Effects of the Reynolds number on the mean skin friction decomposition in turbulent channel flows

As the Reynolds number increases, the skin friction has been identified as the dominant drag in many practical applications. In the present paper, the effects of the Reynolds number on the mean skin friction decomposition in turbulent channel flows up to Reτ= 5 200 are investigated based on two different methods, i.e., the FukagataIwamoto-Kasagi(FIK) identity(FUKAGATA, K., IWAMOTO, K., and KASAGI, N.Contribution of Reynolds stress distribution to the skin friction in wall-bounded flows.Physics of Fluids, 14(11), L73–L76(2002)) and the Renard-Deck(RD) identity(DECK,S., RENARD, N., LARAUFIE, R., and WEISS, P.′E. Large-scale contribution to mean wall shear stress in high-Reynolds-number flat-plate boundary layers up to Reθ= 13 650.Journal of Fluid Mechanics, 743, 202–248(2014)). The direct numerical simulation(DNS) data provided by Lee and Moser(LEE, M. and MOSER, R. D. Direct numerical simulation of turbulent channel flow up to Reτ≈ 5 200. Journal of Fluid Mechanics,774, 395–415(2015)) are used. For these two skin friction decomposition methods, their decomposed constituents are discussed and compared for different Reynolds numbers.The integrands of the decomposed constituents are locally analyzed across the boundary layer to assess the actions associated with the inhomogeneity and multi-scale nature of turbulent motion. The scaling of the decomposed constituents and their integrands are presented. In addition, the boundary layer is divided into three sub-regions to evaluate the contributive proportion of each sub-region with an increase in the Reynolds number.

Variational Mode Decomposition for Rotating Machinery Condition Monitoring Using Vibration Signals

The failure of rotating machinery applications has major time and cost effects on the industry.Condition monitoring helps to ensure safe operation and also avoids losses.The signal processing method is essential for ensuring both the efficiency and accuracy of the monitoring process.Variational mode decomposition(VMD)is a signal processing method which decomposes a non-stationary signal into sets of variational mode functions(VMFs)adaptively and non-recursively.The VMD method offers improved performance for the condition monitoring of rotating machinery applications.However,determining an accurate number of modes for the VMD method is still considered an open research problem.Therefore,a selection method for determining the number of modes for VMD is proposed by taking advantage of the similarities in concept between the original signal and VMF.Simulated signal and online gearbox vibration signals have been used to validate the performance of the proposed method.The statistical parameters of the signals are extracted from the original signals,VMFs and intrinsic mode functions(IMFs)and have been fed into machine learning algorithms to validate the performance of the VMD method.The results show that the features extracted from VMD are both superior and accurate for the monitoring of rotating machinery.Hence the proposed method offers a new approach for the condition monitoring of rotating machinery applications.

Domain Decomposition for Wavelet Single Layer on Geometries with Patches

We focus on the single layer formulation which provides an integral equation of the first kind that is very badly conditioned. The condition number of the unpreconditioned system increases exponentially with the multiscale levels. A remedy utilizing overlapping domain decompositions applied to the Boundary Element Method by means of wavelets is examined. The width of the overlapping of the subdomains plays an important role in the estimation of the eigenvalues as well as the condition number of the additive domain decomposition operator. We examine the convergence analysis of the domain decomposition method which depends on the wavelet levels and on the size of the subdomain overlaps. Our theoretical results related to the additive Schwarz method are corroborated by numerical outputs.

Riesz Decomposition Theorems for Continuous-time Fuzzy Supermartingales

Compared with discrete- time fuzzy supermartingales, the structure and the properties of trajectories for continuous-time fuzzy supermartingales are more complex. This paper focuses on Riesz decomposition for continuous-time fuzzy supermartingales. The concepts of two types of Riesz decomposition (Riesz decomposition and level Riesz decomposition) are given and some necessary and sttfficient conditions of that a continuous time fuzzy supermartingale has Riesz decomposition are discussed in detail.

DOMAIN DECOMPOSITION PRECONDITIONERS FOR SECOND-ORDER HYPERBOLIC EQUATIONS ON L-SHAPED REGIONS

Linear systems arising from implicit time discretizations and finite difference space discretizations of second-order hyperbolic equations on L-shaped region are considered. We analyse the use of domain deocmposilion preconditioner.s for the solution of linear systems via the preconditioned conjugate gradient method. For the constant-coefficient second-order hyperbolic equaions with initial and Dirichlet boundary conditions,we prove that the conditionnumber of the preconditioned interface system is bounded by 2+x2 2+0.46x2 where x is the quo-tient between the lime and space steps. Such condition number produces a convergence rale that is independent of gridsize and aspect ratios. The results could be extended to parabolic equations.

