Earthquakes and Structures

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Seismic induced damageability evaluation of steel buildings: a Fuzzy-TOPSIS method

  • Shahriar, Anjuman (Okanagan School of Engineering, The University of British Columbia) ;
  • Modirzadeh, Mehdi (Okanagan School of Engineering, The University of British Columbia) ;
  • Sadiq, Rehan (Okanagan School of Engineering, The University of British Columbia) ;
  • Tesfamariam, Solomon (Okanagan School of Engineering, The University of British Columbia)
  • Received : 2011.05.09
  • Accepted : 2012.01.21
  • Published : 2012.09.25
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Abstract

Seismic resiliency of new buildings has improved over the years due to better seismic codes and design practices. However, there is still large number of vulnerable and seismically deficient buildings. It is not economically feasible to retrofit and upgrade all vulnerable buildings, thus there is a need for rapid screening tool. Many factors contribute to the damageability of buildings; this makes seismic evaluation a complex multi-criteria decision making problem. Many of these factors are noncommensurable and involve subjectivity in evaluation that highlights the use of fuzzy-based method. In this paper, a risk-based framework earlier proposed by Tesfamariam and Saatcioglu (2008a) is extended using Fuzzy-TOPSIS method and applied to develop an evaluation and ranking scheme for steel buildings. The ranking is based on damageability that can help decision makers interpret the results and take appropriate decision actions. Finally, the application of conceptual model is demonstrated through a case study of 1994 Northridge earthquake data on seismic damage of steel buildings.

