Rotating tank experiments for the study of geophysical fluid dynamics

Geophysical fluid dynamics(GFD)is an interdisciplinary field that studies the large-scale motion of fluids in the natural world.With a wide range of applications such as weather forecasts and climate prediction,GFD employs various research approaches including in-situ observations,satellite measurements,numerical simulations,theoretical analysis,artificial intelligence,and physical model experiments in laboratory.Among these approaches,rotating tank experiments provide a valuable tool for simulating naturally-occurring fluid motions in laboratories.With proportional scaling and proper techniques,scientists can reproduce multi-scale physical processes of stratified fluids in the rotation system,which allows for the simulation of essential characteristics of fluid motions in the atmosphere and oceans.In this review,rotating tanks of various scales in the world are introduced,as these tanks have been actively used to explore fundamental scientific questions in ocean and atmosphere dynamics.To illustrate the GFD experiments,three representative cases are presented to demonstrate the frontier achievements in the the GFD study by using rotating tank experiments:mesoscale eddies in the ocean,convection processes,and plume dynamics.Detailed references for the experimental procedures are provided.Future studies are encouraged to further explore the utilization of rotating tanks with improvements in experimental design and integration of other research methods.This is a promising direction of GFD to help enhance our understanding of the complex nature of fluid motions in the natural world and to address the challenges posed by global environmental changes.

Cognitive interference decision method for air defense missile fuze based on reinforcement learning

To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is proposed.First,dividing the distance between the missile and the target into multiple states to increase the quantity of state spaces.Second,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference parameters.The interference effect is determined by detecting whether the fuze signal disappears.Finally,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference form.The effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile rendezvous.The optimal interference form for each distance state has been obtained.Compared with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference.

Automatic modulation recognition of radio fuzes using a DR2D-based adaptive denoising method and textural feature extraction

The identification of intercepted radio fuze modulation types is a prerequisite for decision-making in interference systems.However,the electromagnetic environment of modern battlefields is complex,and the signal-to-noise ratio(SNR)of such environments is usually low,which makes it difficult to implement accurate recognition of radio fuzes.To solve the above problem,a radio fuze automatic modulation recognition(AMR)method for low-SNR environments is proposed.First,an adaptive denoising algorithm based on data rearrangement and the two-dimensional(2D)fast Fourier transform(FFT)(DR2D)is used to reduce the noise of the intercepted radio fuze intermediate frequency(IF)signal.Then,the textural features of the denoised IF signal rearranged data matrix are extracted from the statistical indicator vectors of gray-level cooccurrence matrices(GLCMs),and support vector machines(SVMs)are used for classification.The DR2D-based adaptive denoising algorithm achieves an average correlation coefficient of more than 0.76 for ten fuze types under SNRs of-10 d B and above,which is higher than that of other typical algorithms.The trained SVM classification model achieves an average recognition accuracy of more than 96%on seven modulation types and recognition accuracies of more than 94%on each modulation type under SNRs of-12 d B and above,which represents a good AMR performance of radio fuzes under low SNRs.

Underwater four-quadrant dual-beam circumferential scanning laser fuze using nonlinear adaptive backscatter filter based on pauseable SAF-LMS algorithm

The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance.

Underdetermined direction of arrival estimation with nonuniform linear motion sampling based on a small unmanned aerial vehicle platform

Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.

Three-Dimensional Convection in an Inclined Porous Layer Subjected to a Vertical Temperature Gradient

