Back analysis of thermal parameters of roller compacted concrete dam based on parallel particle swarm optimization

Xiao-fei Zhang, Xianfeng Huai, Shouyi Li, Bo-Ren Yang
{"title":"Back analysis of thermal parameters of roller compacted concrete dam based on parallel particle swarm optimization","authors":"Xiao-fei Zhang, Xianfeng Huai, Shouyi Li, Bo-Ren Yang","doi":"10.1109/ICNC.2011.6022398","DOIUrl":null,"url":null,"abstract":"According to the randomness of thermal parameters of laboratory test and the defects of traditional back analysis method which is easy to fall into premature and has low efficiency and great computational complexity, the back analysis method based on parallel particle swarm optimization is developed. The back analysis steps of thermal parameters of mass concrete structure is demonstrated detailedly. When three-dimensional finite element relocating mesh method and improved BP neural network method are used to inverse thermal parameters based on the measured temperature, the parameters which reflect the true performance can be obtained. The results show that this method has a better stability and convergency and is feasible to inverse thermal parameters.","PeriodicalId":87274,"journal":{"name":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","volume":"65 1","pages":"2011-2014"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Computing, Networking, and Communications : [proceedings]. International Conference on Computing, Networking and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2011.6022398","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

According to the randomness of thermal parameters of laboratory test and the defects of traditional back analysis method which is easy to fall into premature and has low efficiency and great computational complexity, the back analysis method based on parallel particle swarm optimization is developed. The back analysis steps of thermal parameters of mass concrete structure is demonstrated detailedly. When three-dimensional finite element relocating mesh method and improved BP neural network method are used to inverse thermal parameters based on the measured temperature, the parameters which reflect the true performance can be obtained. The results show that this method has a better stability and convergency and is feasible to inverse thermal parameters.
基于平行粒子群优化的碾压混凝土坝热参数反分析
针对实验室试验热参数的随机性和传统反分析方法易陷入过早、效率低、计算量大的缺陷,提出了基于并行粒子群优化的反分析方法。详细阐述了大体积混凝土结构热参数的反分析步骤。利用三维有限元重定位网格法和改进的BP神经网络方法,基于实测温度反演热参数,可以得到反映真实性能的参数。结果表明,该方法具有较好的稳定性和收敛性,对热参数反演是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信