A New Method for Deriving High-Vertical-Resolution Wind Vector Data from the L-Band Radar Sounding System in China

High-vertical-resolution radiosonde wind data are highly valuable for describing the dynamics of the meso-and microscale atmosphere. However, the current algorithm used in China's L-band radar sounding system for calculating highvertical-resolution wind vectors excessively smooths the data, resulting in significant underestimation of the calculated kinetic energy of gravity waves compared to similar products from other countries, which greatly limits the effective utilization of the data. To address this issue, this study proposes a novel method to calculate high-vertical-resolution wind vectors that utilizes the elevation angle, azimuth angle, and slant range from L-band radar. In order to obtain wind data with a stable quality, a two-step automatic quality control procedure, including the RMSE-F(root-mean-square error F) test and elemental consistency test are first applied to the slant range data, to eliminate continuous erroneous data caused by unstable signals or radar malfunctions. Then, a wind calculation scheme based on a sliding second-order polynomial fitting is utilized to derive the high-vertical-resolution radiosonde wind vectors. The evaluation results demonstrate that the wind data obtained through the proposed method show a high level of consistency with the high-resolution wind data observed using the Vaisala Global Positioning System and the data observed by the new Beidou Navigation Sounding System. The calculation of the kinetic energy of gravity waves in the recalculated wind data also reaches a level comparable to the Vaisala observations.

Parameterization of Tree and Shrub Stem Wood Density Adaptions to Multiple Climate and Soil Factor Gradients

Wood density(WD)is an important quality and functional trait of wood.However,despite the relationships between WD and abiotic factors being important to model or predict spatial distributions of functional traits,as well as responses of vegetation to climate changes,in current Earth system models or dynamic global vegetation models(ESMs/DGVMs),WD is often oversimplified,being defined as a globally uniform constant either for all plant functional types(PFTs)or for each individual PFT.Such oversimplifications may lead to simulation biases in the morphology of woody PFTs,as well as ecosystem transition and vegetation-atmosphere interactions.Moreover,existing conclusions about the relationships between WD and abiotic factors drawn from field observations remain mixed,making model parameterization improvements difficult.This study systematically investigated the influences of climate and soil factors on WD across various PFTs.Optimal fitting models for predicting WD within each PFT were then constructed by utilizing our collated global database of 138604 observations.For WDs of tree PFTs,climate emerges as a more influential factor than soil characteristics,whereas for shrub PFTs the effects of climate and soil are of equivalent significance.Across all six PFTs,correlation coefficients between predictions by fitting models and observed WD range from 0.49 to 0.93.The predicted and observed WD exhibit good agreement across climate space.It is expected that the incorporation of our research findings into DGVMs will improve the simulation of tree height and forest fractional coverage,particularly in the central forest areas and forest transition zones.

A statistical analysis of the Kappa-type energy spectrum distribution of radiation belt electrons observed by Van Allen Probes

The energy spectrum of energetic electrons is a key factor representing the dynamic variations of Earth’s Van Allen radiation belts.Increased measurements have indicated that the commonly used Maxwellian and Kappa distributions are inadequate for capturing the realistic spectral distributions of radiation belt electrons.Here we adopt the Kappa-type(KT)distribution as the fitting function and perform a statistical analysis to investigate the radiation belt electron flux spectra observed by the Van Allen Probes.By calculating the optimal values of the key KT distribution parameters(i.e.,κandθ2)from the observed spectral shapes,we fit the radiation belt electron fluxes at different L-shells under different geomagnetic conditions.In this manner,we obtain typical values of the KT distribution parameters,which are statistically feasible for modeling the radiation belt electron flux profiles during either geomagnetically quiet or active periods.A comparison of the KT distribution model results with those using the Maxwellian or Kappa distribution reveals the advantage of the KT distribution for studying the overall properties of the radiation belt electron spectral distribution,which has important implications for deepening the current understanding of the radiation belt electron dynamics under evolving geomagnetic conditions.

