Improved stochastic dissimilar diffusion bonding model with experimental validation
Bryan Ferguson, Neha Kulkarni, D.G. Sanders, Eric Bol, M. Ramulu
download PDFAbstract. Diffusion bonding is a solid-state welding operation that has seen wide spread use in the aerospace industry, especially in combination with superplastic forming. It combines two relatively flat, clean surfaces at high temperature to create a near flawless weld over a large surface area. Modelling of diffusion bonding has been challenging due in part because of the larger variations in voids formed from the mating surfaces. This paper attempts to compensate for that inadequacy by implementing a stochastic diffusion bonding model based with theoretical voids formed from interacting surfaces. The model uses a statistical version of Pilling’s model in combination with surface roughness based initial conditions that estimates the possibilities of voids formed. The results of the model are compared with experimental results for three different alloys at a variety of process conditions along with presenting an investigation of the mechanics of the model for future improvements.
Keywords
Diffusion Bonding, Voids, Superplastic Forming, Statistical Modeling
Published online , 17 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Bryan Ferguson, Neha Kulkarni, D.G. Sanders, Eric Bol, M. Ramulu, Improved stochastic dissimilar diffusion bonding model with experimental validation, Materials Research Proceedings, Vol. 32, pp 338-354, 2023
DOI: https://doi.org/10.21741/9781644902615-39
The article was published as article 39 of the book Superplasticity in Advanced Materials
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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