Re ned rigorous perturbation bounds for the SR decomposition

In this article,some new rigorous perturbation bounds for the SR decomposition un-der normwise or componentwise perturbations for a given matrix are derived.Also,the explicit expressions for the mixed and componentwise condition numbers are presented by utilizing the block matrix-vector equation approach.Hypothetical and trial results demonstrate that these new bounds are constantly more tightly than the comparing ones in the literature.

Application of signal sparse decomposition in dynamic test

In dynamic test,sampling rate is high and noise is strong,so a signal sparse decomposition method based on Gabor dictionary is put forward.This method iteratively decomposes the signal with the matching pursuit(MP)algorithm and takes the coherence ratio of the threshold as a condition of iteration termination.Standard MP algorithm is time-consuming,thus an adaptive genetic algorithm is introduced to MP method,which makes computation speed accelerate effectively.Experimental results indicate that this method not only can effectively remove high-frequency noise but also can compress the signal greatly.

The <i>H</i>-Decomposition Problem for Graphs

The concept of H-decompositions of graphs was first introduced by Erd?s, Goodman and Pósa in 1966, who were motivated by the problem of representing graphs by set intersections. Given graphs G and H, an H-decomposition of G is a partition of the edge set of G such that each part is either a single edge or forms a graph isomorphic to H. Let Ф(n,H) be the smallest number Ф, such that, any graph of order n admits an H-decomposition with at most Ф parts. The exact computation of Ф(n,H) for an arbitrary H is still an open problem. Recently, a few papers have been published about this problem. In this survey we will bring together all the results about H-decompositions. We will also introduce two new related problems, namely Weighted H-Decompositions of graphs and Monochromatic H-Decom- positions of graphs.

Flow and sound fields of scaled high-speed trains with different coach numbers running in long tunnel

Segregated incompressible large eddy simulation and acoustic perturbation equations were used to obtain the flow field and sound field of 1:25 scale trains with three,six and eight coaches in a long tunnel,and the aerodynamic results were verified by wind tunnel test with the same scale two-coach train model.Time-averaged drag coefficients of the head coach of three trains are similar,but at the tail coach of the multi-group trains it is much larger than that of the three-coach train.The eight-coach train presents the largest increment from the head coach to the tail coach in the standard deviation(STD)of aerodynamic force coefficients:0.0110 for drag coefficient(Cd),0.0198 for lift coefficient(Cl)and 0.0371 for side coef-ficient(Cs).Total sound pressure level at the bottom of multi-group trains presents a significant streamwise increase,which is different from the three-coach train.Tunnel walls affect the acoustic distribution at the bottom,only after the coach number reaches a certain value,and the streamwise increase in the sound pressure fluctuation of multi-group trains is strengthened by coach number.Fourier transform of the turbulent and sound pressures presents that coach number has little influence on the peak frequencies,but increases the sound pressure level values at the tail bogie cavities.Furthermore,different from the turbulent pressure,the first two sound pressure proper orthogonal decomposition(POD)modes in the bogie cavities contain 90%of the total energy,and the spatial distributions indicate that the acoustic distributions in the head and tail bogies are not related to coach number.

Rice condition numbers of QR and Cholesky factorizations

A condition number is an amplification coefficient due to errors in computing. Thus the theory of condition numbers plays an important role in error analysis. In this paper, following the approach of Rice, condition numbers are defined for factors of some matrix factorizations such as the Cholesky factorization of a symmetric positive definite matrix and QR factorization of a general matrix. The condition numbers are derived by a technique of analytic expansion of the factor dependent on one parameter and matrix-vector equation. Condition numbers of the Cholesky and QR factors are different from the ones previously introduced by other authors, but similar to Chang's results. In Cholesky factorization, corresponding with the condition number of the factor matrix L , K _L is a low bound of Stewart's condition number K .

GPR信号去噪的变分模态分解

为了进一步提高探地雷达(ground penetrating radar,GPR)数据的信噪比,压制由随机扰动引起的随机绕射能量,将二维变分模态分解(two-dimensional variational mode decomposition,2D-VMD)引入二维GPR数据的噪声压制处理中。首先,对GPR数据进行2D-VMD处理,并分析各阶本征模态函数(intrinsic mode function,IMF)分量及其对应的频率-波数域谱来确定雷达剖面中的各回波类型。然后,计算IMF分量与原始数据的互相关系数来确定信号模态和噪声模态,并对信号模态进行重构得到降噪后的数据。理论数据和实测数据测试表明,相比于传统的1D-VMD法,2D-VMD滤波后的含噪正演记录峰值信噪比由6.44 dB增加到7.72 dB;经2D-VMD降噪处理后的雷达剖面在保留有效信号的基础上,可以有效压制随机扰动带来的噪声,并且得到的雷达剖面同相轴连续性更好。

