Journal of Failure Analysis and Prevention

, Volume 10, Issue 1, pp 11–17 | Cite as

Investigation of the Failure of an Automobile Torsion Bar

  • S. A. Rodríguez
  • F. A. Quiceno
  • J. J. Coronado
Case History---Peer-Reviewed

Abstract

This paper presents the failure analysis of a steel torsion bar of the automobile suspension system. The bar fractures in service and the fracture surface was 45° to the axis of the bar, with radial marks and shear lips, characteristic of the brittle fracture of a mechanical element under torsion. Scanning electron microscope was used to characterize the fracture surface that did not present evidence of extensive plastic deformation. The torsion bar fracture initiated at a weld point which had produced a fatigue crack and a martensite transformation in the heat-affected zone. The instrumented indentation technique was used for the mechanical characterization (microhardness and elastic modulus) of the microscopic and macroscopic regions near failure. The heat-affected zone was approximately 400–600 μm in thickness and the weld was a “point” approximately 4 mm diameter. The results obtained allowed differentiating the tempered martensite from the martensite (without tempering) in the heat-affected zone, the latter being 47% harder.

Keywords

Torsion bar Weld Failure analysis Instrumented indentation 

Notes

Acknowledgments

The authors thank CNPq, the Surface Phenomena Laboratory (LFS) at the University of Sao Paulo and the reviewers for contributing to improvement of the paper.

References

  1. 1.
    Neri-Flores, M., Carreño-Gallardo, C., Estrada-Guel, I.: Failure analysis of a power steering torsion bar. Microsc. Microanal. 11, 1612–1613 (2005)Google Scholar
  2. 2.
    Berkovits, A.: Estimation of loads causing fatigue failures in accident investigations. Eng. Fail. Anal. 2(3), 215–226 (1995)CrossRefGoogle Scholar
  3. 3.
    Bhushan, B., Li, X.: Nanomechanical characterization of solid surfaces and thin films. Int. Mater. Rev. 48(3), 125–164 (2003)CrossRefGoogle Scholar
  4. 4.
    Oliver, W.C., Pharr, G.M.: An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments. J. Mater. Res. 7(6), 1564–1583 (1992)CrossRefADSGoogle Scholar
  5. 5.
    Mata, M., Alcalá, J.: Mechanical property evaluation through sharp indentations in elastoplastic and fully plastic contact regimes. J. Mater. Res. 18(7), 1705–1709 (2003)CrossRefADSGoogle Scholar
  6. 6.
    Jang, J., Son, D., Lee, Y., Choi, Y., Kwon, D.: Assessing welding residual stress in A335 P12 steel welds before and after stress-relaxation annealing through instrumented indentation technique. Scr. Mater. 48(6), 743–748 (2003)CrossRefGoogle Scholar
  7. 7.
    Metals Handbook, vol. 11, Failure Analysis and PreventionGoogle Scholar
  8. 8.
    McClaflin, D., Fatemi, A.: Torsional deformation and fatigue of hardened steel including mean stress and stress gradient effects. Int. J. Fatigue 26, 773–784 (2004)CrossRefGoogle Scholar
  9. 9.
    Slámečka, K., Ponížil, P., Pokluda, J.: Quantitative fractography in bending-torsion fatigue. Mater. Sci. Eng. A 462, 359–362 (2007)CrossRefGoogle Scholar
  10. 10.
    King, R.B.: Elastic analysis of some punch problems for a layered medium. Int. J. Solids Struct. 23(12), 1657–1664 (1987)MATHCrossRefGoogle Scholar
  11. 11.
    Gere, J.M., Timoshenko, S.: Resistencia de Materiales. Thomson Learning Ibero, 187–190 (2002)Google Scholar
  12. 12.
    Hay, J.L., Pharr, G.M.: Instrumented indentation testing. Mechanical testing and evaluation. In: Kuhn, H., Medlin, D. (eds.), ASM Handbook, vol. 8, pp. 232–243. ASM International, Materials Park, OH (2000)Google Scholar

Copyright information

© ASM International 2009

Authors and Affiliations

  • S. A. Rodríguez
    • 1
  • F. A. Quiceno
    • 2
  • J. J. Coronado
    • 1
    • 2
  1. 1.Surface Phenomena Laboratory, Mechanical Engineering DepartmentUniversidade de São PauloSão PauloBrazil
  2. 2.Escuela de Ingeniería MecánicaUniversidad del Valle, Ciudad Universitaria MeléndezCaliColombia

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