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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.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

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. [ABSTRACT FROM AUTHOR]

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.

Geotechnical designs and analyses of earth structures and foundations exclusively involve the assessment and consideration of unsaturated soil shear strength. The laboratory testing equipment and methods for predicting the unsaturated soil shear strength are complicated and more expensive. The experimental program attempted to involve undrained triaxial and filter paper for evaluating the unsaturated soil shear strength of identically compacted clayey soil. This study undertakes a comparison of shear strength in clayey soil under undrained loads, examining both saturated and unsaturated conditions. A 60 kPa air entry suction value is the key point at which linearity between the unsaturated shear strength parameter Øb and effective friction Ø′ with 15° linear slopes turns to non-linearity. Unsaturated shear strength increased by 22.76% in optimally wet conditions, 52.68% in optimum conditions, and 77.81% in optimally dry conditions as compared to saturated shear strength. This study utilizes an artificial neural network (ANN) to predict clayey soil's unsaturated shear strength, finding that the optimal ANN configuration (2-5-1 topology, Levenberg–Marquard optimization, and logsig transfer function) achieved high reliability with a correlation coefficient (R) of 0.9289 and mean square error values of 2.22, 7.12, and 3.012 for training, testing, and validation, respectively. This experimental investigation improves our understanding of clayey soil shear strength and emphasizes the importance of saturation and moisture content in geotechnical assessments under undrained loading conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Smart materials with reversible wettability have attracted a lot of attention for application in sewage treatment. In this work, a pH-responsive polymer was prepared via the one-step free radical polymerization of 3-(trimethoxysilyl) acrylate and 2-dimethylaminoethyl methacrylate. The obtained pH-responsive polymer was then coated with a hydrogenated styrene–ethylene–butadiene–styrene block copolymer to endow the material with pH-responsive switchable superhydrophilic and superhydrophobic properties. Due to the excellent self-cleaning and mechanical stability of the coating, it was used to modify paper, which was then successfully utilized in the treatment of oily wastewater, showing great potential for use in advanced applications. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In recent years, the field of flexible electronics has become one of the cross-disciplinary research hotspots, attracting worldwide attention and making rapid advances. So far, there has been plenty of research on the use of two-dimensional (2D) materials in flexible electronics, including graphene, transition metal dichalcogenide, and so on. In this work, we successfully prepared quasi-one-dimensional (Q1D) Nb2Pd0.73S5.97 superconductors on flexible paper by mechanical friction and systematically studied their physical properties at low temperatures. Superconductivity with transition temperature (Tc) ∼ 6.05 K by Meissner effect was observed in Nb2Pd0.73S5.97 wires coated on flexible paper, and a resistance drop at 4.80 K was confirmed in electrical transport measurements. The lower critical field (Hc1) of coated paper shows anisotropy effect under parallel and perpendicular magnetic fields, exhibiting a 2D-like feature, unlike the bulk Nb2Pd0.73S5.97 fibers. Our work provides a broader platform for the application of low-dimensional materials in flexible functional devices. [ABSTRACT FROM AUTHOR]

Because of the overly averaged element sensitivity in the topological optimization of an irregular structure with a grid independent filter, a topological optimization model was built for the structural domain. The maximization of stiffness was first taken as the goal for the topological optimization of irregular structure stiffness. Subsequently, an element size filter was proposed to address the overly averaged local element sensitivity with the grid independent filter when the designed domain element size varied dramatically. Finally, the element sensitivity of the objective function was derived under the given constraints. A case study was then conducted on a naval gun mount with the maximization of structural flexibility as the objective function and the volume of structural material as a constraint. A stiffness optimization model based on the bi-directional evolutionary structural optimization algorithm was adopted for the topological optimization of the gun mount. Structural optimization was conducted for the gun mount with different shooting angles to realize its optimal stiffness and strength under the constraint of consistent material volume. The optimization results proved that the element independent filter proposed in this paper could be effectively applied in the topological optimization of an irregular structure and used to explore the topological optimization of the supporting structure under impact. [ABSTRACT FROM AUTHOR]

