Abstract
The concept of constructing parameter spaces for process control and the prediction of properties within the heat affected zone (HAZ) of welds using inverse modeling is examined. These parameter spaces can be, in principle, either independent or a function of weld process conditions. The construction of these parameter spaces consists of two procedures. One procedure entails calculation of a parameterized set of temperature histories using inverse heat transfer analysis of the heat deposition occurring during welding. The other procedure entails correlating these temperature histories with either a specific process control parameter or physical property of the weld that is measurable. Two quantitative case study analyses based on inverse modeling are presented. One analysis examines the calculation of temperature histories as a function of process control parameters. For this case, the specific process control parameter adopted as prototypical is the electron beam focal point. Another analysis compares some general characteristics of inverse and direct modeling with respect to the prediction of properties of the HAZ for deep penetration welding of aluminum alloys. For this case, the specific property adopted as prototypical is hardness. This study provides a foundation for an examination of 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.
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Acknowledgments
The authors would like to thank Mr. Vassilis Stergiou of HAI for performing EB experiments. Some of the calculations presented here (thermal histories) are based on work supported by a Naval Research Laboratory 6.1 Core program in welding. 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.
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Zervaki, A., Haidemenopoulos, G. & Lambrakos, S. Analysis of Heat Affected Zone in Welded Aluminum Alloys Using Inverse and Direct Modeling. J. of Materi Eng and Perform 17, 402–410 (2008). https://doi.org/10.1007/s11665-007-9145-9
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DOI: https://doi.org/10.1007/s11665-007-9145-9