Vibration and acoustic radiation of bogie area under random excitation in high-speed trains

Based on the experiments on a platform with real vehicle structure and finite element simulation, the vibration and interior acoustic radiation under random excitations of high-speed trains’ bogie area were studied. Firstly, combined with line tests, a vehicle body with a length of 7 m was used as the research object. By comparing the results of experiment and simulation, the accuracy of the finite element model was verified. Secondly, the power spectral density curves at typical measuring points in bogie area were obtained by processing and calculating the line test data, which was measured when the vehicle ran at high speeds, and the standard vibration spectrum of the bogie area was obtained by the extreme envelope method. Furthermore, the random vibration test and simulation prediction analysis of the real vehicle structure were carried out to further verify the accuracy of the noise and vibration prediction model. Finally, according to the vibration and acoustic radiation theory, the indirect boundary element method was adopted to predict the acoustic response of the real vehicle. The analysis shows that the simulated power spectral density curves of acceleration and sound pressure level are highly consistent with the experimental ones, and the error between the simulated prediction and the experimental result is within the allowable range of 3 dB.

Random Subspace Learning Approach to High-Dimensional Outliers Detection

We introduce and develop a novel approach to outlier detection based on adaptation of random subspace learning. Our proposed method handles both high-dimension low-sample size and traditional low-dimensional high-sample size datasets. Essentially, we avoid the computational bottleneck of techniques like Minimum Covariance Determinant (MCD) by computing the needed determinants and associated measures in much lower dimensional subspaces. Both theoretical and computational development of our approach reveal that it is computationally more efficient than the regularized methods in high-dimensional low-sample size, and often competes favorably with existing methods as far as the percentage of correct outlier detection are concerned.

间歇与持续训练对体力活动不足成人生活质量影响的Meta分析

目的:高强度间歇训练(high-intensity interval training,HIIT)和中等强度持续训练(moderate-intensity continuous training,MICT)对临床慢性病患者生活质量均有改善作用,但其对于体力活动不足成人的应用效果与调节因素尚不明确。文章旨在探究HIIT与MICT对体力活动不足成人生活质量的应用效果与调节因素。方法:在Web of Science核心合集、Medline(EBSCO Host)、PubMed和Cochrane Library数据库中进行文献检索,检索时限为各数据库建库至2023年9月。纳入文献类型为随机对照试验,研究对象为体力活动不足成人。采用RevMan 5.4软件和GRADE证据评价框架对纳入文献进行质量评价。使用R Studio(版本4.2.0)进行随机效应模型的主效应合并。亚组分析、回归分析和敏感性分析用于探讨研究异质性来源和调节因素。结果:①纳入32项中等至高质量的随机对照试验,共2083名体力活动不足成人对象(HIIT组474例;MICT组708例;对照组901例)。②相比于无训练对照组,HIIT(Hedges’g=0.61;95%CI:0.40-0.83;I2=45%)与MICT(Hedges’g=0.66;95%CI:0.25-1.08;I2=89%)均能显著提升生活质量。当直接比较HIIT与MICT时,二者之间的影响未观察到显著差异(Hedges’g=-0.01;95%CI:-0.23-0.21;I2=0%)。③亚组分析结果显示,HIIT和MICT在提高身体层面的生活质量更为有效(HIIT:Hedges’g=0.82 vs.0.75;MICT:Hedges’g=0.74 vs.0.55),而骑行在提高整体生活质量方面有更好的趋势(HIIT:Hedges’g=0.74 vs.0.36;MICT:Hedges’g=1.08 vs.0.52)。④回归分析未识别出任何显著的调节因素(所有因素P>0.05)。⑤上述Meta分析均未发现发表偏倚(Egger检验P>0.05)。结论:①中高级别的证据表明,HIIT与MICT均能改善体力活动不足成人的生活质量,且二者之间的干预效果类似。因此,在选择这两种方案时,需综合考虑安排灵活性、时间经济性以及应用可行性等因素制订个性化运动方案。②文章推荐在应用HIIT时,3次/周,使用低量方案(例如,每次5组,每组1 min),以80%-95%最大心率进行骑行可达理论最佳改善效果。③尽管MICT可提高生活质量,但尚无充分证据显示增加运动时长会带来额外益处。因此,建议在实施MICT时,每周进行3次以上,每次训练时长控制在25-60 min,并以50%-75%最大心率进行骑行,以达到理论上预期的最佳改善效果。

