PC) flux reversal permanent magnet (FRPM) motor is proposed for obtaining a wide speed range. According to the general air-gap field modulation theory, the permanent magnet (PM) magnetic field is modulated into a series of harmonics with different pole numbers by rotor teeth. By introducing an especial PM arrangement, two groups of working harmonics with different pole-pair numbers are generated in the proposed 12-7 PC-FRPM motor due to the modulation of rotor teeth. Based on the calculated slot pitch angles of these harmonics, two winding connections can be obtained for PC operation to achieve two operating modes. The electromagnetic performance of PC-FRPM motor before and after PC are analyzed using finite element analysis and verified by the experimental test results. [ABSTRACT FROM AUTHOR]

To expand an areal density of hard disk drives, bit-patterned magnetic recording (BPMR) using a patterned medium instead of a granular medium as employed in perpendicular magnetic recording is attracting much attention as the next-generation recording technology. To further increase the storage capacity of BPMR, multi-layer magnetic recording can be combined with BPMR. Therefore, this paper considers double-layer magnetic recording with a single-reader/two-track reading technique for the staggered BPMR system, which is performed together with a rate-3/5 modulation code. This paper proposes to utilize a multilayer perceptron decoder to decode and estimate the log-likelihood ratio value of the recorded bit sequence that is obtained from the equalized channel. Simulation results show that at a bit-error rate of 10−4, the proposed system with a double-layer recording medium can achieve an improvement gain of about 1.2 decibel if compared to that with a regular single-layer recording medium, even in the presence of media noise. [ABSTRACT FROM AUTHOR]

Identification of abnormal user behavior helps reduce non-technical losses and regulatory operating costs for power marketing departments. Therefore, this paper proposes an adaptive golden jackal algorithm optimization improved tri-training method to identify user abnormal behavior. First, this paper constructs multiple weak learners based on the abnormal behavior data of users, combined with the method of sampling and putting back, and uses the filtering method to select the tri-training base model. Second, aiming at the problem that the traditional optimization algorithm has a slow convergence speed and is easy to fall into local optimization, the adaptive golden jackal algorithm is used to realize the parameter optimization of tri-training. Based on the electricity consumption data of a certain place in the past five years, it is found that the model can provide stable identification results: accuracy = 0.987, f1-score = 0.973. [ABSTRACT FROM AUTHOR]

Due to the influence of the connection distance between the mutual inductor primary circuit and the metering device secondary circuit, the detection induced current of the traditional method is extremely small, which cannot accurately detect the authentic situation of the wiring, resulting in long detection time and low detection accuracy. Therefore, this paper proposes the automatic detection method of the secondary circuit connection of the metering device mutual inductor. Through the voltage sampling circuit, the secondary circuit measurement data are obtained. Using the pulse signal shaping function and the ADE7753 chip to process the secondary circuit measurement data, the secondary circuit connection fault judgment is determined. According to the judgment, the electric energy meter is used, combined with the secondary circuit measurement data, and the automatic detection of the secondary circuit connection is achieved by calculation. The experimental results show that compared with the traditional detection method, the automatic detection method of the secondary circuit connection of the metering device mutual inductor designed in this paper achieves normal and stable detection induction current. There is no inductive current with an extremely small condition, the detection accuracy is high, and the detection time is short, indicating that the method is suitable for application in actual detection projects. [ABSTRACT FROM AUTHOR]

With the rapid growth of big data information and the continuous iteration progress of CPU architecture, the implementation of a new memory-based cache architecture is urgent and challenging. In the paper, a CPU cache architecture system based on MRAM is built. Firstly, the performance of SRAM, STT-MRAM and SOT-MRAM as caches from 8 kb to 32 Mb is evaluated. Secondly, by summarizing the performance of SRAM and MRAM in different cache levels, a new quad-core CPU cache architecture design scheme with SOT-MRAM as the first level of cache and STT-MRAM as the second level of cache is determined. Thirdly, the built cache system is simulated. A non-inclusive strategy is proposed to replace the inclusive strategy in order to solve the problem of high dynamic energy of STT-MRAM at the second level. The idea of having a quad-core CPU dynamically share the second-level cache is proposed in the paper. Finally, the caching system in the paper is compared with the other previous works, showing up to 60.78% energy consumption advantage and 33.22% leakage power advantage. The proposed MRAM-based CPU cache system and the corresponding cache strategy have potential application with the benefits of low power and less area. [ABSTRACT FROM AUTHOR]

