DOI QR코드

DOI QR Code

Upgraded salp swarm algorithm for optimal design of semi-active MR dampers in buildings

  • Received : 2022.07.11
  • Accepted : 2023.03.13
  • Published : 2023.04.25

Abstract

In the case of designing control devices in a building, reliance on experimental formulation or engineering concepts without using optimization algorithms leads to non-optimal solutions or design parameters, which makes the use of control devices costly and unreasonable. The optimization algorithms are capable of identifying the required number of parameters for a specific design problem, however, this process is difficult and inefficient in dealing with some specific optimal design processes. This paper aims to introduce an upgraded version of the salp swarm algorithm to handle some engineering design. The performance of the new upgraded algorithm is tested using some benchmark test functions as well as a six-story benchmark building equipped with semi-active MR dampers. The simulation results show that the proposed algorithm can be successfully applied to get an optimal design of the MR dampers in the building.

Keywords

Acknowledgement

This research is supported by the research grant of University of Tabriz (No. 2632).

References

  1. Alih, S.C., Vafaei, M., Ismail, N. and Pabarja, A. (2018), "Experimental study on a new damping device for mitigation of structural vibrations under harmonic excitation", Earthq. Struct., 14(6), 567-576. https://doi.org/10.12989/eas.2018.14.6.567.
  2. Amini, F. and Ghaderi, P. (2012), "Optimal locations for MR dampers in civil structures using improved ant colony algorithm", Opt. Control Appl. Meth., 33(2), 232-248. https://doi.org/10.1002/oca.991.
  3. Arfiadi, Y. and Hadi, M. (2011), "Optimum placement and properties of tuned mass dampers using hybrid genetic algorithms", Iran Univ. Sci. Technol., 1(1), 167-187.
  4. Aydin, E. (2012), "Optimal damper placement based on base moment in steel building frames", J. Constr. Steel Res., 79, 216-225. https://doi.org/10.1016/j.jcsr.2012.07.011.
  5. Aydin, E., Boduroglu, M. and Guney, D. (2007), "Optimal damper distribution for seismic rehabilitation of planar building structures", Eng. Struct., 29(2), 176-185. https://doi.org/10.1016/j.engstruct.2006.04.016.
  6. Azar, B.F., Veladi, H., Raeesi, F. and Talatahari, S. (2020), "Control of the nonlinear building using an optimum inverse TSK model of MR damper based on modified grey wolf optimizer", Eng. Struct., 214, 110657. https://doi.org/10.1016/j.engstruct.2020.110657.
  7. Azar, B.F., Veladi, H., Talatahari, S. and Raeesi, F. (2020), "Optimal design of magnetorheological damper based on tuning Bouc-Wen model parameters using hybrid algorithms", KSCE J. Civil Eng., 24, 867-878. https://doi.org/10.1007/s12205-020-0988-z.
  8. Chen, G. and Wu, J. (2001), "Optimal placement of multiple tune mass dampers for seismic structures", J. Struct. Eng., 127(9), 1054-1062. https://doi.org/10.1061/(ASCE)0733-9445(2001)127:9(1054).
  9. Cheng, F.Y. (2008), Smart Structures: Innovative Systems for Seismic Response Control, CRC Press.
  10. Choi, K.M., Cho, S.W., Jung, H.J. and Lee, I.W. (2004), "Semiactive fuzzy control for seismic response reduction using magnetorheological dampers", Earthq. Eng. Struct. Dyn., 33(6), 723-736. https://doi.org/10.1002/eqe.372.
  11. Der Kiureghian, A., Zhang, Y. and Li, C.C. (1994), "Inverse reliability problem", J. Eng. Mech., 120(5), 1154-1159. https://doi.org/10.1061/(ASCE)0733-9399(1994)120:5(1154).
