A Comprehensive Method to Predict Wear and to Define the Optimum Geometry of Fretting Surfaces

[+] Author and Article Information
L. Gallego, D. Nélias

 LaMCoS—UMR CNRS 5514, INSA Lyon, France

C. Jacq

 SNECMA, Villaroche, France

J. Tribol 128(3), 476-485 (Mar 01, 2006) (10 pages) doi:10.1115/1.2194917 History: Received June 08, 2005; Revised March 01, 2006

This paper presents a fast and robust three-dimensional contact computation tool taking into account the effect of cyclic wear induced from fretting solicitations under the gross slip regime. The wear prediction is established on a friction-dissipated energy criteria. The material response is assumed elastic. The contact solver is based on the half-space assumption and the algorithm core is similar to the one originally proposed by Kalker (1990, Three Dimensional Elastic Bodies in Rolling Contact, Kluwer, Dordrecht) for normal loading. In the numerical procedure the center of pressure may be imposed. The effect of surface shear stress is considered through a Coulomb friction coefficient. The conjugate gradient scheme presented by Polonsky and Keer (1999, Wear, 231, pp. 206–219) and an improved fast Fourier transform (FFT) acceleration technique similar to the one developed by Liu (2000, Wear, 243, pp. 101–111) are used. Results for elementary geometries in the gross slip regime are presented. It is shown that the surface geometry influences the contact pressure and surface shear stress distributions found after each loading cycle. It is also shown that wear tends to be uniformly distributed. This process continuously modifies the micro- and macrogeometry of the rubbing surfaces, leading after a given number of cycles to (i) an optimum or ideal contact geometry and (ii) a prediction of wear.

Copyright © 2006 by American Society of Mechanical Engineers
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Figure 1

Fretting regimes and their corresponding fretting cycles

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Figure 2

Blade-disk contact submitted to fretting

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Figure 3

Wear prediction tool diagram

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Figure 5

Detail of the geometry

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Figure 7

Initial geometry (for all simulations) and the worn geometry after Nmax cycles (simulation 1)

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Figure 8

Evolution of wear and pressure distribution (simulation 1)

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Figure 9

Evolution of the wear depth and coefficient of variation (simulation 1)

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Figure 10

Influence of ΔN on the computation time (simulation 2)

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Figure 11

Consequence of ΔN on the width of the worn area and the wear depth (simulation 2)

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Figure 12

Evolution of the coefficient of variation and worn area width for different ΔN (simulation 2)

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Figure 13

Evolution of the wear depth and its error for different ΔN (simulation 2)

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Figure 14

Consequence of the discretization on the wear final wear depth (simulation 3)

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Figure 15

Evolution of the coefficient of variation for different grid sizes (simulation 3)

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Figure 16

Consequence of the misalignment on the wear distribution (simulation 4)

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Figure 17

Evolution of test data compared to data used for simulation

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Figure 18

Evolution of the friction dissipated energy

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Figure 19

Wear distribution of simulation and test after a similar friction dissipated energy




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