| 注册
首页|期刊导航|水力发电|基于优选地震强度参数的地下倒虹吸结构易损性分析

基于优选地震强度参数的地下倒虹吸结构易损性分析

段朝杰 陈荣国 石艳柯 王智磊 门文博 何志佳

水力发电2024,Vol.50Issue(8):28-37,10.
水力发电2024,Vol.50Issue(8):28-37,10.

基于优选地震强度参数的地下倒虹吸结构易损性分析

Fragility Analysis of Underground Inverted Siphon Structures Based on Preferred Seismic Intensity Measures

段朝杰 1陈荣国 1石艳柯 2王智磊 2门文博 1何志佳1

作者信息

  • 1. 中铁七局集团武汉工程有限公司,湖北 武汉 430074
  • 2. 华北水利水电大学土木与交通学院,河南 郑州 450045
  • 折叠

摘要

Abstract

Seismic fragility analysis has proven to be an effective way to study the seismic performance of structures.Compared with above-ground hydraulic structures such as ferries and dams,the seismic vulnerability of underground inverted siphon structures had been less studied.Taking the underground inverted siphon structure in Xiazhuang,Yunnan Province as the research object,16 scalar ground vibration intensity measures(IM)are selected and soil-structure dynamic nonlinear finite element calculations are carried out for the underground inverted siphon structure using the IDA method.Four parameters of effectiveness,practicality,efficiency and relevance are used as evaluation indexes to preferably select scalar IM to form vector IMs.A GA-BP neural network is established by optimizing a back propagation(BP)neural network using genetic algorithm(GA),and the preferable vector IMs are used as input for training.The vulnerability surface of the underground inverted siphon structure is established by the trained neural network.The results show that the preferentially composed vector IMs can better respond to the seismic performance of the underground inverted siphon structure,and can reduce the computational cost of seismic susceptibility analysis by 70% for the structure in this paper.

关键词

地下倒虹吸/易损性分析/地震强度参数/人工神经网络/遗传算法

Key words

underground inverted siphon/seismic fragility analysis/seismic intensity measure/artificial neural network/genetic algorithm

分类

建筑与水利

引用本文复制引用

段朝杰,陈荣国,石艳柯,王智磊,门文博,何志佳..基于优选地震强度参数的地下倒虹吸结构易损性分析[J].水力发电,2024,50(8):28-37,10.

基金项目

河南省水利科技攻关项目(GG202333) (GG202333)

水力发电

OACSTPCD

0559-9342

访问量0
|
下载量0
段落导航相关论文