  12. Dorigo, M. and Birattari, M. (2010), "Ant colony optimization. Encyclopedia of machine learning", Ant Colony Optimization: A Component-Wise Overview, Marti, R., Ed, 1-28.
  13. Dyke, S., Spencer Jr, B., Sain, M. and Carlson, J. (1996), "Modeling and control of magnetorheological dampers for seismic response reduction", Smart Mater. Struct., 5(5), 565. https://doi.org/10.1088/0964-1726/5/5/006.
  14. Ghaffarzadeh, H. and Raeisi, F. (2016), "Damage identification in truss structures using finite element model updating and imperialist competitive algorithm", Jordan J. Civil Eng., 10(2), 266.
  15. Hadidi, A., Azar, B.F. and Shirgir, S. (2019), "Reliability assessment of semi-active control of structures with MR damper", Earthq. Struct., 17(2), 131-141. https://doi.org/10.12989/eas.2019.17.2.131.
  16. Jansen, L.M. and Dyke, S.J. (2000), "Semiactive control strategies for MR dampers: Comparative study", J. Eng. Mech., 126(8), 795-803. https://doi.org/10.1061/(ASCE)0733-9399(2000)126:8(795).
  17. Kaveh, A. and Talatahari, S. (2010), "A novel heuristic optimization method: charged system search", Acta Mechanica, 213(3-4), 267-289. https://doi.org/10.1007/s00707-009-0270-4.
  18. Kennedy, J. and Eberhart, R. (1995), "Particle swarm optimization", Proceedings of ICNN'95-International Conference on Neural Networks.
  19. Kwok, N., Ha, Q., Nguyen, M., Li, J. and Samali, B. (2007), "Bouc-Wen model parameter identification for a MR fluid damper using computationally efficient GA", ISA Trans., 46(2), 167-179. https://doi.org/10.1016/j.isatra.2006.08.005.
  20. Metered, H., Bonello, P. and Oyadiji, S. (2010), "The experimental identification of magnetorheological dampers and evaluation of their controllers", Mech. Syst. Signal Pr., 24(4), 976-994. https://doi.org/10.1016/j.ymssp.2009.09.005.
  21. Mirjalili, S., Gandomi, A.H., Mirjalili, S.Z., Saremi, S., Faris, H. and Mirjalili, S.M. (2017), "Salp Swarm Algorithm: A bioinspired optimizer for engineering design problems", Adv. Eng. Softw., 114, 163-191. https://doi.org/10.1016/j.advengsoft.2017.07.002.
  22. Mirjalili, S., Mirjalili, S.M. and Lewis, A. (2014), "Grey wolf optimizer", Adv. Eng. Softw., 69, 46-61. https://doi.org/10.1016/j.advengsoft.2013.12.007.
  23. Mirzai, N.M., Zahrai, S.M. and Bozorgi, F. (2017), "Proposing optimum parameters of TMDs using GSA and PSO algorithms for drift reduction and uniformity", Struct. Eng. Mech., 63(2), 147-160. https://doi.org/10.12989/sem.2017.63.2.147.
  24. Raeesi, F., Azar, B.F., Veladi, H. and Talatahari, S. (2020), "An inverse TSK model of MR damper for vibration control of nonlinear structures using an improved grasshopper optimization algorithm", Struct., 26, 406-416. https://doi.org/10.1016/j.istruc.2020.04.026.
  25. Raeesi, F., Shirgir, S., Azar, B.F., Veladi, H. and Ghaffarzadeh, H. (2020), "Enhanced salp swarm algorithm based on opposition learning and merit function methods for optimum design of MTMD", Earthq. Struct., 18(6), 719-730. https://doi.org/10.12989/eas.2020.18.6.719.
  26. Raeesi, F., Veladi, H., Azar, B.F. and Talatahari, S. (2020), "A hybrid CSS-GW algorithm for finding optimum location of multi semi-active MR dampers in buildings", Int. J. Model., Identif. Control, 35(3), 191-202. https://doi.org/10.1504/IJMIC.2020.114194.
  27. Sapre, S. and Mini, S. (2019), "Opposition-based moth flame optimization with Cauchy mutation and evolutionary boundary constraint handling for global optimization", Soft Comput., 23(15), 6023-6041. https://doi.org/10.1007/s00500-018-3586-y.
