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Severe vibration of the core of ultra-high voltage (UHV) shunt reactors under operating conditions often leads to the occurrence of suspension electrode, and such a suspended discharge defect will destroy the oil-paper insulation. It is necessary to investigate the influence of vibration on suspended discharge when determining the best operating condition of UHV shunt reactors. The vibration frequency of the suspension electrode and the phase difference between the applied voltage and the vibration are studied by simulation and experiment. The simulation results show that the phase difference between the voltage and the vibration parameters will lead to an increase in the surface maximum field strength. The distortion of the field intensity caused by several typical vibration frequencies of reactor vibration is ranked (in ascending order) thus: 100, 300, 50, and 200 Hz. There is a coupling relationship between the phase difference and the vibration frequency on the suspended discharge, which will lead to an inconsistency between the field intensity and each single factor. The partial discharge test results of the collision between the suspension electrode and the high-voltage electrode show that the discharge generated by vibration at 100 Hz is much higher than that at other frequencies, followed by those at 300 and 50 Hz, and the discharge generated by vibration at 200 Hz is very small. When the phase difference of voltage advance vibration is between 0° and 90°, the quantity of local discharge is large. When the phase difference is between 90° and 180°, the local discharge is small.

Partial Discharges (PDs) are a significant factor in reducing the insulation life of traction transformers. In recent years, the Acoustic Emission (AE) method has become the most advanced method for detecting PD signals in transformers. The AE method utilizes AE sensors placed on the transformer tank to detect ultrasonic signals emitted by PD and determine the Time Of Arrival (TOA) of the head wave. The windings and cores of a traction transformer consist mainly of metal, which greatly affects the propagation of PD ultrasonic waves. This paper establishes a 110 kV “pressure acoustic, transient” physical field model of the traction transformer with dimensions of 4.63 × 1.48 × 2.84 m3. The model is used to carry out the PD pressure acoustic physical field simulation study of the traction transformer, to clarify the physical characteristics of the ultrasound of the PD defects, and to establish observation points on the transformer tanks to receive ultrasonic time-domain waveforms for PD detection. The simulation results indicate that PD ultrasonic waves exhibit complex propagation characteristics, including reflection, refraction, and reverberation, as they pass through the windings and cores to the observation points. The TOA of the head wave in the ultrasound time-domain waveform is indicated by the first maximum value of the wave crest line. Finally, this paper proposes a multi-level localization method based on the AE method to determine which winding generates the PD in the large-scale traction transformer using only four dynamically moving observation points.

The regular operation of transformers is significantly impacted by the insulation effectiveness of the transformer insulation oil–paper. In order to explore the mechanism of the influence of an electric field on the thermal decomposition performance of insulating oil–paper, this paper simulated the process of electrothermal coupling decomposition of insulating oil–paper from the micro-level based on molecular dynamics. It was determined that the insulating oil is made up of three 16-carbon hydrocarbon molecules, while the insulating paper is made up of 30 fibrous disaccharide molecules. Using the molecular dynamics simulation approach, the pyrolysis of the insulating oil and insulating paper under various electric field strengths was simulated, and the lysis of reactants and the distribution of products were statistically examined. This paper also studied how the electric field affected the microscopic process of the insulating oil–paper pyrolysis. The findings demonstrate that under the influence of electrothermal coupling, the big molecules of the insulating oil and insulating paper are pyrolyzed to produce a variety of tiny molecules. For the insulating oil, it is easily subject to electron displacement polarization under the influence of an external electric field since it contains non-polar molecules, especially impacted by an electric field of 100 V/m. For the insulating paper, its polar nature, on the other hand, makes itself a good candidate for guiding polarization when exposed to an external electric field. So, the greater the electric field strength is, the greater the impact on the thermal decomposition of the insulating paper is.

As an important high-voltage electrical equipment in the substation, the performance stability of high-voltage current transformers is directly related to the safe operation of the power grid. The insulating medium of the traditional oil-immersed current transformer is an oil-immersed paper structure. When the oil-immersed current transformer malfunctions, it is easy to cause fire and explosion, resulting in very serious consequences. If the transformer with the epoxy resin impregnated paper insulation medium is used, there is no oil and gas inside; thus, it has high reliability, which greatly reduces the risk of fire and explosion. Based on this, considering the application research on the high-voltage current transformers epoxy resin impregnated paper technology, this paper mainly analyzes some precautions for the application of epoxy resin impregnated paper technology to the high-voltage current transformers from three aspects: the research on the insulation performance of the epoxy resin impregnated paper transformers, the research on the mechanical properties, and the research on the relevant experimental methods of the epoxy resin impregnated paper technology application to the high-voltage current transformers.

Frequency Domain Spectroscopy (FDS) is widely used to estimate oil–paper insulation. The high moisture and long aging change the FDS characteristics of the insulating oil–paper, so normalization processing is required. Still, the choice of single activation energy needs further research. This paper studies the FDS characteristic of oil–paper insulation samples with different moisture and aging degrees and improves the traditional temperature correction method. The enhanced Arrhenius model uses the segmented activation energy to make the normalized FDS curve coincide better with the target curve, and the error is reduced. In addition, to verify the method’s effectiveness, this paper proposes an iterative correction process. It corrects the tan δ-f curve of the bushing with an aging time of 800 h based on segmented activation energy, and the overall normalization effect is improved.

We report a liquid metal microstrip antenna on a printing paper whose resonant frequency was tunable by folding the paper. The gallium-based alloy was used as liquid metal, which is instantly oxidized in ambient air. The oxidized liquid metal is easily wettable on printing paper surfaces, while it is non-wettable on laser-printed toner surfaces. An antenna with a 3 mm wide and 39 mm long copper-liquid metal overlapped-feedline linked to the liquid metal microstrip rectangle-shaped patch (40 × 31 mm2) was designed. The antenna pattern was printed on a printing paper using a laser printer. A liquid metal soaked roller was rolled on the antenna pattern printed paper, resulting in a liquid metal pattern where there was no toner. The resonant frequency of the liquid metal on the paper microstrip patch antenna was 2.88 GHz with −18.5 dB S11. The measured characteristics of the antenna were in good agreement with the simulation results. When the antenna was folded, the resonant frequency was changed to 2.68 GHz (x-axis folding) or 2.72 GHz (y-axis folding). Liquid metal on paper fabrication is simple but effective for creating custom-designed antennas that are easily re-designed and fabricated in the field.

