基于SEResNet的内河高桩码头损伤诱因反演研究

L. Jia, Cai Fenglin, Zhu Qitao, Yang Tongxin, Zhang Qian
{"title":"基于SEResNet的内河高桩码头损伤诱因反演研究","authors":"L. Jia, Cai Fenglin, Zhu Qitao, Yang Tongxin, Zhang Qian","doi":"10.23977/jaip.2023.060409","DOIUrl":null,"url":null,"abstract":": Based on SEResNet neural network algorithm, the inversion model of damage incentives of inland high-piled wharf is constructed. The stress data of pile foundation under the action of damage incentives of high-piled wharf are obtained by using solid element finite element model calculation and indoor model test methods. The parameterized finite element calculation model of high-piled wharf is established by using subprocess in Python program to call MANSYS module, and verified with solid element model. The parameterized simplified finite element model meets the needs of inversion calculation. Based on the stress data samples of the pile foundation of the high-piled wharf obtained from the model test, the inversion analysis of single and multiple damage incentives is carried out. The model can identify the location, size and type of injury causative agent with good generalization ability.","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on Inversion of Damage Incentives of High Pile Wharf in Inland River Based on SEResNet\",\"authors\":\"L. Jia, Cai Fenglin, Zhu Qitao, Yang Tongxin, Zhang Qian\",\"doi\":\"10.23977/jaip.2023.060409\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": Based on SEResNet neural network algorithm, the inversion model of damage incentives of inland high-piled wharf is constructed. The stress data of pile foundation under the action of damage incentives of high-piled wharf are obtained by using solid element finite element model calculation and indoor model test methods. The parameterized finite element calculation model of high-piled wharf is established by using subprocess in Python program to call MANSYS module, and verified with solid element model. The parameterized simplified finite element model meets the needs of inversion calculation. Based on the stress data samples of the pile foundation of the high-piled wharf obtained from the model test, the inversion analysis of single and multiple damage incentives is carried out. The model can identify the location, size and type of injury causative agent with good generalization ability.\",\"PeriodicalId\":293823,\"journal\":{\"name\":\"Journal of Artificial Intelligence Practice\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Artificial Intelligence Practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23977/jaip.2023.060409\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Artificial Intelligence Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23977/jaip.2023.060409","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

基于SEResNet神经网络算法,建立了内陆高桩码头损伤激励的反演模型。采用实体单元有限元模型计算和室内模型试验方法,获得了高桩码头在损伤激励作用下桩基的应力数据。利用Python程序中的子过程调用MANSYS模块,建立了高桩码头参数化有限元计算模型,并用实体单元模型进行了验证。参数化简化有限元模型满足反演计算的需要。基于模型试验获得的高桩码头桩基应力数据样本,进行了单损伤和多损伤激励的反演分析。该模型能够识别损伤病原体的位置、大小和类型,具有较好的泛化能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on Inversion of Damage Incentives of High Pile Wharf in Inland River Based on SEResNet
: Based on SEResNet neural network algorithm, the inversion model of damage incentives of inland high-piled wharf is constructed. The stress data of pile foundation under the action of damage incentives of high-piled wharf are obtained by using solid element finite element model calculation and indoor model test methods. The parameterized finite element calculation model of high-piled wharf is established by using subprocess in Python program to call MANSYS module, and verified with solid element model. The parameterized simplified finite element model meets the needs of inversion calculation. Based on the stress data samples of the pile foundation of the high-piled wharf obtained from the model test, the inversion analysis of single and multiple damage incentives is carried out. The model can identify the location, size and type of injury causative agent with good generalization ability.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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