A novel evolutionary algorithm for identifying multiple alternative solutions in model updating

Structural Health Monitoring

Volumn 10, Issue 5, 2011, Pages 491-501

  Caicedo, Juan M ^a   Yun, Gun Jin ^b  

^a The Department of Mechanical Engineering   (United States)

^b University of Akron   (United States)

Author keywords

genetic algorithms; model updating; modeling to generate alternatives

Indexed keywords

AMERICAN SOCIETY OF CIVIL ENGINEERING; BENCHMARK STRUCTURE; EXISTING STRUCTURE; EXPERIMENTAL DATA; GLOBAL MINIMA; LOCAL MINIMUMS; MATHEMATICAL FUNCTIONS; MODEL UPDATING; MODEL UPDATING TECHNIQUES; MODELING ERRORS; MODELING TO GENERATE ALTERNATIVES; NUMERICAL EXAMPLE; NUMERICAL MODELS; OBJECTIVE FUNCTIONS; PLAUSIBLE MODEL; STEADY-STATE GENETIC ALGORITHMS; STRUCTURAL SYSTEMS; SYSTEM FEATURES; UPDATED MODEL;

BRIDGE DECKS; CIVIL ENGINEERING; ERRORS; FUNCTIONS; GENETIC ALGORITHMS; MATHEMATICAL OPERATORS; STRUCTURAL HEALTH MONITORING;

MATHEMATICAL MODELS;

EID: 80052046402     PISSN: 14759217     EISSN: 17413168     Source Type: Journal    
DOI: 10.1177/1475921710381775     Document Type: Article

References (39)

