Matlab code toolkit that compute the values of current assessment measures for hybrid simulation.
This toolkit enables the researcher to readily compute the values of standard assessment measures used to evaluate the fidelity of a hybrid simulation. MATLAB (ver. 2012b) codes are available to compute the values, and two example experimental data sets are included with the toolkit. Sample codes are provided for using the toolkit to compute the values of the assessment measures.
This toolkit is an outcome of the second meeting of the Task Force on Hybrid Simulation, March 27-28 2014 at Purdue University. The related report from that meeting is prohttps://nees.org/resources/12876
Carlos Andreas Riascos is a PhD student at the Universidad del Valle.
Gaby (Ge) Ou is a PhD student at Purdue University.
This toolkit is linked to the report of the workshop attendees:
Hybrid Simulation: A Discussion of Current Assessment Measures
The workshop that triggered the development of this toolkit was funded by the US National Science Foundation (NSF) under Award Number CMMI-0927178. Sample data used within this report is published at nees.org. Mr. Riascos was supported in part by the Universidad del Valle, Cali, Colombia during his visit to Purdue.
1. Ahmadizadeh, M. and Mosqueda, G. (2009) "Online energy-based error indicator for the assessment of numerical and experimental errors in a hybrid simulation." Engineering Structures, 31(9), 1987-1996.
2. Filiatrault A, Leger P, Tinawi R. (1994) “On the computation of seismic energy in inelastic structures”. Engineering Structrure, 16(6):425-436.
3. Gao, X. (2012) "Development of a Robust Framework for Real-Time Hybrid Simulation: From Dynamical System, Motion Control to Experimental Error Verification", Doctoral Dissertation, Purdue University, West Lafayette, IN.
4. Guo, T., Chen, C., Xu, W., and Sanchez F., “A frequency response analysis approach for quantitative assessment of actuator tracking for real-time hybrid simulation”, Smart Materials and Structures, 23(4), 2014, doi:10.1088/0964-1726/23/4/045042Mosqueda, G., Stojadinovic, B., and Mahin, S. A. (2007), “Real-time error monitoring for hybrid simulation. Part I: Methodology and Experimental Verification.” Journal of Structural Engineering, 133(8), 1100-1108.
5. Mosqueda, G., Stojadinovic, B., and Mahin, S. A. (2007), “Real-time error monitoring for hybrid simulation. Part II: Structural response modification due to errors.” Journal of Structural Engineering, 133(8), 1109-1117
6. Mercan, O., and Ricles, J. M. (2007) “Stability and accuracy analysis of outer loop dynamics in real-time pseudodynamic testing of SDOF systems.” Earthquake Engineering ans Structural Dynamics, 36(11), 1523-1543
7. Naru Nakata; Shirley Dyke; Jian Zhang; Gilberto Mosqueda; Xiaoyun Shao; Hussam Mahmoud; Monique Hite Head; Michael Bletzinger; Gemez A. Marshall; Gaby Ou; Cheng Song (2014) "Hybrid Simulation Primer and Dictionary," https://nees.org/resources/7702.
8. Phillips, B. M. and Spencer, B. F. (2011) "Model-Based Feedforward-Feedback Tracking Control for Real-Time Hybrid Simulation", Newmark Structural Engineering Laboratory Report Series, University of Illinois at Urbana-Champaign, Urbana, IL, No. 28.
9. Shirley J. Dyke; Naru Nakata; Khalid Mosalam; Carol Shield; James Ricles; Billie F. Spencer (2013), "Hybrid Simulation Survey Report, July 2013," https://nees.org/resources/7157.
10. Terras, Audrey, (2009) “Fourier analysis on finite groups and applications”, Cambridge University Press, ISBN 978-0-521-45718-7
11. Hybrid Simulation and Real-time Hybrid Simulation Resources in the NEEShub, https://nees.org/topics/RTHSwiki
12. D. Gomez, S.J. Dyke and A. Maghareh. “On the Role of Hybrid and Real-time Hybrid Simulation in Advancing the Practice of Earthquake Engineering,” Proceedings of the 6th World Conference on Structural Control and Monitoring, Barcelona, SPAIN July 2014.
13. Hybrid Simulation Current Assessment Measures (HSCAM) toolkit, https://nees.org/resources/hscam.
Cite this work
Researchers should cite this work as follows: