| Issue |
MATEC Web of Conferences
Volume 12, 2014
FDMD II - JIP 2014 - Fatigue Design & Material Defects
|
|
|---|---|---|
| Article Number | 05004 | |
| Number of page(s) | 2 | |
| Section | Session 5: DVM/SF2M Evaluation of Constructional Manufacturing Defects with Regard to Structural Fatigue | |
| DOI | https://doi.org/10.1051/matecconf/20141205004 | |
| Published online | 09 June 2014 | |
Model for fracture mechanics based prediction of the fatigue strength of engineering alloys containing microscopical initial defects
1 BAM Federal Instituite for Materials Research, Berlin, Germany
2 Technische Universität Darmstadt, Germany
a Corresponding author : uwe.zerbst@bam.de
Recently two of the authors of the present paper proposed a model for fracture mechanics based prediction of the S-N characteristics of metallic components with large microstructural defects and supported this by a validation excercise on an aluminium alloy AL5380 H321. Within this presentation the authors extend the study using a number of data sets from the literature. Despite of necessary assumptions for the compensation of partially missing input information the results are fairly reasonable, with the exception of high loading levels where the analyses of two of the data sets yield non-conservative results. The authors propose multiple crack initiation as the potential root of the problem and discuss methods for extending the model for taking into account crack initiation.
© Owned by the authors, published by EDP Sciences, 2014
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.