Abstract

A model for the prediction of fatigue life based on the statistical distribution of pores, intermetallic particles and grains is presented here. This has been applied to a cast Al alloy A206 before and after friction stir processing (FSP). the model computes the probability of initiating a small crack based on the probability of finding combinations of defects and grains on the surface. Crack initiation and the propagation life of small cracks due to these defect and grain combinations are computed and summed to obtain the total fatigue life. the defect and grain combinations are ranked according to total fatigue life and the failure probability computed. Bending fatigue experiments were carried out on A206 before and after FSP. FSP eliminated the porosity, broke down the particles and refined the microstructure. the model predicted the fatigue life of A206 before and after FSP well. the cumulative probability distribution vs. fatigue life was fitted to a three parameter Weibull distribution function. the scatter reduced after FSP, and the fatigue threshold increased. the potential improvement in the fatigue life of A206 for a microstructure consisting of a finer distribution of particle sizes after FSP was predicted using the model. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Department(s)

Electrical and Computer Engineering

Second Department

Materials Science and Engineering

Comments

National Science Foundation, Grant 1157754

Keywords and Phrases

Al alloys; Cast alloys; Fatigue; Friction stir processing; Probabilistic life prediction

International Standard Serial Number (ISSN)

1359-6454

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Elsevier; Acta Materialia, All rights reserved.

Publication Date

01 May 2011

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