Encyclopedia of Earthquake Engineering

2015 Edition
| Editors: Michael Beer, Ioannis A. Kougioumtzoglou, Edoardo Patelli, Siu-Kui Au

Seismic Response Prediction of Degrading Structures

  • Ching Hang Ng
  • Nopdanai Ajavakom
  • Fai MaEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-3-642-35344-4_276


Degrading structures; Hysteresis; Nonlinear response; System identification


All structures degrade when acted upon by cyclic forces such as those associated with earthquakes, high winds, and sea waves. Development of a practical model of degrading structures that would match experimental observations is an important task. Furthermore, identification and prediction of deterioration is a problem of considerable practical significance. Under cyclic excitation, degradation manifests itself in the evolution of the associated hysteresis loops. Theoretical research in internal friction in the last few decades has noticeably increased the conceptual understanding of hysteresis (Kojic and Bathe 2005; Krasnoselskii and Pokrovskii 1989). Practical issues related to internal friction, however, have not been adequately addressed. The lack of a practical theory of hysteretic evolution is at present a major barrier to successful design of structures against performance...

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  1. Baber TT, Noori MN (1986) Modeling general hysteresis behavior and random vibration application. ASME J Vib Acoust Stress Reliab Des 108:411–420CrossRefGoogle Scholar
  2. Baber TT, Wen YK (1981) Random vibration of hysteretic degrading systems. ASCE J Eng Mech 107(6):1069–1087Google Scholar
  3. Bertsekas DP (1999) Nonlinear programming, 2nd edn. Athena Scientific, BelmontzbMATHGoogle Scholar
  4. Bouc R (1967) Forced vibration of mechanical systems with hysteresis. In: Proceedings of 4th conference on nonlinear oscillations, Prague, Czechoslovakia, p 315Google Scholar
  5. Foliente GC (1995) Hysteretic modeling of wood joints and structural systems. ASCE J Struct Eng 121:1013–1022CrossRefGoogle Scholar
  6. Furukawa T, Yagawa G (1997) Inelastic constitutive parameter identification using an evolutionary algorithm with continuous individuals. Int J Numer Methods Eng 40:1071–1090zbMATHCrossRefGoogle Scholar
  7. Goldberg DE (1989) Genetic algorithms in search, optimization & machine learning. Addison-Wesley, ReadingzbMATHGoogle Scholar
  8. Iman RL, Helton JC (1991) The repeatability of uncertainty and sensitivity analyses for complex probabilistic risk assessments. Risk Anal 11:591–606CrossRefGoogle Scholar
  9. Kojic M, Bathe KJ (2005) Inelastic analysis of solids and structures. Springer, BerlinGoogle Scholar
  10. Krasnoselskii MA, Pokrovskii AV (1989) Systems with hysteresis. Springer, BerlinCrossRefGoogle Scholar
  11. Krawinkler H, Parisi F, Ibarra L, Ayoub A, Medina R (2001) Development of a testing protocol for woodframe structures. CUREE-Caltech woodframe project report W-02, Consortium of Universities for Research in Earthquake Engineering, RichmondGoogle Scholar
  12. Kyprianou A, Worden K, Panet M (2001) Identification of hysteretic systems using the differential evolution algorithm. J Sound Vib 248:289–314CrossRefGoogle Scholar
  13. Lampinen J, Storn R (2004) Differential evolution. In: Onwubolu GC, Babu BV (eds) New optimization techniques in engineering. Springer, Berlin, pp 125–166Google Scholar
  14. Ma F, Zhang H, Bockstedte A, Foliente GC, Paevere P (2004) Parameter analysis of the differential model of hysteresis. ASME J App Mech 71:342–349zbMATHCrossRefGoogle Scholar
  15. Ma F, Ng CH, Ajavakom N (2006) On system identification and response prediction of degrading structures. Struct Control Health Monit 13(1):347–364CrossRefGoogle Scholar
  16. Ni YQ, Ko JM, Wong CW (1998) Identification of nonlinear hysteretic isolators from periodic vibration tests. J Sound Vib 217:737–756CrossRefGoogle Scholar
  17. Papoulis A, Pillai SU (2002) Probability, random variables, and stochastic processes, 4th edn. McGraw-Hill, New YorkGoogle Scholar
  18. Price K, Storn R (1997) Differential evolution. Dr Dobb’s J 22:18–24zbMATHGoogle Scholar
  19. Roberts JB, Spanos PD (1990) Random vibration and statistical linearization. Wiley, New YorkzbMATHGoogle Scholar
  20. Schwefel HP (1995) Evolution and optimum seeking. Wiley, New YorkzbMATHGoogle Scholar
  21. Sobol IM (1993) Sensitivity estimates for nonlinear mathematical models. Math Model Comput Exp 1:407–414MathSciNetzbMATHGoogle Scholar
  22. Song J, Der Kiureghian A (2006) Generalized Bouc-Wen model for highly asymmetric hysteresis. ASCE J Eng Mech 132(6):610–618CrossRefGoogle Scholar
  23. Sues RH, Mau ST, Wen YK (1988) System identification of degrading hysteretic restoring forces. ASCE J Eng Mech 114:833–846CrossRefGoogle Scholar
  24. Wen YK (1976) Method for random vibration of hysteretic systems. ASCE J Eng Mech 102(2):249–263Google Scholar
  25. Zhang H, Foliente GC, Yang Y, Ma F (2002) Parameter identification of inelastic structures under dynamic loads. Earthq Eng Struct Dyn 31(5):1113–1130CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.US Nuclear Regulatory Commission, Office of Nuclear Reactor RegulationWashingtonUSA
  2. 2.Department of Mechanical EngineeringChulalongkorn UniversityBangkokThailand
  3. 3.Department of Mechanical EngineeringUniversity of California, BerkeleyBerkeleyUSA