Cellulose insulation paper is an essential part of the transformer oil-paper insulation system, and many types of nano-modified insulating paper are available. For studying the effects of various nano-modified molecules on cellulose and the differences in performance, the pure cellulose model and polyoctaaminophenylsesquioxane and grafted 3-aminopropyltriethoxysilane (KH550) SiO2 and Al2O3 cellulose models were developed using molecular dynamics methods, and the mechanical properties and thermally stability were calculated and compared. The findings show that, in general, all three nano-modification models improved the thermal stability and mechanical properties, with nano-SiO2-KH550 cellulose having the best overall modification effect. In terms of mechanical properties, the nano-SiO2-KH550 cellulose showed the largest increase in compressive strength, with an 18.1% improvement. In terms of thermal stability, the KH550 grafted nano-silica/cellulose composite model showed the best modification effect, as evidenced by the smaller cohesive energy density and free volume region compressing the space between cellulose molecules, making the modified cellulose more compact internally, thus achieving the effect of inhibiting the movement of cellulose chains. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

With the development of electronic technology, semiconductor memory is gradually shifting toward smaller area with less power consumption. SOT-MRAM is one of the competitive substitutes for DRAM and SRAM due to its superior endurance and switching speed. In contrast to STT-MRAM, the separation of read and write routes allows SOT-MRAM to have a lower error rate and higher lifetime, but this comes at the expense of the memory density. In recent years, vertical integrated circuits have relied on TSV to complete 3D stacking to ease the pressure of Moore's Law on scaling circuits. SOT-MRAM can take advantage of 3D stacking to reduce power and latency. More importantly, the density of SOT-MRAM can be improved at the same time. In the paper, simulation is conducted based on DESTINY, with the TSV model supplemented to NVSIM to evaluate the performance of MRAM 3D structures. The 3D SOT-MRAM structure in DESTINY can be implemented with a bus layer and interconnect structure between layers, which greatly reduces the expense of area. However, the 3D structure requires a more complex interconnect structure to truly meet the requirements of high density. For this reason, 3D model of unit interconnection using TSV is presented in the paper. Memory has several components, of which the memory array is the one with the largest area share. This paper explores the spatial structure of the array and proposes a new model which allows more complex interconnect structures to be accomplished on the same area. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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%. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, aiming at the current distribution network with power operation in the presence of outdoor bright light, the operating scene is complex and not fixed, the transmission lines and lead samples are small and uneven, leading to poor accuracy of machine learning and other methods of distribution network with power operation robot identification and localization, this paper selects three-dimensional LIDAR to design a set of support vector machine (SVM) classifier and correlation analysis based on the target recognition method. This paper selects three-dimensional LIDAR to design a set of support vector machine (SVM) classifier and correlation analysis based on the target recognition method. First, in the context of power distribution network operations, we have explored various filtering methods suitable for preprocessing transmission line data. These methods aim to remove outliers and clutter from point clouds, thus enhancing both point cloud quality and processing speed. This, in turn, improves the efficiency of real-time on-site detection. We conducted experimental comparisons of various clustering algorithms and opted for a region-based point cloud clustering algorithm to achieve the segmentation of individual point clouds. Secondly, we proposed a multi-feature composite approach based on the Viewpoint Feature Histogram (VFH) features, which helps maintain the scale-invariant characteristics of the features. We then introduced a multi-feature composite criterion based on VFH features to extract features from segmented point clouds. Subsequently, an SVM classifier based on this composite feature criterion was developed to achieve target identification and classification. Experimental results have demonstrated improved accuracy in target identification. Finally, we integrated this system with a bucket-arm vehicle for coordinate conversion and precise navigation of the robot to the target station. This method significantly improves the overall operational efficiency of power distribution tasks. [ABSTRACT FROM AUTHOR]

Minimizing the offloading latency of agricultural drip irrigation and fertilization tasks has long been a pressing issue in agricultural drip irrigation and fertilization wireless sensor networks (AIFWSNs). The introduction of edge computing as a robust and practical aid to cloud computing in AIFWSNs can significantly improve the execution speed of agricultural drip irrigation and fertilization tasks and effectively reduce the task offloading latency. Therefore, this paper investigates the optimization method of drip irrigation and fertilization task offloading delay in AIFWSNs based on edge computing and proposes a new edge task offloading method for AIFWSNs, namely, Quantum Chaotic Genetic Optimization Algorithm (QCGA). This paper introduces a novel quantum operator in QCGA, comprising a quantum non-gate and a quantum rotation gate, to improve the algorithm's global search capability. The quantum operator accomplishes the updating of quantum rotating gates without querying the quantum rotation angle table, which reduces the computational complexity of introducing quantum optimization into the task offloading problem of AIFWSNs. This paper proposes a new chaotic operator to make the initial solution more uniformly distributed in the search space by chaotic mapping. This paper's simulation experiments compared QCGA and snake optimizer (SO), genetic algorithm (GA), particle swarm optimization (PSO), sequential offloading, and random offloading methods. Simulation results showed that, compared with SO, GA, PSO, sequential offloading, and random offloading methods, the average delay of QCGA was reduced by 9.96%, 26.78%, 29.31%, 44.67%, and 61.24%. [ABSTRACT FROM AUTHOR]