For a resistance random access memory whose insulating matrix is based on transition metal oxides, the underlying microscopic mechanism of its conductive filaments is crucial yet challenging to understand. In this paper, our first-principles calculations predict that titanium oxide prefers its anatase phase over rutile either with or without aluminum doping. We report that an oxygen vacancy in the anatase titanium oxide is stable in its neutral charge state when free of an external field, while it is unstable in the singly and doubly charged states. By calculating the dissociation energy of a single vacancy from a conductive filament, we also study the filament rupture that is modeled by an array of oxygen vacancies, with or without a nearby aluminum dopant. We find that for the dopants at a specific site, the conductive filaments tend to disconnect, which, in turn, enhances the endurance of a non-filamentary resistance random access memory. [ABSTRACT FROM AUTHOR]

Oil impregnated paper bushing is the key equipment connecting a transformer and a power grid. Insulation deterioration may cause partial discharge, which poses a great threat to the safe operation of power systems. In order to realize the online diagnosis for partial discharge and automatic identification of insulation defects of transformer bushings, an ultra-micro-convolutional neural network with only more than 3000 parameters is designed, which adaptively extracts partial discharge characteristics based on small samples, so as to judge the defect category and the reasons. The accuracy rate can reach 97.1%, the computational complexity is lower, the real-time performance is stronger, and it can be easily deployed on various embedded platforms. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries are widely used in various electronic devices as well as electric vehicles, and accurate estimation of the battery capacity is important to ensure safe and reliable operation of the system. However, in practice, the complex working conditions and the limitation of the number of charge/discharge cycles lead to insufficient historical data and inaccurate capacity estimation. In order to improve the adaptability as well as accuracy under different operating conditions, this paper proposes a lithium-ion battery capacity estimation model based on Transformer-Adversarial Discriminative Domain Adaptation (T-ADDA). The model takes charging voltage, charging current, and charging temperature as inputs and uses a transformer network to extract the time series features from the data. Then, adversarial domain adaptation is trained on the source and target domain data by the domain discrimination network of the ADDA model so as to find the domain invariant features between the source and target domains. Finally, the regression network of ADDA is used to achieve cross-domain prediction for the target domain data. The experimental results show that the T-ADDA model can accurately achieve cross-domain prediction and that the average error of prediction under different operating conditions is only 3.9225%. Therefore, the T-ADDA model has good adaptability and accuracy, and it can significantly improve the performance of lithium-ion battery capacity estimation. [ABSTRACT FROM AUTHOR]

Electricity load forecasting is one of the important tasks of the power marketing department, and accurate load forecasting is extremely important to ensure real-time dispatch and security of the power system. In order to obtain accurate and reliable load forecasting results, an ultra-short-term power load forecasting model based on an improved random forest regression algorithm is proposed in this paper. First, data pre-processing is performed on the original dataset. Then the pre-processed time data and historical load data are used as inputs to the model, and optimization of the model using the Gaussian mixture-based tree-structured Parzen estimator algorithm is carried out. Finally, the final prediction results were derived. Experimental analysis was conducted with real load data from a region of China, and the experimental results show that the method has better prediction accuracy than the original random forest algorithm and other traditional machine learning algorithms. [ABSTRACT FROM AUTHOR]

