Experimental verification of an accessible geographically distributed real-time hybrid simulation platform
Corresponding Author
Ali Irmak Ozdagli
Lyles School of Civil Engineering, Purdue University, West Lafayette, Indiana
Correspondence
Ali Irmak Ozdagli, Lyles School of Civil Engineering, Purdue University, West Lafayette, Indiana.
Email: [email protected]
Search for more papers by this authorWang Xi
Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, California
Search for more papers by this authorGaby Ou
Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, Utah
Search for more papers by this authorShirley J. Dyke
School of Mechanical Engineering, Purdue University, West Lafayette, Indiana
Search for more papers by this authorBin Wu
School of Civil Engineering, Harbin Institute of Technology, Harbin, China
Search for more papers by this authorJian Zhang
Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, California
Search for more papers by this authorDing Yong
School of Civil Engineering, Harbin Institute of Technology, Harbin, China
Search for more papers by this authorGuoshan Xu
School of Civil Engineering, Harbin Institute of Technology, Harbin, China
Search for more papers by this authorTao Wang
College of Architecture and Civil Engineering, Heilongjiang University of Science and Technology, Harbin, China
Search for more papers by this authorCorresponding Author
Ali Irmak Ozdagli
Lyles School of Civil Engineering, Purdue University, West Lafayette, Indiana
Correspondence
Ali Irmak Ozdagli, Lyles School of Civil Engineering, Purdue University, West Lafayette, Indiana.
Email: [email protected]
Search for more papers by this authorWang Xi
Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, California
Search for more papers by this authorGaby Ou
Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, Utah
Search for more papers by this authorShirley J. Dyke
School of Mechanical Engineering, Purdue University, West Lafayette, Indiana
Search for more papers by this authorBin Wu
School of Civil Engineering, Harbin Institute of Technology, Harbin, China
Search for more papers by this authorJian Zhang
Department of Civil and Environmental Engineering, University of California Los Angeles, Los Angeles, California
Search for more papers by this authorDing Yong
School of Civil Engineering, Harbin Institute of Technology, Harbin, China
Search for more papers by this authorGuoshan Xu
School of Civil Engineering, Harbin Institute of Technology, Harbin, China
Search for more papers by this authorTao Wang
College of Architecture and Civil Engineering, Heilongjiang University of Science and Technology, Harbin, China
Search for more papers by this authorSummary
Real-time hybrid simulation (RTHS) has become a recognized methodology for isolating and testing complex, rate-dependent structural components and devices to understand their behavior and to evaluate their ability to improve the performance of structures exposed to severe dynamic loading. Although RTHS is efficient in its utilization of equipment and space compared with conventional testing techniques, the laboratory resources may not always be available in a single testing facility to conduct large-scale experiments. Consequently, distributed systems, capable of connecting multiple RTHS setups located at several geographically distributed facilities through appropriate information exchange, become desirable. This study presents a distributed RTHS (dRTHS) platform that enables the integration of geographically distributed physical and numerical components across the Internet. The essential capabilities needed to establish such a dRTHS platform are discussed, including the communication architecture, network components, and connection reliability. One significant challenge for conducting successful dRTHS is sustaining real-time communication between test sites. To accommodate realistic network delays due to variations in the Internet service, a Smith predictor-based delay compensation algorithm that includes a network time delay estimator is developed. A series of numerical and experimental studies is conducted to verify the platform and to quantify the impact of uncertainties present in a typical distributed system. Through an evaluation of the results, it is demonstrated that dRTHS is feasible for coupling laboratory capabilities and is a viable alternative to traditional testing techniques.
REFERENCES
- 1Atkins DE, Droegemeier KK, Feldman SI, et al. Revolutionizing science and engineering through cyberinfrastructure, Report of the National Science Foundation Blue-Ribbon Advisory Panel on. National Science Foundation: Cyberinfrastructure; 2003.
- 2Oden, J. T., Belytschko, T., Fish, F., Hughes, T. J. R., Johnson, C., Keyes, D., Laub, A., Petzold, L., Srolovitz, D., Yip, S., and Bass, J. (2006). Revolutionizing engineering science through simulation, Report of the National Science Foundation Blue Ribbon Panel on Simulation-Based Engineering Science. National Science Foundation.
- 3 Cyberinfrastructure Council (2007). Cyberinfrastructure vision for 21st century discovery. National Science Foundation.
- 4Dyke SJ, Christenson R, Jiang Z, Gao X, Feinstein Z. Tele-operation tools for bench-scale shake tables for instruction in earthquake engineering. Seismological Research Letters, Seismological Society of America. 2007; 78(4).
