Characteristics of the electromagnetic wave propagation in magnetized plasma sheath and practical method for blackout mitigation

“Magnetic window”is considered as an effective method to solve the communication blackout issue.COMSOL software package based on the finite element method is utilized to simulate the propagation of right-handed circularly polarized wave in the magnetized plasma sheath.We assume a double Gaussian model of electron density and an exponential attenuation model of magnetic field.The propagation characteristics of right-handed circularly polarized wave are analyzed by the observation of the reflected,transmitted and loss coefficient.The numerical results show that the propagation of right-handed circularly polarized wave in the magnetized plasma sheath varies for different incident angles,collision frequencies,non-uniform magnetic fields and non-uniform plasma densities.We notice that reducing the wave frequency can meet the propagation conditions of whistle mode in the weak magnetized plasma sheath.And the transmittance of whistle mode is less affected by the variation of the electron density and the collision frequency.It can be used as a communication window.

The multi-peak point phenomenon of broadband microwave reflection caused by inhomogeneous plasma

During spacecraft re-entry,the challenge of measuring plasma sheath parameters directly contributes to difficulties in addressing communication blackout.In this work,we have discovered a phenomenon of multiple peaks in reflection data caused by the inhomogeneous plasma.Simulation results show that the multi-peak points fade away as the characteristic frequency is approached,resembling a series of gradually decreasing peaks.The positions and quantities of these points are positively correlated with electron density,yet they show no relation to collision frequency.This phenomenon is of significant reference value for future studies on the spatial distribution of plasmas,particularly for using microwave reflection signals in diagnosing the plasma sheath.

Intelligent identification of landslides in loess areas based on the improved YOLO algorithm:a case study of loess landslides in Baoji City

Loess landslides are one of the geological hazards prevalent in mountainous areas of Loess Plateau,seriously threatening people's lives and property safety.Accurate identification of landslides is a prerequisite for reducing the risk of landslide hazards.Traditional landslide interpretation methods often have the disadvantage of being laborious and difficult to use on a large scale compared with the recently developed deep learning-based landslide detection methods.In this study,we propose an improved deep learning model,landslide detectionyou only look once(LD-YOLO),based on the existing you only look once(YOLO)model for the intelligent identification of old and new landslides in loess areas.Specifically,remote sensing images of landslides in Baoji City,Shaanxi Province,China are acquired from the Google Earth Engine platform.The landslide images of Baoji City(excluding Qianyang County)are used to establish a loess landslide dataset for training the model.The landslide data of Qianyang County is used to verify the detection performance of the model.The focal and efficient IoU(Focal-EIoU)loss function and efficient channel attention(ECA)mechanism are incorporated into the 7th version of YOLO(YOLOv7)model to construct the LD-YOLO model,which makes it more suitable for the landslide detection task.The experiments yielded an improved LD-YOLO model with average precision of 92.05%,precision of 92.31%,recall of 90.28%,and F1-score of 91.28%for loess landslide detection.The landslides in Qianyang County were divided into two test sets,new landslides and old landslides,which were used to test the detection performance of LD-YOLO for both types of landslides.The results show that LD-YOLO detects old landslides with a detection precision of 82.75%and a recall of 80%.When detecting new landslides,the detection precision is 94.29%and the recall is 91.67%.It indicates that our proposed LD-YOLO model has strong detection performance for both new and old landslides in loess areas.Through a proposed solution that can realize the accurate detection of landslides in loess areas,this paper provides a valuable reference for the application of deep learning methods in landslide identification.

Numerical and experimental studies on the effectiveness of time-varying electromagnetic fields in reducing electron density

When an aircraft or a hypersonic vehicle re-enters the atmosphere,the plasma sheath generated can severely attenuate electromagnetic wave signals,causing the problem of communication blackout.A new method based on time-varying E×B fields is proposed to improve on the existing static E×B fields and mitigate the radio blackout problem.The use of the existing method is limited by the invalid electron density reduction resulting from current density j=0 A m^(-2)in plasma beyond the Debye radius.The most remarkable feature is the introduction of a time-varying electric field to increase the current density in the plasma to overcome the Debye shielding effect on static electric field.Meanwhile,a magnetic field with the same frequency and phase as the electric field is applied to ensure that the electromagnetic force is always acting on the plasma in one direction.In order to investigate the effect of time-varying E×B fields on the plasma electron density distribution,two directions of voltage application are considered in numerical simulation.The simulation results indicate that different voltage application methods generate electromagnetic forces in different directions in the plasma,resulting in repulsion and vortex effects in the plasma.A comparison of the vortex effect and repulsion effect reveals that the vortex effect is better at reducing the electron density.The local plasma electron density can be reduced by more than 80%through the vortex effect,and the dimensions of the area of reduced electron density reach approximately 6 cm×4 cm,meeting the requirements of electromagnetic wave propagation.Besides,the vortex effect of reducing the electron density in RAM-C(radio attenuation measurements for the study of communication blackout)reentry at an altitude of 40 km is analyzed.On the basis of the simulation results,an experiment based on a rectangular-window discharge device is proposed to demonstrate the effectiveness of the vortex effect.Experimental results show that time-varying E×B fields can reduce the electron density in plasma of 3 cm thickness by 80%at B=0.07 T and U_(0)=1000 V.The investigations confirm the effectiveness of the proposed method in terms of reducing the required strength of the magnetic field and overcoming the Debye shielding effect.Additionally,the method is expected to provide a new way to apply a magnetic window in engineering applications.