Keywords

References

  1. ASCE. (1998), Handbook for seismic evaluation of buildings - A prestandard, Prepared by the American Society of Civil Engineers, published by the Federal Emergency Management Agency, (FEMA 310 report), Washington, D.C.
  2. ATC. (2001), Database on the performance of structures near strong-motion recordings: 1994 Northridge, California, Earthquake, Applied Technology Council, ATC-38 Report, Redwood City, California.
  3. ATC. (2002), Rapid visual screening of buildings for potential seismic hazard: A handbook (Second edition), prepared by the Applied Technology Council, published by the Federal Emergency Management Agency, (FEMA 154 report), Washington, D.C.
  4. ATC. (1985), Earthquake damage evaluation data for California, Applied Technology Council, ATC-13 Report, Redwood City, California.
  5. Boissonnade, A.C. and Shah, H.C. (1985), Use of patter recognition and fuzzy sets in seismic risk analysis, Report 67, Stanford, California: John A. Blume Earthquake Engineering Center.
  6. Carlsson, C. and Fullr, R. (1996), "Fuzzy multiple criteria decision making: recent developments", Fuzzy Set. Syst, 78(2), 139-153. https://doi.org/10.1016/0165-0114(95)00165-4
  7. Chang, H.Y., Lin, C.C. J., Lin, K.C. and Chen, J.Y. (2009), "Role of accidental torsion in seismic reliability assessment for steel buildings", Steel Compos. Struct., 9(5), 457-472. https://doi.org/10.12989/scs.2009.9.5.457
  8. Chen, S.H. (1985), "Ranking fuzzy numbers with maximizing set and minimizing set", Fuzzy Set. Syst, 17(2), 113-129. https://doi.org/10.1016/0165-0114(85)90050-8
  9. Chen, S.J. and Hwang, C.L. (1992), Fuzzy multiple attribute decision making methods and applications, Springer-Verlag, Berlin.
  10. Chen, S.M. and Lee, L.W. (2010), "Fuzzy multiple attributes group decision-making based on the interval Type- 2 TOPSIS method", Expert Syst. Appl., 37(4), 2790-2798. https://doi.org/10.1016/j.eswa.2009.09.012
  11. Chen, T.C. (2000), "Extensions of the TOPSIS for group decision making under fuzzy environment", Fuzzy Set. Syst., 114(1), 1-9. https://doi.org/10.1016/S0165-0114(97)00377-1
  12. Chu, T.C. (2002), "Facility location selection using fuzzy TOPSIS under group decisions", Int. J. Uncertain. Fuzz., 10(6), 687-701. https://doi.org/10.1142/S0218488502001739
  13. Chu, T.C. and Lin, Y.C. (2003), "A fuzzy TOPSIS method for robot selection", Int. J. Adv. Manuf. Tech., 21(4), 284-290. https://doi.org/10.1007/s001700300033
  14. Cornell, C.A., Jalayer, F., Hamburger, R.O. and Foutch, D.A. (2002), "Probabilistic basis for 2000 SAC Federal Emergency Management Agency steel moment frame guidelines", J. Struct. Eng.-ASCE, 128(4), 526-533. https://doi.org/10.1061/(ASCE)0733-9445(2002)128:4(526)
  15. Daodeviren, M., Yavuz, S., Kln, N., Ertuðrul, I. and Karakaþoolu, N. (2008), "Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection", Int. J. Adv. Manuf. Tech., 39(7-8), 783-795. https://doi.org/10.1007/s00170-007-1249-8
  16. FEMA-273. (1997), NEHRP Guidelines for the seismic rehabilitation of buildings.
  17. Fragiacomo, M., Amadio, C. and Macorini, L. (2004), "Seismic response of steel frames under repeated earthquake ground motions", Eng. Struct., 26(13), 2021-2035. https://doi.org/10.1016/j.engstruct.2004.08.005
  18. Hadipriono, F.C. and Ross, T.J. (1991), "A rule-based fuzzy logic deduction technique for damage assessment of protective structures", Fuzzy Set. Syst., 44(3), 459-468. https://doi.org/10.1016/0165-0114(91)90250-T
  19. Hwang, C.L. and Yoon, K. (1981), Multiple attribute decision making: Methods and applications: A state of the art survey, New York: Springer-Verlag.
  20. Hwang, C.L. and Yoon, K. (1981), Multiple attribute decision making: Methods and applications: A state of the art survey, New York: Springer-Verlag.
  21. Kenarangui, R. (1991), "Event-tree analysis by fuzzy probability", IEEE T. Reliab., 40(1), 120-124. https://doi.org/10.1109/24.75348
  22. Klir, G.J. and Yuan, B. (1995), Fuzzy sets and fuzzy logic: Theory and applications, Upper Saddle River, NJ: Prentice Hall International.
  23. Lee, E.S. and Li, R.L. (1988), "Comparison of fuzzy numbers based on the probability measure of fuzzy events", Comput. Math. Appl., 15(10), 887-896. https://doi.org/10.1016/0898-1221(88)90124-1
  24. Lee, L.W. and Chen, S.M. (2008), "Fuzzy multiple attributes group decision-making based on the extension of TOPSIS method and interval Type-2 fuzzy sets", Proceedings of the 2008 International Conference on Machine Learning and Cybernetic, China, 3260-3265.
  25. Liang, G.S. (1999), "Fuzzy MCDM based on ideal and anti-ideal concepts", Eur J. Oper Res, 112(3), 682-691. https://doi.org/10.1016/S0377-2217(97)00410-4
  26. Liou, T.S. and Wang, M.J.J. (1992), "Ranking fuzzy numbers with integral value", Fuzzy Set. Syst., 50(3) 247- 255. https://doi.org/10.1016/0165-0114(92)90223-Q
