A High Order Accurate Bound-Preserving Compact Finite Difference Scheme for Two-Dimensional Incompressible Flow

For solving two-dimensional incompressible flow in the vorticity form by the fourth-order compact finite difference scheme and explicit strong stability preserving temporal discretizations,we show that the simple bound-preserving limiter in Li et al.(SIAM J Numer Anal 56:3308–3345,2018)can enforce the strict bounds of the vorticity,if the velocity field satisfies a discrete divergence free constraint.For reducing oscillations,a modified TVB limiter adapted from Cockburn and Shu(SIAM J Numer Anal 31:607–627,1994)is constructed without affecting the bound-preserving property.This bound-preserving finite difference method can be used for any passive convection equation with a divergence free velocity field.

An Adaptive SVP Simplification Based on Area Difference

Sound velocity profile(SVP)data is indispensable in the multi-beam data processing.The sampling density is of great importance for SVP to represent the vertical variation of sound velocity accurately and guarantee the accuracy of sound ray tracing(SRT).However,the SVP also affects the SRT efficiency significantly,especially in deep-sea multi-beam sounding data processing.To improve SRT efficiency and ensure SRT accuracy,an adaptive SVP simplification method based on area difference is proposed in this article.Firstly,the relationship between the area difference of the raw SVP and the simplified one and SRT bias is studied,and the relationship model of them is built.Then,by considering the constraint of SRT accuracy,the SVP simplification method and the simplifying SVP procedure SVP are given.Finally,a deep water experiment is conducted to verify the proposed method.Compared to the existing method,the proposed method improves the robustness,feasibility of SVP simplification as well as the accuracy and efficiency of SRT.

A Problem of Testing Homogeneity Against Order Constraints on Risk Differences

Consider I pairs of independent binomial variates x0i and x1i with corresponding parameters P0i and p1i and sample sizes n0i and n1i for i=1, …,I. Let △i = P1i-P0i be the difference of the two binomial parameters, where △i’s are to be of interest and P0i’s are nuisance parameters. The null hypothesis of homogeneity on the risk difference can be written as

A continuous time delay-difference type model(CTDDM) applied to stock assessment of the southern Atlantic albacore Thunnus alalunga

A continuous time delay-difference model(CTDDM) has been established that considers continuous time delays of biological processes.The southern Atlantic albacore(Thunnus alalunga) stock is the one of the commercially important tuna population in the marine world.The age structured production model(ASPM) and the surplus production model(SPM) have already been used to assess the albacore stock.However,the ASPM requires detailed biological information and the SPM lacks the biological realism.In this study,we focus on applying a CTDDM to the southern Atlantic albacore(T.alalunga) species,which provides an alternative method to assess this fishery.It is the first time that CTDDM has been provided for assessing the Atlantic albacore(T.alalunga) fishery.CTDDM obtained the 80%confidence interval of MSY(maximum sustainable yield) of(21 510 t,23 118 t).The catch in 2011(24 100 t) is higher than the MSY values and the relative fishing mortality ratio(F_(2011)/F_(MSY)) is higher than 1.0.The results of CTDDM were analyzed to verify the proposed methodology and provide reference information for the sustainable management of the southern Atlantic albacore stock.The CTDDM treats the recruitment,the growth,and the mortality rates as all varying continuously over time and fills gaps between ASPM and SPM in this stock assessment.

Constructal design of a rectangular porous fin considering minimization of maximum temperature difference and pumping power consumption

A heat dissipation model of a rectangular porous fin is established based on constructal theory. First, the constructal design of rectangular porous fin is conducted by selecting a complex function minimization, which composed of linear weighting sum of maximum temperature difference and pumping power consumption, as optimization objective. Effects of gap height, air inlet velocity, total porous fin volume and porosity on the optimal constructs are investigated, respectively. The findings show that the complex function can attain its double minimum at a value of 0.802 when the fin length and number are optimized, and the corresponding optimal fin length and number are 8.01 mm and 10, respectively. In comparison to original design, the complex function and maximum temperature difference after twice optimization are decreased by 19.80% and 66.31%, respectively.Second, the comprehensive performance of porous fin is improved by simultaneously optimizing the fin length and number. The artificial neural network is applied to predict the fin performances, which is used to conduct multi-objective optimization based on NSGA-II algorithm. Optimal structure of porous fin for multiple requirements is gained by LINMAP and TOPSIS decisionmaking strategies. The findings in this study can serve as theoretical guides for fin thermal designs of electronic devices.

