A goal-oriented field measurement filtering technique for the identification of material model parameters
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Abstract
The post-processing of experiments with nonuniform fields is still a challenge: the information is often much richer, but its interpretation for identification purposes is not straightforward. However, this is a very promising field of development because it would pave the way for the robust identification of multiple material parameters using only a small number of experiments. This paper presents a goal-oriented filtering technique in which data are combined into new output fields which are strongly correlated with specific quantities of interest (the material parameters to be identified). Thus, this combination, which is nonuniform in space, constitutes a filter of the experimental outputs, whose relevance is quantified by a quality function based on global variance analysis. Then, this filter is optimized using genetic algorithms.
Keywords
Parameter identification Local field measurements Global sensitivity analysisPreview
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- 1.Lubineau G, Ladeveze P, Violeau D (2006) Durability of CFRP laminates under thermomechanical loading: A micro-meso damage model. Compos Sci Technol 66(7-8): 983–992CrossRefGoogle Scholar
- 2.Herakovich CT (1997) Mechanics of fibrous composites. Wiley, New YorkGoogle Scholar
- 3.Iosipescu N (1967) New accurate procedure for single shear testing of metals. J Mater 2(3): 537–566Google Scholar
- 4.Arcan M, Hashin Z, Voloshin A (1978) A method to produce uniform plane stress states with applications to fiber-reinforced materials. Exp Mech 18(14): 141–146CrossRefGoogle Scholar
- 5.Pierron F, Green B, Wisnom MR, Hallett SR (2007) Full-field assessment of the damage process of laminated composite open-hole tensile specimens. Compos Part A 38: 2321–2332CrossRefGoogle Scholar
- 6.Guinard S, Allix O, Guédra-Degeorges D, Vinet A (2002) A 3d damage analysis of low-velocity impacts on laminated composites. Compos Sci Technol 62: 585–589CrossRefGoogle Scholar
- 7.Kucerova A, Brancherie D, Ibrahimbegovic A, Zeman J, Bittnar Z (2009) Novel anisotropic continuum-discrete damage model capable of representing localized failure of massive structures. Eng Comput Int J Comput Aided Eng Softw 26(1/2): 128–144CrossRefGoogle Scholar
- 8.Sutton MA, Cheng M, Peters WH, Chao YJ, McNeill SR (1986) Application of an optimized digital correlation method to planar deformation analysis. Image Vis Comput 4(3): 143–150CrossRefGoogle Scholar
- 9.Sutton MA, Wolters WJ, Peters WH, Ranson WF, McNeill SR (1983) Determination of displacements using an improved digital correlation method. Image Vis Comput 1(3): 133–139CrossRefGoogle Scholar
- 10.Grédiac M, Toussaint E, Pierron F (2002) Identification of the mechanical properties of materials with the virtual fields method, an alternative to finite element model updating. Comptes Rendus Mecanique 330(2): 107–112MATHCrossRefGoogle Scholar
- 11.Grédiac M (1989) Principe des travaux virtuels et identification. Comptes Rendus Mecanique 309: 1–5MATHGoogle Scholar
- 12.Geymonat G, Hild F, Pagano S (2002) Identification of elastic parameters by displacement field measurement. Comptes Rendus Mecanique 330(6): 403–408MATHCrossRefGoogle Scholar
- 13.Claire D, Hild F, Roux S (2002) Identification of damage fields using kinematic measurements. Comptes Rendus Mecanique 330: 729–734MATHCrossRefGoogle Scholar
- 14.Avril S, Bonnet M, Bretelle A-S, Grédiac M, Hild F, Ienny P, Latourte F, Lemosse D, Pagano S, Pagnacco E, Pierron F (2008) Overview of identification methods of mechanical parameters based on full-field measurements. Exp Mech 48: 381–402CrossRefGoogle Scholar
- 15.Avril S, Huntley JM, Pierron F, Steele DD (2008) 3d heterogeneous stiffness reconstruction using MRI and the virtual fields method. Exp Mech 48: 479–494CrossRefGoogle Scholar
- 16.Sobol IM (1993) Sensitivity estimates for nonlinear mathematical models. MMCE 1(4): 407–414MATHMathSciNetGoogle Scholar
- 17.Saltelli A, Sobol IM (1995) About the use of rank transformation in sensitivity analysis of model output. Reliab Eng Syst Saf 50: 225–239CrossRefGoogle Scholar
- 18.Sobol IM (2001) Global sensitivity indices for nonlinear mathematical models and their monte carlo estimates. Math Comput Simul 55: 217–280MathSciNetGoogle Scholar
- 19.Sobol IM (1969) Multidimensional quadrature formulas and Haar functions. NaukaGoogle Scholar
- 20.Archer GEB, Saltelli A, Sobol IM (1997) Sensitivity measures, anova-like techniques and the use of bootstrap. J Stat Comput Simul 58(2): 99–120MATHCrossRefGoogle Scholar
- 21.Zohdi TI (2003) Genetic design of solids possessing a random-particulate microstructure. Philos Trans Roy Soc Math Phys Eng Sci 361(1806): 1021–1043MATHCrossRefMathSciNetGoogle Scholar
- 22.Zohdi TI (2003) Constrained inverse formulations in random material design. Comput Meth Appl Mech Eng 192(28-30): 3179–3194MATHCrossRefGoogle Scholar
- 23.Owen A (1995) Monte Carlo and Quasi-Monte Carlo methods in scientific computing. Chapter randomly permuted (t,m,s)-Nets and (t,s)-Sequences. Springer-Verlag, New YorkGoogle Scholar
- 24.McKay MD, Beckman R, Conover W (1979) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21(2): 239–245MATHCrossRefMathSciNetGoogle Scholar
- 25.Halton JH (1960) On the efficiency of certain quasi-random sequences of point sequence. Numer Math 2: 84–90CrossRefMathSciNetGoogle Scholar
- 26.Sobol IM (1967) On the distribution of points in a cube and the approximate evaluation of integrals. USSR Comput Math Math Phys 7: 86–112MATHCrossRefMathSciNetGoogle Scholar
- 27.Faure H (1982) Discrépance de suites associées à un système de numération (en dimension s). Acta Arith 41: 337–351MATHMathSciNetGoogle Scholar
- 28.Saltelli A, Chan K, Scott EM (2000) Sensitivity analysis. Wiley, New YorkMATHGoogle Scholar
- 29.Turanyi T (1990) Sensitivity analysis of complex kinetic system, tools and applications. J Math Chem 5: 203–248CrossRefMathSciNetGoogle Scholar