Wideband radar cross-section reduction by a double-layer-plasma-based metasurface

Reduction of the radar cross-section(RCS) is the key to stealth technology. To improve the RCS reduction effect of the designed checkerboard metasurface and overcome the limitation of thinlayer plasma in RCS reduction technology, a double-layer-plasma-based metasurface—composed of a checkerboard metasurface, a double-layer plasma and an air gap between them—was investigated. Based on the principle of backscattering cancellation, we designed a checkerboard metasurface composed of different artificial magnetic conductor units;the checkerboard metasurface can reflect vertically incident electromagnetic(EM) waves in four different inclined directions to reduce the RCS. Full-wave simulations confirm that the doublelayer-plasma-based metasurface can improve the RCS reduction effect of the metasurface and the plasma. This is because in a band lower than the working band of the metasurface, the RCS reduction effect is mainly improved by the plasma layer. In the working band of the metasurface,impedance mismatching between the air gap and first plasma layer and between first and second plasma layers cause the scattered waves to become more dispersed, so the propagation path of the EM waves in the plasma becomes longer, increasing the absorption of the EM waves by the plasma. Thus, the RCS reduction effect is enhanced. The double-layer-plasma-based metasurface can be insensitive to the polarization of the incoming EM waves, and can also maintain a satisfactory RCS reduction band when the incident waves are oblique.

Diagnosing ratio of electron density to collision frequency of plasma surrounding scaled model in a shock tube using low-frequency alternating magnetic field phase shift

A non-contact low-frequency(LF)method of diagnosing the plasma surrounding a scaled model in a shock tube is proposed.This method utilizes the phase shift occurring after the transmission of an LF alternating magnetic field through the plasma to directly measure the ratio of the plasma loop average electron density to collision frequency.An equivalent circuit model is used to analyze the relationship of the phase shift of the magnetic field component of LF electromagnetic waves with the plasma electron density and collision frequency.The applicable range of the LF method on a given plasma scale is analyzed.The upper diagnostic limit for the ratio of the electron density(unit:m^(-3))to collision frequency(unit:Hz)exceeds 1×10^(11),enabling an electron density to exceed 1×10^(20)m^(-3)and a collision frequency to be less than 1 GHz.In this work,the feasibility of using the LF phase shift to implement the plasma diagnosis is also assessed.Diagnosis experiments on shock tube equipment are conducted by using both the electrostatic probe method and LF method.By comparing the diagnostic results of the two methods,the inversion results are relatively consistent with each other,thereby preliminarily verifying the feasibility of the LF method.The ratio of the electron density to the collision frequency has a relatively uniform distribution during the plasma stabilization.The LF diagnostic path is a loop around the model,which is suitable for diagnosing the plasma that surrounds the model.Finally,the causes of diagnostic discrepancy between the two methods are analyzed.The proposed method provides a new avenue for diagnosing high-density enveloping plasma.

Effect of rotating liquid samples on dynamic propagation and aqueous activation of a helium plasma jet

This paper aims to explore the effects of a rotating plasma-activated liquid on the dynamic propagation and biomedical application of a helium plasma jet.The spatial distribution of reactive species and the associated physico-chemical reactions are altered by the rotating liquid,which shows a significant weakening in the axial propagation of the plasma bullet and a strengthening in its radial expansion at the liquid surface.The phenomenon is prompted by the nonzero rotational velocity of the liquid and is regulated by airflow,target distance and liquid permittivity.The concentrations of aqueous reactive species,especially OH and O~-,and the inactivation effectiveness on cancer cells are weakened,indicating that a rotating liquid is not conducive to water treatment of the plasma jet although the treatment area of the plasma jet increases dynamically.This finding is of significance for the plasma–liquid interaction and the biomedical-related applications of plasma jets.