- 5Magana AJ, Ortega-Alvarez JD, Lovam R, Gomez D, Marulanda J, Dyke SJ. Virtual, local and remote laboratories for conceptual understanding of dynamic systems. International Journal of Engineering Education. 2017. (in press)
- 6Takanashi M, Udagawa K, Seki M, Okada T, Tanaka H. Nonlinear earthquake response and analysis of structures by a computer-actuator on-line system. Bulletin of Earthquake Resistant Structure Research Center. 1975.
- 7Mahin S, Shing P. Pseudodynamic method for seismic testing. Journal of Structural Engineering. 1985; 111(7): 1482-1503.
- 8Nakata, N., Yang, G., and Spencer, B. F. (2004). System requirements for mini-most experiment. Technical report, NEESgrid.
- 9Nakashima M, Kato H, Takaoka E. Development of real-time pseudo dynamic testing. Earthquake Engineering & Structural Dynamics. 1992; 21(1): 79-92.
- 10Saouma V, Sivaselvan M. Hybrid simulation: Theory, implementation and applications. Taylor & Francis; 2008.
- 11Christenson RE, Lin YZ, Emmons A, Bass B. Large-scale experimental verification of semiactive control through real-time hybrid simulation. Journal of Structural Engineering. 2008; 134: 522-534.
- 12Sun Z, Ou G, Dyke SJ, Lu C. A state estimation method for wireless structural control systems. Struct. Control Health Monit. 2017; 24:e1929. https://doi.org/10.1002/stc.1929
- 13Deierlein, G., Arduino, P., Asimaki, D., Caicedo, J. M., Dyke, S. J., Hachem, M. M., Irfanoglu, A., McKenna, F., Lynett, P., Lowes, L. N., Mejia, L., Mazzoni, S., Mosqueda, G., Nakata, N., Zhang, J., and Rodgers, G. P. (2011). NEES vision report on computational and hybrid simulation.
- 14Coulouris GF, Dollimore J, Kindberg T. Distributed systems: Concepts and design (4th Edition). Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc.; 2005.
- 15 NEESgrid (2003). The MOST experiment—Whitepaper 1.0. Technical report.
- 16Pearlman, L., D'arcy, M., Johnson, E., Kesselman, C., and Plaszczak, P. (2004). NEESgrid teleoperation control protocol (NTCP)—TR-2004-23. Technical report.
- 17 NEESgrid (2004). The MOST experiment: Earthquake engineering on the grid—TR-2004-41. Technical report.
- 18Spencer, B. F., Finholt, T., Foster, I., Kesselman, C., Beldica, C., Futrelle, J., Gullapalli, S., Hubbard, P., Liming, L., Marcusiu, D., Pearlman, L., Severance, C., and Yang, G. (2004). NEESgrid: A distributed collaboratory for advanced earthquake engineering experiment and simulation. In 13th World Conference on Earthquake Engineering.
- 19Mosqueda G, Stojadinovic B, Hanley J, Sivaselvan M, Reinhorn A. Hybrid seismic response simulation on a geographically distributed bridge model. Journal of Structural Engineering. 2008; 134(4): 535-543.
- 20Stojadinovic B, Mosqueda G, Mahin S. Event-driven control system for geographically distributed hybrid simulation. Journal of Structural Engineering. 2006; 132(1): 68-77.
- 21Kwon, O. S., Nakata, N., Park, K. S., Elnashai, A., and Spencer, B. (2007). User manual and examples for UI-SIMCOR v2.6. Technical report.
- 22Spencer B, Elnashai AS, Kwon OS, Park KS, Nakata N. The UI-SimCor hybrid simulation framework. Ispra, Italy: The 2nd World Forum on Collaborative Research in Earthquake Engineering; 2007.
- 23Elnashai AS, Spencer B, Kuchma DA, et al. The multi-axial full-scale sub-structured testing and simulation (MUST-SIM) facility at the University of Illinois at Urbana-Champaign. In: Advances in earthquake engineering for urban risk reduction. Dordrecht: Springer; 2006: 245-260.
10.1007/1-4020-4571-9_16 Google Scholar
- 24Sextos A., Bousias S., Taskari O., Evangeliou N., Kwon O.-S., Elnashai A., DiSarno L., and Palios, X. (2014). An intercontinental hybrid simulation experiment for the purposes of seismic assessment of a three-span R/C bridge. Tenth U.S. National Conference on Earthquake Engineering, Frontiers of Earthquake Engineering, July 21-25, 2014, 10NCEE Anchorage, Alaska
- 25Cowart C, Hubbard P, Miller L, Crawford G. NHCP reference implementation and protocol reference guide. San Diego: Technical report, University of California; 2007.
- 26Takahashi Y, Fenves GL. Software framework for distributed experimental computational simulation of structural systems. Earthquake Engineering & Structural Dynamics. 2006; 35(3): 267-291.
- 27Schellenberg, A. H., Mahin, S. A., and Fenves, G. L. (2009). Advanced implementation of hybrid simulation—PEER 2009/104. Technical report, University of California, Berkeley.