In this paper,we study the onset and development of three-dimensional convection in a tilted porous layer saturated with a liquid.The layer is subjected to a gravitational field and a strictly vertical temperature gradient.Typically,problems of thermal convection in tilted porous media saturated with a liquid are studied by assuming constant different temperatures at the boundaries of the layer,which prevent these systems from supporting conductive(non-convective)states.The boundary conditions considered in the present work allow a conductive state and are representative of typical geological applications.In an earlier work,we carried out a linear stability analysis of the conductive state.It was shown that at any layer tilt angles,the most dangerous type of disturbances are longitudinal rolls.Moreover,a non-zero velocity component exists in z-direction.In the present work,threedimensional non-linear convection regimes are studied.The original three-dimensional problem is reduced to two-dimensional one with an analytical expression for the velocity z-component v_(z)=v_(z)(x,y).It is shown that the critical Rayleigh number values obtained through numerical solutions of the obtained 2D problem by a finite difference method for different layer inclination angles,are in a good agreement with those predicted by the linear theory.The number of convective rolls realized in nonlinear calculations also fits the linear theory predictions for a given cavity geometry.Calculations carried out at low supercriticalities show that a direct bifurcation takes place.With increasing supercriticality,no transitions to other convective regimes are detected.The situation studied in this problem can be observed in oil-bearing rock formations under the influence of a geothermal temperature gradient,where the ensuing fluid convection can affect the distribution of oil throughout the layer.

Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

Formation of Water Quality of Surface Water Bodies Used in the Material Processing

In the process of production or processing of materials by various methods,there is a need for a large volume of water of the required quality.Today in many regions of the world,there is an acute problem of providing industry with water of a required quality.Its solution is an urgent and difficult task.The water quality of surface water bodies is formed by a combination of a large number of both natural and anthropogenic factors,and is often significantly heterogeneous not only in the water area,but also in depth.As a rule,the water supply of large industrial enterprises is located along the river network.Mergers are the most important nodes of river systems.Understanding the mechanism of transport of pollutants at the confluence of rivers is critical for assessing water quality.In recent years,thanks to the data of satellite images,the interest of researchers in the phenomenon of mixing the waters of merging rivers has increased.The nature of the merger is influenced by the formation of transverse circulation.Within the framework of this work,a study of vorticity,as well as the width of the mixing zone,depending on the distance from the confluence,the speeds of the merging rivers and the angle of confluence was carried out.Since the consumer properties of water are largely determined by its chemical and physical indicators,the intensity of mixing,determined largely by the nature of the secondary circulation,is of fundamental importance for assessing the distribution of hydrochemical indicators of water quality in the mixing zone.These characteristics are important not only for organizing water intake for drinking and technical purposes with the best consumer properties,but also for organizing an effective monitoring system for confluence zones.

Is magnesium deficiency the major cause of needle chlorosis of Pinus taeda in Brazil?

Needle chlorosis(NC)in Pinus taeda L.systems in Brazil becomes more frequent after second and third harvest rotation cycles.In a study to identify factors contributing to yellowing needle chorosis(YNC),trees were grown in soils originating from contrasting parent materials,and soils and needles(whole,green and chlorotic portions)from 1-and 2-year-old branches and the first and second needle flush release at four sites with YNC on P.taeda were analyzed for various elements and properties.All soils had very low base levels(Ca^(2+),Mg^(2+)and K^(+))and P,suggesting a possible lack of multiple elements.YNC symptoms started at needle tips,then extended toward the needle base with time.First flush needles had longer portions with YNC than second flush needles did.Needles from the lower crown also had more symptoms along their length than those higher in the canopy.Symptoms were similar to those reported for Mg.In chlorotic portions,Mg and Ca concentrations were well below critical values;in particular,Mg levels were only one third of the critical value of 0.3 g kg^(-1).Collectively,results suggest that Mg deficiency is the primary reason for NC of P.taeda in various parent soils in Brazil.

Health risk assessment of heavy metal pollution in groundwater of a karst basin,SW China

To investigate the presence of metal elements and assess their health risk for the populace in the Nandong Underground River Basin(NURB),we conducted an analysis of eleven common heavy metals in the water body.A Health risk assessment(HRA)model was employed to analyze 84 water samples from the NURB.The detection results revealed the following order of heavy metals concentrations:Fe>Al>Mn>Zn>As>Cd>Pb>Cr>Ni>Cu>Hg.Correlation analysis indicated a certain similarity in material source and migration transformation among these eleven metal elements.Our study identified that the health risks for local residents exposed to metal elements in the water of NURB primarily stem from carcinogenic risk(10^(−6)–10^(−4)a^(−1))through the drinking water pathway.Moreover,the health risk of heavy metal exposure for children through drinking water was notably higher than for adults.The maximum health risks of Cr in both underground and surface water exceeded the recommendation standard(5.0×10^(−5)a^(−1))from ICRP,surpassing the values recommended by the Swedish Environmental Protection Agency,the Dutch Ministry of Construction and Environment and the British Royal Society(5.0×10^(−6)a^(−1)).The results of the health risk assessment indicate that Cr in the water of NURB is the primary source of carcinogenic risk for local residents,followed by Cd and As.Consequently,it is imperative to control these three carcinogenic metals when the water was used as drinking water resource.