This paper aims to address the challenges of short optical communication distances and high Bit Error Rates (BERs) caused by seawater absorption, scattering, and underwater turbulence. This paper establishes an optical communication channel model based on the Monte Carlo method and simulates and analyzes the process of received optical power attenuation when light is transmitted underwater due to absorption and scattering. The simulation model focuses on the influence of seawater type, transmission distance, receiver position, and angle on the received optical power attenuation. The results of this simulation will provide theoretical support for the development of prototype underwater optical communication systems and experiments in complex environments. To solve the long-range weak signal reception and processing issues in underwater optical wireless communication systems, this paper proposes the design and implementation of an underwater optical wireless communication system using optimized on-off keying high-power light-emitting diode/laser diode modulation technology and avalanche photodiode (APD)/photomultiplier (PMT) receiver modules. In addition, this paper describes the design of the underwater optical communication host computer software, which provides functions such as mode selection, BER monitoring, and file transfer. To test the performance of the proposed system, this paper conducts experiments in a 35 m long pool, fixed platform, and underwater mobile platform, as well as cross-air-water interface optical communication performance test experiments in a complex hydrological environment. The results show that the system achieved a 35 m underwater medium communication distance, transmission rate of 5–20 Mbps, and cross-domain wireless optical communication function under the condition of a BER of less than 10−6. The experiments also revealed that the communication distance decreases as the turbidity of the water body increases and the PMT receiver module selected at the receiver end has a longer communication distance than the APD receiver module. Overall, this paper demonstrates the feasibility of the proposed technology for underwater optical communication systems in complex waters, providing theoretical and data support for the next engineering practice. [ABSTRACT FROM AUTHOR]

In the Bayesian estimation method for the parameters of random distributions, the process of selecting hyperparameters for the prior distributions is one of the important and complex matters that determine the efficiency of the estimation. Therefore, researchers have recently been interested in the expected Bayesian (E-Bayes) estimation as a solution to hyperparameter problems. In this paper, we discuss the Bayes and E-Bayes estimation process based on generalized type-I hybrid censored data from Burr-XII distribution. We used symmetric and asymmetric loss functions, such as squared error, Degroot, quadratic, and linear exponential loss functions. All of these methods were compared using Monte Carlo simulations, using which mean square errors and average of estimators were calculated. Moreover, real data were used as an applied and illustrative example. Finally, some conclusions were drawn in the concluding comments of this paper. [ABSTRACT FROM AUTHOR]

Magneto-mechano-electric (MME) generators consisting of piezoelectric and magnetostrictive materials can convert the stray magnetic noise to useful electric energy for the wireless sensor networks utilizing the magnetoelectric coupling effect and magnetic interactions. In this paper, a scalable engineering approach was proposed to fabricate the laminate MME generator composed of a PZT/Fe–Ga/PZT sandwich structure. The Goss-oriented Fe81Ga19 thin sheet with a large magnetostriction of 244 ppm was produced by a simple and low-cost approach, and the commercial polycrystalline piezoelectric ceramic products (PZT-5H) were used as the PZT layers. The effect of grain orientation, device structure, magnetic field amplitude, and resonance frequency on the electrical output of the PZT/Fe–Ga/PZT MME generator was investigated. The electrical output of the MME generator containing the Goss-oriented Fe81Ga19 thin sheet reached an AC voltage of 4.58 V and the ME coefficient of 76.33 V/cm·Oe under a low excitation magnetic field of 26 Oe at a low resonance frequency of 26 Hz. The MME generator with a Goss-oriented Fe–Ga layer shows 4.7 times higher output voltage and ME coupling coefficient than that with the no-oriented polycrystalline Fe–Ga layer, but only 81% of the latter's resonance frequency. This is related to the significant increase in magnetostriction due to the texture transition after secondary recrystallization annealing at the temperature of 950 °C. This paper provides a very promising solution to meet the self-power supply needs of the Internet of Things utilizing low-value and low-frequency magnetic fields. [ABSTRACT FROM AUTHOR]