低容量高强度间歇训练对肥胖或超重人群心血管疾病风险因子影响的Meta分析

目的:通过Meta分析综合定量评价低容量高强度间歇训练对预防肥胖或超重人群心血管疾病的效果,进一步验证低容量高强度间歇训练在肥胖等特殊人群中应用的可行性。方法:在中国知网、PubMed、Web of Science、Cochrane Library和EBSCO-SPORTD运动科学全文数据库检索关于低容量高强度间歇训练相关研究的随机对照试验文献,检索时限为各数据库建库至2024年2月。由2名研究人员对所纳入的研究进行筛选、质量评价和数据提取,采用RevMan 5.4和Stata 17.0软件对结局指标进行Meta分析,包括合并效应量、亚组分析、Leave-One-Out敏感性分析以及发表Egger检验和绘制漏斗图。该方案已在国际系统综述前瞻性注册中心注册(CRD42024534409)。结果:①最终筛选纳入符合要求的13项随机对照试验,共包含349例受试者,纳入文献整体质量较高。②低容量高强度间歇训练干预对心肺适能(SMD=-0.65,95%CI:-0.87至-0.43,P<0.05)、收缩压(SMD=0.38,95%CI:0.11-0.65,P<0.05)、舒张压(SMD=0.42,95%CI:0.15-0.68,P<0.05)和体脂百分比(SMD=0.25,95%CI:0.02-0.49,P<0.05)4项指标具有改善效果。③低容量高强度间歇训练与中等强度持续训练相比在改善超重或肥胖人群心肺适能、收缩压、舒张压、体脂百分比、标准体质量、体质量指数、高密度脂蛋白、低密度脂蛋白和总胆固醇指标方面干预效果相似(P>0.05),但在改善三酰甘油效果方面中等强度持续训练优于低容量高强度间歇训练(SMD=-0.30,95%CI:-0.57至-0.02,P<0.05)。④亚组分析结果进一步显示,低容量高强度间歇训练和中等强度持续训练干预对各项指标的改善效果相似。结论:当前证据表明,低容量高强度间歇训练可以有效提升超重或肥胖人群的心肺适应能力以及促进减脂和血压调控,且改善效果与中等强度持续训练相似。短时间的低容量高强度间歇训练相比于长时间的中等强度持续训练更具有时间效益。建议未来通过更多研究确定适用于超重或肥胖人群最佳的低容量高强度间歇训练运动处方。

Parallel computation of seismic analysis of high arch dam

Parallel computation programs are developed for three-dimensional meso-mechanics analysis of fully-graded dam concrete and seismic response analysis of high arch dams （ADs）, based on the Parallel Finite Element Program Generator （PFEPG）. The computational algorithms of the numerical simulation of the meso-structure of concrete specimens were studied. Taking into account damage evolution, static preload, strain rate effect, and the heterogeneity of the meso-structure of dam concrete, the fracture processes of damage evolution and configuration of the cracks can be directly simulated. In the seismic response analysis of ADs, all the following factors are involved, such as the nonlinear contact due to the opening and slipping of the contraction joints, energy dispersion of the far-field foundation, dynamic interactions of the dam-foundation- reservoir system, and the combining effects of seismic action with all static loads. The correctness, reliability and efficiency of the two parallel computational programs are verified with practical illustrations.

Low sidelobe robust imaging in random frequency-hopping wideband radar based on compressed sensing

High resolution range imaging with correlation processing suffers from high sidelobe pedestal in random frequency-hopping wideband radar. After the factors which affect the sidelobe pedestal being analyzed, a compressed sensing based algorithm for high resolution range imaging and a new minimized ll-norm criterion for motion compensation are proposed. The random hopping of the transmitted carrier frequency is converted to restricted isometry property of the observing matrix. Then practical problems of imaging model solution and signal parameter design are resolved. Due to the particularity of the proposed algorithm, two new indicators of range profile, i.e., average signal to sidelobe ratio and local similarity, are defined. The chamber measured data are adopted to testify the validity of the proposed algorithm, and simulations are performed to analyze the precision of velocity measurement as well as the performance of motion compensation. The simulation results show that the proposed algorithm has such advantages as high precision velocity measurement, low sidelobe and short period imaging, which ensure robust imaging for moving targets when signal-to-noise ratio is above 10 dB.