Microscopic defects formation and dynamic mechanical response analysis of Q345 steel plate subjected to explosive load

As the basic protective element, steel plate had attracted world-wide attention because of frequent threats of explosive loads. This paper reports the relationships between microscopic defects of Q345 steel plate under the explosive load and its macroscopic dynamics simulation. Firstly, the defect characteristics of the steel plate were investigated by stereoscopic microscope(SM) and scanning electron microscope(SEM). At the macroscopic level, the defect was the formation of cave which was concentrated in the range of 0-3.0 cm from the explosion center, while at the microscopic level, the cavity and void formation were the typical damage characteristics. It also explains that the difference in defect morphology at different positions was the combining results of high temperature and high pressure. Secondly, the variation rules of mechanical properties of steel plate under explosive load were studied. The Arbitrary Lagrange-Euler(ALE) algorithm and multi-material fluid-structure coupling method were used to simulate the explosion process of steel plate. The accuracy of the method was verified by comparing the deformation of the simulation results with the experimental results, the pressure and stress at different positions on the surface of the steel plate were obtained. The simulation results indicated that the critical pressure causing the plate defects may be approximately 2.01 GPa. On this basis, it was found that the variation rules of surface pressure and microscopic defect area of the Q345 steel plate were strikingly similar, and the corresponding mathematical relationship between them was established. Compared with Monomolecular growth fitting models(MGFM) and Logistic fitting models(LFM), the relationship can be better expressed by cubic polynomial fitting model(CPFM). This paper illustrated that the explosive defect characteristics of metal plate at the microscopic level can be explored by analyzing its macroscopic dynamic mechanical response.

Determination of Material Parameters of EVA Foam under Uniaxial Compressive Testing Using Hyperelastic Models

The objective of this research was to determine the mechanical parameter from EVA foam and also investigate its behavior by using Blatz-Ko,Neo-Hookean,Mooney model and experimental test.The physical characteristic of EVA foam was also evaluated by scanning electron microscopy(SEM).The results show that Blatz-Ko and Neo-Hookean model can fit the curve at 5%and 8%strain,respectively.The Mooney model can fit the curve at 50%strain.The modulus of rigidity evaluated from Mooney model is 0.0814±0.0027 MPa.The structure of EVA foam from SEM image shows that EVA structure is a closed cell with homogeneous porous structure.From the result,it is found that Mooney model can adjust the data better than other models.This model can be applied for mechanical response prediction of EVA foam and also for reference value in engineering application.

Comparison of engineering failures and seismic responses of 500 kV transformer-bushing systems in the 2022 Luding earthquake

Cemented and mechanically clamped types of end fittings(fitting-C and fitting-M)are commonly used in transformer bushings.During the Luding Ms 6.8 earthquake that occurred in China on September 5,2022,all transformer bushings with the two types of end fittings in a 500 kV substation were damaged.Post-earthquake field investigations were conducted,and the failures of the two types of bushings were compared.Two elementary simulation models of the transformer-bushing systems were developed to simulate the engineering failures,and further compute their seismic responses for comparison.The results indicate that the hitch lugs of the connection flange are structurally harmful to seismic resistance.Fitting-M can decrease the bending stiffness of the bushing due to the flexible sealing rubber gasket.Since it provides a more flexible connection that dissipates energy,the peak accelerations and relative displacements at the top of the bushing are significantly lower than those of the bushing with fitting-C.Compared with fitting-C,fitting-M transfers the high-stress areas from the connection flange to the root of the porcelain,so the latter becomes the most vulnerable component.Fitting-M increases the failure risk of the low-strength porcelain,indicating the unsuitability of applying it in high-intensity fortification regions.