This paper reports a study on the production of plasma jets that are out of equilibrium through numerical solutions of electron energy distribution function using a self-consistent methodology. The approach includes the integration of the continuity, momentum, and Poisson equations, which allows the use of the mean electron energy to fit the transport and source coefficients. The paper concurrently presents an analysis of cold plasma generation in a tube. This investigation utilizes COMSOL Multiphysics software to simulate the electric field, potential, and electron density in space. Moreover, the study examines how the dielectric's permittivity impacts plasma propagation. The simulated outcomes are compared with experimental and numerical results. As electron density, ionization rate and electric potential vary during plasma propagation on a dielectric surface, and the permittivity of dielectric materials increases, it promotes an increase in electron density around it. This, in turn, accelerates the ionization front, indicating efficient polarization and accumulation of electric charges, specifically electrons, near the dielectric surface. [ABSTRACT FROM AUTHOR]

Permanent magnet vernier motor (PMVM) is extremely attractive in low-speed large-torque, whereas it always suffers from poor power factor. In order to realize the cooperative improvement of torque and power factor, this paper applies dual-three phase winding in PMVM, and investigates the influence of phase shift on torque and power factor improvement from the perspective of working harmonics and non-working harmonics. The key of this paper is to decompose the armature field harmonics. Through appropriated phase shift, increasing the armature working harmonics to improve the torque, and eliminating the armature non-working harmonics to enhance the power factor. Then the 24/38 DTP-PMVM is designed. Through theoretical derivation and simulation, it is verified that the DTP-PMVM torque is optimal and power factor is improved by phase shift 30°, compared with phase shift 0°. [ABSTRACT FROM AUTHOR]

As the effect of factors like temperature and stress on the magnetic properties of electrical steel materials are gradually being emphasized, many research teams are carrying out related tests. Currently, most studies focus only on the effect of a single factor on the magnetic properties, while in reality, multiple factors exist simultaneously in electrical equipment. Therefore, accurate data of alternating (1D) and rotational (2D) magnetic properties under simultaneous loading of temperature and stress are very important. In this paper, a system based on a vertical rotational single sheet tester (VRSST) with temperature and stress loading parts is designed and constructed. Then, the 1D and 2D magnetic properties under many combinations of different temperatures, uniaxial and biaxial stress are measured and analyzed. [ABSTRACT FROM AUTHOR]

The core loss directly determines the performance of high-frequency transformers. This paper presents an enhanced method for calculating core losses by integrating the LLG equation and Maxwell's diffusion equation. By the method, the losses caused by the rotation of the magnetic moment can be obtained. The loss attributed to domain wall displacement is derived from the total loss by subtracting losses due to magnetic moment rotation, further categorized into the hysteresis loss and the residual loss. The observation of the dynamic variation of nanocrystalline magnetic domains with applied excitation verifies the feasibility of the improved method. Finally, the causes of residual loss generation are also analyzed the model accuracy is verified by comparing the measured and modelled values and the traditional loss separation model. [ABSTRACT FROM AUTHOR]

Fast neutron radiography technology has unique application advantages in the field of non-destructive testing. However, due to the interaction between the gamma rays and the charge-coupled device camera, a large amount of gamma white spots noise is attached to the fast neutron images, which affects the subsequent analysis. In this paper, we propose a simple and effective method to remove gamma white spots noise in fast neutron images. First, the image is down-sampled by the dilated down-sampling method to reduce the influence of noise. Then, the existence of gamma white spots noise is accurately identified by noise detection. Finally, the image is denoised using an improved median filtering method. In order to verify the performance of the proposed method, several commonly used noise reduction methods and the proposed method are used to conduct test experiments on both simulated and fast neutron images, and several image quality evaluation indices are used for quantitative assessment. The results show that the proposed method not only performs well in visual effects but also achieves satisfactory results in evaluation indices. [ABSTRACT FROM AUTHOR]