Diagnostics in generalized nonlinear models based on maximum L_q-likelihood estimation

In order to detect whether the data conforms to the given model, it is necessary to diagnose the data in the statistical way. The diagnostic problem in generalized nonlinear models based on the maximum Lq-likelihood estimation is considered. Three diagnostic statistics are used to detect whether the outliers exist in the data set. Simulation results show that when the sample size is small, the values of diagnostic statistics based on the maximum Lq-likelihood estimation are greater than the values based on the maximum likelihood estimation. As the sample size increases, the difference between the values of the diagnostic statistics based on two estimation methods diminishes gradually. It means that the outliers can be distinguished easier through the maximum Lq-likelihood method than those through the maximum likelihood estimation method.

Maximum modulus principle estimates for one dimensional fractional diffusion equation

We present scheme I for solving one-dimensional fractional diffusion equation with variable coefficients based on the maximum modulus principle and two Grunwald approxima- tions. Scheme II is obtained by using classic Crank-Nicolson approximations in order to improve the time convergence. Schemes are proved to be unconditionally stable and second-order accuracy in spatial grid size for the problem with order of fractional derivative belonging to [（√17- 1）/2, 2] using the maximum modulus principle. A numerical example is given to confirm the theoretical analysis result.

High-order maximum-principle-preserving and positivity-preserving weighted compact nonlinear schemes for hyperbolic conservation laws

In this paper,the maximum-principle-preserving(MPP)and positivitypreserving(PP)flux limiting technique will be generalized to a class of high-order weighted compact nonlinear schemes(WCNSs)for scalar conservation laws and the compressible Euler systems in both one and two dimensions.The main idea of the present method is to rewrite the scheme in a conservative form,and then define the local limiting parameters via case-by-case discussion.Smooth test problems are presented to demonstrate that the proposed MPP/PP WCNSs incorporating a third-order Runge-Kutta method can attain the desired order of accuracy.Other test problems with strong shocks and high pressure and density ratios are also conducted to testify the performance of the schemes.

Comparison between methods for predicting maximum solid solubility of transition metals in solvent metal

It is important to know the maximum solid solubility( C max ) of various transition metals in a metal when one designs multi component alloys. There have been several semi empirical approaches to qualitatively predict the C max , such as Darken Gurry(D G) theorem, Miedema Chelikowsky(M C) theorem, electron concentration rule and the bond parameter rule. However, they are not particularly valid for the prediction of C max . It was developed on the basis of energetics of alloys as a new method to predict C max of different transition metals in metal Ti, which can be described as a semi empirical equation using the atomic parameters, i e, electronegativity difference, atomic diameter and electron concentration. It shows that the present method can be used to explain and deduce D G theorem, M C theorem and electron concentration rule.

Rules for maximum solid solubility of transition metals in Ti,Zr and Hf solvents

Based on the principle of energy change of alloy formation, the rules for the maximum solid solubility ( C max ) of various transition metals in the metals Ti, Zr and Hf were studied. It is deduced that the C max of transition metals in the metals Ti, Zr and Hf can be described as a semi empirical equation using three atomic parameters, i.e., electronegativity difference, atomic diameter and electron concentration. From the equation analysis by using experimental data, it shows that atomic size parameter and electronegativity difference are the main factors that affect the C max of the transition metals in the metals Ti, Zr and Hf while electron concentration parameter has the smallest effect on C max .

基于领域自适应的变工况轴承故障诊断

针对轴承故障诊断中存在训练样本和测试样本分布不同及各类故障数据不平衡导致故障识别率低的问题,设计了一种基于改进残差网络(ResNet)的领域自适应故障诊断方法。在诊断网络第1层使用多维度卷积结构进行特征提取,得到不同维度的故障特征信息;在领域自适应层采用局部最大平均差异(LMMD)对齐源域和目标域的分布,获取更多细粒度信息;使用类平衡损失函数(CBLoss)解决不平衡数据的训练问题,以Adam优化网络实现故障诊断。实验结果表明,所提方法可在故障样本类别不平衡下有较高的诊断结果。在2个轴承数据集和采集的风力发电机数据上进行实验验证,结果表明,所提方法具有一定的优越性,在数据样本不平衡情况下,诊断性能优于深度神经网络和领域自适应网络等深度迁移学习方法,可作为一种有效的跨工况故障分析方法。

