Development and Verification of Distributed Real-Time Hybrid Simulation Methods
Publication: Journal of Computing in Civil Engineering
Volume 31, Issue 4
Abstract
Hybrid simulation combines numerical simulation and physical testing, and is thus considered to be an efficient alternative to traditional testing methodologies in the evaluation of global performance of large or complex structures. Real-time hybrid simulation (RTHS) is performed when it is important to fully capture rate-dependent behaviors in the physical substructure. Although the demand to test more complex systems grows, not every laboratory has the right combination of computational and equipment resources available to perform large-scale experiments. Distributed real-time hybrid simulation (dRTHS) facilitates testing that is to be conducted at multiple geographically distributed laboratories while utilizing the Internet to couple the substructures. One major challenge in dRTHS is to accommodate the unpredictable communication time delays between the various distributed sites that occur as a result of Internet congestion. Herein, a dRTHS framework is proposed where a modified Smith predictor is adopted to accommodate such communication delays. To examine and demonstrate the sensitivity of the proposed framework to communication delays and to modeling errors, parametric analytical case studies are presented. Additionally, the effectiveness of this dRTHS framework is verified through successful execution of multisite experiments. The results demonstrate that this framework provides a new option for researchers to evaluate the global response of structural systems in a distributed real-time environment.
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Acknowledgments
The authors gratefully acknowledge the partial support of this research by U.S. National Science Foundation under awards 1148255 and 1148215, the National Natural Science Foundation of China under awards 51261120377 and China Scholarship Council. The unique RTHS facilities in the Intelligent Infrastructure Systems Lab was developed through NSF CNS 1028668 and with support from Purdue University’s School of Mechanical Engineering.
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Information & Authors
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Published In
Journal of Computing in Civil Engineering
Volume 31 • Issue 4 • July 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Oct 20, 2015
Accepted: Oct 5, 2016
Published ahead of print: Feb 22, 2017
Published online: Feb 23, 2017
Published in print: Jul 1, 2017
Discussion open until: Jul 23, 2017
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