The parameter of tensile strength for transformer bushing insulating paper occupies an important position in the structural design and life evaluation of transformer bushing. In order to precisely achieve the effect of aging time and moisture content on the tensile strength of transformer bushing paper, transformer insulating paper samples with a thickness of 0.13 mm were prepared for tensile strength and dielectric strength testing under different moisture contents and aging states. The results show that the tensile strength (MPa) of insulating paper decreases linearly in the range of 0–648 h under accelerated thermal aging at 130 °C. However, there is a more serious exponential decline in the tensile strength (MPa) of insulation paper with its moisture content is boosted. The moisture content in insulation paper is the most important factor for insulation paper deterioration in oil-impregnated paper insulation equipment, which could accelerate the end of insulation service life. The value of capacitance increment ΔC of the insulation paper samples displayed closely linear growth with a moisture content from 0.5% to 5.9%. Strictly controlling the moisture content by monitoring the ΔC value of transformer insulation paper is of significance for prolonging its service life.

Accurate monitoring of insulation aging of oil-paper insulation power equipment such as oil-immersed transformers is a key and difficult point in the field of high voltage research. In this paper, a method based on Raman spectroscopy to diagnose the aging degree of oil-paper insulation is discussed. Raman detections of the samples were carried out on a self-built Raman detection platform. The partial least squares method was used to extract and analyze the spectral features. The aging time of the sample was used to supervise the feature extraction of oil-paper insulation Raman data, and the intrinsic mathematical relationship between the Raman features of oil-paper insulation and the aging was excavated. Finally, a quantitative aging diagnostic model based on Raman spectral features of oil-paper insulation to predict its aging state was built with the assistance of the support vector regression method. The results of aging time prediction for 30 test samples show that the mean square error is 0.0123 and the square of correlation coefficient is 0.987. The proposed method provides a new idea for Raman aging diagnosis of oil-paper insulation.

In this study, we composite coated silica nanoparticles with functional groups on paper to form a double-size surface roughness, then hexafluorobutyl methacrylate was polymerized with 3-trimethoxymethylsilyl propyl methacrylate (TSPM), a one-step method is used to prepare a hydrophobic polymer with low surface energy (PHFMA-co-TSPM), and the superhydrophobic surface was prepared by hydrophobic treatment of the paper with a low surface energy polymer. Further tests show that the superhydrophobic paper prepared by this method not only exhibits extremely strong hydrophobicity, but also has strong stability, transparency, and self-cleaning properties.

The accuracy of insulation defect diagnosis based on the dielectric spectrum response is severely influenced by temperature for oil-impregnated paper bushing. The dielectric loss (tan δ) mathematical model with a temperature–frequency factor to restrict the application of the frequency domain dielectric spectrum (FDS) for insulation diagnosis is not clear. In this paper, five temperatures are selected to study the frequency temperature characteristic of the FDS and polarization current for oil-impregnated paper bushing. The experimental results show that the temperature has different effects on the lower frequency (0.001 Hz–1 Hz) and higher frequency (1000 Hz–10 kHz) of FDS. With the increasing temperature, the lower frequency tan δ of 1 mHz–1 Hz shows a better pattern of exponential growth, while the higher frequency tan δ at 1 kHz–10 kHz shows the declining law with the rising temperature. With the increasing temperature, the polarization current shows a better pattern of exponential growth, while resistance obviously shows the declining law of the exponential pattern. The FDS curve of oil-impregnated paper bushings can be amended by the mathematical model of tan δ for the dielectric response on site for accuracy diagnosis.

Thermodynamic properties of cellulose insulation paper are vital factors affecting the life of a transformer; in order to obtain cellulose insulation paper with better thermodynamic properties, three types of silane coupling agents—3-aminopropyltriethoxy silane (KH550), 3-glycidoxypropyltrimethoxy silane (KH560), and 3-methacryloyloxypropyltrimethoxy silane (KH570)—were grafted on the surface of nano-SiO2, and thermodynamic properties of cellulose modified with nano-SiO2 were explored. The molecular dynamics method was used to establish a composite model of nano-SiO2/cellulose. Also, different silane coupling agent grafted nano-SiO2/cellulose models were established to explore the effect of mechanical properties, interaction energy, free volume, and hydrogen bonds on thermodynamic properties. The results showed that KH550 was the best modification of the nano-SiO2/cellulose system among the three grafted silane coupling agents because KH550 grafted on the surface of nano-SiO2 formed more hydrogen bonds in the cellulose system. The interfacial bonding strength between the nano-SiO2 and the cellulose chains can effectively improve the thermal stability of the cellulose insulating paper.

A study of plasma treatment of clay-coated paper is presented. The wettability of the paper surface before and after the plasma treatment was determined by measuring the water contact angle and surface free energy. The appearance of the surface-functional groups was determined by using high-resolution X-ray photoelectron spectroscopy, while changes in the surface morphology were monitored by scanning electron microscopy. Already after 0.25 s of the plasma treatment, the paper surface improved its wettability. The X-ray photoelectron spectroscopy analyses showed a gradual increase of oxygen-rich functional groups on the surface while scanning electron microscopy analyses did not show a significant modification of the morphology and no alternation of the surface structure after the plasma treatment.