CFAR DETECTORS FOR HIGH RESOLUTION RADAR IN NON-GAUSSIAN CLUTTER

For high resolution radar, the echoes of target come from several points rather than one point as in low resolution radar. In this case the target is called an extended target. This paper presents two CFAR detectors for such a target in non Gaussian clutter, which are CA CFAR and OS CFAR detectors. The detection performances of the two detectors are evaluated.

Fatigue Life Estimation of High Strength 2090-T83 Aluminum Alloy under Pure Torsion Loading Using Various Machine Learning Techniques

The ongoing effort to create methods for detecting and quantifying fatigue damage is motivated by the high levels of uncertainty in present fatigue-life prediction approaches and the frequently catastrophic nature of fatigue failure.The fatigue life of high strength aluminum alloy 2090-T83 is predicted in this study using a variety of artificial intelligence and machine learning techniques for constant amplitude and negative stress ratios(R?1).Artificial neural networks(ANN),adaptive neuro-fuzzy inference systems(ANFIS),support-vector machines(SVM),a random forest model(RF),and an extreme-gradient tree-boosting model(XGB)are trained using numerical and experimental input data obtained from fatigue tests based on a relatively low number of stress measurements.In particular,the coefficients of the traditional force law formula are found using relevant numerical methods.It is shown that,in comparison to traditional approaches,the neural network and neuro-fuzzy models produce better results,with the neural network models trained using the boosting iterations technique providing the best performances.Building strong models from weak models,XGB helps to predict fatigue life by reducing model partiality and variation in supervised learning.Fuzzy neural models can be used to predict the fatigue life of alloys more accurately than neural networks and traditional methods.

Optimal Rules to Adopt High Technology under Uncertainty

In the research of choosing the optimal timing for the high technology products, especially IT products to the market, most studies prefer to provide the scope or infnnum of timing. In this paper, an optimal rule is adopted to guild the timing of high technology product to the market, this idea is illustrated through the theory of optimal stopping, and a high approach is developed to theoretical framework for timing decision. On this basis, a random programming model is established, in which the objective function is the expected profit to adopt high technology and the constraint condition is the successful probability over critical value a with all variables beyond the rule, and it is used to find the optimal timing of adopt high technology product.

HIERACHICAL STRUCTURES FOR GENERATING PSEUDO-RANDOM SEQUENCES AND ARRAYS

This paper proposes new hierarchical structures for generating pseudorandom sequences and arrays. The principle of the structures is based on a new concept-multi-interleaving. It is the generalization of normal sequence decimation(sampling). The kernal of the structures is a lower speed linear feedback shift register together with several high speed time-division multiplexers arranged hierarchically. These new structures have much higher speed compared with that of other schemes proposed before.

高阶伪随机信号在对地通讯中的应用

对地通讯(Through-The-Earth Communication,TTEC)以大地为传播介质,使用低频电磁波来传输信息,在地下工程建设调度、预警、救援中有着重要作用.高阶伪随机信号可同时包含数十个频率,其具有易于实现、频率可控、抗干扰能力强的特点,有应用于对地通讯的潜力和价值.鉴于此,本文提出一种基于高阶伪随机信号的对地通讯新方法.通过在高阶伪随机信号中设置静态频组和动态频组,利用静态频组保证多个主频的平均幅值以维持发射稳定性,利用动态频组对通讯信息编码,传输有效信息.在实际工作时,发射端将通讯信息编码转换为高阶伪随机信号,利用长导线源向大地发射,接收端利用电极或者线圈接收电磁信号,经模式识别、时频变换、反向解码转换为有效通讯信息.通过仿真测试和在济南市某煤矿井下试验,完成有效通讯信息的发射、传输、解译等过程,实现了基于高阶伪随机信号的对地通讯方法,验证了方法在地下工程通讯的可行性和可靠性.