TEAM Problem 35, a benchmark problem in the optimization of electrical equipment, is a multi-objective, multi-variable optimization problem involving uniform field optimization. This paper proposes a novel guided optimization algorithm to address this problem and achieve optimal magnetic field regulation. First, the deep learning method is used to predict the magnetic field of the solenoid; second, the generated magnetic field cloud map is screened to extract the magnetic field information of the more optimal solution with uniform magnetic field distribution by calculating the variance of the generated magnetic field map; finally, the magnetic field features are combined with the particle swarm optimization algorithm; specifically, the variance of the calculated magnetic field map is added to the objective function of the optimization algorithm to strengthen the optimization process. This integration improves the convergence speed of the optimization process and ensures the continuity and stability of the obtained Pareto solutions. To optimize the solenoid, this paper considers the uniformity of magnetic field distribution and power loss as the primary optimization objectives. The radius of the coil is chosen as the design variable. The optimization results are compared with those obtained by conventional optimization algorithms, demonstrating superior optimization performance. [ABSTRACT FROM AUTHOR]

Sound source localization has a wide range of application prospects in many fields, such as smart home and audio monitoring. Traditional methods are difficult to achieve accurate location in the face of multi-path reflection, reverberation, and ambient noise. In this paper, a complex mapping conversion method for sound source location is proposed. By using complex-valued convolutional neural networks to fuse the amplitude and phase information of the data, a more accurate and comprehensive analysis can be carried out to improve its robustness and realize the accurate location of the sound source. The sound source location method based on complex-valued convolutional neural networks is studied, and the complex mapping principle is analyzed. Simulation and experimental studies were carried out, and the results of simulation and experiment are basically consistent. In the experiment, the positioning accuracy of the complex mapping method is 9.49% higher than that of the absolute value method and 15.81% higher than that of the phase angle method. In addition, its localization success rate, respectively, increased by 4.9% and 8.6% compared to two other methods. This paper opens up a new way for the application of complex-valued convolutional neural networks in sound source localization. [ABSTRACT FROM AUTHOR]

This document is a retraction notice from AIP Advances regarding four manuscripts that have been retracted due to evidence of manipulation in the publication and peer review processes. The editors of AIP Advances have retracted these papers after questions were raised about the data processing and analysis. The retraction is based on the discovery of identical reviewer reports and requests for revisions to add citations to unrelated works by the authors, indicating peer review manipulation. The authors maintain that the data support the validity of the papers, but the editors believe that the issues with the peer review process undermine their confidence in the validity of the papers. [Extracted from the article]

This document is an erratum for a published paper titled "Computation of the masses of the elementary particles." The author has identified two errors in the original paper and provides corrections for them. The corrections involve replacing equations, code tables, and graph figures. The corrected results are qualitatively the same as the original paper, but not quantitatively. The author suggests that using high-performance computing and refining the integrations may result in predicted particle masses closer to the measured values. The erratum includes tables, code listings, and graphs to support the corrections. [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In response to the challenges in mobile robot path tracking using model predictive control, where the predictive model weakens the controller’s ability to respond to sudden changes in the reference path curvature and heading, this paper proposes a composite control strategy suitable for agricultural robots. The strategy combines the maximum torque per ampere control and an Extended State Observer (ESO). The paper initially establishes a mathematical model for a Permanent Magnet Synchronous Motor (PMSM) considering aggregated disturbances. It designs a position tracking controller based on a non-singular terminal sliding mode and convergence law. This controller, employing a non-cascaded structure, replaces traditional position and velocity loop controllers and is proven to be stable with finite-time convergence through Lyapunov’s theorem. To enhance the system’s disturbance rejection capabilities further, the paper introduces an ESO to estimate system disturbances and applies it for feedforward compensation. The paper concludes by providing stability proof for the overall PMSM servo system in agricultural robots. Finally, the paper conducts simulations and experimental verifications based on the designed controller, demonstrating that the controller exhibits excellent path tracking performance, fast convergence, and robustness against external disturbances. [ABSTRACT FROM AUTHOR]

