%0 Journal Article
%T 基于核密度估计的结构地震需求信息熵重要性分析
%A 王秀振
%A 钱永久
%A 瞿浩
%J 振动与冲击
%D 2019
%X 对8个输入随机变量进行了抽样，分别选取7条地震动记录和El Centro地震动记录，利用有限元软件OpenSEES进行了动力非线性时程分析，得到了基底剪力、顶点位移、最大楼层加速度和最大层间位移角4种结构地震需求。将核密度估计用于结构地震需求信息熵重要性分析的求解中，并用方差重要性分析方法进行了对比。结果表明：采用的抽样方法在样本量为几百时即可得到较好的结果，这远远少于现有的抽样方法所需要的成千上万的样本数，是一种准确高效的抽样方法；基于核密度估计得到的各个输入随机变量的信息熵重要性排序与方差重要性分析方法得到的各个输入随机变量的重要性排序基本一致，可见基于信息熵的重要性测度分析方法是一种良好的重要性分析方法。</br>Abstract：8 input random variables including the selected 7 ground motion records and an El Centro one were sampled, respectively.The dynamic nonlinear time history analysis was conducted for a multi-floor building with the finite element software OpenSees.Its base shear, top point displacement, the maximum floor acceleration and the maximum interlayer displacement angle were obtained as the structure’s seismic demands.The kernel density estimation was used to do the structural seismic demand information entropy importance analysis, and the results were compared with those using the variance importance analysis method.The results showed that the used sampling method can get better results when the sample number is hundreds, and this number is far less than thousands required by the existing sampling method, so it is an accurate and efficient sampling method; the information entropy importance sequencing of each input random variable based on the kernel density estimation and that based on the variance importance analysis are basically consistent, so the importance measure analysis method based on information entropy is a good method of importance analysis.
%K 信息熵
%K 核密度估计
%K 地震需求
%K 重要性分析&lt
%K /br&gt
%U http://jvs.sjtu.edu.cn/CN/abstract/abstract8171.shtml