A Comprehensive 3-Steps Methodology for Vibration-Based Fault Detection,Diagnosis and Localization in Rotating Machines

In any industry,it is the requirement to know whether the machine is healthy or not to operate machine further.If the machine is not healthy then what is the fault in the machine and then finally its location.The paper is proposing a 3-Steps methodology for the machine fault diagnosis to meet the industrial requirements to aid the maintenance activity.The Step-1 identifies whether machine is healthy or faulty,then Step-2 detect the type of defect and finally its location in Step-3.This method is extended further from the earlier study on the 2-Steps method for the rotor defects only to the 3-Steps methodology to both rotor and bearing defects.The method uses the optimised vibration parameters and a simple Artificial Neural Network(ANN)-based Machine Learning(ML)model from the earlier studies.The model is initially developed,tested and validated on an experimental rotating rig operating at a speed above 1st critical speed.The proposed method and model are then further validated at 2 different operating speeds,one below 1st critical speed and other above 2nd critical speed.The machine dynamics are expected to be significantly different at these speeds.This highlights the robustness of the proposed 3-Steps method.

Spatial Analysis of Structural Changes and Floristic Distribution of Forest Landscapes in the Centre-West Region of Burkina Faso

Land use and occupation dynamics impact landscape structure, diversity, richness and balance of vegetation cover. The aim of this study is to describe the process of fragmentation of the forest landscape from 1990 to 2020 and its effects on the degradation of the floristic characteristics of the vegetation in the Central West region of Burkina Faso. To achieve this, satellite data were collected and processed as part of a mapping approach to describing the landscape and the different types of landscape fragmentation. Mapping indices of landscape fragmentation (relative richness, change process, patch zones, Shannon diversity index) were also calculated. These indices were programmed in Idrisi Selva’s Landscape Pattern and change process analysis module. Spatio-temporal analysis revealed that in 1990, the landscape was dominated by natural vegetation formations, covering 66.33% of the territory. By 2020, these had been degraded to 44.80% by farmlands. The mapping analysis of indices also showed that the study area is characterized by four types of landscape fragmentation, including attrition, aggregation, creation and dissection. We also observed an abundant homogeneity, diversity and richness of conservation areas with legal and land tenure status. However, the structure is heterogeneous in landscapes outside protected areas and in areas under human occupation. This shows the crucial role played by conservation areas in preserving and balancing the diversity of vegetative cover in the study area.

Labyrinth seal leakage and dynamics characteristics analysis based on Black Model

One of the important problems to be tackled in turbo machines is the leakage dynamics characteristics of labyrinth seals. In this paper we analyzed the effect of labyrinth seal structure and the change in fluid flow pressure on the leakage characteristics of seal. Computational fluid dynamics (CFD) model for 3D labyrinth seal was built which provides a basis for reducing steam flow excitation. The streamline pattern and the pressure drop characteristics for leakage of steam through a labyrinth seal was investigated. Simulations of internal flow and leakage characteristics had been performed by CFD software and Black-Child model. The results showed that the amount of leakage is directly proportional to the tooth gap and inlet pressure and inversely proportional to the cavity depth and outlet pressure. The proposed CFD model provides a feasible method to predict the leakage characteristics of labyrinth seal in response to the structure of seal and the change in inlet-outlet pressures.