1. Mottershead JE and Friswell MI Model updating in structural dynamics - a survey. J Sound Vibration 1993; 167(2): 347-375.
2. Sohn H., Farrar C., Hemez F., Shunk D., Stinemates D. and Nadler B. A review of structural health monitoring literature: 1996-2001, Rep. No. LA-13976-MS, Los Alamos National Laboratory, Los Alamos, NM, 2003.
3. Doebling SW, Farrar C., Prime MB and Shevitz DW Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review. Los Alamos, New Mexico: Los Alamos National Laboratory, 1996, p. 127.
4. Ching J. and Beck JL Two-step Bayesian structural health monitoring approach for IASC-ASCE phase II simulated and experimental benchmark studies. California, Pasadena, CA: Institute of Technology, 2003, p. 113.
5. Katafygiotis LS and Beck JL Updating models and their uncertainties. II: model identifiability. J Eng Mech 1998; 124(4): 463-467.
6. Katafygiotis LS and Yuen K.-V. Bayesian spectral density approach for modal updating using ambient data. Earthquake Eng Struct Dyn 2001; 30: 1103-1123.
7. Beck JL and Katafygiotis LS Updating models and their uncertainties. I: Bayesian statistical framework. J Eng Mech 1998; 124(4): 455-461.
8. Caicedo JM and Dyke SJ Experimental validation of structural health monitoring for flexible bridge structures. J Struct Contr Monit 2005; 12: 425-443.
9. Caicedo JM, Dyke SJ and Johnson EA Natural excitation technique and eigensystem realization algorithm for phase I of the IASC-ASCE benchmark problem: simulated data. J Eng Mech 2004; 130(1): 49-60.
10. Xia P-Q. and Brownjohn JMW. Bridge structural condition assessment using systematically validated finite-element model. J Bridge Eng 2004; 9(5): 418-423.
11. Jaishi B. and Ren WX Finite element model updating based on eigenvalue and strain energy residuals using multiobjective optimisation technique. Mechl Syst Signal Process 2007; 21(5): 2295-2317.
12. Lu Y. and Tu Z. Dynamic model updating using a combined genetic-eigensensitivity algorithm and application in seismic response prediction. Earthquake Eng Struct Dyn 2005; 34(9): 1149-1170.
13. Haralampidis Y., Papadimitriou C. and Pavlidou M. Multi-objective framework for structural model identification. Earthquake Eng Structl Dyn 2005; 34(6): 665-685.
14. D'Ambrogio W. and Fregolent A. Dynamic model updating using virtual antiresonances. Shock Vib 2004; 11(3-4): 351-363.
15. Salawu OS Detection of structural damage through changes in frequency: a review. Eng Struct 1997; 19(9): 718-723.
16. Mares C., Friswell MI and Mottershead JE Model updating using robust estimation. Mech Syst Signal Process 2002; 16(1): 169-183.
17. Brill Jr ED The Use of Optimization Models in Public Sector Planning. Water Resour Res 1979; 15(4): 750-756.
18. Brill Jr ED, Flach JM, Hopkins LD and Ranjithan S. MGA: A decision support system for complex, completely defined problems. IEEE Trans Syst Man Cyb 1990; 20(4): 745-757.
19. Gupta A., Kripakaran P., Mahinthakumar G. and Baugh JW Genetic algorithm-based decision support for optimizing seismic response of piping systems. J Struct Eng 2005; 131(3): 389-398.
20. Baugh Jr JW, Caldwell SC and Brill Jr ED A mathematical programming approach for generating alternatives in discrete structural optimization. Eng Optim 1997; 28(1): 1-31.
21. Kripakaran P. and Gupta A. MGA - A mathematical approach to generate design alternatives. Lect Notes Artif Intell 2006; 4200: 408-415.
22. Zechman EM and Ranjithan SR An evolutionary algorithm to generate alternatives (EAGA) for engineering optimization problems. Eng Optim 2004; 36(5): 539-553.
23. Uber JG, Brill Jr ED and Pfeffer JT Use of Mathematical-Programming Methods for Complex-Systems. J Water Res Plan Manag-ASCE 1992; 118(3): 281-294.
24. Loughlin DH, Ranjithan SR, Brill ED and Baugh JW Genetic algorithm approaches for addressing unmodeled objectives in optimization problems. Eng Optim 2001; 33: 549-569.
25. Zarate BA, Caicedo JM and Dutta A. Model updating of cable-stayed bridges using MGA. In: International Modal Analysis Conference (IMAC), Orlando, Florida, 2007.
26. Chang SY, Brill Jr ED and Hopkins LD Use of mathematical models to generate alternative solutions to water resources planning problems. Water Resour Res 1982; 18(1): 58-64.
27. Nakamura Mand Brill Jr ED Mathematical methods for use in planning regional wastewater treatment systems. Urbana USA: University of Illinois at Urbana-Champaign, 1977.
28. Brill Jr ED, Chang SY and Hopkins LD Modeling to generate alternatives: the HSJ approach and an iilustration using a problem in land user planning. Manag Sci 1982; 25(2): 221-235.
29. Harrell LJ and Ranjithan S. Methods for generating alternatives to manage water quality in watersheds. In: Poster Presentation, 1998 Quadrangle Environmental Conference, UNC-Chapel Hill, January 30, 1998.
30. Mahfoud SW Niching methods for genetic algorithms. Doctoral Dissertation, University of Illinois at Urbana-Champaign, 1995.
31. Syswerda G. A study of reproduction in generational and steady state genetic algorithms. In: Proceedings of Foundations of Genetic Algorithms Conference, Morgan Kaufmann, 1991.
32. Yun GJ, Ogorzalek KA, Dyke SJ and Song W. A two-stage damage detection approach based on subset of damage parameters and genetic algorithms. Smart Struct Syst 2008; 5(1): 1-21.
33. Moslem K. and Nafaspour R. Structural damage detection by genetic algorithms. AIAA J 2002; 40(7): 1395-1401.
34. Johnson EA, Lam HF, Katafygiotis LS and Beck JL Phase I IASC-ASCE structural health monitoring benchmark problem using simulated data. J Eng Mech 2004; 130(1): 3-15.
35. Ventura CE, Prion HGL, Black C., Rezai KM and Latendresse V. Modal properties of a steel frame used for seismic evaluation studies. In: 15th International Modal Analysis Conference, Orlando, Florida, 1997.
36. Black C. and Ventura CE Blind test on damage detection of a steel frame structure. In: 16th International Modal Analysis Conference, Santa Barbara, CA, 1998.
37. Van Overschee P. and de Moor BLR. Subspace identification for linear systems: theory, implementation, applications. Boston: Kluwer Academic Publishers, 1996, p. 254.
38. Giraldo D. A structural health monitoring framework for civil structures. Doctoral Dissertation, Department of Civil Engineering, Washington University in St. Louis, 2006, p. 157.
39. Allemang RJ The modal assurance criterion - twenty years of use and abuse. J Sound Vibration 2003; 37(8): 14-23.