The damage level assessment of equipment function is an important part of equipment battle damage assessment. In practice, it is often difficult to obtain accurate damage level assessment results due to a lack of damage test data and insufficient modeling. Aiming at this problem, a functional damage assessment method based on Bayesian networks and transfer learning is proposed in the case of small sample test data. First, a Bayesian network model considering the correlation of component damage is constructed, which can more accurately reflect the damage results of equipment when incomplete damage information is obtained. Then, an improved TrAdaboost transfer learning method is proposed for the Bayesian network model, which overcomes the disadvantage that the traditional TrAdaboost method is unable to transfer the results with randomization. Finally, the method proposed in this paper is applied to the Asia network and a certain type of radar vehicle functional damage level assessment process, and the results prove the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Currently, China is using the SF6/N2 gas mixture to gradually replace SF6 in GIS and other equipment. However, gas-insulated equipment will inevitably have local overheating faults. The SF6/N2 gas mixture will decompose to some extent at high temperatures. Impurities such as moisture in the equipment can affect this decomposition process. At present, there are fewer studies on the moisture content of the superheated decomposition of the SF6/N2 gas mixture. Therefore, this paper carries out the SF6/N2 mixed gas superheat decomposition experiment on the constructed superheat decomposition simulation experiment platform. By changing the content of trace water, the influence of trace water on the decomposition of the SF6/N2 mixed gas insulation medium with superheat failure was initially investigated. It is found that trace H2O will promote the generation of SF6 characteristic decomposition products, especially for the generation of SO2F2. The generation of SO2 in the product is the largest, and its generation process needs the full participation of H2O. In addition, the addition of trace water will also improve the yield of nitrogen-containing products NO and NO2, and under the experimental conditions of this paper, by adding the microwater, the yield reaches 100–300 µl/l. The reaction mechanism of H2O decomposition and combining with N atoms to generate NO and NO2 at high temperatures was analyzed in this paper. The thermodynamic properties of the main reaction paths and the equilibrium constants were calculated based on the density functional theory, which provided theoretical references for the further study of the mechanism of SF6/N2 superheated decomposition. [ABSTRACT FROM AUTHOR]

Amorphous alloys are widely used as the core material for motors and transformers, which are subjected to stresses during manufacturing and operation processes. For instance, the compressive stress can influence the magnetic properties of amorphous alloys which leads to local overheating in the device and reduce the reliability. A high-frequency magnetizer with a stress application unit is designed and constructed to investigate the magnetic properties of amorphous alloys up to kilohertz range under stress conditions. The amorphous alloy sheets will fracture under stress because of their poor ductility and brittleness, so this paper uses laminated amorphous alloy sheets as the sample. The hysteresis loops and loss characteristics of amorphous alloys under stress ranging from 20 MPa tensile stress to 20 MPa compressive stress at a frequency of 50 Hz to 4 kHz are investigated. This research can provide data support for the design of cores in electromagnetic devices. [ABSTRACT FROM AUTHOR]

The use of fractal–fractional derivatives has attracted considerable interest in the analysis of chaotic and nonlinear systems as they provide a unique capability to represent complex dynamics that cannot be fully described by integer-order derivatives. The fractal–fractional derivative with a power law kernel is used in this paper as an analytical tool to analyze the dynamics of a chaotic integrated circuit. Using coupled ordinary differential equations of classical order, the complexity of an integrated circuit is modeled. The classical order model is generalized via fractal–fractional derivatives of the power law kernel. Moreover, this paper is concerned with investigating the Ulam stability of the model and conducting theoretical studies in order to analyze equilibrium points, identify unique solutions, and verify the existence of such solutions. By examining the complex dynamics that result in chaotic behavior, these investigations shed light on the fundamental properties of integrated circuits. For the purpose of exploring the non-linear fractal–fractional order system, a numerical algorithm has been developed to facilitate our analysis. MATLAB software has been used to implement this algorithm, making it possible to carry out detailed simulations. Simulating solutions are accomplished using 2D and 3D portraits, which provide visual and graphical representations of the results. Throughout the simulation phase, particular attention is given to the impact of fractional order parameter and fractal dimension. As a result of this study, we have gained a comprehensive understanding of the behavior of the system and its response to variations in values. [ABSTRACT FROM AUTHOR]