Spatio-Temporal Dynamics of the Noun Floodplain (Cameroon) Using Remote Sensing

In Cameroon, the pressure on wetlands appears to be increasing, leading to desertification and land degradation. This study aims to characterize the spatial and temporal dynamics of land cover in the Noun floodplain in Cameroon using multi-date satellite data. To achieve this, the methodology consisted in using remote sensing and geographical information’s systems techniques to identify spatial units and detect changes over a 22-year period (1999 to 2021). The land cover maps were produced from an unsupervised classification with maximum likelihood. The results identified eight classes: herbaceous savannahs with shrubs, forest galleries, fields and plantations, herbaceous tan, young fallows, mineralized and built-up soils, bare soils and surface waters. It appears that in 1999, the landscape was dominated by natural vegetation (72.6%) located from north to south of the Noun plain. However, since 2004, the landscape has been dominated by agricultural areas (56.8%). Natural formations have been progressively reduced in space over time. The evolution of the Noun floodplain landscape reveals that 14.3% of the space has remained stable. These are fields and plantations, young fallows, mineralized soils and surface water. This space has not migrated to other classes. While about 73.9% of the area has moved to higher classes, of which 35.6% to herbaceous tans and 26% to fields and plantations. On the other hand, 72.6% of the area (herbaceous savannahs and forests gallery) has been heavily degraded. These results show that the landscape of the Noun floodplain is marked by a progressive agricultural extension, which would be at the origin of the land degradation. Therefore they alert the different actors in the territory on the level of advanced land degradation and suggest sustainable land management on a local scale.

多层多孔金属泡沫填充的水基散热器冷却CPU:基于热液和熵产分析角度

本研究利用多层多孔金属泡沫从热液和熵产分析角度来改善散热器的性能,并采用计算流体力学方法进行数值模拟,将结果与单层金属泡沫和无金属泡沫情况进行了比较。对于多层泡沫,考虑了两种模式:层间渗透率随着CPU距离的增加而逐渐增加或减少。结果表明,当泡沫层渗透率随着CPU距离的增加而逐渐减少时,散热器的温度分布均匀性最好,热阻最低,对流系数最高,热液综合性能最好;当泡沫层渗透率随着CPU距离的增加而逐渐增加时,多层泡沫的摩擦熵最低,热熵最高,总熵产率最低。与不含金属泡沫的散热器相比,摩擦熵、热熵和总熵产率分别降低了64.51%~73.02%、42.80%~220.34%和19.68%~62.36%。

Nonlinear mixing-based terahertz emission in inclined rippled density plasmas

We propose to investigate the THz field generation using nonlinear mixing mechanism of laser beat wave with inclined rippled density plasmas.Two laser pulses with frequencies(ω_(1),ω_(2)) and wave vectors(k_(1),k_(2)) co-propagate and resultant laser beat wave forms at beat frequency(ω_(1)-ω_(2)).Laser beat wave imparts a nonlinear force on the ambient electrons and pushes them outward with nonlinear velocity v_(NL).Coupling of induced density perturbation and nonlinear velocity v_(NL)generates nonlinear currents at laser beat frequency that further generates electromagnetic field E_((ω_(1)-ω_(2))) in terahertz(THz)range.In the present scheme,density ripples are introduced at an angle with respect to laser propagation and flat Gaussian index(f) is introduced in laser field profile that transform curved top of Gaussian field envelope into flat top field envelope.The combined effect of flat laser pulses with inclined density ripples in plasmas shows 10-fold enhancement in THz field amplitude when flat-Gaussian index(f) varies from 1 to 4.Also,the THz field intensifies when density ripples inclination increases upto a certain angle and then decreases.

