Penetration modeling of ultra-high performance concrete using multiscale meshfree methods

Terminal ballistics of concrete is of extreme importance to the military and civil communities. Over the past few decades, ultra-high performance concrete (UHPC) has been developed for various applications in the design of protective structures because UHPC has an enhanced ballistic resistance over conventional strength concrete. Developing predictive numerical models of UHPC subjected to penetration is critical in understanding the material's enhanced performance. This study employs the advanced fundamental concrete (AFC) model, and it will run inside the reproducing kernel particle method (RKPM)-based code known as the nonlinear meshfree analysis program (NMAP). NMAP is advantageous for modeling impact and penetration problems that exhibit extreme deformation and material fragmentation. A comprehensive experimental study was conducted to characterize the UHPC. The investigation consisted of fracture toughness testing, the utilization of nondestructive microcomputed tomography analysis, and lastly projectile penetration shots on the UHPC targets. To improve the accuracy of the model, a new scaled damage evolution law (SDEL) is employed within the microcrack informed damage model. During the homogenized macroscopic calculation, the corresponding microscopic cell needs to be dimensionally equivalent to the mesh dimension when the partial differential equation becomes ill posed and strain softening ensues. To ensure arbitrary mesh geometry for which the homogenized stress-strain curves are derived, a size scaling law is incorporated into the homogenized tensile damage evolution law. This ensures energy-bridging equivalence of the microscopic cell to the homogenized medium irrespective of arbitrary mesh geometry. Results of numerical investigations will be compared with results of penetration experiments.     

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最小二乘支持向量回归滤波系统性能分析

支持向量机(Support Vector Machine: SVM)一直作为机器学习方法在统计学习理论基础上被研究和发展,本文从信号与系统的角度出发,证明了平移不变核最小二乘支持向量机(Least Squares SVM: LS-SVM)是一个线性时不变系统.以Ricker子波核为例,探讨了不同参数对最小二乘支持向量回归(Least Squares Support Vector Regression: LS-SVR)滤波器频率响应特性的影响,这些参数的不同选择相应地控制着滤波器通带上升沿的陡峭性、通带的中心频率、通带带宽以及信号能量的衰减,即滤波器长度越长通带的上升沿越陡,核参数值越大通带的中心频率越高,且通带带宽越宽,正则化参数值越小,通带带宽越窄(但通带中心频率基本保持恒定),有效信号幅度衰减越严重.合成地震记录的仿真实验结果表明,Ricker子波核LS-SVR滤波器在处理地震勘探信号的应用中,滤波性能优于径向基函数(Radial Basic Function: RBF)核LS-SVR滤波器以及小波变换滤波和Wiener滤波方法.     

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Statistical procedures for developing earthquake damage fragility curves

This paper describes statistical procedures for developing earthquake damage fragility functions. Although fragility curves abound in earthquake engineering and risk assessment literature, the focus has generally been on the methods for obtaining the damage data (i.e., the analysis of structures), and little emphasis is placed on the process for fitting fragility curves to this data. This paper provides a synthesis of the most commonly used methods for fitting fragility curves and highlights some of their significant limitations. More novel methods are described for parametric fragility curve development (generalized linear models and cumulative link models) and non‐parametric curves (generalized additive model and Gaussian kernel smoothing). An extensive discussion of the advantages and disadvantages of each method is provided, as well as examples using both empirical and analytical data. The paper further proposes methods for treating the uncertainty in intensity measure, an issue common with empirical data. Finally, the paper describes approaches for choosing among various fragility models, based on an evaluation of prediction error for a user‐defined loss function. Copyright © 2015 John Wiley & Sons, Ltd.     

Development of empirical and analytical fragility functions using kernel smoothing methods

Fragility functions that define the probabilistic relationship between structural damage and ground motion intensity are an integral part of performance‐based earthquake engineering or seismic risk analysis. This paper introduces three approaches based on kernel smoothing methods for developing analytical and empirical fragility functions. A kernel assigns a weight to each data that is inversely related to the distance between the data value and the input of the fragility function of interest. The kernel smoothing methods are, therefore, non‐parametric forms of data interpolation. These methods enable the implicit treatment of uncertainty in either or both of ground motion intensity and structural damage without making any assumption about the shape of the resulting fragility functions. They are particularly beneficial for sparse, noisy, or non‐homogeneous data sets. For illustration purposes, two types of data are considered. The first is a set of numerically simulated responses for a four‐story steel moment‐resisting frame, and the second is a set of field observations collected after the 2010 Haiti earthquake. The results demonstrate that these methods can develop continuous representations of fragility functions without specifying their functional forms and treat sparse data sets more efficiently than conventional data binning and parametric curve fitting methods. Moreover, various uncertainty analyses are conducted to address the issues of over‐fitting, bias, and confidence intervals. Copyright © 2014 John Wiley & Sons, Ltd.     

基于核密度估计的南京二手房活跃度特征及影响机制研究

随着越来越多住房可通过网络查询和交易,为住房空间研究提供一个全新数据来源。本文通过对南京搜房网二手房数据挖掘,采用核密度估计空间分析方法,研究南京二手房活跃度的空间特征,重点探讨不同二手房活跃度影响因素,并通过河西、大光路和夫子庙3个案例,实证二手房活跃度的影响机制。研究发现,南京二手房活跃度空间呈现“一心三组团”的结构。二手房活跃度高的地区主要集中在南京市鼓楼区和建邺区;东部玄武高教区、南部江宁二手房活跃度较低,住房空间较为固化,居住空间发展较为成熟。影响二手房活跃度空间差异主要有住房内因和住房外因2个方面。通过多元回归模型分析表明,住房内因的价格、住房层数、绿化率和装修程度和外因的学区、地铁和区域变量显著影响二手房活跃度。居住层数、物业管理费、生活配套设施在活跃度高低2个层面 显著。     

中国15个副省级城市经济转型成效测度及影响因素分析

基于城市经济转型内涵,应用以综合赋权为基础的模糊物元模型和核密度估计模型等评价方法,对2000~2012年中国城市经济转型成效的时空格局演变进行分析。结果表明：① 2000~2012年中国经济转型低值地区发展速度提升较快,高值地区发展有减缓趋势,但整体呈现出较好的转型态势且区域间差距逐渐缩小。2005年特别是2008年金融危机以后取得成效并不显著。② 城市经济发展水平稳步提升,但空间格局变化甚微。经济规模扩张度、结构优化度、发展持续度在空间上呈现正向变化,转型成效明显;经济效益提升度却呈现出正反向回旋式变化,说明转型中政府政策的实施存在时滞效应且转型对就业产生了一定的挤出效应。③ 城市经济转型的时空格局演变是多种因素综合作用的结果。历史性基础因素奠定了城市经济转型的基础,提升性动力因素为其注入了活力,二者相互作用共同决定了当前经济转型现状,未来影响城市经济转型的主要因素包括内生发展能力和政策导向因素。     

集成改进Mean Shift和区域合并两种算法的图像分割

Mean Shift算法分割图像时,带宽的大小直接影响分割效果。带宽分为空间带宽和值域带宽。本文根据待分割遥感图像的空间分辨率参考选定空间带宽,基于渐近积分均方差最小原则计算每一波段值域带宽;针对MS算法分割图像时存在过分割问题,提出基于区域面积加权的区域相似度准则和基于区域熵的合并停止准则来合并分割后区域。MATLAB软件3组实验结果表明:本文方法相比EDISON软件能得到更好的分割效果,且能在一定程度上提高遥感影像分割的自动化。