Next Article in Journal
Thermal Analysis and SEM Microscopy Applied to Studying the Efficiency of Ionic Liquid Immobilization on Solid Supports
Previous Article in Journal
Microstructure and Morphology Control of Potassium Magnesium Titanates and Sodium Iron Titanates by Molten Salt Synthesis
Previous Article in Special Issue
Vickers Micro-Hardness of New Restorative CAD/CAM Dental Materials: Evaluation and Comparison after Exposure to Acidic Drink
Article Menu

Export Article

Open AccessArticle

On the Statistical Size Effect of Cast Aluminium

Christian Doppler Laboratory for Process based Component Design, 8700 Leoben, Austria
*
Author to whom correspondence should be addressed.
Materials 2019, 12(10), 1578; https://doi.org/10.3390/ma12101578
Received: 23 April 2019 / Revised: 6 May 2019 / Accepted: 9 May 2019 / Published: 14 May 2019
(This article belongs to the Special Issue Probabilistic Mechanical Fatigue and Fracture of Materials)
  |  
PDF [2422 KB, uploaded 17 May 2019]
  |  

Abstract

Manufacturing process based imperfections can reduce the theoretical fatigue strength since they can be considered as pre-existent microcracks. The statistical distribution of fatigue fracture initiating defect sizes also varies with the highly-stressed volume, since the probability of a larger highly-stressed volume to inherit a potentially critical defect is elevated. This fact is widely known by the scientific community as the statistical size effect. The assessment of this effect within this paper is based on the statistical distribution of defect sizes in a reference volume V 0 compared to an arbitrary enlarged volume V α . By implementation of the crack resistance curve in the Kitagawa–Takahashi diagram, a fatigue assessment model, based on the volume-dependent probability of occurrence of inhomogeneities, is set up, leading to a multidimensional fatigue assessment map. It is shown that state-of-the-art methodologies for the evaluation of the statistical size effect can lead to noticeable over-sizing in fatigue design of approximately 10 % . On the other hand, the presented approach, which links the statistically based distribution of defect sizes in an arbitrary highly-stressed volume to a crack-resistant dependent Kitagawa–Takahashi diagram leads to a more accurate fatigue design with a maximal conservative deviation of 5 % to the experimental validation data. Therefore, the introduced fatigue assessment map improves fatigue design considering the statistical size effect of lightweight aluminium cast alloys. View Full-Text
Keywords: cast aluminium; fatigue assessment; shrinkage pores; statistical distribution; extreme value statistics; highly-stressed volume cast aluminium; fatigue assessment; shrinkage pores; statistical distribution; extreme value statistics; highly-stressed volume
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Aigner, R.; Pomberger, S.; Leitner, M.; Stoschka, M. On the Statistical Size Effect of Cast Aluminium. Materials 2019, 12, 1578.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Materials EISSN 1996-1944 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top