A frequency domain estimation and compensation method for system synchronization parameters of distributed-HFSWR

To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on the target detection performance,firstly,a spatial detection model of distributed high-frequency surface wave radar(distributed-HFSWR)is established in this paper.In this model,a method for accurate extraction of direct wave spectrum based on curve fitting is proposed to obtain accurate system internal delay and frequency synchronization error under complex electromagnetic environment background and low signal to noise ratio(SNR),and to compensate for the shift of range and Doppler frequency caused by time-frequency synchronization error.The direct wave component is extracted from the spectrum,the range estimation error and Doppler estimation error are reduced by the method of curve fitting,and the fitting accuracy of the parameters is improved.Then,the influence of frequency synchronization error on target range and radial Doppler velocity is quantitatively analyzed.The relationship between frequency synchronization error and radial Doppler velocity shift and range shift is given.Finally,the system synchronization parameters of the trial distributed-HFSWR are obtained by the proposed spectrum extraction method based on curve fitting,the experimental data is compensated to correct the shift of the target,and finally the correct target parameter information is obtained.Simulations and experimental results demonstrate the superiority and correctness of the proposed method,theoretical derivation and detection model proposed in this paper.

A Residual Frequency Offset Estimation Method Based on Range Migration Fitting

Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.

Data Mining Based Research of Development Direction of Waist Protection Equipment

[Objectives]To explore the trend of brands towards the design of waist protection products through data mining,and to provide reference for the design concept of the contour of waist protection pillow.[Methods]The structural design information of all waist protection equipment was collected from the national Internet platform,and the data were classified and a database was established.IBM SPSS 26.0 and MATLAB 2018a were used to analyze the data and tabulate them in Tableau 2022.4.After the association rules were clarified,the data were imported into Cinema 4D R21 to create the concept contour of waist protection pillow.[Results]The average and standard deviation of the single airbag design were the highest in all groups,with an average of 0.511 and a standard deviation of 0.502.The average and standard deviation of the upper and lower dual airbags were the lowest in all groups,with an average of 0.015 and a standard deviation of 0.120;the correlation coefficient between single airbag and 120°arc stretching was 0.325,which was positively correlated with each other(P<0.01);the correlation coefficient between multiple airbags and 360°encircling fitting was 0.501,which was positively correlated with each other and had the highest correlation degree(P<0.01).[Conclusions]The single airbag design is well recognized by companies,and has received the highest attention among all brand products.While focusing on single airbag design,most brands will consider the need to add 120°arc stretching elements in product design.At the time of focusing on multiple airbag design,some brands believe that 360°encircling fitting elements need to be added to the product,and the correlation between the two is the highest among all groups.

Method for Improving Digital Elevation Model Precision of Consumer Level Unmanned Aerial Vehicles

Currently,the aerial survey system of low-altitude unmanned aerial vehicles(UAVs)has been widely used in acquiring digital map 4D products,mapping,digital linear maps,and other aspects.However,there are problems,such as low precision and weak practicability in constructing digital elevation model(DEM)products through the data collected using consumption level UAVs.Therefore,improving the accuracy of DEM products obtained by consumption level UAVs is a crucial and complex issue in the research of UAV aerial survey systems.In precision elevation measurement,the geodetic height of a certain number of ground points with reasonable distribution in the region is often obtained first.Then,the normal height of the ground points is obtained by leveling,and the elevation residual value surface of the region is fitted.Finally,the normal height of the points to be solved in the region is obtained by fitting the elevation residual surface.Therefore,the elevation residual fitting method was used to improve the accuracy of consumer UAV DEM products in this study.First,a high-quality ground point cloud was obtained by constructing the gradient filtering-cloth simulation filtering(GF-CSF)model.Second,an abnormal elevation fitting residual DEM model was constructed.Lastly,the final DEM was obtained using the DEM difference method.The experimental results show that among the 20 random sampling inspection points,the average elevation residual was 2.3 mm,and the root mean square error(RMSE)was 16.7 mm after the DEM accuracy was improved by the method.The average elevation residual without improving the DEM accuracy was 28.6 mm,and RMSE was 33.7 mm.