Cantilevers are one of the most utilized mechanical elements for acoustic sensing. In comparison to the edge clamped diaphragms of different shapes, a single edge clamped cantilever makes an acoustic sensor mechanically sensitive for detection of lower pressure. The aspect ratio of cantilevers is one of the most important parameters which affect sensitivity. Herein, we present a mathematical, finite element method and experimental analysis to determine the effect of the aspect ratio on the resonant frequency, response time, mechanical sensitivity, and capacitive sensitivity of a cantilever-based acoustic pressure sensor. Three cantilevers of different aspect ratios (0.67, 1, and 1.5) have been chosen for sound pressure application to detect capacitance change. The cantilever with the smallest aspect ratio (0.67) has the highest response time (206 ms), mechanical sensitivity, and capacitive sensitivity (22 fF), which reduce after increasing the aspect ratio. The resonant frequency of the cantilever was also analyzed by applying sweep in sound frequency. It was found to be minimum for the cantilever with the smallest aspect ratio (510 Hz) and increases with an increase in the aspect ratio. We have applied the garage fabrication process using low cost, recyclable, and easily available materials such as metal coated polymer sheets, mounting tapes and glass slides as alternative materials for expensive materials.

In order to improve the thermal stability of insulation paper cellulose in micro-water environment, the molecular simulation was used to compare and analyze the thermal stability of polysiloxane-grafted cellulose with 3% micro-water content in the present study. The static mechanics, glass transition temperature and number of hydrogen bonds are used to characterize the thermal stability of insulating paper cellulose in this paper. First, analysis of the mechanical properties of the model demonstrated that the value of the elastic moduli (E) and bulk moduli (K) of the grafted model were greater than those of the ungrafted model at each temperature. Second, the glass transition temperature of the grafted model was 60 K higher than that of the ungrafted model. Finally, the analysis of the radial distribution function (RDF) and hydrogen bonding showed that polysiloxane-grafted insulation paper cellulose can reduce the number of hydrogen bonds formed between the water molecules and the cellulose chains, which can reduce the damage caused to the cellulose chains by the water molecules. Therefore, the present study shows that the polysiloxane-grafted insulation paper cellulose can improve its thermal stability in micro-water environment.

We have coated phase change materials (PCMs) on rough and flexible substrates to achieve multicolor changeable devices. The principle of the device is based on an earlier discovery that lights have strong interference effect in PCM films, leading to various colors by reflection. In this work, paper substrates are laminated by parylene layers to protect the device from water before coated with functional PCM films. The PCM-based color printing (PCP) on paper is not affected by rough surfaces and shows a similar color appearance as that on smooth surfaces. In particular, the color-printed device can be patterned by UV lithography to display a clear and tunable optical image, and it exhibits a low sensitivity to the angle of view. Such PCP has potential applications for low-cost, disposable, and flexible displays.

We presented a distance-based detection method for visual quantification of mercury ions on a microfluidic paper-based analytical device (μPAD). Dithizone in NaOH solution was used as chromogenic reagent and deposited onto paper channel delimited by hydrophobic wax barrier. Reactions happened between mercury ions and dithizone to form an insoluble colored complex, producing colored precipitate on the paper channel. The length of colored precipitate could be readily measured using the printed ruler along each device. The length of precipitate increase linearly with the mercury concentrations, mercury in sample solution could be quantified by measuring the length of the colored precipitate. Being free of any electronic instruments, this method has the advantages of portability, ease of use, low cost and disposability. This presented method was used to detect mercury ions in a synthetic sample, demonstrating its potential in on-site and real time analysis.

The effect of silica nanoparticle (Nano-SiO2) dopants on insulation paper cellulose, and the interaction between them, was investigated using molecular dynamics simulations. The mechanical properties, interactions, and cellulose-Nano-SiO2 compatibility of composite models of cellulose doped with Nano-SiO2 were studied. An increase in Nano-SiO2 size leads to a decrease in the mechanical properties, and a decrease in the anti-deformation ability of the composite model. The binding energies and bond energies per surface area of the composite models indicate that the bonding interaction between spherical Nano-SiO2 and cellulose is the strongest among the four different Nano-SiO2 shapes that are investigated. The solubilities of the four composite models decrease with increasing Nano-SiO2 size, and the difference between the solubility of pure cellulose and those of the composite models increases with increasing Nano-SiO2 size. Good doping effects with the highest cellulose-Nano-SiO2 compatibility are achieved for the cellulose model doped with spherical Nano-SiO2 of 10 Å in diameter. These findings provide a method for modifying the mechanical properties of cellulose by doping, perhaps for improving insulation dielectrics.

Paper-based batteries represent a new frontier in battery technology. However, low-flexibility and poor ionic conductivity of solid electrolytes have been major impediments in achieving practical mechanically flexible batteries. This work discuss new highly ionic conductive polymer gel electrolytes for paper-based battery applications. In this paper, we present a poly(vinylidene fluoride-hexafluoropropylene) (PVDH-HFP) porous membrane electrolyte enhanced with lithium bis(trifluoromethane sulphone)imide (LiTFSI) and lithium aluminum titanium phosphate (LATP), with an ionic conductivity of 2.1 × 10−3 S cm−1. Combining ceramic (LATP) with the gel structure of PVDF-HFP and LiTFSI ionic liquid harnesses benefits of ceramic and gel electrolytes in providing flexible electrolytes with a high ionic conductivity. In a flexibility test experiment, bending the polymer electrolyte at 90° for 20 times resulted in 14% decrease in ionic conductivity. Efforts to further improving the flexibility of the presented electrolyte are ongoing. Using this electrolyte, full-cell batteries with lithium titanium oxide (LTO) and lithium cobalt oxide (LCO) electrodes and (i) standard metallic current collectors and (ii) paper-based current collectors were fabricated and tested. The achieved specific capacities were (i) 123 mAh g−1 for standard metallic current collectors and (ii) 99.5 mAh g−1 for paper-based current collectors. Thus, the presented electrolyte has potential to become a viable candidate in paper-based and flexible battery applications. Fabrication methods, experimental procedures, and test results for the polymer gel electrolyte and batteries are presented and discussed.

