MATEC Web Conf.
Volume 165, 201812th International Fatigue Congress (FATIGUE 2018)
|Number of page(s)||6|
|Published online||25 May 2018|
A new method for evaluating the influences of surface topography on fatigue propriety of the random machined surfaces
School of Mechanical Engineering, Zhengzhou University, Zhengzhou, 450001, China
2 Henan Key Engineering Laboratory for Anti-fatigue Manufacturing Technology, Zhengzhou, 450001, China
3 School of Mechanics & Engineering Science, Zhengzhou University, Zhengzhou, Henan, 450001, China
The Stress concentration factor (SCF) induced by the machined surface is more complex than that resulting from macro-geometry discontinuities and has great effect on fatigue life of structure. However, another important parameter, stress gradient (SG), was always ignored. The notch roots or valleys of the wave surface constitute fatigue hot points, where cracks occur, so it is essential to study the SCF and SG at valleys rather than just the root-mean-square SCF variable. In this work, a new method for evaluating the influences of surface topography on fatigue propriety of the random machined surfaces was given. An analytical method using Fourier transformation to simulate machined surface topography is presented. Analytical formulae for SCF and SG for random machined surfaces are derived subjected to a general loading and validate these formulae via finite element method (FEM). Joint probability-distribution function for SCF and SG at the valleys of the random machined-surface topography of the machined sample was obtained after different cycles fatigue test. This method gave us how the surface topography effect the fatigue properties of machined components. Fatigue test of machined sample for a single crystal nickel based alloy were established for validated this method. The obtained results should be useful in studying and evaluating fatigue properties of machined components.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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