基于高分一号遥感影像的水体提取方法对比分析与改进

以高分一号遥感影像为数据源,以安徽省黄山市屯溪流域内的东方红水库为研究对象,采用单波段阈值法、两波段差值法、波段比值法、归一化差分水体指数(NDWI)法、归一化差分植被指数(NDVI)法共5种水陆像元度量方法,分别应用平均值法和最大类间方差迭代法两种阈值选取方法对东方红水库进行水体提取,探索最大类间方差迭代法在水体提取变量上的改进效果,在此基础上提出了一种改进的最大类间方差联合水体提取法,并对比了改进前后的水体提取效果。结果表明:改进后的水体提取方法可以很好地降低影像提取中产生的噪点,提高水体提取的精度,提取成果的平均相对误差为4.69%,决定系数为0.8579,相比于改进前平均相对误差降低了0.68%,决定系数提高了0.0539。

磁悬浮轨道梁均匀温度及温差分量极值研究

与一般公铁桥梁不同,磁悬浮轨道梁的温度场会受到周围磁场与功能件升温的影响。由于我国规范暂未对磁浮轨道梁均匀温度和温差分量的极值作出明确规定,研究具有概率保证的温度分量代表值具有重要意义。根据长沙磁浮运营线某混凝土箱梁1年多的现场温度监测数据,分析梁体均匀温度与竖向等效线性温差的时变特征。研究分别采用单变量线性回归法(ULR法)和梯度提升回归树法(GBRT法)建立基于气象因素的结构温度分量预测模型,对比发现GBRT法不仅能提高均匀温度的预测精度,还能克服ULR法无法预测竖向等效线性温差的局限性。而后将1960—2019年的长期气象数据输入到建立好的GBRT预测模型中,得到磁浮箱梁各温度分量60年的长期预测值,经整理后得到均匀温度和竖向等效线性温差的日极值、年极值样本。结合最大熵极值模型和Fourier函数得到各温度分量的日极值时变曲线,对年极值样本建立最大熵模型并确定百年重现期下的温度分量代表值。研究结果表明:磁浮箱梁均匀温度呈现以年为周期的季节性变化,竖向等效线性温差受太阳辐射影响,呈夏季高、冬季低的特点;百年重现期下磁浮箱梁均匀温度和竖向等效线性温差的代表值分别为44.4℃、8.6℃。该方法结合GBRT算法和最大熵极值模型,解决了极值分析中年极值样本不足的问题,结果可为磁浮轨道梁的温度变形设计提供参考。

基于相变材料的混凝土吊罐温控数值模拟研究

为保证混凝土吊罐在垂直运输时其内部混凝土的温度,采用相变石蜡作为吊罐温控措施,通过Fluent软件探究了不同季节和不同相变石蜡厚度下混凝土温度变化情况。结果表明:在不同季节,采用相变石蜡作为吊罐温控措施,可有效控制其内部混凝土温度的波动;在冬季环境中,当相变石蜡厚度小于40 mm时,混凝土内外温度差减小有限,消峰填谷效果不理想;在夏季环境中,随着相变石蜡厚度的增加,混凝土表面最大温度的降低程度呈现先增大后减小的趋势,当相变石蜡厚度为20 mm时,混凝土表面温度达到最低。

基于LPNN的无源ML-TDOA估计

针对无源时差定位(TDOA)领域的非线性方程求解问题,提出了一种基于最大似然估计的改进型拉格朗日规划神经网络迭代求解算法。该算法利用最大似然估计构建代价函数,结合时空约束条件,建立TDOA方程的一般约束优化问题,并通过迭代求解算法对网络的收敛性和渐近稳定性进行了证明。针对两种常见的阵列排布方式进行了仿真验证与性能分析。仿真实验结果表明,该算法能够提供精确的坐标估计,误差小于1.414×10^(-3)。与传统算法相比,该方法在各类噪声环境下表现出更优的性能,尤其在0 dB噪声环境下,其均方误差为0.7866。