Experimental investigation on de-icing by an array of impact rod-type plasma synthetic jets

Since flight accidents due to aircraft icing occur from time to time,this paper proposes an array of impact rod-type plasma synthetic jet de-icing methods for aircraft icing problems.The impact rod-type plasma synthetic jet actuator(PSJA)is based on the traditional PSJA with an additional impact rod structure for better de-icing in the flight environment.In this work,we first optimize the ice-breaking performance of a single-impact rod-type PSJA,and then conduct an array of impact rod-type plasma synthetic jet ice-breaking experiments to investigate the relationship between crack expansion and discharge energy,ice thickness and group spacing.The results show that the impact force and impulse of a single-impact rod-type PSJA are proportional to the discharge energy,and there exists a threshold energy Qmin for a single actuator to break the ice,which is proportional to the ice thickness.Only when the discharge energy reaches above Qmin can the ice layer produce cracks,and at the same time,the maximum radial crack length produced during the ice-breaking process is proportional to the discharge energy.When the ice is broken by an array of impact rod PSJAs,the discharge energy and group spacing together determine whether the crack can be extended to the middle region of the actuator.When the group spacing is certain,increasing the energy can increase the intersection of cracks in the middle region,and the ice-fragmentation degree is increased and the ice-breaking effect is better.At the same time,the energy estimation method of ice breaking by an array of impact rod-type PSJAs is proposed according to the law when a single actuator is breaking ice.

Investigation of the interaction between NS-DBD plasma-induced vortexes and separated flow over a swept wing

The effect of nanosecond pulsed dielectric barrier discharge(NS-DBD) plasma flow separation control is closely related to the actuation frequency,because it involves the interaction between plasma-induced vortexes and separated flow.In order to study the mechanism of NS-DBD plasma flow separation control over a swept wing,especially the influence of the actuation frequency,at first,experimental studies of the actuation frequencies at 100 Hz are conducted to validate the numerical simulation method.Then,numerical studies of different actuation frequencies which are 50 Hz,100 Hz,160 Hz,200 Hz,500 Hz,and 1000 Hz,respectively are conducted.The interaction between the plasma-induced vortexes and the separated flow is analyzed.Results show that there is a range of the actuation frequency which includes the frequency(160 Hz) calculated by the average aerodynamic chord length to make the control effect good,but when the actuation frequencies are too low(50 Hz) or too high(1000 Hz),the control effect will get worse.The former is because plasmainduced vortexes disappear in a period within an actuation cycle;the latter is because plasma-induced vortexes cannot develop completely,resulting in a weak vortex intensity.

Parameter estimation method for a linear frequency modulation signal with a Duffing oscillator based on frequency periodicity

In view of the complexity of existing linear frequency modulation(LFM)signal parameter estimation methods and the poor antinoise performance and estimation accuracy under a low signal-to-noise ratio(SNR),a parameter estimation method for LFM signals with a Duffing oscillator based on frequency periodicity is proposed in this paper.This method utilizes the characteristic that the output signal of the Duffing oscillator excited by the LFM signal changes periodically with frequency,and the modulation period of the LFM signal is estimated by autocorrelation processing of the output signal of the Duffing oscillator.On this basis,the corresponding relationship between the reference frequency of the frequencyaligned Duffing oscillator and the frequency range of the LFM signal is analyzed by the periodic power spectrum method,and the frequency information of the LFM signal is determined.Simulation results show that this method can achieve high-accuracy parameter estimation for LFM signals at an SNR of-25 dB.

Experimental and numerical investigation of a self-supplementing dual-cavity plasma synthetic jet actuator

The primary issue regarding the plasma synthetic jet actuator(PSJA)is its performance attenuation at high frequencies.To solve this issue,a self-supplementing,dual-cavity,plasma synthetic jet actuator(SD-PSJA)is designed,and the static properties of the SD-PSJA are investigated through experiments and numerical simulations.The pressure measurement shows that the SD-PSJA has two saturation frequencies(1200 Hz and 2100 Hz),and the experimental results show that both the saturation frequencies decrease as the volume of the bottom cavity of the SD-PSJA increases.As the size of the supplement hole increases,the first saturation frequency increases continuously,while the second saturation frequency shows a trend of first decreasing and then increasing.Numerical simulations show that the working process of the SD-PSJA is similar to that of the PSJA,but the volume of the cavity in the SD-PSJA is smaller than that of the PSJA;the SD-PSJA can supplement air to the top cavity through two holes,thus reducing the refresh time and effectively improving the jet intensity of the actuator at high frequencies.