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Inverse Thermal Analysis of Heat-Affected Zone in Al2129 and Al2198 Laser Welds

  • A. D. Zervaki
  • G. N. Haidemenopoulos
  • S. G. Lambrakos
Article

Abstract

Case study analyses of A12139 and Al2198 laser welds are presented. These analyses demonstrate the concept of constructing parameter spaces for prediction of properties within the heat-affected zone (HAZ) of welds using inverse modeling, which are in turn for process control. The construction of these parameter spaces consists of two procedures. One procedure entails calculation of a parameterized set of temperature histories by inverse analysis of the heat deposition occurring during welding. The other procedure entails correlating these temperature histories with a specific physical property of the weld that is measurable. The analyses presented here examines some characteristics of inverse modeling with respect to the prediction of hardness within the HAZ for deep penetration laser welding of the Aluminum alloys A12139 and Al2198. This study further demonstrates the feasibility of constructing a parameter space for the prediction of weld properties using weld cross section measurements that are independent of weld process conditions.

Keywords

joining modeling processes welding 

Notes

Acknowledgments

The calculations presented here (thermal histories) are based on work supported by a Naval Research Laboratory 6.1 Core program in inverse methods of analysis. In particular, S.G.L would like to thank the Department of Mechanical Engineering at the University of Thessaly for its continued collaboration concerning welding and materials processing.

References

  1. 1.
    S.G. Lambrakos and J.G. Michopoulos, Algorithms for Inverse Analysis of Heat Deposition Processes, Mathematical Modelling of Weld Phenomena, Vol. 8, 847. Verlag der Technischen Universite Graz, Austria, 2007Google Scholar
  2. 2.
    S.G. Lambrakos and J.O. Milewski: Analysis of Welding and Heat Deposition Processes using an Inverse-Problem Approach, Mathematical Modelling of Weld Phenomena, Vol. 7, 1025. Verlag der Technischen Universite Graz, Austria, 2005, p 1025–1055Google Scholar
  3. 3.
    J. Xie and J. Zou, Numerical Reconstruction of Heat Fluxes, SIAM J. Numer. Anal., 2005, 43(4), p 1504–1535CrossRefGoogle Scholar
  4. 4.
    A. Tarantola, Inverse Problem Theory and Methods for Model Parameter Estimation, SIAM, Philadelphia, PA, 2005CrossRefGoogle Scholar
  5. 5.
    H.S. Carslaw and J.C. Jaegar, Conduction of Heat in Solids, 2nd ed., Clarendon Press, Oxford, 1959, p 374Google Scholar
  6. 6.
    S.G. Lambrakos, A.D. Zervaki, and G.N. Haidemenopoulos, A Numerical Method for Inverse Thermal Analysis of Steady-State Energy Deposition in Plate Structures, J. Mater. Eng. Perform., 2012, 21(2), p 180–190CrossRefGoogle Scholar
  7. 7.
    A.D. Zervaki, G.N. Haidemenopoulos, and S.G. Lambrakos, Case-Study Inverse Thermal Analysis of Al2139 Laser Welds, J. Mater. Eng. Perform., 2012, 21(6), p 177–185Google Scholar
  8. 8.
    A.D. Zervaki, G.N. Haidemenopoulos, and S.G. Lambrakos, Case-Study Inverse Thermal Analysis of Al2198 Laser Welds, J. Mater. Eng. Perform., 2012, 21(4), p 471–480CrossRefGoogle Scholar
  9. 9.
    A. Engstrom, I. Hoglud, and J. Agren, Computer Simulation of Diffusion in Multiphase Systems, Metall. Mater. Trans., 1994, 25 A, p 1127–1134CrossRefGoogle Scholar
  10. 10.
    A.D. Zervaki, G.N. Haidemenopoulos, and S.G. Lambrakos, Analysis of Heat Affected Zone using Direct and Inverse Modeling in 6XXX Aluminum Alloys, Mathematical Modelling of Weld Phenomena, Vol. 8, 1025. Verlag der Technischen Universite Graz, Austria, 2007Google Scholar

Copyright information

© ASM International 2012

Authors and Affiliations

  • A. D. Zervaki
    • 1
  • G. N. Haidemenopoulos
    • 1
  • S. G. Lambrakos
    • 2
  1. 1.Department of Mechanical EngineeringUniversity of ThessalyVólosGreece
  2. 2.Materials Science and Technology Division, Code 6390Naval Research LaboratoryWashingtonUSA

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