高速铁路自复位摇摆桥墩抗震性能分析

基于OpenSEES平台分别建立4跨高速铁路传统简支梁桥和摇摆桥墩简支梁桥系统的有限元模型,并依据摇摆桥墩的基本抗震设防目标,设计摇摆桥墩耗能构件的面积和承载力。在考虑地震动随机性基础上,进行自复位摇摆桥墩在高铁桥梁系统中的抗震性能研究。结果表明:罕遇地震下自复位摇摆耗能装置能够有效降低墩底最大弯矩,减震率达20.26%,进而减少墩身损伤,但碰撞效应使墩底最大轴力放大了74.7%;墩底耗能构件基本进入塑性但未完全被破坏,可实现震后快速修复;摇摆桥墩的最大墩顶位移比传统桥墩增加了66%,但位移组成中可自复位的刚体旋转变形远大于弯曲变形,因此震后残余位移减少了35%;摇摆耗能机制对支座最大变形的减震率达12.3%,使主梁最大变形增大了约49%,但对其残余变形的影响在1 mm内;轨道约束会削弱桥墩摇摆行为,使墩顶最大位移减少了14%,但对墩顶残余位移无明显影响。

不可忽略的无响应缺失下的协变量选择

本文旨在建立一个存在不可忽略的无响应缺失时高维协变量向量的协变量选择方法.由于有不可忽略的缺失响应数据,必须建立一种新的协变量选择方法来删除既与响应变量也与缺失机制无关的协变量.一旦冗余协变量被删除,现有的缺失机制估计和其他基于逆缺失机制加权的分析方法可以被应用.我们提供了一些模拟结果来展示我们方法的有效性.

近断层地震动作用下土石坝加速度分布研究

近断层地震动较远场地震动具有频率高、速度快、能量更加集中的特点,在短时间内会释放大量能量,对工程结构具有严重危害。规范提供的加速度分布系数不适用于高度超过150 m的大坝,随着技术不断进步,我国超过150 m的土石坝越来越多,规范已不能满足现有需求。基于中国台湾集集近断层地震动记录,建立随机脉冲型地震动模型,分别对高度为40 m、70 m、150 m和200 m的土石坝进行随机动力分析,研究坝体的动态分布系数。结果表明,近断层地震动的低频速度脉冲使坝体的加速度反应谱有较宽的敏感段,易覆盖坝体自振周期,显著增加坝体的加速度。该研究通过总结近断层区域土石坝的加速度分布规律,建议了近断层脉冲型地震动区域的土石坝坝体动态分布系数,为近断层高地震风险情况下土石坝的抗震理论和方法提供参考。

数字乡村建设赋能县域经济高质量发展研究——基于技术进步偏向视角

利用全国1869个县域数据,基于新发展理念构建指标体系,采用随机森林算法测度并描述全国县域高质量发展水平,并进一步从技术进步偏向的视角分析数字乡村建设赋能县域高质量发展的效应和机制。研究发现:第一,中国县域高质量发展水平稳步提高,综合指数均值整体呈现波动上升趋势,且存在着显著的全局空间集聚效应和地域差异,障碍因素诊断发现创新相较于其他四个维度障碍度的比例较大。第二,数字乡村建设能够显著促进中国县域的高质量发展。第三,技术进步偏向在数字乡村建设对中国县域高质量发展的影响中发挥中介作用。具体而言,数字乡村建设能够加快促进中国县域技术进步发生由劳动偏向型向资本偏向型的转变,并进而增加县域创新产出来显著推动中国县域经济高质量发展。因此,应继续强化数字赋能,引导资本更多向县域流动,强化技术进步的资本偏向,以发挥数字乡村建设赋能县域高质量发展的作用。