  27. Mahin, S.A. (1998), "Lessons from damage to steel buildings during the Northridge earthquake", Eng. Struct., 20(4-6), 261-270. https://doi.org/10.1016/S0141-0296(97)00032-1
  28. Malekly, H., Mousavi, S.M. and Hashemi, H. (2010), "A Fuzzy integrated methodology for evaluating conceptual bridge design", Expert. Syst. Appl., 37(7), 4910-4920. https://doi.org/10.1016/j.eswa.2009.12.024
  29. NIBS. (1999), Earthquake loss estimation methodology technical manual, HAZUS99 Service Release 2 (SR2), Developed by the National Institute of Building Sciences for the Federal Emergency Management Agency Washington, D.C.
  30. NRC. (1992), Manual for screening of buildings for seismic investigation, Institute for Research in Construction, National Research Council of Canada, Ottawa, Ontario.
  31. NRC. (1993), Guidelines for seismic evaluation of existing buildings, Institute for Research in Construction, National Research Council of Canada, Ottawa, Ontario.
  32. NZSEE. (2006), Assessment and improvement of the structural performance of buildings in earthquake, New Zealand Society for Earthquake Engineering, Auckland, New Zealand.
  33. Reyes-Salazar, A., Soto-Lopeza, M.E., Bojorquez-Mora, E. and Lopez-Barraza, A. (2012), "Effect of modeling assumptions on the seismic behavior of steel buildings with perimeter moment frames", Struct. Eng. Mech., 41(2), 183-204. https://doi.org/10.12989/sem.2012.41.2.183
  34. Ribeiro, R.A. (1996), "Fuzzy multiple attribute decision making: a review and new preference elicitation techniques", Fuzzy Set. Syst., 78(2), 155-181. https://doi.org/10.1016/0165-0114(95)00166-2
  35. Rivera, S.S. and Barn, J.H. (1999), "Using fuzzy arithmetic in containment event trees", International Conference on Probabilistic Safety Assessment- PSA 99, Washington, USA, 22-25.
  36. Ross, T.J. (2005), Fuzzy logic with engineering applications, John Wiley & Sons, Singapore.
  37. Saaty, T.L. (1980), The analytic hierarchy process, McGraw-Hill, New York.
  38. Salehi, M. and Tavakkoli-Moghaddam, R. (2008), "Project selection by using a fuzzy TOPSIS technique", Proceedings of World Academy of Science, Engineering and Technology, 40, 85-90.
  39. Tesfamariam, S. and Saatcioglu, M. (2008a), "Risk-based seismic evaluation of reinforced concrete buildings", Earthq. Spectra., 24(3), 795-821. https://doi.org/10.1193/1.2952767
  40. Tesfamariam, S. and Saatcioglu, M. (2008b), "Seismic risk assessment of RC buildings using fuzzy synthetic evaluation", J. Earthq. Eng., 12(7), 1157-1184. https://doi.org/10.1080/13632460802003785
  41. Tesfamariam, S. and Saatcioglu, M. (2010), "Seismic vulnerability assessment of reinforced concrete buildings using hierarchical fuzzy rule base modeling", Earthq. Spectra, 26(1), 235-256. https://doi.org/10.1193/1.3280115
  42. Tesfamariam, S. and Liu, Z. (2010), "Earthquake induced damage classification for reinforced concrete buildings", Struct. Saf., 32(2), 154-164. https://doi.org/10.1016/j.strusafe.2009.10.002
  43. Triantaphyllou, E. and Lin, C.T. (1996), "Development and evaluation of five fuzzy multi-Attribute decisionmaking methods", Int. J. Approx. Reason., 14(4), 281-310. https://doi.org/10.1016/0888-613X(95)00119-2
  44. Tsaur, S.H., Chang, T.Y. and Yen, C.H. (2002), "The evaluation of airline service quality by fuzzy MCDM", Tourism. Manage., 23(2), 107-115. https://doi.org/10.1016/S0261-5177(01)00050-4
  45. Wang, J.W., Cheng, C.H. and Cheng, H.K. (2009), "Fuzzy hierarchical TOPSIS for supplier selection", Appl. Soft. Comput., 9(1), 377-386. https://doi.org/10.1016/j.asoc.2008.04.014
  46. Wang, Y.M. and Elhag, T. (2006), "Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment", Expert. Syst. Appl., 31(2), 309-319. https://doi.org/10.1016/j.eswa.2005.09.040
  47. Yang, T. and Hung, C.C. (2007), "Multiple attribute decision making methods for plant layout design prediction problem", Robot. Cim.-Int. Manuf., 23(1), 126-137. https://doi.org/10.1016/j.rcim.2005.12.002
  48. Zadeh, L.A. (1965), "Fuzzy sets", Infor Cont, 8, 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X
  49. Zhang, G. and Lu, J. (2003), "An integrated group decision-making method dealing with fuzzy preferences for alternatives and individual judgments for selection criteria", Group. Decis. Negot., 12(6), 501-515. https://doi.org/10.1023/B:GRUP.0000004197.04668.cf
  50. Zhao, R. and Govind, R. (1991), "Algebraic characteristics of extended fuzzy numbers", Inform. Sciences, 54(1991), 103-130. https://doi.org/10.1016/0020-0255(91)90047-X
  51. Zwick, R., Carlstein, E. and Budescu, D.V. (1987), "Measures of similarity among fuzzy concepts: A comparative analysis", Int. J. Approx Reason., 1(2), 221-242. https://doi.org/10.1016/0888-613X(87)90015-6

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