Advertisement

Practical Challenges in Formulating Virtual Tests for Structural Composites

  • Brian N. Cox
  • S. Mark Spearing
  • Daniel R. Mumm
Part of the Computational Methods in Applied Sciences book series (COMPUTMETHODS, volume 10)

Abstract

Taking advantage of major recent advances in computational methods and the conceptual representation of failure mechanisms, the modeling community is building increasingly realistic models of damage evolution in structural composites. The goal of virtual tests appears to be reachable, in which most (but not all) real experimental tests can be replaced by high fidelity computer simulations. The payoff in reduced cycle time and costs for designing and certifying composite structures is very attractive; and the possibility also arises of considering material configurations that are too complex to certify by purely empirical methods. However, major challenges remain, the foremost being the formal linking of the many disciplines that must be involved in creating a functioning virtual test. Far more than being merely a computational simulation, a virtual test must be a system of hierarchical models, engineering tests, and specialized laboratory experiments, organized to address the assurance of fidelity by applications of information science, model-based statistical analysis, and decision theory. The virtual test must be structured so that it can function usefully at current levels of knowledge, while continually evolving as new theories and experimental methods enable more refined depictions of damage.

To achieve the first generation of a virtual test system, we must pay special attention to unresolved questions relating to the linking of theory and experiment: how can we assure that damage models address all important mechanisms, how can we calibrate the material properties embedded in the models, and what constitutes sufficient validation of model predictions? The virtual test definition must include real tests that are designed in such a way as to be rich in the information needed to inform models; and model-based analyses of the tests are required to mine the information. To date these compelling issues have been greatly underserved by both the modeling and experimental communities. Model-based analysis of tests has been undertaken only in terms of very simple (linear or continuum) engineering concepts; information-rich tests for more complex damage mechanisms have not been defined; and in fact the information in which experiments need to be rich has not been stated. Specific challenges in designing experiments for informing virtual tests and some promising experimental methods are summarized here.

