Real-time hybrid simulation of structural systems with soil-foundation interaction effects using neural networks

IF 4.3 2区 工程技术 Q1 ENGINEERING, CIVIL
Safwan Al-Subaihawi, James Ricles, Spencer Quiel, Thomas Marullo, Faisal Malik
{"title":"Real-time hybrid simulation of structural systems with soil-foundation interaction effects using neural networks","authors":"Safwan Al-Subaihawi,&nbsp;James Ricles,&nbsp;Spencer Quiel,&nbsp;Thomas Marullo,&nbsp;Faisal Malik","doi":"10.1002/eqe.4236","DOIUrl":null,"url":null,"abstract":"<p>Real-time hybrid simulation (RTHS) involves dividing a structural system into numerical and experimental substructures. The experimental substructure is challenging to model analytically and is therefore modeled physically in the laboratory. Analytical substructures are conventionally modeled using the finite element method. The two substructures are kinematically linked, and the governing equations of motion are solved in real-time. Thus, the state determination of the analytical substructure needs to occur within the timestep, which is of the order of a few milliseconds. All structural systems are supported by a soil-foundation system and any evaluation of the efficacy of response modification devices placed in the structure should consider soil-foundation structure interaction (SFSI) effects. SFSI adds compliance to a structural system, thereby altering the natural frequencies. Additionally, nonlinear behavior in the soil can result in residual deformations in the foundation and structure, as well as provide added damping. These effects can occur under both wind and earthquake loading. To overcome the barrier of the large computational effort required to model SFSI effects in real-time using the conventional finite element approach, a neural network (NN) model is combined with an explicit-based analytical substructure and experimental substructure with dampers to create a framework for performing RTHS with SFSI effects. The framework includes a block of long-short term memory (LSTM) layers that is combined with a parallel rectified linear unit (ReLU) to form a NN model of the soil-foundation system. RTHS of a tall 40-story steel building equipped with nonlinear viscous dampers and subjected to a windstorm are performed to illustrate the framework. It was found that a number of factors have an effect on the quality of RTHS results. These include: (i) the discretization of the wind loading into bins of basic wind speed; (ii) the extent of the NN model training as determined by the root mean square error (RMSE); (iii) noise in the restoring forces produced by the NN model and its interaction with the integration algorithm; and, (iv) the bounding of outliers of the NN model's output. Guidelines for extending the framework for the RTHS of structures subjected to seismic loading are provided.</p>","PeriodicalId":11390,"journal":{"name":"Earthquake Engineering & Structural Dynamics","volume":"53 15","pages":"4688-4718"},"PeriodicalIF":4.3000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eqe.4236","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earthquake Engineering & Structural Dynamics","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/eqe.4236","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0

Abstract

Real-time hybrid simulation (RTHS) involves dividing a structural system into numerical and experimental substructures. The experimental substructure is challenging to model analytically and is therefore modeled physically in the laboratory. Analytical substructures are conventionally modeled using the finite element method. The two substructures are kinematically linked, and the governing equations of motion are solved in real-time. Thus, the state determination of the analytical substructure needs to occur within the timestep, which is of the order of a few milliseconds. All structural systems are supported by a soil-foundation system and any evaluation of the efficacy of response modification devices placed in the structure should consider soil-foundation structure interaction (SFSI) effects. SFSI adds compliance to a structural system, thereby altering the natural frequencies. Additionally, nonlinear behavior in the soil can result in residual deformations in the foundation and structure, as well as provide added damping. These effects can occur under both wind and earthquake loading. To overcome the barrier of the large computational effort required to model SFSI effects in real-time using the conventional finite element approach, a neural network (NN) model is combined with an explicit-based analytical substructure and experimental substructure with dampers to create a framework for performing RTHS with SFSI effects. The framework includes a block of long-short term memory (LSTM) layers that is combined with a parallel rectified linear unit (ReLU) to form a NN model of the soil-foundation system. RTHS of a tall 40-story steel building equipped with nonlinear viscous dampers and subjected to a windstorm are performed to illustrate the framework. It was found that a number of factors have an effect on the quality of RTHS results. These include: (i) the discretization of the wind loading into bins of basic wind speed; (ii) the extent of the NN model training as determined by the root mean square error (RMSE); (iii) noise in the restoring forces produced by the NN model and its interaction with the integration algorithm; and, (iv) the bounding of outliers of the NN model's output. Guidelines for extending the framework for the RTHS of structures subjected to seismic loading are provided.

Abstract Image

利用神经网络对具有土壤-地基相互作用效应的结构系统进行实时混合模拟
实时混合模拟(RTHS)是指将结构系统分为数值子结构和实验子结构。实验子结构对分析建模具有挑战性,因此需要在实验室中进行物理建模。分析子结构通常采用有限元法建模。这两个子结构在运动学上是相互关联的,其运动控制方程是实时求解的。因此,分析子结构的状态确定需要在几毫秒量级的时间步内完成。所有结构系统都由土壤-地基系统支撑,因此在评估结构中放置的响应修正装置的有效性时,应考虑土壤-地基结构相互作用(SFSI)效应。SFSI 会增加结构系统的顺应性,从而改变固有频率。此外,土壤中的非线性行为会导致地基和结构的残余变形,并提供额外的阻尼。在风荷载和地震荷载作用下都会产生这些效应。使用传统的有限元方法对 SFSI 效应进行实时建模需要大量的计算工作,为了克服这一障碍,我们将神经网络(NN)模型与基于显式分析的下部结构和带阻尼器的实验下部结构相结合,创建了一个框架,用于执行具有 SFSI 效应的 RTHS。该框架包括一个长短期记忆(LSTM)层块,它与并行整流线性单元(ReLU)相结合,形成了一个土壤-地基系统的 NN 模型。为说明该框架,对一栋装有非线性粘性阻尼器的 40 层高钢结构建筑进行了 RTHS 验证。研究发现,许多因素都会影响 RTHS 结果的质量。这些因素包括(i) 将风荷载离散化为基本风速分段;(ii) 根据均方根误差 (RMSE) 确定的 NN 模型训练程度;(iii) NN 模型产生的恢复力中的噪声及其与积分算法的交互作用;以及 (iv) NN 模型输出离群值的界限。还提供了将该框架扩展到承受地震荷载的结构的 RTHS 的指导原则。
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
Earthquake Engineering & Structural Dynamics
Earthquake Engineering & Structural Dynamics 工程技术-工程:地质
CiteScore
7.20
自引率
13.30%
发文量
180
审稿时长
4.8 months
期刊介绍: Earthquake Engineering and Structural Dynamics provides a forum for the publication of papers on several aspects of engineering related to earthquakes. The problems in this field, and their solutions, are international in character and require knowledge of several traditional disciplines; the Journal will reflect this. Papers that may be relevant but do not emphasize earthquake engineering and related structural dynamics are not suitable for the Journal. Relevant topics include the following: ground motions for analysis and design geotechnical earthquake engineering probabilistic and deterministic methods of dynamic analysis experimental behaviour of structures seismic protective systems system identification risk assessment seismic code requirements methods for earthquake-resistant design and retrofit of structures.
×
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