一种基于三角数分解的可配置2-D卷积器优化方法

多尺寸2-D卷积通过特征提取在检测、分类等计算机视觉任务中发挥着重要作用。然而,目前缺少一种高效的可配置2-D卷积器设计方法,这限制了卷积神经网络(CNN)模型在边缘端的部署和应用。该文基于乘法管理以及奇平方数的三角数分解方法,提出一种高性能、高适应性的卷积核尺寸可配置的2-D卷积器。所提2-D卷积器包含一定数量的处理单元(PE)以及相应的控制单元,前者负责运算任务,后者负责管理乘法运算的组合,二者结合以实现不同尺寸的卷积。具体地,首先根据应用场景确定一个奇数列表,列表中为2-D卷积器所支持的尺寸,并利用三角数分解得到对应的三角数列表;其次,根据三角数列表和计算需求,确定PE的总数量;最后,基于以小凑大的方法,确定PE的互连方式,完成电路设计。该可配置2-D卷积器通过Verilog硬件描述语言(HDL)设计实现,由Vivado 2 022.2在XCZU7EG板卡上进行仿真和分析。实验结果表明,相比同类方法,该文所提可配置2-D卷积器,乘法资源利用率得到显著提升,由20%~50%提升至89%,并以514个逻辑单元实现1 500 MB/s的吞吐率,具有广泛的适用性。

基于模态分解的轴向通流共转腔流场特性分析

为了深入理解高压压气机旋转盘腔内的流场特性,基于雷诺平均N-S方程对轴向通流共转盘腔进行非定常数值模拟。采用本征正交分解方法识别了流场的相干结构,并对比分析了不同浮升力参数、罗斯比数以及盘轴旋转比下模态空间结构和平均流场的变化规律。结果表明,盘腔高半径处观察到一对非定常大尺度气旋/反转环流,借助本征正交分解方法能够有效提取其运动状态。低阶的旋进驱动模态主要反映了大尺度流动结构的旋进状态,对应盘腔内流场在整个径向范围的主频成分;高阶的谐振诱导模态则主要反映了腔内相干结构诱导的复杂涡系,对应主频的高阶倍频成分。气旋/反转环流结构的相干性随浮升力参数增加而增强(旋进驱动模态能量占比提高23.2%),随罗斯比数增加而减弱(相应能量占比降低12.3%)。盘轴反转会削弱低半径区域的环形涡,而对高半径区域流场影响较小。

一种自适应选取参数的改进变分模态分解方法

针对传统的变分模态分解(VMD)方法中模态数和惩罚参数难以确定的问题,提出了一种自适应选取参数的改进变分模态分解方法。首先,综合考虑了故障的冲击性和周期性特点,以Gini指数和谱峰比指标为基础构建了加权谱峰比(WSPR)指标;然后,采用非洲秃鹫优化算法(AVOA)进行了寻优,得到了最佳的模态数和惩罚参数组合,克服了人为主观选择参数的弊端;最后,在VMD分解信号后,利用加权谱峰比最大原则自适应选取了敏感内涵模态分量,对最佳IMF进行了包络解调分析,提取了滚动轴承早期故障特征,利用仿真信号、单一故障滚动轴承试验信号及复合故障滚动轴承试验信号对所述方法进行了验证。实验结果表明:该方法可以准确地提取出仿真信号的故障频率(100 Hz)、单一故障信号的故障频率(236.4 Hz)和复合故障信号的故障频率(内圈故障频率149.14 Hz、外圈故障频率86.39 Hz),并且在与其他方法和指标的对比中,其最佳IMF的包络谱图中故障特征频率及其倍数频的谱峰更加明显,准确率更高且鲁棒性更强。研究结果表明:该方法能够有效提取轴承早期故障信号的微弱特征,实现故障类型准确识别的目的。

基于小波包的电缆混合线路接地故障诊断方法研究

发生接地故障时负载电压数值会出现明显增大的情况,根据负载电压数值变化行为,提出基于小波包的电缆混合线路接地故障诊断方法。根据小波包分解与重构原则,对故障数据实施预处理,通过求解功率预测指标的方式,完成对电缆混合线路的短期故障功率预测。在故障属性集合中,判定故障行为表现特征,联合三角模糊数的计算结果,完成基于小波包的电缆混合线路接地故障诊断。对比实验结果表明,在小波包理论作用下,发生接地故障时负载电压数值达到了485 V,与非故障电压之间的差值超过100 V,电缆主机可以根据负载电压变化行为实现对混合线路接地故障行为的准确诊断。

外加电流和磁流下前包钦格复合体神经元中混合簇放电的动力学分析

新生哺乳动物呼吸节律的产生与pre-Botzinger复合体中神经元的节律性放电密切相关.放电行为是神经系统中一种复杂的非线性现象,表现为多种模式.混合簇放电是实验观察到的一类放电模式,其产生涉及复杂的动力学机制.磁流和电流的引入对神经元的放电模式具有重要的调节作用.我们分别探索了磁流和电流对单个pre-Botzinger复合体神经元内混合簇放电模式的影响.通过快慢分解和双参数分岔分析,研究了磁流和电流对混合簇放电的产生及转迁的动力学机制.结果表明,磁流和刺激电流都能引起混合簇个数的增减性的多次变化,不同于其它簇放电在磁流和刺激电流的作用下引起混合簇个数的单调增加或减少的现象,该结果显示了节律变化现象的多样性.本研究结果有助于揭示和解释呼吸节律中复杂节律模式的动力学机制.