Exploring a New Lifetime Distribution for Modelling the Waiting Time of Bank Customers

The fitting of lifetime distribution in real-life data has been studied in various fields of research. With the theory of evolution still applicable, more complex data from real-world scenarios will continue to emerge. Despite this, many researchers have made commendable efforts to develop new lifetime distributions that can fit this complex data. In this paper, we utilized the KM-transformation technique to increase the flexibility of the power Lindley distribution, resulting in the Kavya-Manoharan Power Lindley (KMPL) distribution. We study the mathematical treatments of the KMPL distribution in detail and adapt the widely used method of maximum likelihood to estimate the unknown parameters of the KMPL distribution. We carry out a Monte Carlo simulation study to investigate the performance of the Maximum Likelihood Estimates (MLEs) of the parameters of the KMPL distribution. To demonstrate the effectiveness of the KMPL distribution for data fitting, we use a real dataset comprising the waiting time of 100 bank customers. We compare the KMPL distribution with other models that are extensions of the power Lindley distribution. Based on some statistical model selection criteria, the summary results of the analysis were in favor of the KMPL distribution. We further investigate the density fit and probability-probability (p-p) plots to validate the superiority of the KMPL distribution over the competing distributions for fitting the waiting time dataset.

Vision-based Dynamics Monitoring(VDM)for Diagnosing the Variations of Wind Turbine Tower Foundation Conditions

A slight uneven settlement of the foundation may cause the wind turbine to shake,tilt,or even collapse,so it is increasingly necessary to realize remote condition monitoring of the foundations.At present,the wind turbine foundation monitoring system is incomplete.The current monitoring research of the tower foundation is mainly of contact measurements,using acceleration sensors and static-level sensors for monitoring multiple reference points.Such monitoring methods will face some disadvantages,such as the complexity of monitoring deployment,the cost of manpower,and the load effect on the tower structure.To solve above issues,this paper aims to investigate wind turbine tower foundation variation dynamic monitoring based on machine vision.Machine vision monitoring is a kind of noncontact measurement,which helps to realize comprehensive diagnosis of early foundation uneven settlement and loose faults.The FEA model is firstly investigated as the theoretical foundation to investigate the dynamics of the tower foundation.Second,the Gaussian-based vibration detection is adopted by tracking the tower edge points.Finally,a tower structure with distributed foundation support is tested.The modal parameters obtained from the visual measurement are compared with those from the accelerometer,proving the vision method can effectively monitor the issues with tower foundation changes.

Seismic dip estimation based on the twodimensional Hilbert transform and its application in random noise attenuation

In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signal-to-noise ratio by suppressing random noise and improve the accuracy of seismic data interpretation without losing useful information. Hence, we propose a structure-oriented polynomial fitting filter. At the core of structure-oriented filtering is the characterization of the structural trend and the realization of nonstationary filtering. First, we analyze the relation of the frequency response between two-dimensional（2D） derivatives and the 2D Hilbert transform. Then, we derive the noniterative seismic local dip operator using the 2D Hilbert transform to obtain the structural trend. Second, we select polynomial fitting as the nonstationary filtering method and expand the application range of the nonstationary polynomial fitting. Finally, we apply variableamplitude polynomial fitting along the direction of the dip to improve the adaptive structureoriented filtering. Model and field seismic data show that the proposed method suppresses the seismic noise while protecting structural information.

Extraction of cable forces due to dead load in cable-stayed bridges under random vehicle loads

To extract the cable forces due to dead load in cable-stayed bridges from the monitoring data,the effects of various factors are eliminated step by step by different statistical methods.The information of cable tension sensors recorded by the health monitoring system of Nanjing No.3 Yangtze River Bridge is taken as an example. Temperature effects are eliminated by linear fitting analysis;a 5-level wavelet de-noising method is applied to eliminate the noise signal by the wavelet basis function of DB8.The rest cable force data is tested by the method of extreme-value type-Ⅲ distribution, and the fitted location parameter is selected as the cable force due to dead load.The results show that the cable force has a linear relationship with temperature. Sometimes, the temperature effect is significant.Noise effect accounts for a small percentage,and the vehicle loads effect has twice the temperature effect on the traffic volume in 2007. The calculation results of other stay cables verify the reliability and validity of the proposed method.

