Magneto-Rheological Damper In Structures for Seismic Mitigation Adam Davies, Chris Amaro, Jesus Caballero, Priscila Silva, Juvi Marin Dr. Cheng Chen Jun Jian Liang 1
Overview Background/ Motivation Brief overview of MR Dampers / Computational Models Data Analysis Metropolis-Hastings Algorithm Summary 2
Background San Francisco, California Carrizo Plain, California 3 4
Smart Material Changes its viscosity when subjected to a magnetic field Sidpara, Ajay. Magnetorheological Finishing: a Perfect Solution to Nanofinishing Requirements.
5 Magneto-Rheological (MR) Damper Truong, D. Q., and K. K. Ahn. MR Fluid Damper and Its Application to Force Sensorless Damping Control System. 6
Computational Damper Models Hyperbolic Tangent Model Bouc-Wen Model Viscous-Dahl Model Maxwell Non-Linear Slider Model
Jiang, Zhaoshuo, et al. Application of MR Damper in Real-Time Structural Damage Detection Using Extended Kalman Filter. ResearchGate 7 Hyperbolic Tangent Model vs Viscous-Dahl Model Hyperbolic Tangent Model Force equation:
Viscous-Dahl Model Force equation: Jiang, Zhaoshuo, et al. Application of MR Damper in Real-Time Structural Damage Detection Using Extended Kalman Filter. ResearchGate Liang, Jun Jian. "Comparison of Models for Large-Scale Magneto-Rheological Damper to Account for Uncertainty in Seismic Hazard Mitigation." 8
Hyperbolic Tangent Model vs Viscous-Dahl Hyperbolic Tangent Model Parameters Model Viscous-Dahl Model Parameters Liang, Jun Jian. "Comparison of Models for Large-Scale Magneto-Rheological Damper to Account for Uncertainty in
Seismic Hazard Mitigation." 9 Software Used MATLAB Simulink UQ Lab (Uncertainty
Quantification) 10 Simulink Simulation Engine Easy to create damper models from differential equations Easy access to
simulations in our research 11 Viscous-Dahl Model in Simulink 12
Bouc-Wen Damper Behavior Force increases with increasing current
Area in closed curve shows dissipated energy 13 Bouc-Wen
Force increases with velocity and reaches point of saturation I 14 Graphic User Interface (GUI)
Interact using graphical components Alternative to text based commands Efficient and easy to use
15 GUI interface 16 UQ Lab Uncertainty Quantification
MatLab Based Sensitivity Analysis Tool Uncertainty Quantification. Uncertainty Quantification | SmartUQ, www.smartuq.com/resources/uncertainty-quantification/. 17
Data Analysis Parameters correspond to respective model equations Variable with the highest value = most sensitive Each bar corresponds to variable sensitivity Charts to be modified are evenly distributed
18 Data: VD, NPA Identified Parameters for Viscous Plus Dahl Model Identified Parameters for Non-Parametric Algebraic
Model 19 Bouc-Wen Data Identified Parameters for Bouc-Wen Model 20
Hyperbolic Tangent Data Identified Parameters for Hyperbolic Tangent Model 21 Metropolis-Hastings Algorithm 22
Non-Parametric Algebraic MHA Results 23 Viscous-Dahl MHA Results 24 Conclusion
Probabilistic more precise than deterministics for our trials Recommendation of analyzing parameters of other computational models Future work including Single-degree of Freedom 25 Summary Magneto-Rheological dampers
Computational Models Analysis of Data Gathered Conclusions Future Work 26 27 References
1. Jiang, Z., and R. Christenson. "A Comparison of 200 KN Magneto-rheological Damper Models for Use in Real-time Hybrid Simulation Pretesting." Smart Materials and Structures 20.6 (2011): 065011. Web. 2. Chae, Yunbyeong, James M. Ricles, and Richard Sause. "Modeling of a Large-scale Magneto-rheological Damper for Seismic Hazard Mitigation. Part I: Passive Mode." Earthquake Engineering & Structural Dynamics 42.5 (2012): 669-85. Web.
3. Caicedo, Juan M., Zhaoshuo Jiang, and Sarah C. Baxter. "Including Uncertainty in Modeling the Dynamic Response of a Large-Scale 200 KN MagnetoRheological Damper." ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 3.2 (2017): n. pag. Web. 4. D.Q. Troung and AhnK.K. MR Fluid Damper and Its Application to Force Sensorless Damping Control System. Intech (2012): DOI: 10.5772/51391. Web 5. Liang, Jun Jian. "Comparison of Models for Large-Scale Magneto-Rheological Damper to Account for Uncertainty in Seismic Hazard Mitigation." Comparison of Models for Large-Scale Magneto-Rheological Damper to Account for Uncertainty in Seismic Hazard Mitigation (2018): 1-14. Web. 6. USGS: California Has 99.7 Percent Chance of Big Earthquake in Next 30 Years. Fox News, FOX News Network, 15 Apr. 2008,
www.foxnews.com/story/2008/04/15/usgs-california-has-7-percent-chance-big-earthquake-in-next-30-years.html. 7. Truong, D. Q., and K. K. Ahn. MR Fluid Damper and Its Application to Force Sensorless Damping Control System. MR Fluid Damper and Its Application to Force Sensorless Damping Control System | InTechOpen, InTech, 17 Oct. 2012, www.intechopen.com/books/smart-actuation-and-sensing-systems-recent-advances-and-future-challenges/mr-fluid-damper-and-its-application-to-force-sensorlessdamping-control-system . 8. Sidpara, Ajay. Magnetorheological Finishing: a Perfect Solution to Nanofinishing Requirements. Optical Engineering, International Society for Optics and Photonics, 1 Sept. 2014, opticalengineering.spiedigitallibrary.org/article.aspx?articleid=1857354. 9. Jiang, Zhaoshuo, et al. Application of MR Damper in Real-Time Structural Damage Detection Using Extended Kalman Filter. ResearchGate, 10 Aug. 2015, 10. www.researchgate.net/figure/281792403_fig2_Figure-31-Schematic-of-the-MR-damper-hyperbolic-tangent-model.
Uncertainty Quantification. Uncertainty Quantification | SmartUQ, www.smartuq.com/resources/uncertainty-quantification/. 28 Questions ? 29