Electric devices called motors, which have a history of 100 years, are the devices that use the most electricity in the world. Therefore, the development of high-efficiency motors leads to efficient power use and carbon neutrality. In motor design, the combination of poles and slots is very important. It affects many characteristics including back electromotive force waveform and magnitude, torque and torque ripple, cogging torque, noise and vibration, and efficiency. The most widely used combination of poles and slots is 8 poles and 12 slots. And recently, 8-pole 9-slots are also attracting attention for their various advantages. This paper compares the characteristics of 8-pole 12 slots and 8-pole 9 slots through computer simulation. And to overcome the weaknesses of 8 poles and 9 slots, a multiple of the pole-slot combination is applied. Finally, the comparative values are verified through an experiment. [ABSTRACT FROM AUTHOR]

Accurate estimation of high frequency magnetic core losses under non-sinusoidal excitations is critical to the design of solid-state transformers. This paper proposes a waveform transformation principle, termed the equal derivative transformation (EDT), for piecewise linear flux density waveforms. Under the same maximum flux density, an asymmetric triangular flux density wave can be transformed into a symmetric one with a different frequency in terms of the calculation of core losses, hence the introduction of the improved waveform coefficient Steinmetz equation (iWcSE). The magnetic characteristics of three different toroidal samples (nanocrystalline alloy FT-3KL, amorphous alloy 1K101, ferrite N87) under square excitation at different duty ratios and certain frequencies are measured. Core losses predicted by the model are in good agreement with the measurement. [ABSTRACT FROM AUTHOR]

In this paper, an asymmetrical multi-layer flux barriers permanent magnet (AMFB-PM) motor is proposed. The key of this study is to design the d-q-axis magnetic field reasonably. Firstly, the influence of d-axis inductance on the constant power speed range is analyzed. To optimize the constant power speed regulation performance, an asymmetric flux barrier is employed to adjust the saturation degree of the d-axis magnetic circuit under flux-weakening state. Additionally, the introduction of the asymmetrical flux barrier enables directional deflection of reluctance torque, thereby enhancing the output torque. The analysis results verify the effectiveness of the asymmetrical flux barrier design, which provide a wide speed regulation with constant power operation and high torque density for PM motors. [ABSTRACT FROM AUTHOR]

The value for core hysteresis loss (CHL) resistance in Buntenbach's analogy hysteresis model does not consider the impact of frequency variations. In order to address this issue, this paper proposes a calculation expression for CHL resistance that takes into account the influence of frequency variation through a variable coefficient. The paper analyzes changes in CHL resistance values at different frequencies using hysteresis loss characteristics and circuit theory. To validate the proposed calculation method for CHL resistance, Buntenbach's analogy hysteresis model is applied to model the Epstein frame and magnetically saturated controllable reactor. The comparative results reveal that the proposed calculation expression for CHL resistance is effective. [ABSTRACT FROM AUTHOR]

Seismic instruments are widely used in projects related to geophysical prospecting. Quality data from seismic recorders help to determine subterranean structures with high precision. This paper first introduces a field experiment carried out by deploying seismic stations equipped with two kinds of seismic recorders: GEI (China) and Reftek 130 (USA). Then, the three-component seismograms from GEI are measured and evaluated by comparing with those from Reftek 130 in different aspects: waveforms in time and frequency domain, quantitative analysis by calculation and statistic of correlation coefficient, and signal to noise ratio of seismic signal. Our results were presented by multiple images as the following: (I) Both the time and frequency waveforms of GEI were almost exactly coincident with those of Reftek 130, with over 98.60 percent of the correlation coefficients in the time domain within 0.95–1.0, and all those in the frequency domain above 0.9977. (II) The accurate time lag estimation of GEI's signal was gained by the lag and correlation algorithms based on left–right sliding windows. The GEI clock was 7.3545 ns behind the Reftek 130 clock after every 1 s, which could be utilized to correct the internal clock to improve the synchronous accuracy of seismic recorders. (III) Some seismic signals from GEI were obviously stronger than those from Reftek 130. Our results may potentially promote and support the optimization of seismic recorders and their application in geophysics methods. [ABSTRACT FROM AUTHOR]