Study of plasma-based stable and ultrawideband electromagnetic wave absorption for stealth application

A plasma-based stable,ultra-wideband electromagnetic（EM） wave absorber structure is studied in this paper for stealth applications.The stability is maintained by a multi-layer structure with several plasma layers and dielectric layers distributed alternately.The plasma in each plasma layer is designed to be uniform,whereas it has a discrete nonuniform distribution from the overall view of the structure.The nonuniform distribution of the plasma is the key to obtaining ultra-wideband wave absorption.A discrete Epstein distribution model is put forward to constrain the nonuniform electron density of the plasma layers,by which the wave absorption range is extended to the ultra-wideband.Then,the scattering matrix method（SMM） is employed to analyze the electromagnetic reflection and absorption of the absorber structure.In the simulation,the validation of the proposed structure and model in ultra-wideband EM wave absorption is first illustrated by comparing the nonuniform plasma model with the uniform case.Then,the influence of various parameters on the EM wave reflection of the plasma are simulated and analyzed in detail,verifying the EM wave absorption performance of the absorber.The proposed structure and model are expected to be superior in some realistic applications,such as supersonic aircraft.

Energy dissipation and power deposition of electromagnetic waves in the plasma sheath

Energy dissipation and power deposition of electromagnetic waves(EMW)in the reentry plasma sheath provide an opportunity to investigate‘communication blackout’phenomena.Based on afinite element method(FEM)simulation,we analyze variation of EMW energy dissipation and power deposition profiles dependent on the wave polarization,wave incident angle,plasma density profile and electron collision frequency.Cutoff and resonance of EMW in the plasma sheath are crucial in explaining the regulation of energy dissipation and power deposition.

One-shot detection limits of time-alignment two-photon illumination radar

Quantum radar has recently gained increasing importance in a number of military applications.The estimation accuracy of one-shot quantum illumination events is significant in target detection.However,the accuracy is inevitably deteriorated by measurement noises.The traditional one-shot illumination emits a single photon towards a certain area which thermal noise exists in the path to,and the states of the received photons are hard to distinguish in the following processing.Therefore,a new optical probe source is proposed in this work.The independent detecting unit in the enhanced illumination is comprised of two photons aligned in time by using Hong–Ou–Mandel(HOM)interferometer.Further,oneshot detection in a general discrete model is realized and it proves a significant promotion in accuracy.The expansion of useful parts in parameter space and the lower minimal error probability for hypothesis testing have been mathematically demonstrated.The accuracy of one-shot detection can be effectively improved by the proposed scheme implying that it possesses great potential applications in quantum illumination and imaging.

Sparsity-Enhanced Model-Based Method for Intelligent Fault Detection of Mechanical Transmission Chain in Electrical Vehicle

In today’s world,smart electric vehicles are deeply integrated with smart energy,smart transportation and smart cities.In electric vehicles(EVs),owing to the harsh working conditions,mechanical parts are prone to fatigue damages,which endanger the driving safety of EVs.The practice has proved that the identification of periodic impact characteristics(PICs)can effectively indicate mechanical faults.This paper proposes a novel model-based approach for intelligent fault diagnosis ofmechanical transmission train in EVs.The essential idea of this approach lies in the fusion of statistical information and model information froma dynamic process.In the algorithm,a novel fractal wavelet decomposition(FWD)is used to investigate the time-frequency representation of the input signal.Based on the sparsity of the PIC model in the Hilbert envelope spectrum,amethod for evaluating PIC energy ratio(PICER)is defined based on an over-complete Fourier dictionary.A compound indicator considering kurtosis and PICER of dynamic signal is designed.Using this index,evaluations of the impulsiveness of the cycle-stationary process can be enabled,thus avoiding serious interference from the sporadic impact during measurements.The robustness of the proposed approach to noise is demonstrated via numerical simulations,and an engineering application is employed to validate its effectiveness.

Application of shifted lattice model to 3D compressible lattice Boltzmann method

An additional potential energy distribution function is introduced on the basis of previous D3Q25 model,and the equilibrium distribution function of D3Q25 is obtained by spherical function.A novel three-dimensional(3D)shifted lattice model is proposed,therefore a shifted lattice model is introduced into D3Q25.Under the finite volume scheme,several typical compressible calculation examples are used to verify whether the numerical stability of the D3Q25 model can be improved by adding the shifted lattice model.The simulation results show that the numerical stability is indeed improved after adding the shifted lattice model.

