ARTICLE
Residual stress profile determination by the hole-drilling method with calibration coefficients obtained using FEM
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Federal University of Paraná, Postgraduate Program in Mechanical Engineering, Curitiba – PR, Brazil
Submission date: 2021-05-27
Final revision date: 2021-08-09
Acceptance date: 2021-08-28
Online publication date: 2021-09-28
Publication date: 2021-10-20
Journal of Theoretical and Applied Mechanics 2021;59(4):661-673
KEYWORDS
TOPICS
ABSTRACT
Residual Stresses (RS) in mechanical components can be undesirable, and their accurate
identification can prevent component damage. There are many semi-destructive methods
for determination of RS. The hole-drilling method offers many advantages when compared
to other methods due to its practicality, applicability to different materials, and low-cost
execution. According to the American Society for Testing and Materials (ASTM) E837-
-13a Standard, the RS are assumed to be constant at each depth level when employing the
hole-drilling method. Thus, calibration coefficients are necessary to calculate stress values
at each level using the relaxed strains measured on the component surface, as incremental
drillings are performed. However, the coefficients provided by the Standard were obtained
using a coarsely-discretized 2D finite element model. This work aims to find new calibration
coefficients based on the linear elasticity theory and using the Finite Element Method (FEM)
with a refined mesh. A numerical model consisting of linear tetrahedral finite elements
was constructed to simulate the resulting strains, as unitary stresses are applied at each
depth level of the component inner surface. Using this method, two matrices of calibration
coefficients are obtained, one related to normal stresses, and another related to shear stresses.
The results show that the RS obtained using the new coefficients presented a 3.9% relative
average error compared to analytical values in the four experiments conducted, while the
ASTM Standard coefficients resulted in a 9.7% relative average error.
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