Keywords

Digital Image Correlation Cohesive Zone Engineering Test Practical Challenge Cohesive Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Abraham FF (2003) How fast can cracks move? A research adventure in materials failure using millions of atoms and big computers. Adv Phys 52:727-790CrossRefADSGoogle Scholar
  2. 2.
    Abraham FF, Walkup R, Gao H et al. (2002) Simulating materials failure by using up to one billion atoms and the world’s fastest computer: brittle fracture. Proc Natl Acad Sci USA 99:5777-5782CrossRefPubMedADSGoogle Scholar
  3. 3.
    Ashby MF (1992) Physical modelling or materials problems. Mat Sci Technol 8:102-111Google Scholar
  4. 4.
    Bao G, Suo Z (1992) Remarks on crack-bridging concepts. Appl Mech Rev 24:355-366CrossRefGoogle Scholar
  5. 5.
    de Borst R (2003) Numerical aspects of cohesive-zone models. Eng Fract Mech 70:1743-1757CrossRefGoogle Scholar
  6. 6.
    Buehler MJ (2006) Nature designs tough collagen: Explaining the nanostructure of collagen fibrils. Proc Natl Acad Sci USA 103:12285-12290CrossRefGoogle Scholar
  7. 7.
    Buehler MJ (2006) Large-scale hierarchical modeling of nanoscale, natural and biological materials. J Comput Theor Nanosci 3:603-623Google Scholar
  8. 8.
    Buehler MJ, Gao H (2005) Ultra large scale atomistic simulations of dynamic fracture. In: Rieth M, Schommers W (eds) Handbook of Theoretical Computational Nanotechnology, Volume X, pp 1-41, American Scientific Publishers Ranch, CAGoogle Scholar
  9. 9.
    Cai W, Bulatov VV, Chang J et al. (2004) Dislocation core effects on mobility. In: Nabarro FNR, Hirth JP (eds) Dislocations in Solids, Volume 12, Chapter 64, Elsevier, AmsterdamGoogle Scholar
  10. 10.
    Camanho PP, D ávila CG, Pinho ST (2004) Fracture analysis of composite co-cured structural joints using decohesion elements. Fatigue Fract Eng Mat Struct 27:745-757CrossRefGoogle Scholar
  11. 11. Carpinteri A(ed)(1999) Nonlinear Crack Models for Nonmetallic Materials. Kluwer, Dordrecht, The NetherlandsGoogle Scholar
  12. 12.
    Carroll FE, Mendenhall MH, Traeger RH, Brau C et al. (2003) Pulsed tunable monochromatic X-ray beams from a compact source: New opportunities. Am J Roentgenol 181:1197-1202Google Scholar
  13. 13.
    Case SW, Reifsnider KL (1999) Mrlife12 theory manual - a strength and life prediction code for laminated composite materials. Technical report, Materials Response Group, Virginia Polytechnic Institute and State UniversityGoogle Scholar
  14. 14.
    Corigliano A (1993) Formulation, identification and use of interface models in the numerical analysis of composite delamination. Int J Solids Struct 30:2779-2811CrossRefGoogle Scholar
  15. 15.
    Cox BN (1999) Constitutive model for a fiber tow bridging a delamination crack. Mech Compos Mat Struct 6:117-138CrossRefGoogle Scholar
  16. 16.
    Cox BN (2005) Snubbing effects in the pullout of a fibrous rod from a laminate. Mech Adv Mat Struct 12:85-98CrossRefGoogle Scholar
  17. 17.
    Cox BN, Marshall DB (1991) The determination of crack bridging forces. Int J Fract 49: 159-176Google Scholar
  18. 18.
    Cox BN, Marshall DB (1994) Concepts for bridged cracks in fracture and fatigue. Acta Metall Mater 42:341-363CrossRefGoogle Scholar
  19. 19.
    Cox BN, Marshall DB (1996) Crack initiation in brittle fiber reinforced laminates. J Am Ceram Soc 79:1181-1188CrossRefGoogle Scholar
  20. 20.
    Cox BN, Yang QD (2006) In quest of virtual tests for structural composites. Science 314:1102-1107CrossRefPubMedADSGoogle Scholar
  21. 21.
    Dawood TA, Shenoi RA, Sahin M (2007) A procedure to embed fibre Bragg grating strain sensors into GFRP sandwich structures. Compos Part A 38:217-226CrossRefGoogle Scholar
  22. 22.
    Dobashi K, Fukuasawa A, Uesaka M et al. (2005) Design of compact monochromatic tunable hard X-ray source based on X-band linac. Jpn J Appl Phys 44:1999-2005CrossRefADSGoogle Scholar
  23. 23.
    Dvorak GJ, Laws N (1987) Analysis of progressive matrix cracking in composite laminates. II - First ply failure. J Compos Mat 21:309-329CrossRefGoogle Scholar
  24. 24.
    Elices M, Guinea GV, Gomez J et al. (2002) The cohesive zone model: Advantages, limitations and challenges. Eng Fract Mech 69:137-163CrossRefGoogle Scholar
  25. 25.
    Emery T, Dulieu-Barton JM, Cunnigham PR (2005) Identification of damage in composite structures using thermoelastic stress analysis. Key Eng Mat 293-294:583-590CrossRefGoogle Scholar
  26. 26.
    Falk ML, Needleman A, Rice JR (2001) A critical evaluation of cohesive zone models of dynamic fracture. J de Phys IV 11:43-50Google Scholar
  27. 27.
    Fawcett A, Trostle J, Ward S (1997) 777 empennage certification approach. In: Scott ML (ed) 11th International Conference on Composite Materials, Gold Coast, Australia. Technomic Publishing, Lancaster, PAGoogle Scholar
  28. 28.
    Francis Rose LR (1987) Crack reinforcement by distributed springs. J Mech Phys Solids 35:383-405CrossRefMathSciNetGoogle Scholar
  29. 29.
    Gonz ález C, Llorca J (2006) Multiscale modeling of fracture in fiber-reinforced composites. Acta Mater 54:4171-4181CrossRefGoogle Scholar
  30. 30. Gumbsch P (2001) Brittle fracture and the breaking of atomic bonds. In: The Society for Materials Science, Osaka, Japan (JSMS) (ed) Materials Science for the 21st Century, Volume A, pp 50-58Google Scholar
  31. 31.