Wireless Power Transmission (WPT) is widely used. In practical engineering applications, the transmitter and receiver of a stable and reliable WPT system need to establish not only a power transmission channel but also a data transmission channel to realize closed-loop control and information interaction. In this paper, a novel simultaneous wireless power and data transfer system based on a series–parallel (SP) resonant network is proposed. The system integrates an SP higher-order resonant network with series carrier injection, which makes power transmission and data transmission share a magnetic coupling channel. The isolation between power and data is realized by exploiting the frequency characteristics of the compensation network, thus realizing efficient power transmission and data transmission. In this paper, accurate and detailed mathematical modeling of the system is conducted, and the gain characteristics of the power transmission channel and the data transmission channel are demonstrated. Meanwhile, the mutual interference between the two channels is analyzed, and a feasible and effective parameter design method is developed. Finally, an experimental prototype with an output power of 16 W and a backward data rate of 100 Kbps is constructed to verify the feasibility of the proposed system and the correctness of the parameter design.

This paper deals with self-absorption in a cylindrical high-pressure Hg–TℓI discharge for which local thermodynamic equilibrium can be assumed. Calculations of the densities of species, especially thallium, have been performed using a parabolic temperature profile and a constant mercury/thallium ratio throughout the discharge tube. This paper focuses on studying the self-absorption thallium lines by comparing them to those of mercury. Particular attention has been paid to the study of the additive effects on the self-absorption of spectral intensities.

Transformer oil plays the role of heat dissipation and insulation in power transformers, and its electrical and thermal characteristics are directly related to the stable operation of the transformer. At the same time, it is important to master the electric–thermal characteristics of transformer oil for transformer state evaluation, latent fault prediction, and maintenance planning. Based on this, the gas production rule and electrical characteristics of transformer oil under accelerated aging are studied in this paper. First, the experimental platform for power transformer aging is established to accelerate the aging of power transformers. Second, the accelerated aging transformer oil is taken as the research object, and the power frequency, DC, lightning, and gas chromatography are measured and analyzed. Finally, a transformer oil aging evaluation model is established, which takes into account four factors: carbon and oxygen gas factors in transformers, life loss factors calculated by hotspot temperature, hydrocarbon gas factors dissolved in transformer oil, and oil quality factors, and conducts aging evaluation. The conclusion shows that the T parameter proposed in this paper can effectively evaluate the quality of transformer oil. When T is less than or equal to 0.6, there is no aging of the oil. When T is greater than 0.6 and less than 1, the transformer oil has been aging, but it is not manifested. Those are parameters whose chromatography and breakdown voltage are not far beyond the IEEE standard. When T = 1, the aging of oil with significant changes in gas content and breakdown voltage can be observed. When T is greater than 1, the oil has undergone serious aging.

Inter-turn short circuit fault (ISCF) is the main fault type of dry-type air-core reactors (DARs), and the reactor burnout event caused by winding ISCF seriously threatens the safe and stable operation of the electric power system. In order to effectively curb the further worsening of ISCF in DARs, a fault detection method based on frequency response analysis was proposed. First, the effect of ISCF on the frequency response curve of the windings was investigated based on the distributed parameter model of DARs. Then, four sets of eigenvalues were proposed for ISCF diagnosis based on the influence law and curve data analysis theory. Finally, based on the eigenvalues, the support vector machine model optimized by the sparrow search algorithm was used to effectively classify the degree of ISCF of the reactor, and the accuracy reached 96%. Furthermore, a test platform was built based on the theoretical analysis for experimental verification, and the test results are consistent with the simulation results. Hence, the method proposed in this paper could effectively classify the ISCF and its severity in DARs. The research in this paper could provide effective guidance for the diagnosis of ISCF in DARs.

A frequency and beam reconfigurable antenna based on encoded reflectors for Wi-Fi and IoT applications is proposed in this paper. By modifying the traditional Alford antenna, extending the transmission line, adding radiation arms, and loading PIN diodes, the frequency reconfigurable function can be realized. Then, the three-layer reflectors are loaded around the antenna. The pattern reconfigurable function of the antenna can be achieved by encoding the operating states of the PIN diodes on the reflectors. The antenna is fed from the bottom via a coaxial transmission line, and the dimension of the antenna is 0.99λ0 × 0.99λ0. The simulated and measured results show that the working frequencies of the antenna can be switched between 1.65, 2, and 2.4 GHz with bandwidths of 2.4%, 4.4%, and 1.2%, gains of 3, 4.5, and 2 dBi, and efficiencies of 48.8%, 75.0%, and 49.6% in directional mode, respectively. The antenna works in omnidirectional radiation mode with a scanning accuracy of 10°, bandwidths of 6.6%, 4.9%, and 0.8%, gains of 0.3, 0.52, and −2.8 dBi, and efficiencies of 73.1%, 74.1%, and 51.9% at 1.65, 2, and 2.4 GHz, respectively, when the PIN diodes are tuned in off states. The antenna proposed in this paper offers several advantages, including a wider frequency band, a broader angular range, and higher precision compared to other frequency and pattern reconfigurable antennas. The antenna can be utilized for Wi-Fi and IoT communication, thereby reducing the number of antennas, enhancing communication quality and accuracy, and improving device integration.

Under turbulent conditions, the images of objects may be severely blurred and become unrecognizable because of the complex aberrations introduced by turbulence. Using adaptive optics (AO) to compensate for these wavefront aberrations can theoretically solve the problem of image blurring under turbulent conditions. However, due to its small field of view and high cost, the AO system is difficult to widely use. In recent years, using the technology of light field photography to correct turbulence images has been proposed. However, the current studies are either based on the structure of the non-focused light field camera, which makes it hard to achieve good image quality, or on the need to redesign the core sensor of the non-focused light field camera, which greatly increases the cost and complexity. We believe that the structure of a focused light field camera has a good potential for turbulence image correction and propose a new method of achieving a corrected focused image using a focused light field camera in this paper. We propose to use phase estimation instead of depth estimation for a focused light field camera and phase maps instead of a depth map as the basis for achieving a focused image. By the proposed method, a corrected focused image with a large field of view under turbulent conditions is achieved without using independent wavefront correction devices or redesigning the light field camera. The experiments are given to verify the effectiveness of the proposed method under strong turbulent conditions in the laboratory and real turbulent conditions in the outdoors. The proposed method in this paper provides a new and low-cost solution for image correction for optical imaging systems under turbulent conditions, so it has a high application value.