It provides a challenge for remaining useful life prediction due to the complexity of the engine degradation process. Therefore, this paper proposes an improved method for engine remaining useful life prediction with long and short memory neural networks (LSTM) and extraction of health indicators for measured parameters. In order to overcome the limitation of measured parameters, a second-order polynomial approach is implemented to construct novel virtual parameters based on the existing parameters and improve the representativeness of the data to the engine degradation process. Then, random forests are used to score the importance of these parameters on the basis of which the higher rated parameters are filtered to reduce the computational burden. For the hyperparameter optimization problem of LSTM, an improved golden jackal optimization method is proposed in this paper, in which chaotic mapping is used to initialize the population to increase the uniformity of the initial population distribution in space. An adaptive method is introduced to improve the exploration and exploration capabilities of the golden jackal algorithm. Finally, the effectiveness of the proposed method is verified by NASA's public dataset. The experimental results show that the R2 of the proposed method is greater than 0.99, the error of mean absolute percentage error is within 3%, and the root mean square error is smaller than 4. The proposed method can provide better predicted performance compared with the traditional methods. [ABSTRACT FROM AUTHOR]

Influenced by multiple factors such as low light intensity, dispersed light, excessive dust, and excessive ambient noise inside cable tunnels, the images captured by cable tunnel inspection robots have shortcomings such as low contrast, low pixel values, and high noise. To improve the image quality, this paper proposes an image enhancement method suitable for cable tunnel inspection robot. First, in this paper, a bivariate hybrid optimization module using the alternating direction multiplier method and the adaptive learning rate acceleration SVRG algorithm is constructed to achieve image pre-processing. Second, a feature extraction module combining a U-Net network and a coordinate attention mechanism is constructed to extract features from the original image and the pre-processed image. Third, the progressive feature fusion module and the image recovery module are constructed to fuse the above features and are combined with the original image to obtain the enhanced image. Finally, the pixel compensation module is constructed to compensate for the features of the enhanced image and recover the lost texture details. [ABSTRACT FROM AUTHOR]

More evidence indicates that central nervous system diseases are related to abnormal regulation of the reciprocal expression of nerve cells and astrocytes. In this paper, we investigated the dynamics of a model incorporating both a neuron and an astrocyte to elucidate the effective interaction between the two components. In this coupled system, external stimulation is applied to the neuron and the astrocyte, respectively. The results showed that after successive stimuli separated by 20 s, both neurons and astrocytes can exhibit the so-called hyperexcitability and nonlinear wave characterized by a decrease in the threshold for activation and an increase in spontaneous firing rate. Furthermore, this paper reveals the potential dynamic changes in the formation and disappearance of hyperexcitability and its transition mechanisms. It can be helpful for further understanding the bifurcation behavior during the progression of central nervous system dysfunction. [ABSTRACT FROM AUTHOR]

3D magnetic inversion is an important method for detecting underwater or underground magnetic objects, which can obtain the physical parameters and geometric features of the target. In order to solve the problem of smooth inversion results of L2 norm regularization, this paper proposes a three-dimensional inversion method of magnetic gradient data based on equivalent source weighting. First, the center position of the magnetic object is estimated using the correlation imaging method, and then the equivalent source weighting function is constructed based on the acquired center position. The weights are calculated according to the distance from the grid to the center of the magnetic object. The further away the grid is, the higher weight will be given. The Euclidean distance and Chebyshev distance are used for calculating the weights of grids. Finally, the equivalent source weighting function is added to the total objective function and solved by conjugate gradient method. Simulation experiments show that the equivalent source weighting function can reduce the root-mean-square error of the inversion results and improve the structural similarity. Compared with the Euclidean distance, the inversion result of the edges and corners of cubic magnetic body model is better when weighted with the Chebyshev distance. The proposed method does not require iterative solving and can avoid generating too smooth results, which improves the inversion accuracy. [ABSTRACT FROM AUTHOR]