- 28Park DU, Yun CB, Lee JW, Nagata K, Watanabe E, Sugiura K. On-line pseudo-dynamic network testing on base-isolated bridges using internet and wireless internet. Experimental Mechanics. 2005; 45(4): 331-343.
- 29Xiao, Y., Hu, Q., Guo, Y., Zhu, P., and Yi, W. (2004). Development of a network platform for remote hybrid dynamic testing. In 13th World Conference on Earthquake Engineering.
- 30Yang YS, Hsieh SH, Tsai KC, et al. Isee: Internet-based simulation for earthquake engineering part i: Database approach. Earthquake Engineering & Structural Dynamics. 2007; 36(15): 2291-2306.
- 31Wang KJ, Tsai KC, Wang SJ, Cheng WC, Yang YS. Isee: Internet-based simulation for earthquake engineering part ii: The application protocol approach. Earthquake Engineering & Structural Dynamics. 2007; 36(15): 2307-2323.
- 32Pan P, Tomofuji H, Wang T, Nakashima M, Ohsaki M, Mosalam KM. Development of peer-to-peer (P2P) internet online hybrid test system. Earthquake Engineering & Structural Dynamics. 2006; 35(7): 867-890.
- 33Kim, S. J., Christenson, R., Phillips, B., and Spencer, B. F. (2012). Geographically distributed real-time hybrid simulation of MR dampers for seismic hazard mitigation, chapter 34, pages 382–393. ASCE.
- 34Ojaghi M, Williams MS, Dietz MS, Blakeborough A, Lamata MI. Real-time distributed hybrid testing: Coupling geographically distributed scientific equipment across the internet to extend seismic testing capabilities. Earthquake Engineering & Structural Dynamics. 2014; 43(7): 1023-1043.
- 35 MathWorks (2015). MATLAB and statistics toolbox release 2015b.
- 36 ISO (1196). ISO/IEC 7498-1: 1994 Information technology—Open systems interconnection—Basic reference model: The basic model. Technical report.
- 37Postel, J. (1981a). Internet protocol. ISI.
- 38Postel, J. (1981b). Transmission control protocol. ISI.
- 39Smith OJ. A controller to overcome dead time. ISA J. 1959; 6(2): 28-33.
- 40Spencer BF, Dyke SJ, Sain MK, Carlson JD. Phenomenological model for magnetorheological dampers. Journal of Engineering Mechanics. 1997; 123(3): 230-238.
- 41Dyke SJ, Spencer BF, Sain MK, Carlson JD. Modeling and control of magnetorheological dampers for seismic response reduction. Smart Materials and Structures. 1996; 5(5): 565.
- 42Juang JN, Pappa RS. An eigensystem realization-algorithm for modal parameter-identification and model-reduction. Journal of Guidance Control and Dynamics. 1985; 8(5): 620-627.
- 43Ozdagli AI. Distributed real-time hybrid simulation: Modeling, development and experimental validation. Dissertation: Purdue University; 2015.
- 44Ho C, Lang ZQ, Sapiński B, Billings SA. Vibration isolation using nonlinear damping implemented by a feedback-controlled MR damper. Smart Materials and Structures. 2013; 22(10):105010.
- 45Ou G, Ozdagli AI, Dyke SJ, Wu B. Robust integrated actuator control: Experimental verification and real-time hybrid-simulation implementation. Earthquake Engng Struct. Dyn. 2015; 44: 441-460. https://doi.org/10.1002/eqe.2479
- 46Christenson, R., Dyke, S.J., Zhang, J., Mosqueda, G., Chen, C., Nakata, N., Laplace, P., Song, W., Chae, Y., Marshall, G., Ou, G., Gonzales, C.A.R., and Song C. (2014). Hybrid simulation: A discussion of current assessment measures. NEES. Report accessible from: https://datacenterhub.org/resources/13816/download/Hybrid_Simulation_Assessment_Measures_Jan2015_revised.pdf
- 47Maghareh A, Dyke SJ, Prakash A, Bunting GB. Establishing a predictive performance indicator for real-time hybrid simulation. Earthquake Engineering & Structural Dynamics. 2014; 43(15): 2299-2318.
- 48Maghareh A, Dyke SJ, Prakash A, Rhoads JF. Establishing a stability switch criterion for effective implementation of real-time hybrid simulation. Smart Struct. Syst. 2014; 14(6): 1221-1245.
- 49Li X, Ozdagli AI, Dyke SJ, Lu X, Christenson R. Development and verification of distributed real-time hybrid simulation methods. Journal of Computing in Civil Engineering. 2017; 31(4):04017014.
- 50Ou G, Dyke SJ, Prakash A. Real time hybrid simulation with online model updating: An analysis of accuracy. Mechanical Systems and Signal Processing. 2017; 84: 223-240.