In recent years, the rapid development of photovoltaic (PV) power generation has led to an increased focus on accurate forecasting of PV power output. Interval forecasting, which provides uncertainty measurement information for forecasting results, has become a hot research topic in this field. However, the accuracy of single models or traditional multi-model forecasting methods is often insufficient for meeting the forecasting requirements. In addition, interval forecasting places higher demands on the learning and generalization capabilities of forecasting models. To address these issues, this paper proposes an intelligent multi-model forecasting method based on output features clustering and convolutional neural network–long short term memory (CNN–LSTM) for PV power interval forecasting. First, multiple feature indices are constructed to represent the differences in PV output features for different months. The intelligent clustering method is then employed to achieve the multi-model clustering for forecasting model. Finally, CNN–LSTM is utilized to implement the PV power interval forecasting. The combination of CNN and LSTM effectively improves the modeling accuracy of the intelligent forecasting model. Based on actual data from PV power stations, the method described in this paper narrows down the forecasting interval compared with the single model, reducing prediction interval normalized average width by more than 4%.

In order to obtain a flexible strain sensor with higher sensitivity, a resistive flexible strain sensor based on the AgNWs-graphene-PDMS sensitive layer is prepared in this paper. This paper presents the preparation of a flexible sensitive layer, the preparation and encapsulation of the flexible strain sensor, and the performance tests of the sensor prepared with AgNWs-graphene (AgNWs-Gr) mixtures at different concentrations. The test results indicate that the prepared sensor has a wide detection range with a maximum stretchable length of 118%. The flexible strain sensor prepared with the AgNWs-Gr mixture at a concentration of 5% has the highest sensitivity and the maximum strain sensitivity of up to 236. It also has good repeatability, stability, and rapid response, and it has been tested for practical applications. The results show that the flexible strain sensor has a broad application prospect in fields such as wearable devices and intelligent robots.

Potential transfer is an essential link in equipotential live-line work (EPLW), which has a potential safety hazard. To ensure the safety of the linemen, this paper conducted experimental research on this process. First, to investigate the discharge characteristics of the potential transfer gap in EPLW, this paper developed a simplified experimental platform to examine the relationship between the transfer voltage and gap distance, as well as the electrode structure, during the potential transfer process. Second, to explore the discharge development process of potential transfer, this paper built a discharge observation experimental platform to observe the discharge process and explore the effects of gap distance and type of the floating electrode on the discharge development process and potential transfer current. The research results are valuable for practical projects and linemen safety.

To enhance the utilization of clean energy sources, such as wind power and photovoltaic within virtual power plants, and mitigate carbon emissions, this paper proposes a virtual power plant participation in the electricity carbon joint market optimization operation model based on ensemble empirical mode decomposition–improved bat algorithm (IBA)–Markov chain new energy output prediction. First, complementary set empirical mode decomposition is performed on historical data to construct a Markov chain based wind power and photovoltaic prediction model optimized by IBA. Second, this prediction model is used to predict the daily generation power of wind power and photovoltaic power. Finally, with the optimization goals of maximizing the benefits and minimizing the carbon costs of virtual power plants, a virtual power plant system participating in the electricity carbon joint market model based on wind power and photovoltaic output prediction results is constructed. At the same time, demand response factors are introduced and solved using the NSGA-II algorithm. Taking a certain park as an example for simulation analysis, the research results show that the combined effect of carbon market and demand response can achieve 99.82% of new energy consumption in virtual power plants without significantly reducing profits, basically achieving complete new energy consumption, demonstrating the effectiveness of the proposed model in this paper.

Designing advanced combustors that operate at high temperatures and produce little pollution, especially in the absence of primary and dilution holes, is a difficult task that may bring significant challenges. In this regard, this paper introduces a Kriging surrogate model approach to optimize the outlet temperature distribution of the combustor to achieve such advanced low-pollution combustors. Building upon previous research, this study explores the effects of the swirler blade installation angle on the outlet temperature distribution of the combustor without primary or dilution holes. Traditional methods, such as the control variable method using computational fluid dynamics (CFD) for numerical simulation, are limited in application due to the complex coupling of flow, heat transfer, mass transfer, and combustion processes. In contrast, surrogate models, especially the Kriging model, offer a rapid and efficient alternative to extensive CFD simulations that provide accurate predictions and error estimates for the solution of the problem. In summary, this paper details the process of generating sample points through three-dimensional numerical simulations, develops a Kriging surrogate model through Latin hypercube sampling, and optimizes the model to identify the most uniform outlet temperature distribution achievable by adjusting the installation angle of the swirl blade. The optimal design parameters, which are quickly obtained through the Kriging model, showed a significant reduction in the overall temperature distribution function and the radial temperature distribution function by 21% and 27.14%, respectively.

Magnesium alloy shows promise of becoming a new generation of degradable biomaterials because of its good biocompatibility and mechanical properties. This paper details the preparation of magnesium alloy by adding calcium and zinc elements to pure magnesium at a specific ratio and strengthened by solid solution treatment and extrusion. The magnesium alloy is subjected to micro-motion wear testing, in vitro degradation product analysis, and in vitro biocompatibility testing and demonstrates excellent performance. The study demonstrates that the prepared Mg-2.0Zn-1.6Ca alloy friction ring has an elliptical shape with a low friction coefficient, which notably enhances the wear resistance of the material. Furthermore, the corrosion of magnesium alloy products in simulated body fluids does not adversely affect the human body. This is because the surface of the magnesium alloy favors cell growth and has excellent antimicrobial properties. The purpose of this paper is to enhance the preparation, surface friction properties, and biocompatibility of magnesium alloys and to provide theoretical and practical guidance for the preparation, processing, and application of high-performance medical magnesium alloys.