基于Vector Fitting的光伏并网逆变器控制器参数频域辨识方法

光伏并网逆变器通常含有内外环、锁相环等不同带宽控制环节,且控制器参数往往并不可知,即存在“灰箱”问题。为准确辨识不同带宽控制器参数,提出一种基于端口导纳特性的光伏并网逆变器控制器参数频域辨识方法。首先,建立典型控制下光伏并网逆变器交流端口的dq理论导纳模型,得到其理论导纳标准式;然后,通过扫频手段获得光伏并网逆变器交流端口的测量导纳数据,并采用Vector Fitting算法对测量的端口导纳数据进行矢量拟合,得到拟合导纳标准式;最后,运用最小二乘原理使理论导纳标准式与拟合导纳标准式对应项系数差值的平方和最小,从而辨识得到光伏并网逆变器控制器参数的估计值。参数辨识实例表明,所提方法能够同时准确辨识出不同带宽控制器参数。

一类阶为2qp^n的群的构造

利用可解群的性质,通过群的扩张理论,证明了Sylowp-子群为循环群的2qpn(q<p奇素数)阶群的构造:①2q 1(modp),若p≡1(modq),有6型;若p 1(modq),有4型.②2q≡1(modp)时,有4型.

Weight-based shape modification of NURBS curves by constrained optimization

A new method for shape modification of non-uniform rational B-splines (NURBS) curves was presented, which was based on constrained optimization by means of altering the corresponding weights of their control points. Using this method, the original NURBS curve was modified to satisfy the specified geometric constraints, including single point and multi-point constraints. With the introduction of free parameters, the shapes of modified NURBS curves could be further controlled by users without destroying geometric constraints and seem more naturally. Since explicit formulae were derived to compute new weights of the modified curve, the method was simple and easy to program. Practical examples showed that the method was applicable for computer aided design (CAD) system.

Overlapped peaks resolution for linear sweep polarography using Gaussian-like distribution

A resolution method based on Gaussian-like distribution for overlapped linear sweep polarographic peaks was proposed to simultaneously detect the polymetallic components, such as Zn（Ⅱ） and Co（Ⅱ）, coexisting in the leaching solution of zinc hydrometallurgy. A Gaussian-like distribution was constructed as the sub-model of overlapped peaks by analyzing the characteristics of linear sweep polarographic curve. Then, the abscissas of each peak and trough were pinpointed through multi-resolution wavelet decomposition, the curve and its derivative curves were fitted by using nonlinear weighted least squares （NWLS）. Finally, overlapped peaks were resolved into independent sub-peaks based on fitted reconstruction parameters. The experimental results show that the relative error of half-wave potential pinpointed by multi-resolution wavelet decomposition is less than 1% and the accuracy of Ip fitted by NWLS is higher than 96%. The proposed resolution method is effective for overlapped linear sweep polarographic peaks of Zn（Ⅱ） and Co（Ⅱ）.

Interval Q inversion based on zero-offset VSP data and applications

In order to obtain stable interval Q factor, by analyzing the spectrum of monitoring wavelet and down-going wavelet of zero-offset VSP data and referring the spectrum expression of Ricker wavelet, we propose a new expression of source wavelet spectrum. Basing on the new expression, we present improved amplitude spectral fitting and spectral ratio methods for interval Q inversion based on zero-offset VSP data, and the sequence for processing the zero-offset VSP data. Subsequently, we apply the proposed methods to real zero-offset VSP data, and carry out prestack inverse Q filtering to zero-offset VSP data and surface seismic data for amplitude compensation with the estimated Q value.

Rhizome Elongation Growth of Umbrella Bamboo(Fargesia murielae) Seedlings at Its Native Home in Central China

[Objective] The aim was to investigate the rhizome elongation growth of umbrella bamboo （Fargesia murielae） seedlings in China. [Method] The study was conducted in Liangfengya, Shennongjia National Nature Reserve. In the field investigation, six clumps of umbrella bamboo which grow independently were randomly selected and labeled. Rhizome elongation growth parameters, length and diameter of all the ages were measured. The age classes of bamboo rhizome were ascertained by age grade backtracking method. [Result] Field investigation suggested that at seedling phase, rhizome of umbrella bamboo prolonged very quickly under yearly time sequence, following an exponential curve. It indicated that although it was 15 years since the mother population died back, new generation had not been established its stable population yet. [Conclusion] Studying elongation regulation of umbrella bamboo may provide the theory understanding of life cycle of this long lived bamboo species.