An improved SLAM based on RK-VIF:Vision and inertial information fusion via Runge-Kutta method

Simultaneous Localization and Mapping(SLAM)is the foundation of autonomous navigation for unmanned systems.The existing SLAM solutions are mainly divided into the visual SLAM(vSLAM)equipped with camera and the lidar SLAM equipped with lidar.However,pure visual SLAM have shortcomings such as low positioning accuracy,the paper proposes a visual-inertial information fusion SLAM based on Runge-Kutta improved pre-integration.First,the Inertial Measurement Unit(IMU)information between two adjacent keyframes is pre-integrated at the front-end to provide IMU constraints for visual-inertial information fusion.In particular,to improve the accuracy in pre-integration,the paper uses the RungeKutta algorithm instead of Euler integral to calculate the pre-integration value at the next moment.Then,the IMU pre-integration value is used as the initial value of the system state at the current frame time.We combine the visual reprojection error and imu pre-integration error to optimize the state variables such as speed and pose,and restore map points’three-dimensional coordinates.Finally,we set a sliding window to optimize map points’coordinates and state variables.The experimental part is divided into dataset experiment and complex indoor-environment experiment.The results show that compared with pure visual SLAM and the existing visual-inertial fusion SLAM,our method has higher positioning accuracy.

Temperature dependence of single-event transients in SiGe heterojunction bipolar transistors for cryogenic applications

We experimentally demonstrate that the dominant mechanism of single-event transients in silicon-germanium heterojunction bipolar transistors(SiGe HBTs)can change with decreasing temperature from+20℃to-180℃.This is accomplished by using a new well-designed cryogenic experimental system suitable for a pulsed-laser platform.Firstly,when the temperature drops from+20℃to-140℃,the increased carrier mobility drives a slight increase in transient amplitude.However,as the temperature decreases further below-140℃,the carrier freeze-out brings about an inflection point,which means the transient amplitude will decrease at cryogenic temperatures.To better understand this result,we analytically calculate the ionization rates of various dopants at different temperatures based on Altermatt's new incomplete ionization model.The parasitic resistivities with temperature on the charge-collection pathway are extracted by a two-dimensional(2D)TCAD process simulation.In addition,we investigate the impact of temperature on the novel electron-injection process from emitter to base under different bias conditions.The increase of the emitter-base junction's barrier height at low temperatures could suppress this electron-injection phenomenon.We have also optimized the built-in voltage equations of a high current compact model(HICUM)by introducing the impact of incomplete ionization.The present results and methods could provide a new reference for effective evaluation of single-event effects in bipolar transistors and circuits at cryogenic temperatures,and could provide a new evidence of the potential of SiGe technology in applications in extreme cryogenic environments.

Tool Wear State Recognition with Deep Transfer Learning Based on Spindle Vibration for Milling Process

The wear of metal cutting tools will progressively rise as the cutting time goes on. Wearing heavily on the toolwill generate significant noise and vibration, negatively impacting the accuracy of the forming and the surfaceintegrity of the workpiece. Hence, during the cutting process, it is imperative to continually monitor the tool wearstate andpromptly replace anyheavilyworn tools toguarantee thequality of the cutting.The conventional tool wearmonitoring models, which are based on machine learning, are specifically built for the intended cutting conditions.However, these models require retraining when the cutting conditions undergo any changes. This method has noapplication value if the cutting conditions frequently change. This manuscript proposes a method for monitoringtool wear basedonunsuperviseddeep transfer learning. Due to the similarity of the tool wear process under varyingworking conditions, a tool wear recognitionmodel that can adapt to both current and previous working conditionshas been developed by utilizing cutting monitoring data from history. To extract and classify cutting vibrationsignals, the unsupervised deep transfer learning network comprises a one-dimensional (1D) convolutional neuralnetwork (CNN) with a multi-layer perceptron (MLP). To achieve distribution alignment of deep features throughthe maximum mean discrepancy algorithm, a domain adaptive layer is embedded in the penultimate layer of thenetwork. A platformformonitoring tool wear during endmilling has been constructed. The proposedmethod wasverified through the execution of a full life test of end milling under multiple working conditions with a Cr12MoVsteel workpiece. Our experiments demonstrate that the transfer learning model maintains a classification accuracyof over 80%. In comparisonwith the most advanced tool wearmonitoring methods, the presentedmodel guaranteessuperior performance in the target domains.