基于多源域自适应残差网络的滚动轴承故障诊断

针对传统无监督领域自适应方法扩展到多工况滚动轴承故障诊断场景适用性较弱的问题,提出了一种多源域自适应残差网络(multi-source domain adaptive residual network,MDARN),通过对齐来自多个源域的相关子域,从而提高模型在多工况下的故障诊断性能。首先,利用ResNeXt残差网络从源域和目标域充分提取可迁移特征;然后,引入局部最大平均差异(local maximum mean difference,LMMD)准则,以两个源域的子域为基础对齐目标域中相关子域,减少相关子域间和全局域间的分布差异;最后,利用美国凯斯西储大学轴承数据集和MFS机械综合故障试验台产生的真实的轴承振动数据集,对所提方法进行了试验验证。结果表明,该方法在多工况下的平均故障诊断精度高达99.76%。与现有代表性方法相比,所提方法具有更好的故障诊断效果。

机械冲击下坐姿人体舒适性主客观评价

为减小主观随意性带来的偏差,引入最大化差异度量(MaxDiff)方法展开机械冲击下坐姿人体不适的主观评价试验,并结合加速度和惯性力客观指标对舒适性进行评价。构造了16个具有不同标称频率或位移幅值的冲击信号,基于MaxDiff方法得到12名受试者的主观评分。利用加速度传感器和测力板获取受试者的客观数据,提取其峰值、峰峰值、振动剂量值、最大瞬态振动值等客观评价指标,并采用相关性分析方法以及线性回归拟合进行主客观关联性分析。主观评价结果表明,随着机械冲击信号标称频率和位移幅值的增大,人体舒适性均变差。标称频率主客观数据之间具有较大相关性,客观指标(除振动剂量值外)的相关系数均在0.9左右。线性拟合回归结果表明,加速度和惯性力的峰值、峰峰值、最大瞬态振动值可作为表征冲击工况下坐姿人体舒适性的客观指标,而加速度比惯性力更适合用于表征舒适性。

未知信号传播速度的TDOA定位方法研究

研究了未知信号传播速度时的到达时间差(Time-Difference-Of-Arrival,TDOA)定位问题,提出两种联合估计信号传播速度和目标位置的定位方法。第一种方法为两步加权最小二乘方法。在该方法中,首先不考虑变量之间关系,得到一个关于未知变量的初始加权最小二乘估计。为改进第一步估计的性能,第二步考虑第一步估计中变量之间的关系,将其转换为一个标准的广义信赖域子问题,最终获得更高精度的估计性能。第二种方法为半正定松弛方法,通过构建非线性非凸加权最小二乘问题,然后利用半正定松弛技术将其松弛为凸的半正定规划问题,容易求解。仿真结果表明,所提两种方法均能够在高斯噪声下,且噪声不太大时达到克拉美-罗界。

农药最大残留限量标准差异对我国茶叶出口RCEP成员国的贸易效率影响研究——基于随机前沿引力模型

目前,茶叶外贸面临着来自技术性贸易壁垒的挑战,以农药最大残留限量(MRLs)标准差异为切入点,构建异质性贸易指数(HIT)量化各国农药MRLs的具体差异,利用随机前沿引力模型研究农药MRLs标准差异对我国茶叶出口区域全面经济伙伴关系协定(RCEP)国家的贸易效率的影响。结果表明,中国与RCEP成员国的农药MRLs标准存在差异,但总体呈缩小的趋势。中国与RCEP成员国的农药MRLs标准的负面差异会导致中国出口茶叶的贸易效率降低;抑制作用路径表现为显著降低了茶叶出口额和出口单价。我国应进一步完善农药MRLs标准体系,使之与国际标准接轨,推动RCEP区域内国家间的标准互认,减小贸易壁垒的不利影响。

基于图谱功率谱熵和最大均值差异的GIS机械状态辨识方法

针对常规方法对于气体绝缘金属封闭开关设备(Gas Insulated Switchgear,GIS)机械缺陷的特征识别稳定性差、识别率低的问题,在图谱理论的基础上,提出一种基于图谱功率谱熵和最大均值差异(Maximum Mean Discrepancy,MMD)的GIS机械状态辨识方法。首先将采集得到的GIS振动信号转化为图信号,并利用图傅里叶变换技术变换至图谱域进行分析处理;然后提取图谱功率谱熵作为表征GIS不同状态的特征参数;最后利用MMD距离判别函数实现GIS不同工况下的状态辨识。实验结果表明:在噪声干扰的情况下,所提方法能够有效提取GIS不同状态下的特征参数,并成功区分出屏蔽罩松动及内部异物缺陷,状态辨识精度高达93.89%,较常规方法有明显提高。