The propagation of online rumors is rapid, and its propagation mechanism has always been a research difficulty. In this paper, the network rumors are compared to the nuclear fission process, and a network rumors propagation model is constructed. First, the initial online rumors are compared to neutrons, uranium nuclei are compared to individual rumor receivers, and fission barriers are compared to individual active propagation thresholds. Second, the process of nuclear fission is analyzed and the degree of energy accumulation is used to compare the social impact of online rumors. Finally, the online rumor propagation model based on nuclear fission is constructed. Through experimental simulation, it has been shown that compared to classic infectious disease models, this model can better describe the propagation process of rumors in social networks. Through research and analysis, suggestions for suppressing rumors have been proposed, providing new ideas and references for future researchers. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Infrared thermography technology, leveraging its unique ability to capture temperature features, has significantly improved the precision of high-temperature target localization. However, infrared imaging technology is limited by issues such as low image contrast, difficulty in distinguishing object categories, and limited image clarity. To enable intelligent detection of high-temperature objects that may cause fires in warehouses, this paper proposes an innovative method that integrates deep learning image segmentation with infrared and visible light image technology. We developed a new image segmentation model based on improved Fully Convolutional Networks and Deconvolutional Networks, introducing a batch normalization layer to accelerate convergence and employing the PReLU activation function to prevent neuron death, thereby enhancing convergence speed and accuracy. Through a feature dynamic image registration method combining a joint model and a cross-modulation strategy, we achieved efficient image fusion. In addition, a game theory-based strategy was adopted to correct localization results, ensuring accuracy. Experimental results demonstrate that the improved model achieves localization accuracy and precision rates of up to 89.30% and 88.00%, respectively, in real-world warehouse heat source scenarios, representing a significant improvement of 9.90% and 2.85% compared to the pre-improvement model, fully validating its advancement and effectiveness. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In complex environments, such as mines, ports, and pipelines, wireless power transfer technology is a convenient and safe power supply method. However, the offset and change in direction of the receiving coil greatly weaken the power transfer performance. To address this issue, this paper proposes a variable direction wireless power transfer device for mining based on metamaterials. According to the relationship between incident angle, refracted angle, and permeability, three different metamaterials are selected to fabricate a metamaterial slab arranged in 3 × 3 using printed circuit board technology. Experimental results show that when the transmitting coil and receiving coil are perpendicular to and deviate from each other, the designed power transfer system with the metamaterial slab can effectively increase power transfer by 117.9%. The proposed variable direction transfer system only needs a metamaterial slab without an additional power supply or control structure, and it is convenient for large-scale manufacturing and application. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Recently, lithium niobate thin film laterally excited bulk wave resonators (XBARs) have attracted much attention because of their advantage of high frequency and outstanding electromechanical coupling factor (K2) enabling wide filter bandwidths. These can satisfy the increasing 5G communication demand. However, their large temperature coefficient limits their development to some extent. To improve their temperature stability with little K2 reduction, this paper has proposed a sandwiched structure for temperature compensated XBARs (TC XBARs). This structure includes the top silicon dioxide (SiO2) layer and the bottom SiO2 layer. One layer can improve temperature stability, and the other layer can increase K2. The optimized XBARs have a temperature coefficient of frequency (TCF) of −90.77 ppm⁄°C. The common two-layer TC XBARs can achieve a TCF of −22 ppm⁄°C sacrificing K2 to 8%. However, the proposed sandwiched TC XBARs can achieve a K2 of 12.15 and a TCF of −28.94 ppm⁄°C simultaneously, with a large FoM. Meanwhile, spurious modes can be suppressed in the sandwiched structure. Thus, this sandwiched structure can provide a good solution for the high performance of XBARs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This document is a retraction notice from AIP Advances regarding four manuscripts that have been retracted due to evidence of manipulation in the publication and peer review processes. The editors of AIP Advances have retracted these papers after questions were raised about the data processing and analysis. The retraction is based on the discovery of identical reviewer reports and requests for revisions to add citations to unrelated works by the authors, indicating peer review manipulation. The authors maintain that the data support the validity of the papers, but the editors believe that the issues with the peer review process undermine their confidence in the validity of the papers. [Extracted from the article]

This document is a retraction notice from AIP Advances regarding four manuscripts that have been retracted due to evidence of manipulation in the publication and peer review processes. The editors of AIP Advances have determined that critical steps in the peer review process were manipulated, including the return of identical reviewer reports and author-suggested reviewers requesting revisions to add citations to unrelated works by the authors. As a result, the validity of these papers has been called into question and they are considered potentially unreliable. The authors maintain that the data support the validity of the papers, but the editors believe that the issues with the peer review process undermine confidence in their validity. [Extracted from the article]