X-ray communication based simultaneous communication and ranging

To improve the link efficiency and decrease the payloads in space explorations, a novel simultaneous communication and ranging method based on x-ray communication（XCOM） is proposed in this paper. A delicate signal symbol structure is utilized to achieve simultaneous data transmission and range measurement. With the designed symbol structure, the ranging information is imbedded into the communication signal and transmitted with it simultaneously. The range measurement is realized by the two-way transmission of the range information. To illustrate the proposed method, firstly, the principle of the method is introduced and the signal processing procedure is presented. Then, the performance of the proposed method is analyzed theoretically in various aspects, including the acquisition probability, the bit error rate, the ranging jitter,etc. Besides, numerical experiments are conducted to verify the proposed method and evaluate the system performance.The simulation results show that the proposed method is feasible and that the system performance is influenced by the parameters concerning the signal symbol structure. Compared with the previous methods, the proposed method improves the link efficiency and is beneficial for system miniaturization and integration, which could provide a potential option for future deep space explorations.

Research on simultaneous localization and mapping for AUV by an improved method:Variance reduction FastSLAM with simulated annealing

At present,simultaneous localization and mapping(SLAM) for an autonomous underwater vehicle(AUV)is a research hotspot.Aiming at the problem of non-linear model and non-Gaussian noise in AUV motion,an improved method of variance reduction fast simultaneous localization and mapping(FastSLAM) with simulated annealing is proposed to solve the problems of particle degradation,particle depletion and particle loss in traditional FastSLAM,which lead to the reduction of AUV location estimation accuracy.The adaptive exponential fading factor is generated by the anneal function of simulated annealing algorithm to improve the effective particle number and replace resampling.By increasing the weight of small particles and decreasing the weight of large particles,the variance of particle weight can be reduced,the number of effective particles can be increased,and the accuracy of AUV location and feature location estimation can be improved to some extent by retaining more information carried by particles.The experimental results based on trial data show that the proposed simulated annealing variance reduction FastSLAM method avoids particle degradation,maintains the diversity of particles,weakened the degeneracy and improves the accuracy and stability of AUV navigation and localization system.

An Organic Solvent-Assisted Intercalation and Collection (OAIC) for Ti_(3)C_(2)T_(x) MXene with Controllable Sizes and Improved Yield

A good method of synthesizing Ti_(3)C_(2)T_(x)(MXene)is critical for ensuring its success in practical applications,e.g.,electromagnetic interference shielding,electrochemical energy storage,catalysis,sensors,and biomedicine.The main concerns focus on the moderation of the approach,yield,and product quality.Herein,a modified approach,organic solvent-assisted intercalation and collection,was developed to prepare Ti_(3)C_(2)T_(x) flakes.The new approach simultaneously solves all the concerns,featuring a low requirement for facility(centrifugation speed<4000 rpm in whole process),gram-level preparation with remarkable yield(46.3%),a good electrical conductivity(8672 S cm^(−1)),an outstanding capacitive performance(352 F g^(−1)),and easy control over the dimension of Ti_(3)C_(2)T_(x) flakes(0.47–4.60μm^(2)).This approach not only gives a superb example for the synthesis of other MXene materials in laboratory,but sheds new light for the future mass production of Ti_(3)C_(2)T_(x) MXene.

Three-dimensional simulation of fabrication process-dependent effects on single event effects of SiGe heterojunction bipolar transistor

The fabrication process dependent effects on single event effects （SEEs） are investigated in a commercial silicon- germanium heterojunction bipolar transistor （SiGe HBT） using three-dimensional （3D） TCAD simulations. The influences of device structure and doping concentration on SEEs are discussed via analysis of current transient and charge collection induced by ions strike. The results show that the SEEs representation of current transient is different from representation of the charge collection for the same process parameters. To be specific, the area of C/S junction is the key parameter that affects charge collection of SEE. Both current transient and charge collection are dependent on the doping of collector and substrate. The base doping slightly influences transient currents of base, emitter, and collector terminals. However, the SEEs of SiGe HBT are hardly affected by the doping of epitaxial base and the content of Ge.

Analysis of inverse synthetic aperture radar imaging in the presence of time-varying plasma sheath

The plasma sheath can induce radar signal modulation,causing not only ineffective target detection,but also defocusing in inverse synthetic aperture radar(ISAR)imaging.In this paper,through establishing radar echo models of the reentry object enveloped with time-varying plasma sheath,we simulated the defocusing of ISAR images in typical environment.Simulation results suggested that the ISAR defocusing is caused by false scatterings,upon which the false scatterings’formation mechanism and distribution property are analyzed and studied.The range of false scattering correlates with the electron density fluctuation frequency.The combined value of the electron density fluctuation and the pulse repetition frequency jointly determines the Doppler of false scattering.Two measurement metrics including peak signal-to-noise ratio and structural similarity are used to evaluate the influence of ISAR imaging.