A real‐time hybrid simulation method based on multitasking loading

Author:

Wang Tao12,Hao Jiedun1,Xu Guoshan324ORCID,Wang Zhen5,Meng Liyan1,Zheng Huan1

Affiliation:

1. School of Architecture & Civil Engineering Heilongjiang University of Science & Technology Harbin 150022 China

2. Key Lab of Structures Dynamic Behavior and Control, Ministry of Education Harbin Institute of Technology Harbin 150090 China

3. School of Civil Engineering Harbin Institute of Technology Harbin 150090 China

4. Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin 150090 China

5. School of Civil Engineering and Architecture Wuhan University of Technology Wuhan 430070 China

Abstract

SummaryDue to the real‐time loading property and the limitation of available loading facilities, both of the refined numerical substructure simulations and multiple experimental substructure tests are impossible for traditional real‐time hybrid simulation method (RHSM). For improving the experimental accuracy under limited loading facilities, a RHSM based on multitasking loading (RHSM‐ML) is proposed in this paper. In the proposed method, an inner‐loop multitasking loading strategy is adopted for accurately reproducing the performance of multiple experimental substructures with limited available loading facilities, and an outer‐loop force correction‐based iteration strategy is adopted for further improving the experimental accuracy by allowing refined simulation of the numerical substructures while remaining real‐time loading on the experimental substructures. Firstly, the methodology of the proposed RHSM‐ML is presented. Furthermore, the numerical simulations were conducted for validating the effectiveness and accuracy of the proposed method. Finally, the influence of the structural model on the iterative convergence is analyzed. It is shown that the multitasking loading and the force correction‐based iteration strategy are feasible for RHSM. It is shown from numerical simulations that with the contribution of the multitasking loading strategy, the correlation coefficients under different simulation conditions can up to 0.9999 within five round iterations by the RHSM‐ML and the force correction‐based iteration strategy of the RHSM‐ML can significantly improve the iterative convergence accuracy. It is shown from iterative convergence analysis that under different structural models, the convergence of the RHSM‐ML can be achieved within five round iterations.

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Building and Construction,Architecture,Civil and Structural Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3