Friction plays a key role in the assessment of the safety and stability of mechanical systems (such as superconducting magnet quench explosion, aerospace vehicle bearing wear, etc.). Due to the closeness of the interfaces in engineering structures and the randomness of the contact surfaces, existing methods for measuring static friction force are unable to measure it at the contact interfaces of engineering structures under service conditions. In this paper, a new method for measuring the static friction force at the interface based on electrical signals is proposed. This method enables the measurement of the static friction force at interfaces of complex engineering structures under service conditions solely through electrical signals. The results indicate that the contact resistance gradually decreases with the increase in tangential load during the static friction stage until a monotonic behavior of macroscopic sliding occurs. The evolution of contact resistance is linked to the evolution of the real contact area, and this monotonic behavior can be explained as the deformation form of contact points. The accuracy of the proposed electrical measurement method is verified by comparison with experimental results (with an error of less than 9%). The indirect measurement method of friction force proposed in this paper can effectively measure the static friction force at the interfaces of engineering structures under service conditions, and it is expected to be applied to the detection of friction performance at engineering structure interfaces in extreme service environments.

The purpose of this paper is to study the adaptability and enhancement methods of ignition chips in complex electromagnetic environments. In this paper, combined with simulation and calculation technology, we first establish the electromagnetic–electrical–thermal coupling simulation model of ignition chips and analyze the influence of two electromagnetic environments, continuous electromagnetic wave and nuclear electromagnetic pulse, on the electrical–thermal coupling in the bridge area of the ignition chip. The results show that a continuous electromagnetic wave field strength of 1200 V/m, irradiated for 5 s, a nuclear electromagnetic pulse with a rise time of 5 ns, a half-height width of 24 ns, and a leg wire length of 350 mm will cause the ignition chip to fire accidently. In order to suppress its accidental firing, the electromagnetic protection is enhanced by using parallel Transient Voltage Suppressor (TVS) diodes. It has been shown that parallel TVS diodes provide good protection against both continuous electromagnetic waves and nuclear electromagnetic pulses. In particular, the peak induced current decreases by more than 64.7% during the action of continuous electromagnetic waves, and the maximum temperature in the bridge area decreases by 54.34% during the action of nuclear electromagnetic pulses.

The high temperature superconductors enhanced magnetoplasmadynamic thruster is a promising device for various space mission scenarios. However, a critical issue hindering the enhancement of the thruster’s performance is the problem of anode power deposition. Previous studies have identified the anode fall voltage as a major contributor to this power deposition. This paper introduces an approximate analytical formula for calculating anode power deposition resulting from anode fall voltage. The paper further analyzes and calculates the variation of anode fall voltage with an applied magnetic field and discharge current. The findings reveal a direct correlation between applied magnetic field and both anode fall voltage and power, indicating an increase with higher magnetic field values. In contrast, while the anode fall voltage experiences a slight decline with increased discharge current, the anode power deposition remains elevated due to the transition from field ionization to thermal ionization. To gain a comprehensive understanding of anode power deposition, an experiment was conducted to obtain measurements under different operating conditions, involving varying levels of applied magnetic field and discharge current. The experimental results align with the theoretical predictions. These insights have the potential to serve as a valuable reference for enhancing the efficiency of magnetoplasmadynamic thrusters, bringing us closer to unlocking the full potential of these remarkable propulsion systems in the realm of space exploration.

A rod fastened rotor (RFR), which contains serial disks, rods (or a rod), and a torque tube, is the main form of heavy duty gas turbines and light duty aero engines. The roughness of the interface is the main parameter affecting the bending stiffness of RFR, and the jumpiness of the disks is the intuitive representation of the unbalance of the rotor. In this paper, a multi-optimization algorithm, NSGA-Ⅱ, was used to improve the vibration behavior of the RFR-bearing system. First, the quantitative relation between the bending stiffness of the rotor and the roughness of the interface was set up by combining the Persson contact theory and the Greenwood–Williamson model, and the nondimensional bending stiffness (NS) was proposed as the optimization objective of roughness. Then, the optimization objective of the jumpiness of the disk, (A + B), was rendered based on the minimum unbalance force. Finally, the multi-optimization on the roughness and jumpiness of the RFR was carried out, and the vibration behavior was improved greatly. In addition, this multi-optimization method was applied to a practical RFR, and the experimental results showed that the vibration amplitude was reduced by about 82%. The work in this paper can provide the guidance for vibration reduction of the rotor system.

As a conventional control approach, the skyhook damping control algorithm can respond to changes in road circumstances but not to those in load circumstances. The skyhook inertance control algorithm, a newly developed control approach, may adapt to changes in load circumstances rather than in road circumstances. The recent introduction of double-skyhook control algorithms has allowed vehicle suspension systems to accomplish both load and road adaptation. This paper presents an experimental investigation contrasting the performance of the double-skyhook configuration to that of the traditional skyhook damper configuration and the skyhook inerter configuration. By integrating the double-skyhook control strategy with semi-active devices with variable inertance and damping, the paper proposes two strategies for coordinating skyhook inertance and skyhook damping control. A controller using the double-skyhook control strategy is designed to employ the Development to Production rapid control prototyping platform. The controller mode is adjusted using MotoTune software to implement control methods. Three tests were conducted under various road conditions, load conditions, and impact conditions for semi-active suspension. Test results indicate that the double-skyhook configuration considerably enhances driving comfort compared to the single-skyhook configuration. Moreover, the greater the deterioration of road conditions and the decrease in load, the more pronounced the enhancement.