高层结构-混联Ⅱ型惯容阻尼耗能体系减震性分析

针对高层结构中设置混联Ⅱ型惯容阻尼器组成耗能体系的随机响应分析复杂的问题,提出了结构位移及阻尼器阻尼力响应的封闭解,并基于所获得的封闭解探究了实模态振型数对分析精度的影响和在原结构层间位移超限楼层设置阻尼器能有效减震的布置策略。首先,根据混联Ⅱ型惯容阻尼器力学构造图及设置方式,建立阻尼器阻尼力与结构节点水平位移的微分型本构关系进而重构耗能体系的地震动方程。其次,利用实模态解耦法获得高层结构简明等效的动力学参数,运用功率谱二次式分解法推导出结构节点相对于地面的绝对位移、竖向构件层间位移及阻尼器阻尼力等响应的功率谱精确二次式解进而推导出耗能体系基于双过滤白噪声激励下系列响应的0~2阶谱矩简明封闭解。最后,通过算例,验证了所提封闭解的正确性;研究了实模态振型数对系列响应谱矩分析精度的影响和阻尼器设置位置对结构减震效果的影响。研究表明:对于多自由度结构响应分析时,建议采用原结构自由振动分析时质量参与系数累计达100%时所对应的振型数,可获得稳定的精度和提高大型复杂结构设置混联Ⅱ型惯容阻尼器的响应的分析效率;通过在原结构层间位移超限楼层或连续多层层间位移超限的楼层中间隔一层设置参数合适的混联Ⅱ型惯容阻尼器可有效降低结构的地震动响应,所提惯容阻尼器设置策略具有较好的经济性。所提解析解和惯容系统在高层结构的设置策略可为混联Ⅱ型惯容阻尼器在实际工程应用中提供有益的参考价值。

一种基于经验模态分解和局部极大值点数的配电网高阻接地故障检测方法

配电网高阻接地故障(HIF)因故障特征微弱而难以被常规装置检测到,容易引发过电压、火灾和人身触电等安全问题。本文提出一种将时频分解和阈值判断结合的HIF识别方法。首先,利用经验模态分解(EMD)对零序电流进行处理;然后,选取第二个固有模态分量(IMF)作为特征分量并进行高斯滤波;最后,统计特征分量的局部极大值点的个数来判断是否发生HIF。利用PSCAD/EMTDC软件搭建10kV配电网模型进行算法验证。仿真结果表明,所提方法能够以较高的准确率将HIF和一些常见的干扰事件区分开,并且在发生噪声干扰、采样率变化、系统中性点接地方式改变及系统网络结构改变的情况下,均表现出较好的适应性。

基于标度律的壁湍流运动分解与雷诺数效应

壁湍流广泛存在于自然界和工程中,对其深入研究和理解有助于发展新的计算模型和调控手段。湍流具有多尺度性,壁面带来的各向异性使得壁湍流多尺度运动更为复杂。本文探讨和总结了基于标度律的壁湍流运动分解方法:内–外分解方法和外区分解方法,其中内–外分解方法基于内区湍流运动的雷诺数无关性,而外区分解方法基于Townsend的附着涡标度律;讨论了分解后壁湍流运动统计特性的雷诺数效应,给出了内区湍流运动达到雷诺数无关和出现外区湍流运动的2个临界雷诺数。

Declining number of births in China: a decomposition analysis

Recent drastic changes in marriage and fertility behaviour have a considerable impact on China’s annual number of births.Population momentum and changing fertility policy largely determine the changing number of births in China over the past two decades.While the annual number of births have been steadily fluctuat-ing around 16-18 million,contrary trends in the number of the first births and the second births have been observed.The two-child policy produced marked effects on the rising number of the second births,which is however to a large extent offset by the declining number of the first births resulting from rapidly postponing age at first marriage.A decomposition analysis demonstrates that all demographic factors are depressing birth numbers,including the size of reproductive-age women and its age structure,proportion married and marital fertility in the very recent years.China’s seventh population census conducted in 2020 suggests a more rapid decline in birth numbers,marking the start of a lowest-low fertility in Chinese history.