Advertisement

Structural and Multidisciplinary Optimization

, Volume 56, Issue 6, pp 1353–1368 | Cite as

Optimal seismic design of 3D steel moment frames: different ductility types

  • A. KavehEmail author
  • M. H. Ghafari
  • Y. Gholipour
RESEARCH PAPER

Abstract

Three different types of lateral resisting steel moment frames consisting of ordinary moment frame (OMF), intermediate moment frame (IMF) and special moment frame (SMF) are available for design of 3D frames in literature. In this paper, optimum seismic design of 3D steel moment frames with different types of lateral resisting systems are performed according to the AISC-LRFD design criteria. A comparison is made considering the results of the above mentioned frames of different ductility types. These frames are analyzed by Response Spectrum Analysis (RSA), and optimizations are performed using nine different well-established metaheuristic algorithms. Performances of these algorithms are then compared for introducing the most suitable metaheuristic algorithms for optimal design of the 3D frames.

Keywords

OMF, IMF, and SMF steel frame structures Structural optimization Structural seismic design AISC-LRFD design criteria Comparative study of metaheuristic algorithms 

References

  1. AISC (2002) Seismic provisions for structural steel buildings. American Institute of Steel Construction. Chicago, Illinois, USAGoogle Scholar
  2. AISC (2005) AISC 360–05-specification for structural steel buildings. American Institute of Steel Construction. Chicago, Illinois, USAGoogle Scholar
  3. Al Zaidee SR, Mahdi AS (2016) Meta model for optimum design objective function of steel frames subjected to seismic loads. Int J Civil, Environm Struct Construct Architect Eng 10(12):1542–1551Google Scholar
  4. ASCE (2010) Minimum Design Loads for Buildings and Other Structures. Chicago, Illinois, USAGoogle Scholar
  5. Aydoğdu İ, Akın A, Saka M (2016) Design optimization of real world steel space frames using artificial bee colony algorithm with Levy flight distribution. Adv Eng Softw 92:1–14Google Scholar
  6. Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science. Nagoya, JapanGoogle Scholar
  7. Geem ZW, Kim JH, Loganathan G (2001) A new heuristic optimization algorithm: harmony search. Simul 76(2):60–68CrossRefGoogle Scholar
  8. Hasançebi O, Çarbaş S, Doğan E, Erdal F, Saka MP (2010a) Comparison of non-deterministic search techniques in the optimum design of real size steel frames. Comput Struct 88(17):1033–1048CrossRefGoogle Scholar
  9. Hasançebi O, Çarbaş S, Saka MP (2010b) Improving the performance of simulated annealing in structural optimization. Struct Multidiscip Optim 41(2):189–203CrossRefGoogle Scholar
  10. Karaboga D (2005) An idea based on honey bee swarm for numerical optimization, Technical report-tr06, Erciyes University, Engineering Faculty, Computer Engineering Department. Kayseri, TürkiyeGoogle Scholar
  11. Kaveh A, BolandGerami A (2016) Optimal design of large-scale space steel frames using cascade enhanced colliding body optimization. Struct Multidiscip Optim. doi: 10.1007/s00158-016-1494-2
  12. Kaveh A, Ilchi Ghazaan M (2014) Enhanced colliding bodies optimization for design problems with continuous and discrete variables. Adv Eng Softw 77:66–75CrossRefGoogle Scholar
  13. Kaveh A, Mahdavi VR (2014) Colliding bodies optimization: a novel metaheuristic method. Comput Struct 139:18–27CrossRefGoogle Scholar
  14. Kaveh A, Bakhshpoori T, Azimi M (2015) Seismic optimal design of 3D steel frames using cuckoo search algorithm. Struct Des Tall Special Build 24(3):210–227CrossRefGoogle Scholar
  15. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simmulated annealing. Science 220(4598):671–680CrossRefzbMATHMathSciNetGoogle Scholar
  16. Kripakaran P, Hall B, Gupta A (2011) A genetic algorithm for design of moment-resisting steel frames. Struct Multidiscip Optim 44(4):559–574CrossRefGoogle Scholar
  17. Mehrabian AR, Lucas C (2006) A novel numerical optimization algorithm inspired from weed colonization. Ecolog Inform 1(4):355–366CrossRefGoogle Scholar
  18. Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51–67CrossRefGoogle Scholar
  19. Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61CrossRefGoogle Scholar
  20. Mortazavi A, Toğan V (2016) Simultaneous size, shape, and topology optimization of truss structures using integrated particle swarm optimizer. Struct Multidiscip Optim 54(4):715–736CrossRefMathSciNetGoogle Scholar
  21. Murren P, Khandelwal K (2014) Design-driven harmony search (DDHS) in steel frame optimization. Eng Struct 59:798–808Google Scholar
  22. Saka MP, Geem ZW (2013) Mathematical and metaheuristic applications in design optimization of steel frame structures: an extensive review. Math Prob Eng 2013: Article ID 271031, 33 pGoogle Scholar
  23. SivaPrasad G, Adiseshu S (2013) A comparative study of OMRF and SMRF structural system for tall and high rise buildings subjected to seismic load. Int J Res Eng Techol 2(9):239–250CrossRefGoogle Scholar
  24. Varghese DV, Borkar YR (2013) Comparative study of SMRF building over OMRF building with seismic and wind effect. Int J Eng Res Applic 3(3):1501–1503Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Centre of Excellence for Fundamental Studies in Structural EngineeringIran University of Science and TechnologyTehranIran
  2. 2.Engineering Optimization Research GroupUniversity of TehranTehranIran

Personalised recommendations