A surface defect detection method for hot-rolled steel strips was proposed to address the challenges of detecting small target defects, significant differences in morphology, and unclear defect characteristics. This method is based on multiscale feature perception and adaptive feature fusion. First, based on the spatial distribution characteristics of the steel strip image, redundant background interference is removed using automatic gamma correction and Otsu thresholding. Second, based on the characteristics of surface defects in steel strips, this paper proposes TDB-YOLO (YOLO with a small target detection layer), a Bidirectional Feature Pyramid Network (BiFPN), and Double Cross Stage Partial (CSP) Bottleneck with three convolutions (DC3). To detect small object defects, a small target detection layer with a smaller receptive field focuses on fine-grained features, reducing the model’s probability of missed detection. In terms of feature extraction, DC3 enhances the interaction of feature information from different spatial scales, enabling the model to effectively handle features of varying scales. In terms of feature fusion, the BiFPN is used to adaptively fuse deep-level and shallow-level feature information, enhancing the semantic richness of the feature information. Ultimately, the proposed model in this paper achieved an accuracy of 90.3% and a recall rate of 88.0% for surface defects in steel strips. The mean average precision was 90.4%, and the frames per second was 33. The detection performance of this model outperformed those of other detection models, demonstrating its ability to effectively meet the real-time detection requirements of surface defects in industrial scenarios on steel strips.

This Review explores the transformative impact of artificial intelligence (AI) on the early detection of skin cancer, with a specific focus on melanoma, a potentially lethal form of the disease. Beginning with an overview of traditional diagnostic methods and their limitations, this paper delves into the evolution of AI within dermatology, emphasizing its application in image analysis and pattern recognition. A comprehensive examination of AI algorithms for melanoma detection, including machine learning and deep learning models, is provided. This Review critically assesses the performance metrics, training datasets, and comparative analyses with traditional methods. Addressing challenges such as data quality, interpretability, and ethical considerations, this paper outlines future directions, emphasizing ongoing research, algorithm improvements, and integration with clinical practices. Case studies and success stories highlight the real-world impact of AI in dermatology. This Review concludes by summarizing key findings and underlining the pivotal role of AI in revolutionizing early melanoma detection, with implications for personalized medicine and enhanced patient outcomes.

The star sensor is the most accurate measurement instrument in the spacecraft attitude measurement system, and the accurate centroid of the star point is the basis for ensuring the performance of the star sensor. Currently, the centroid of the gray method is the most widely used centroid extraction method in practice. Systematic errors caused by the centroid of the gray method and random noise in the detector imaging process are the main factors contributing to the deviation of the star centroiding coordinates. Considering the relationship between the point spread function and the pixel gray value, this paper proposes a centroiding method to reduce the star point centroiding error by fusing a priori information and energy distribution. The star charts are first preprocessed using a curvature filter and Gaussian blur to reduce the random noise. Then the complexity of the point spread function is considered, and the pixel gray values are corrected based on a priori information and gray value fuzzy processing. Finally, the symmetry of the one-dimensional energy distribution is used to quickly determine the sub-pixel deviation to get the star centroid coordinates. Through simulation and physical simulation experiments, the method was verified to be effective, and the extraction accuracy met the requirements of high-precision star sensors. The night sky observation test results demonstrate that the method in this paper can improve the measurement accuracy of the star sensors.

With the increasing demand for the resilient capacity of transformers in high-proportion renewable energy grids, the overload capacity of transformers and the thermal conductivity of winding insulation materials have been put forward as important requirements. In response to these requirements, a novel ceramic high temperature tolerance insulation winding is proposed in this paper and is applied in a ceramic insulated winding transformer. A combination of simulation and experimentation is used to analyze the thermal-flow characteristics of this transformer. The temperature and flow field distribution characteristics of transformers with both winding insulation methods (ceramic and Nomex paper) are compared. The internal mechanism of reflux near the iron core and high voltage winding under forced air cooling is clarified. A superior outside cooling condition is obtained. A prototype ceramic insulated winding transformer is developed and tested to verify the accuracy of the simulation model. The results show that the hotspot temperature of the ceramic insulated winding transformer under natural cooling is 10.7% lower than that of the Nomex paper insulated winding transformer. With forced air cooling of 2, 3, 4, 5, and 6 m/s applied at the bottom, the hotspot temperature of the ceramic insulated winding transformer is 11.4%, 10.5%, 9.7%, 14.0%, and 17.8% lower than that of the Nomex paper insulation winding transformer, respectively. Under forced air cooling, a reflux phenomenon is observed in both transformers in the vicinity of the iron core and high voltage winding due to the formation of adverse pressure gradient region and wall viscous force blocking. The strength of the reflux is affected by the magnitude of the forced air cooling flow velocity and the construction of the transformer. The optimal range of the external cooling flow velocity for the ceramic insulated winding transformer is 3–4 m/s. The errors between the simulated temperature and the measured temperature at the nine monitoring points of the prototype are all less than 5%, which verifies the effectiveness of the simulation model. The experimental and theoretical basis for the design and application of resilient capacity dry type transformers is provided by this research.

This is a companion paper to the previous work [P. H. Yoon, Phys. Plasmas 31, 032309 (2024)] in which the nonlinear susceptibilities of weakly turbulent magnetized plasma are derived under a simplifying assumption of electrostatic interaction. The present paper extends the analysis to a general situation of electromagnetic interaction. The main novelty of the previous and present papers is that by employing the Bessel function addition theorem, the mathematical definitions for the susceptibilities are substantially simplified, a procedure that has not been discussed in the existing literature. In the present paper, a full set of Maxwell’s equations are considered in conjunction with the nonlinear Vlasov equation, which is solved by a perturbative method. The result is a fully general nonlinear susceptibility, given in tensorial form, which is applicable for weakly turbulent magnetized plasmas.