    Hampel FR, Ronchetti EM, Rousseeuw PJ et al. (2005) Robust Statistics: The Approach Based on Influence Functions. Wiley, New YorkGoogle Scholar
  32. 32.
    Thompson JB, Kindt JH, Drake B, Hansma HG, Morse DE, Hansma PK (2001) Bone indentation recovery time correlates with bond reforming time. Nature 414:773-776CrossRefPubMedADSGoogle Scholar
  33. 33.
    vanden Heuvel PWJ, Peijs T, Young RJ (1997) Failure phenomena in two-dimensional multi-fibre microcomposites, 2. A raman spectroscopic study of the influence of inter-fibre spacing on stress concentrations. Compos Sci Technol 57:899-911CrossRefGoogle Scholar
  34. 34.
    Hild F, Roux S (2006) Digital image correlation: from displacement measurement to identification of elastic properties - a review. Strain 42:69-80CrossRefGoogle Scholar
  35. 35.
    Ho S, Suo Z (1992) Microcracks tunneling in brittle matrix composites driven by thermal expansion mismatch. Acta Metall Mater 40:1685-1690CrossRefGoogle Scholar
  36. 36.
    Ho S, Suo Z (1993) Tunneling cracks in constrained layers. J Appl Mech 60:890-894CrossRefGoogle Scholar
  37. 37.
    Khor KH, Buffiere JY, Ludwig W et al. (2004) In situ high resolution synchrotron X-ray tomography of fatigue crack closure mechanisms. J Phys Condens Matter 16:S3511-S3515CrossRefADSGoogle Scholar
  38. 38.
    Kortschot MT, Beaumont PWR (1990) Damage mechanics of composite materials: I -Measurements of damage and strength. Compos Sci Technol 39:289-301CrossRefGoogle Scholar
  39. 39.
    Kozhanov AI (1999) Composite Type Equations and Inverse Problems. VSP, Utrecht, The NetherlandsGoogle Scholar
  40. 40. Liang J, Huang R, Prevost JH, Suo Z (2002) Thin film cracking modulated by underlayer creep. Experimental MechanicsGoogle Scholar
  41. 41.
    Marder M (1999) Molecular dynamics of cracks. Comput Sci Eng 1:48-55CrossRefGoogle Scholar
  42. 42.
    Marshall DB, Morris WL, Cox BN et al. (1994) Transverse strengths and failure mechanisms in ti3al matrix composites. Acta Metall Mater 42:2657-2673CrossRefGoogle Scholar
  43. 43.
    Massab ò R, Mumm DR, Cox BN (1998) Characterizing mode II delamination cracks in stitched composites. Int J Fract 92:1-38CrossRefGoogle Scholar
  44. 44.
    Melnikov Y (1998) Influence Functions and Matrices. CRC Press, West Palm Beach, FLGoogle Scholar
  45. 45.
    Mohammed I, Lechti M (2000) Cohesive zone modeling of crack nucleation at biomaterial corners. J Mech Phys Solids 48:735-764CrossRefADSGoogle Scholar
  46. 46.
    Park HS (2005) Three-dimensional bridging scale analysis of dynamic fracture. J Comput Phys 207:588-609CrossRefADSGoogle Scholar
  47. 47.
    Prilepko AI, Orlovsky DG, Vasin IA (1999) Methods for Solving Inverse Problems in Mathematical Physics. Dekker, New YorkGoogle Scholar
  48. 48.
    Remmers JJC, de Borst R, Needleman A (2003) A cohesive segments method for the simulation of crack growth. Comput Mech 31:69-77CrossRefGoogle Scholar
  49. 49.
    Schellekens JCJ, de Borst R (1996) On the numerical modeling of edge delamination in composites. Key Eng Mater 121-122:131-60CrossRefGoogle Scholar
  50. 50.
    Shahwan KW, Waas AM (1997) Non-self-similar decohesion along a finite interface of unilaterally constrained delaminations. Proc Royal Soc Lond A 453:515-550CrossRefMathSciNetADSGoogle Scholar
  51. 51.
    Stigh U (1988) Damage and crack growth analysis of the double cantilever beam specimen. Int J Fract 37:R13-R18CrossRefGoogle Scholar
  52. 52.
    Suo Z, Bao G, Fan B (1992) Delamination R-curve phenomena due to damage. J Mech Phys Solids 40:1-16CrossRefADSGoogle Scholar
  53. 53.
    Suo Z, Prevost JH, Liang J (2003) Kinetics of crack initiation and growth in organic-containing integrated structures. J Mech Phys Solids 51:2169-2190CrossRefADSGoogle Scholar
  54. 54.
    Tarantola A(2004) Inverse Problem Theory and Model Parameter Estimation. SIAM, Philadelphia, PAGoogle Scholar
  55. 55.
    Turrettini A (1996) Ph.D. thesis, University of California, Santa Barbara, CAGoogle Scholar
  56. 56. Vlieks AE, Caryotakis G, Martin D et al. (2004) Compton X-ray source. In: EPAC 2004, pp 2837-2839, Lucerne, SwitzerlandGoogle Scholar
  57. 57.
    Wagner GJ, Liu WK (2003) Coupling of atomistic and continuum simulations using a bridging scale decomposition. J Comput Phys 190:249-274CrossRefADSGoogle Scholar
  58. 58.
    Weinan E, Engquist B, Li X et al. (2007) Heterogeneous multiscale methods: A review. Commun Comput Phys 2:367-450MathSciNetGoogle Scholar
  59. 59.
    Wisnom MR, Chang FK (2000) Modelling of splitting and delamination in notched cross-ply laminates. Compos Sci Technol 60:2849-2856CrossRefGoogle Scholar
  60. 60.
    Yang QD, Cox BN (2005) Cohesive models for damage evolution in laminated composites. Int J Fract 133:107-137CrossRefGoogle Scholar
  61. 61.
    Yorozu M, Yang J, Okada Y, Yanagida T (2001) Short-pulse X-ray generation via Thomson scattering in 0 and 90 interactions. Jpn J Appl Phys 40:4228-4232CrossRefADSGoogle Scholar

Copyright information

© Springer Science + Business Media B.V 2008

Authors and Affiliations

  • Brian N. Cox
    • 1
  • S. Mark Spearing
    • 2
  • Daniel R. Mumm
    • 3
  1. 1.LLCTeledyne Scientific Co.Thousand OaksUSA
  2. 2.School of Engineering SciencesUniversity of SouthamptonSouthamptonUK
  3. 3.University of CaliforniaIrvineUSA

Personalised recommendations