@misc{coratella_application_of_2015, 
author={Coratella, S.,Sticchi, M.,Toparli, M.B.,Fitzpatrick, M.E.,Kashaev, N.},
title={Application of the eigenstrain approach to predict the residual stress distribution in laser shock peened AA7050-T7451 samples},
year={2015},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.surfcoat.2015.03.026},
abstract = {Laser Shock Peening allows the introduction of deep compressive residual stresses into metallic components. It is applicable to most metal alloys used for aerospace applications. The method is relatively expensive in application, and therefore development studies often rely heavily on Finite Element Modeling to simulate the entire process, with a high computational cost. A different approach has been used recently, the so-called eigenstrain approach. The present study looks at the feasibility of applying the eigenstrain method for prediction of the residual stress in a sample that contains curved surface features. The eigenstrain is determined from a simple geometry sample, and applied to the more complex geometry to predict the residual stress after laser shock peening. In particular the prediction of residual stress at a curved edge, and for different values of material thickness, have been studied. The research has demonstrated that the eigenstrain approach gives promising results in predicting residual stresses when only the thickness is altered, but when the geometry of the peened surface is altered the eigenstrain method seems to slightly overestimate the residual stresses. This highlights a limitation of the eigenstrain method where the change in geometry means that the inelastic strain field as a consequence of a treatment – in this case laser shock peening – no longer has similitude.},
note = {Online available at: \url{https://doi.org/10.1016/j.surfcoat.2015.03.026} (DOI). Coratella, S.; Sticchi, M.; Toparli, M.; Fitzpatrick, M.; Kashaev, N.: Application of the eigenstrain approach to predict the residual stress distribution in laser shock peened AA7050-T7451 samples. Surface and Coatings Technology. 2015. vol. 273, 39-49. DOI: 10.1016/j.surfcoat.2015.03.026}}