Manipulation of untethered millimeter-sized devices (bots) inside the human body has many medical applications. Most of the prior work focused on movement of such bots inside fluids, usually at low Reynolds numbers. Yet, many medical procedures are performed within soft tissues. Bot translation in soft materials differs dramatically from their motion in fluid. This paper focuses on trajectory control of small, untethered spheres driven magnetically in soft media commonly used to simulate tissues. While spherical bot shapes offer the advantage of potentially rapid change in the direction of motion, the main challenge in controlling trajectories through soft materials is their nonlinear and history dependent response forces associated with irreversible medium modification. This paper introduces control modules for manipulating spherical bots in soft media along elementary trajectories of circular and straight segments, from which more general trajectories may be assembled. The proposed control is based on a phenomenological model of soft media response forces. Numerical implementation of the proposed trajectory control along circular trajectories is shown to compare well with the results of experimental tests indicating that the accuracy on the order of the bot radius is readily achievable for trajectories whose radii of curvature is on the order of 10 bot radii. [ABSTRACT FROM AUTHOR]

With the development of Artificial Intelligence (AI) in recent years, the fields of computer, biology, medicine, and aerospace have demanded higher requirements for the processing and storage of information. In this paper, a novel Magnetic Tunnel Junction (MTJ) based Spin-Orbital Torque Magnetic Random Access Memory (SOT-MRAM) composed of Fe3GeTe2 (FGT) is employed as a storage medium in the computer architecture. On the basis of the analysis of the fundamentals, model configuration, characteristics and performance advantages of the FGT based SOT device, a hybrid storage (L1, L2, Last Level Cache) is constructed, with FGT-SOT-MRAM, conventional SOT-MRAM and STT-MRAM replacing the original static random access memory (SRAM) in the novel triple-level CPU cache architecture. This can override the increasing leakage problem of SRAM, while opening up the application of two-dimensional van der Waals ferromagnets in computer systems at the L1 cache level. Meanwhile, an innovative cache optimization scheme is put forward for magnetic memory to better match the performance of FGT-SOT-MRAM to CPU. The simulation results demonstrate that the FGT-based MRAM can achieve up to 38.03% IPC optimization and 53.41% power optimization in the CPU cache system in contrast to the conventional ones. [ABSTRACT FROM AUTHOR]

Our new density functional theory calculations by Gaussian reproduce the bond lengths and Raman spectra of a number of model tetrahedral Si and P compounds [the ten compounds in the SiHxD4−x and SiFxCl4−x (x = 0–4) series, and the tetramer P4O10]. The number of symmetric A1 peaks is determined by group theory, and the center of mass is especially important for the assignment of the three A1 peaks for P4O10 to the two P–O stretches and the O–P–O bend. Additional Gaussian calculations on isolated C3v PO4 tetrahedra, using the P–O bond lengths and O–P–O bond angles from the P4O10 optimization, also reproduce the three peak P4O10 Raman spectra and provide an important guide to the assignment of the two low energy peaks at ∼500 and ∼700 cm−1 to the P–BO (BO = P–O–P) stretch and BO–P–BO bend, respectively, in contrast to all earlier assignments. In the SiFxCl4−x series, there is a regular increase in the Si–F A1 frequency and a decrease in the Si–Cl A1 frequency across the series. Similar trends are seen in the SiClx(CH3)4−x series, and these trends are due to changes in the electron densities in the tetrahedron when an electronegative F or Cl is replaced by a less electronegative Cl or CH3, as measured by previous Si 2p, F 1s, Cl 2p, and C 1s x-ray photoelectron spectroscopy. These considerations serve as a guide for the interpretation of the Raman spectra of silicate glasses in Paper II [Bancroft et al., AIP Adv. 13, 125216 (2023)]. [ABSTRACT FROM AUTHOR]

As the central component of the traveling wave tube (TWT), the thermal deformation of the electron gun is a critical concern. This paper presents a method for analyzing the electromagnetic characteristics of electron gun after thermal deformation. The method adopts multiple grid acceleration technology. Based on this method, a three-dimensional thermal stress analysis tool called the Thermal Stress Simulator (TSS) is developed. In addition, the TSS can be seamlessly coupled with the Thermal Simulator (TS) and the Electron Optical Simulator (EOS) previously developed by our team to realize the analysis of electromagnetic characteristics changes after thermal deformation and provide support for the reliable design of TWT. [ABSTRACT FROM AUTHOR]