A method of delaying the aging of natural ester oil-paper insulation systems by adding glyceryl triacetate is proposed in this work. A study was conducted on the thermal aging performance of soybean insulating oil mixed with glyceryl triacetate at a volume fraction of 7.5%. Through a 42-day accelerated thermal aging experiment, it was found that the addition of glyceryl triacetate effectively delayed the increase in kinematic viscosity of the insulating oil and reduced the generation of aging products such as moisture and acid. However, the polar compounds in glyceryl triacetate reduced the breakdown voltage of the mixed oil and made the dielectric loss factor higher than that of pure oil. In addition, tests were conducted on the insulating paper immersed in two types of oil, and it was found that the addition of glyceryl triacetate helps to distribute mixed oil molecules on the surface of insulating paper, which effectively helped absorb moisture from the paper, weakening the hydrolysis reaction of cellulose and delaying the aging of insulating paper. In addition, the insulating paper immersed in the mixed oil maintains good power frequency breakdown voltage and dielectric properties throughout the thermal aging experiment.

The “Klemens channel” formalism is commonly used in interpretations of experimental results on the lifetime of longitudinal optic (LO) phonons and Fröhlich polarons (FPs) in polar bulk, polycrystalline, and nanostructured solids. Here, in Paper I of this bipartite article, the two-particle vibrational DOS function(s) for spatially confined longitudinal acoustic and LO phonons is implemented at evaluation on FP decay probability via the “Klemens channel” and its lifetime for the case of FPs confined within InAs quantum dots. This approach yields a convincing elucidation of the earlier experimental data. An alternative model based on the idea of diabatic thermally activated excitation of FP charge carriers and consecutive lattice “depolarization” will be discussed in detail and implemented at simulations on FP lifetime in Paper II [V. Ligatchev, “On thermal stability of Fröhlich polarons in bulk and nano-structured polar solids II: Diabatic ionization and depolarization,” AIP Adv. 14, (2024)].

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.

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.

With the goal of “carbon peak and carbon neutrality,” the need for environmentally friendly gases to replace SF6, a high greenhouse effect gas, is urgent. C4F7N, as an environmentally friendly gas with the greatest potential to replace SF6 as an arc extinguishing medium in circuit breakers, can be mixed with CO2 to greatly improve the shortcomings of its high liquefaction temperature, and the calculation of the physical parameters of the mixed gas plasma is a prerequisite for the computational simulation of the arc process in the opening of circuit breakers. Because solving the physical parameters is expensive, based on the system of differential equations, this paper adopts several machine learning algorithms by mining the relationship between the data using the known physical parameter data to predict the results of the physical parameters to be solved under certain conditions, which greatly reduces the cost of computation. The machine learning algorithms used in this paper are K-nearest-neighbor regression, decision tree, random forest, support vector machine, and gradient boosting regression, of which for the support vector machine, hyperparameters find it difficult to determine the problem of optimization using the gray wolf algorithm. The prediction results of several algorithms show that they are more accurate and that the problem can be solved better by using the method of machine learning. Finally, the comparison results show that the support vector machine exhibits better performance in most cases and that the gray wolf algorithm can make the results of the support vector machine more accurate.

In this paper, we use tracked vehicles as an example to study complex systems and surrogate model building method. Due to the high cost and long development cycle associated with the traditional development approach, involving static design and experimental verification, there is an urgent need to explore an effective dynamic optimization design method to enhance vibration reduction performance. This paper introduces a methodology for constructing a model of complex equipment surrogate, aimed at streamlining subsequent parameter optimization processes. The dynamics model of the tracked vehicle is utilized, and the root-mean-square value of plumb vertical acceleration at the center of mass is selected as the dynamic performance index. The impact of structure parameters on dynamic performance is analyzed, and a range of design parameters are determined. The optimal Latin hypercube experimental design method is employed to generate sample data. A radial basis function neural network, optimized by particle swarm optimization, is used to construct a dynamic surrogate model for the tracked vehicle. The surrogate model constructed in this paper greatly reduces the time cost in optimizing complex equipment parameters. In the past, parameter optimization required conducting numerous simulations to collect data, with each simulation taking about 700 s. However, the surrogate model introduced in this paper only requires ∼100 s for completion. This significant reduction in time not only saves costs but also maintains a high level of accuracy.

The subsurface defects (SSD) of optical elements have a significant impact on the service life and laser damage threshold of the inertial confinement nuclear fusion optical system. Due to the optical diffraction limit, fluorescence microscopy has limited image resolution for detecting SSD in optical elements, making it challenging to meet the requirements for precision detection. A super-resolution method is proposed in this paper for detecting SSD in optical elements based on the fluorescence polarization characteristics of CdSe/ZnS quantum dots fluorescence dichroism. By enhancing the imaging sparsity of adjacent fluorophores through a polarization modulated excitation laser and utilizing the fluorescence polarization modulation algorithm, the resolution is achieved beyond the optical diffraction limit. The results demonstrate that the proposed method in this paper can obtain super-resolution images of SSD in optical elements with at least a two-fold increase in lateral resolution. This approach effectively improves detection accuracy for SSD and holds significant guiding significance. In addition, it also has application value for assessing the quality of high-precision optical elements.

Recent developments on the electron optics simulator (EOS) are reported in this paper. The EOS is a finite element two-dimensional (2D) and three-dimensional (3D) electrostatic particle steady-state trajectory code that has been widely used for beam optics modeling of vacuum electronic devices. To extend the application scope and improve the computation efficiency, four significant advances have been made and are presented in this paper. First, the code is reprogrammed to consider physical models that contain dielectrics and to support charge excitation. Second, more primary particle emission models are added in EOS to meet the needs for simulating electron and ion optics devices for diverse applications. For the precise simulation of the secondary electron emission, the Vaughan model is improved, and the Furman model is newly added in EOS. Finally, the algebraic multigrid algorithm has been embedded in EOS, which can significantly improve the computation efficiency for problems with large-scale matrices. For these developments, the necessary principles and corresponding performance are shown in detail in this paper.