轨道不平顺激励对高温超导磁浮列车电机悬挂的影响

高温超导磁浮列车在运行过程中受到轨道随机不平顺激励的影响,车体和磁浮架的振动会传递至直线电机动子而导致气隙变化,变化后的电磁力反作用于电机悬挂系统,进而影响磁浮架和车体振动。二者的耦合振动一定程度上会影响高温超导磁浮列车的安全运行。为了减少轨道随机不平顺激励对电机悬挂系统的影响,文章建立了多刚体动力学理论模型,并在周期性激励的作用下,对理论模型进行了动力学响应的仿真验证,证明了动力学理论模型的正确性。进一步地,在UM软件中以电机法向力和轨道随机不平顺作为外部激励,对高温超导磁浮列车动力学模型进行仿真,研究了电机悬挂系统的垂向刚度对直线电机气隙、车体和悬浮架振动、列车运行平稳性等参数的影响并对该刚度值进行了合理优化。结果表明:增大直线电机悬挂系统的垂向刚度能一定程度提高车体平稳性;同时增大垂向刚度能一定程度上减小气隙的变化和电机的振动,从而降低和悬浮架的耦合作用。研究结果是在特定的结构参数、负载条件下的仿真分析结果,可为高温超导磁浮列车动力学分析提供一定参考作用。

监管执法公平促进企业高质量发展了吗?——基于证监会随机抽查制度的准自然实验

本文以证监会随机抽查制度作为准自然实验,深入考察了监管执法公平对企业高质量发展的影响及其内在机理。研究发现,证监会随机抽查制度显著提升了上市公司的全要素生产率,即监管执法公平能够有效促进企业高质量发展。该结论经过系列稳健性检验后仍然成立。进一步检验随机抽查制度的公平性效果,发现相较于外部监管效果,随机抽查制度对企业高质量发展的促进作用主要源于监管执法“随机性”和“公开性”的提升。机制检验发现,监管执法公平通过改善会计信息质量、发挥违规惩戒效应来促进企业高质量发展。

基于随机动力分析的高土石坝极限抗震能力研究

地震动的随机性对大坝的动力响应影响较大,极限抗震能力作为大坝抗震安全性能的重要环节,在评估过程中也应该充分考虑荷载随机性的影响。基于大量高土石坝随机动力有限元计算,探究坝顶震陷率和坝坡累计滑移量两个重要坝体变形指标之间的关系,并建议了土石坝安全控制标准。利用概率密度演化法对高土石坝进行极限抗震能力分析。结果表明:震陷率随着累计滑移量的增大而增大,二者之间符合逻辑斯蒂增长模型;取10%的超越概率,以250m规则高面板堆石坝和高心墙堆石坝为例,极限抗震能力分别为0.7g~0.75g和0.8g~0.85g;从概率角度提出了评估大坝极限抗震能力的新方法。

荷载作用下超高层建筑结构风荷载响应仿真

与一般建筑不同,随着高度的增加,超高层建筑结构本身的基本自振周期和柔度增加,阻尼比降低,在荷载作用下会产生一定的位移变化。为了提高超高层建筑结构的稳定性和安全性,提出荷载作用下超高层建筑结构风荷载响应分析方法。基于随机振动理论,建立超高层建筑异形结构在风荷载作用下的运动方程,分析结构位移变化情况;通过静力风效应和动力风效应对建筑异形结构的风效应展开分析;根据分析结果,采用荷载反向识别算法结合离散卡尔曼滤波理论完成建筑结构风荷载响应分析。仿真结果表明,所提方法可准确获得超高层建筑异形结构的湍流度、风速时程、风中心轨迹相关信息,说明该方法的风荷载响应仿真分析结果精度较高。

高血压、心房颤动与阿尔兹海默症风险:一项孟德尔随机研究

目的:采用遗传变异的双样本孟德尔随机化(MR)评估高血压、心房颤动和阿尔兹海默症之间的因果关系,避免观察性研究的局限性。方法:对来自IEU数据库的高血压(HBP)、心房颤动(AF)和阿尔兹海默症(AD)数据集进行MR分析,采用逆方差加权(IVW)、MR Egger、加权中位数、简单模式、加权模式。采用Cochran's Q检验、MR Egger截距检验进行敏感性分析。结果:遗传预测的HBP与AD的风险的关联差异无统计学意义(OR=0.89,95%CI:0.53~1.49,P=0.58);MR Egger未发现遗传多效性的证据(截距=0.007,P=0.39)。AF与AD的风险不存在因果关联(OR=1.04,95%CI:0.97~1.10,P=0.75);MR Egger未发现遗传多效性的证据(截距=0.002,P=0.63)。结论:孟德尔随机化分析未发现HBP、AF与AD之间存在因果关系。