断裂能与统一损伤加载面描述的混凝土本构模型

构建一个混凝土损伤本构模型,研究目的为解决现有模型中存在的损伤演化、双轴强度与网格尺寸依赖性问题。基于试验观察,提出符合实际的压缩损伤演化方程;在不可逆热力学的框架下,利用当量转化应力状态的方法,在应变空间构造统一损伤加载面,以表达混凝土的双轴强度;借助断裂能对损伤阀值正则化的方法,以合理反映应变软化过程中的能量耗散,并达到消除网格尺寸依赖性之目的。采用编制的程序,对单轴与双轴加载、四点弯非比例加载等混凝土试验进行数值计算,验证了模型的合理性与有效性。研究结果表明:模型不仅解决了上述存在的问题,而且具备在较复杂应力路径下预测结构的承载力、变形及裂缝扩展的能力,可为混凝土结构的定量评价提供支持依据。     

形态小波变换在轴承故障信号处理中的应用

基于数学形态学的形态小波变换是对信号基于形态特征的非线性分解，选取合适的信号分解算子既能够抑制噪声，又能够提取信号中的冲击成分。形态小波变换只有加减法和取极大、极小运算，与通用的时频分析方法相比计算简单。仿真数据和实验信号的分析表明：形态小波变换能够准确有效地提取轴承故障的特征频率成分，适用于轴承故障的在线诊断。     

Relations Between Wavelet Network and Feedforward Neural Network

A comparison of construction forms and base functions is made between feedforward neural network and wavelet network. The relations between them are studied from the constructions of wavelet functions or dilation functions in wavelet network by different activation functions in feedforward neural network. It is concluded that some wavelet function is equal to the linear combination of several neurons in feedforward neural network.     

基于多小波分析的暂态信号去噪方法研究

由于多小波分析方法的特殊性,需要对原始信号进行预处理.不同的预处理方法对多小波去噪效果有着非常明显的影响.文中介绍了多小波理论,选用GHM多小波,采用了4种预处理方法对信号进行预处理,分析了基于这4种方法进行信号去噪的结果,并与单小波处理结果进行了比较.将比较结果应用于检测系统输出电压信号进行分析,结果表明,利用多小波变换方法对暂态信号去噪比用单小波方法具有明显的优越性.     

文学本质和现代转型

“五四”新文学所开启的文学的现代转型成为一个众说纷纭的话题，文章试图从文学本质的角度，重新梳理现代转型之于文学现代性追求的作用以及对当下文学的启示意义。     

VARIABLE CUTOFFF REQUENCY NONLINEAR DIGITAL FILTER: II-TWO-DIMENSION

ＶＡＲＩＡＢＬＥＣＵＴＯＦＦＦＲＥＱＵＥＮＣＹＮＯＮＬＩＮＥＡＲＤＩＧＩＴＡＬＦＩＬＴＥＲ：ＩＩ－ＴＷＯ┐ＤＩＭＥＮＳＩＯＮ＊ＧｏＨｏｎｇ（古红）ＺｈｕＹｉｓｈｅｎｇ（朱贻盛）（ＩｎｓｔｉｔｕｔｅｏｆＢｉｏｍｅｄｉｃａｌＥｎｇｉｅｅｒｉｎｇ，Ｓｈａｎ...     

SPSS在拱桥轴线变形观测回归拟合中应用

根据实测获取的桥拱轴线的观测数据,通过应用SPSS程序软件,对桥拱轴线的设计线形进行了拟合,确定了其有关参数和理论数据,使桥梁及其他建筑物的曲线回归、变形分析和精度评定更规律化简单化和高效率,为旧危建筑加固维护,新建筑物施工质量评价,提供了翔实可靠的依据.     

Network Decomposition and Maximum Independent Set Part Ⅱ：Application Research

According to the researches on theoretic basis in part I of the paper，the spanning tree algorithms solving the maximum independent set both in even network and in odd network have been developed in this part，part Ⅱ of the paper．The algorithms trans form first the general network into the pair sets network，and then decompose the pair sets network into a series of pair subsets by use of the characteristic of maximum flow passing through the pair sets network．As for the even network，the algorithm requires only one time of trans formation and decomposition，the maximum independent set can be gained without any iteration processes，and the time complexity of the algorithm is within the bound of O(｜V｜^3)．However，as for the odd network，the algorithm consists of two stages．In the first stage，the general odd network is transformed and decomposed into the pseudo-negative envelope graphs and generalized reverse pseudo-negative envelope graphs alternately distributed at first；then the algorithm turns to the second stage，searching for the negative envelope graphs within the pseudo-negative envelope graphs only．Each time as a negative envelope graphhas been found．renew the pair sets network by iteration at once．and then tum back to the first stage．So both stages form a circulation process up to the optimum．Two available methods，the adjusting search and the picking-off search are specially developed to deal with the problems resulted from the odd network．Both of them link up with each other harmoniously and are embedded together in the algorithm．Analysis and study indicate that the time complexity of this algorithm is within the bound of O(｜V｜^5)．     

基于小波变换的混沌信号特征研究

应用小波方法将混沌信号的频谱特征和吸引子的几何结构相结合进行研究,结果表明,在不同尺度上对混沌信号进行连续小波变换时,其小波系数具有很强的相似性,但不能够完全重构原来的吸引子.对信号进行多尺度分解后发现其低频系数部分基本能够重现原吸引子的结构特征,而高频系数部分不能实现这一目标.为了定量刻画混沌信号在小波变换条件下的分形特征,计算了其在不同尺度时的关联维数,并分析了关联维数计算的影响因素.     

Forecasting demand for high speed rail

It is sometimes argued that standard state-of-practice logit-based models cannot forecast the demand for substantially reduced travel times, for instance due to High Speed Rail (HSR). The present paper investigates this issue by reviewing the literature on travel time elasticities for long distance rail travel and comparing these with elasticities observed when new HSR lines have opened. This paper also validates the Swedish long distance model, Sampers, and its forecast demand for a proposed new HSR, using aggregate data revealing how the air–rail modal split varies with the difference in generalized travel time between rail and air. The Sampers long distance model is also compared to a newly developed model applying Box–Cox transformations. The paper contributes to the empirical literature on long distance travel, long distance elasticities and HSR passenger demand forecasts. Results indicate that the Sampers model is indeed able to predict the demand for HSR reasonably well. The new non-linear model has even better model fit and also slightly higher elasticities.