  28. Sarkhel, R., Chowdhury, T.M., Das, M., Das, N. and Nasipuri, M. (2017), "A novel harmony search algorithm embedded with metaheuristic opposition based learning", J. Intel. Fuzzy Syst., 32(4), 3189-3199. https://doi.org/10.3233/JIFS-169262.
  29. Shan, X., Liu, K. and Sun, P.L. (2016), "Modified bat algorithm based on levy flight and opposition based learning", Scientif. Program., 2016, Article ID 8031560. https://doi.org/10.1155/2016/8031560.
  30. Spencer Jr, B., Dyke, S., Sain, M. and Carlson, J. (1997), "Phenomenological model for magnetorheological dampers", J. Eng. Mech., 123(3), 230-238. https://doi.org/10.1061/(ASCE)0733-9399(1997)123:3(230).
  31. Takewaki, I. (1997), "Optimal damper placement for minimum transfer functions", Earthq. Eng. Struct. Dyn., 26(11), 1113-1124. https://doi.org/10.1002/(SICI)1096- 9845(199711)26:11<1113::AID-EQE696>3.0.CO;2-X.
  32. Talatahari, S., Kaveh, A. and Rahbari, N.M. (2012), "Parameter identification of Bouc-Wen model for MR fluid dampers using adaptive charged system search optimization", J. Mech. Sci. Technol., 26(8), 2523.
  33. Talatahari, S. and Rahbari, N.M. (2015), "Enriched Imperialist Competitive Algorithm for system identification of magnetorheological dampers", Mech. Syst. Signal Pr., 62, 506-516. https://doi.org/10.1016/j.ymssp.2015.03.020.
  34. Talatahari, S., Rahbari, N.M. and Kaveh, A. (2013), "A new hybrid optimization algorithm for recognition of hysteretic nonlinear systems", KSCE J. Civil Eng., 17, 1099-1108. https://doi.org/10.1007/s12205-013-0341-x.
  35. Tizhoosh, H.R. (2005), "Opposition-based learning: A new scheme for machine intelligence", International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCAIAWTIC'06).
  36. Vadtala, I.H., Soni, D.P. and Panchal, D.G. (2013), "Semi-active control of a benchmark building using neuro-inverse dynamics of MR damper", Procedia Eng., 51, 45-54. https://doi.org/10.1016/j.proeng.2013.01.010.
  37. Xu, Z.D. and Guo, Y.Q. (2006), "Fuzzy control method for earthquake mitigation structures with magnetorheological dampers", J. Intel. Mater. Syst. Struct., 17(10), 871-881. https://doi.org/10.1177/1045389X0606104.
  38. Xu, Z.D. and Shen, Y.P. (2003), "Intelligent bi-state control for the structure with magnetorheological dampers", J. Intel. Mater. Syst. Struct., 14(1), 35-42. https://doi.org/10.1177/1045389X0301400.
  39. Xu, Z.D., Shen, Y.P. and Guo, Y.Q. (2003), "Semi-active control of structures incorporated with magnetorheological dampers using neural networks", Smart Mater. Struct., 12(1), 80. https://doi.org/10.1088/0964-1726/12/1/309.
  40. Yang, Y., Xu, Z.D., Xu, Y.W. and Guo, Y.Q. (2020), "Analysis on influence of the magnetorheological fluid microstructure on the mechanical properties of magnetorheological dampers", Smart Mater. Struct., 29(11), 115025. https://doi.org/10.1088/1361-665X/abadd2.
  41. Yang, Y., Xu, Z.D., Guo, Y.Q., Sun, C.L. and Zhang, J. (2021), "Performance tests and microstructure-based sigmoid model for a three-coil magnetorheological damper", Struct. Control Hlth. Monit., 28(11), e2819. https://doi.org/10.1002/stc.2819.
  42. Zemp, R., de la Llera, J.C. and Almazan, J.L. (2011), "Tall building vibration control using a TM-MR damper assembly", Earthq. Eng. Struct. Dyn., 40(3), 339-354. https://doi.org/10.1002/eqe.1033.
  43. Zhou, Y., Hao, J.K. and Duval, B. (2017), "Opposition-based memetic search for the maximum diversity problem", IEEE Trans. Evol. Comput., 21(5), 731-745. https://doi.org/10.1109/TEVC.2017.2674800.